Changes in Biological Pathways During 6,000 Years of Civilization in Europe Evgeny Chekalin, 1 Alexandr Rubanovich, 1 Tatiana V. Tatarinova, 1,2,3,4 Artem Kasianov, 1,5 Nicole Bender, 6 Marina Chekalina, 1 Kaspar Staub, 6 Nikola Koepke, 6 Frank Ru ¨hli, 6 Sergey Bruskin,* ,†,1 and Irina Morozova* ,†,6 1 Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia 2 Department of Biology, University of La Verne, La Verne, CA 3 A. A. Kharkevich Institute for Information Transmission Problems, Moscow, Russia 4 Department of Fundamental Biology and Biotechnology, Siberian Federal University, Krasnoyarsk, Russia 5 Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia 6 Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland † These authors contributed equally to this work. *Corresponding authors: E-mails: [email protected]; [email protected]. Associate editor: Ryan Hernandez Abstract The beginning of civilization was a turning point in human evolution. With increasing separation from the natural environment, mankind stimulated new adaptive reactions in response to new environmental factors. In this paper, we describe direct signs of these reactions in the European population during the past 6,000 years. By comparing whole- genome data between Late Neolithic/Bronze Age individuals and modern Europeans, we revealed biological pathways that are significantly differently enriched in nonsynonymous single nucleotide polymorphisms in these two groups and which therefore could be shaped by cultural practices during the past six millennia. They include metabolic trans- formations, immune response, signal transduction, physical activity, sensory perception, reproduction, and cognitive functions. We demonstrated that these processes were influenced by different types of natural selection. We believe that our study opens new perspectives for more detailed investigations about when and how civilization has been modifying human genomes. Key words: microevolution, selection, European civilization, adaptation, ancient DNA, pathway analysis. Introduction It is generally accepted that the term “civilization” refers to any complex society characterized by urban development, social stratification, symbolic communication forms (typically represented by writing systems), and a perceived separation from and domination over the natural environment (Adams 1966). From an evolutionary point of view, civilization started when humans, instead of reacting to the environment, began to actively shape it. Since the Neolithic transition, mankind has experienced a shift to agriculture, domestication of ani- mals and plants, sedentism, significant increase in population density, and exposure to new pathogens; most of these effects have been self-imposed. Humans have been creating the ar- tificial environment separating them from nature. This new environment induces new responses to it. At present, it is supposed that culturally derived selection pressures should be stronger than noncultural ones (Feldman and Laland 1996; Ehrlich 2000; Bersaglieri et al. 2004; Richerson and Boyd 2005; Laland 2008; Laland et al. 2010). The main reason for this is that using cultural practices led to drastic population growth. As a result, the number of targets for mutations (both advantageous and disadvantageous) in the population increased, as did the number of individuals for selection (Laland 2008). Paradoxically, mutations accumulated in human genomes as a result of relaxed natural selection can also serve as targets for selection in new environmental con- ditions. Moreover, new cultural practices typically spread more quickly than genetic mutations, and the more individ- uals exhibiting the cultural trait, the greater the intensity of selection (Kimura 1955; Boyd and Richerson 1985; Hawks et al. 2007; Laland 2008; Cochran and Harpending 2009). Culturally derived selection leaves signs in the human ge- nome. Some of these signs (like lactase persistence) are quite evident (Holden and Mace 1997; Beja-Pereira et al. 2003; Gamba et al. 2014; Allentoft et al. 2015), whereas many others are still uncertain (Libert et al. 1998; Stephens et al. 1998; Galvani and Slatkin 2003; Sabeti et al. 2005). Revealing and analyzing these selection signatures is of high importance not only for improving our understanding of connections be- tween the human organism and the environment but also for deepening our insight into mechanisms of emergence of the so-called “diseases of civilization.” Article ß The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: [email protected]Mol. Biol. Evol. 36(1):127–140 doi:10.1093/molbev/msy201 Advance Access publication October 30, 2018 127 Downloaded from https://academic.oup.com/mbe/article-abstract/36/1/127/5146762 by Ann Nez user on 16 June 2019
Transcript
Changes in Biological Pathways During 6000 Years ofCivilization in Europe
Evgeny Chekalin1 Alexandr Rubanovich1 Tatiana V Tatarinova1234 Artem Kasianov15 Nicole Bender6
Marina Chekalina1 Kaspar Staub6 Nikola Koepke6 Frank Ruhli6 Sergey Bruskindagger1 andIrina Morozovadagger6
1Vavilov Institute of General Genetics Russian Academy of Sciences Moscow Russia2Department of Biology University of La Verne La Verne CA3A A Kharkevich Institute for Information Transmission Problems Moscow Russia4Department of Fundamental Biology and Biotechnology Siberian Federal University Krasnoyarsk Russia5Center for Data-Intensive Biomedicine and Biotechnology Skolkovo Institute of Science and Technology Moscow Russia6Institute of Evolutionary Medicine University of Zurich Zurich SwitzerlanddaggerThese authors contributed equally to this work
The beginning of civilization was a turning point in human evolution With increasing separation from the naturalenvironment mankind stimulated new adaptive reactions in response to new environmental factors In this paper wedescribe direct signs of these reactions in the European population during the past 6000 years By comparing whole-genome data between Late NeolithicBronze Age individuals and modern Europeans we revealed biological pathwaysthat are significantly differently enriched in nonsynonymous single nucleotide polymorphisms in these two groups andwhich therefore could be shaped by cultural practices during the past six millennia They include metabolic trans-formations immune response signal transduction physical activity sensory perception reproduction and cognitivefunctions We demonstrated that these processes were influenced by different types of natural selection We believe thatour study opens new perspectives for more detailed investigations about when and how civilization has been modifyinghuman genomes
Key words microevolution selection European civilization adaptation ancient DNA pathway analysis
IntroductionIt is generally accepted that the term ldquocivilizationrdquo refers toany complex society characterized by urban developmentsocial stratification symbolic communication forms (typicallyrepresented by writing systems) and a perceived separationfrom and domination over the natural environment (Adams1966) From an evolutionary point of view civilization startedwhen humans instead of reacting to the environment beganto actively shape it Since the Neolithic transition mankindhas experienced a shift to agriculture domestication of ani-mals and plants sedentism significant increase in populationdensity and exposure to new pathogens most of these effectshave been self-imposed Humans have been creating the ar-tificial environment separating them from nature This newenvironment induces new responses to it
At present it is supposed that culturally derived selectionpressures should be stronger than noncultural ones (Feldmanand Laland 1996 Ehrlich 2000 Bersaglieri et al 2004 Richersonand Boyd 2005 Laland 2008 Laland et al 2010) The mainreason for this is that using cultural practices led to drasticpopulation growth As a result the number of targets for
mutations (both advantageous and disadvantageous) in thepopulation increased as did the number of individuals forselection (Laland 2008) Paradoxically mutations accumulatedin human genomes as a result of relaxed natural selection canalso serve as targets for selection in new environmental con-ditions Moreover new cultural practices typically spreadmore quickly than genetic mutations and the more individ-uals exhibiting the cultural trait the greater the intensity ofselection (Kimura 1955 Boyd and Richerson 1985 Hawks et al2007 Laland 2008 Cochran and Harpending 2009)
Culturally derived selection leaves signs in the human ge-nome Some of these signs (like lactase persistence) are quiteevident (Holden and Mace 1997 Beja-Pereira et al 2003Gamba et al 2014 Allentoft et al 2015) whereas many othersare still uncertain (Libert et al 1998 Stephens et al 1998Galvani and Slatkin 2003 Sabeti et al 2005) Revealing andanalyzing these selection signatures is of high importance notonly for improving our understanding of connections be-tween the human organism and the environment but alsofor deepening our insight into mechanisms of emergence ofthe so-called ldquodiseases of civilizationrdquo
Article
The Author(s) 2018 Published by Oxford University Press on behalf of the Society for Molecular Biology and EvolutionAll rights reserved For permissions please e-mail journalspermissionsoupcom
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
The earliest stages of human civilization are the LateNeolithic Age and the Bronze Age These were the epochsthat gave rise to our present lifestyle The 6000 years betweenthat period and modern times encompass the greater part ofhuman civilization events In this paper we study the geneticconsequences of these cultural events
Many different approaches are used to reveal and analyzepossible selection signals (Voight et al 2006 Sabeti et al 2007Tang et al 2007 Williamson et al 2007 Quach et al 2009Grossman et al 2013 Mathieson et al 2015 Field et al 2016)Most are based on modern human genome-wide data andtherefore represent indirect evidence of selection Objectiveinformation can be obtained by direct comparison of ancientand modern human genomes The first steps in this directionwere made relatively recently they became possible thanks towhole-genome next generation sequencing of ancient sam-ples These studies have revealed selection signatures in singlenucleotide polymorphisms (SNPs) associated with skin pig-mentation diet and immunity as well as with some complextraits that is human height (Olalde et al 2014 Allentoft et al2015 Mathieson et al 2015 Dannemann et al 2016 Fu et al2016)
Providing that natural selection should act through phe-notypes we assume that selection signals for multigenic traitsshould be analyzed not only at the level of individual SNPs butalso at the level of biological pathways where the influence ofindividual SNPs is aggregated into functional groups Thisapproach has been previously used for instance to studyselection signatures between human and chimpanzee line-ages (Somel et al 2013) In the present study we appliedpathway analysis to low-covered whole-genome ancientDNA sequence data We compared data on European LateNeolithicBronze Age individuals (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) with those from modern European individuals(httpwwwinternationalgenomeorg) supposedly ofBronze Age ancestry and occupying the same geographicalarea as their ancestors Our aims were 1) to reveal nonsynon-ymous SNPs in ancient and modern groups 2) to associatethese SNPs with biological pathways and 3) to calculate thedifferences in pathway enrichment between the ancient andmodern groups The revealed differences indicate the pro-cesses that we suppose have been shaped by introductionof human cultural practices during the past 6000 years
Results
Compatibility of the DataWe compared whole-genome data from 150 ancient samples(supplementary tables 1 and 2 Supplementary Material on-line) dated between 3500 and 1000 BCE (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al 2015)(fig 1) with data on 305 modern Europeans genotyped in theframework of the 1000 Genomes Project (Gibbs et al 2015)We analyzed 40573 synonymous and 48860 nonsynony-mous SNPs from the Bronze Age group versus 72558 synon-ymous and 96710 nonsynonymous SNPs from the moderngroup using the pipeline shown in figure 2
To test whether there is any genetic continuity betweenthe Bronze Age group and the modern group we applied twodifferent approaches First principal components analysis(PCA) demonstrated that the ancient and modernEuropean individuals are colocated within the same clusterand are separated from modern individuals from other geo-graphic regions (Africa America and Asia) (fig 3)
Second to test whether the analyzed modern individualspossess genetic ancestry of the Bronze Age individuals wemeasured the proportion of the Bronze Age individuals inmodern samples Figure 4 shows that the linear compositionof Bronze Age ancestry in the modern individuals is relativelyhigh and varies from 20 to 90
Therefore we can confidently consider the analyzed mod-ern Europeans to be genetic descendants of the Bronze AgeEuropeans this fact gives us the basis for studying microevo-lution changes that occurred during the past six millennia inEurope
Comparison of Ancient and Modern DataDue to the low coverage of each position on the genome inthe ancient data consideration of individual SNPs for directcomparison of ancient and modern data does not producebiologically or statistically significant results since variant callat each ancient genomic position has limited fidelityTherefore we considered one ancient merged genome andone modern merged genome The ancient merged genomewas assembled from compiling all SNPs of European BronzeAge individuals whereas the modern merged genome wasassembled from all SNPs of modern European individualsGrouping of the SNPs into KEGG biochemical pathways(see Materials and Methods) gave the additional robustnessto the calculations
We assumed that during neutral evolution the same bio-logical pathways in the ancient and in the modern groupsshould accumulate mutations at the same rate whereas un-der selection pressure the rate of accumulation of mutationsin the same pathways should be different Therefore wecalculated two types of enrichment scores for pathways1) differential synonymous SNP enrichment (DSSE) scoresbetween ancient and modern groups and 2) differential non-synonymous SNP enrichment (DNSE) scores for these groups(see Materials and Methods) The enrichment score for eachpathway was calculated as the deviation of the fraction ofancient SNPs in the given pathway from the expected fractionof SNPs in the ancient merged genome Therefore whenthere are more SNPs in the ancient merged genome com-pared with what is expected the enrichment score is positivewhen there are less SNPs in the ancient merged genomecompared with what is expected the enrichment score isnegative Hence a positive enrichment score indicates higherpathway enrichment in the ancient group a negative enrich-ment score indicates higher pathway enrichment in themodern group
Comparative analysis of DSSE scores revealed that none ofthe pathways show significant differences in synonymous SNPenrichment between the ancient and the modern groups(supplementary table 3 Supplementary Material online)
Chekalin et al doi101093molbevmsy201 MBE
128
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
This corresponds to the hypothesis of neutral evolution forthis type of mutations At the same time comparison ofDNSE scores revealed 15 pathways that were differentiallyenriched in nonsynonymous SNPs between the Bronze Ageand modern European individuals (fig 5 and table 1 supple-mentary tables 4 and 5 Supplementary Material online) Wealso normalized nonsynonymous SNPs on synonymous SNPsThe results (fig 6) showed that all P-values of the synonymoustest as well as most P-values of the nonsynonymous test areinside the area of nonsignificant differences (shaded rectan-gle) At the same time P-values of the nonsynonymous testfor 15 differently enriched pathways are outside the area ofnonsignificant differences This confirms the significance ofdifferences in these pathways between ancient and modernEuropeans
The significance of the differences of enrichment scoresbetween the ancient and the modern groups was assessedusing the Bonferroni correction with Plt 001 (table 1)Benjamin et al (2017) proposed to use the threshold ofPlt 0005 (see Materials and Methods) We suggest thatamong 15 revealed pathways the 2 pathways that didnot pass this threshold (pentose and glucuronate intercon-versions and PI3K-Akt signaling pathway) should beinterpreted with caution We also excluded two of thepathways metabolic pathways since this grouping is toogeneral and ascorbate and aldarate metabolism since it isvery reduced in humans and its functions are not unique(Ye and Doak 2009)
Therefore we have identified the following pathways to besignificantly different between the Bronze Age and moderngroups pentose and glucuronate interconversions drugmetabolism by cytochrome P450 chemical carcinogenesisABC transporters antigen processing and presentationgraft-versus-host disease autoimmune thyroid diseasehypertrophic cardiomyopathy olfactory transduction
oocyte meiosis long-term potentiation and dopaminergicsynapse
We also compared the distribution of regulatory SNPsbetween Bronze Age and modern individuals (see Materialsand Methods) A proportion test revealed no difference inenrichment of the KEGG pathways between the ancient andthe modern groups This result was expected since the func-tions of most of the revealed SNPs in the regulatory regionsare not yet known Nonfunctional SNPs contribute to noiseinterfering the detection of functional SNPs (the same situa-tion could happen if we analyzed synonymous and nonsy-nonymous SNPs together)
Verification of the ResultsAs an alternative hypothesis we considered the possibilitythat the obtained results can be explained by insufficientsequence coverage of pathways in Bronze Age individualsTo test this hypothesis we performed the following compu-tations First we calculated the Spearman correlation coeffi-cient between enrichment score and fraction of coveredlength (supplementary fig 1 Supplementary Material online)The coefficient of determination was R2 frac14 01 This impliesthat a change in the coverage can explain only 10 of thevariability of pathway SNP enrichment and cannot be theleading cause of the observed effect Second we analyzedthe median coverage and median length of genes in the path-ways (supplementary fig 2 Supplementary Material online)With the rare exception (three pathways) more than 50 ofindividual genes were covered in the studied pathways Therevealed enriched pathways were clustered together withunenriched pathways Third we calculated average coverageper base pair per sample per pathway and total coverage perbase pair per pathway (supplementary fig 3 SupplementaryMaterial online) In general there is no relationship betweenenrichment and coverage The only exception is olfactory
FIG 1 Location of ancient samples analyzed in the study Data from Allentoft et al (2015) Gamba et al (2014) Haak et al (2015) and Mathiesonet al (2015) (for details see supplementary tables 1 and 2 Supplementary Material online)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
129
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
transduction pathway (supplementary fig 3A SupplementaryMaterial online) whose average coverage per sample is a bitlower in comparison to other pathways However the totalcoverage for this pathway (supplementary fig 3BSupplementary Material online) though a bit lower in com-parison to most of other pathways is not an outlier (there aretwo other pathways with the same coverage which did notshow any difference in enrichment between ancient andmodern groups) For our calculations we used data from
total not average coverage Therefore there is no relationshipbetween enrichment and the genersquos size or coverage
The observed trend might also be the result of generalinterpopulation differences between the two groups Totest this hypothesis we calculated interpopulation differencesbetween modern European groups using the same pathwayenrichment analysis (supplementary table 6 SupplementaryMaterial online) No difference in enrichment in any pathwaywas revealed between present-day Europeans Therefore the
FIG 2 Principal pipeline of the study Analysis for nonsynonymous SNPs is presented All calculations for synonymous SNPs were performed in thesame manner Additional parameters and tool versions are listed in supplementary methods Supplementary Material online
Chekalin et al doi101093molbevmsy201 MBE
130
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
observed differences between the Bronze Age and moderngroups are the results of microevolution changes during thepast 6000 years
DiscussionSince the Late Neolithic the European lifestyle has changeddrastically The main factors determining the relationship be-tween environment and the human body have undergonesignificant alterations For example preagrarian and earlyagrarian populations were exposed to environmental influen-ces from a comparatively small geographical area (Gillingset al 2015) In contrast modern Europeans exist in a global-ized world where global travel (and corresponding environ-mental exposures) as well as different new types of foodclothes and other consumables are common Many newfactors have appeared such as dietary changes new patho-gens new medications as well as high population density andcloser connections between distant groups of people All of
these new conditions inevitably provoke responses from thehuman body
In this paper we studied how introduction of differentcultural practices during the past 6000 years could shapehuman genomes We traced the microevolution of modernEuropeans back to their ancestors carriers of the LateNeolithic and Bronze Age cultures We revealed 13 biologicalpathways that are significantly different between the BronzeAge and modern groups For most of them (except 3) thenumber of nonsynonymous mutations is higher in the mod-ern group than in the Bronze Age group which means theaccumulation of mutations during the past 6000 years In thenext paragraphs we attempt to explain what civilizationevents during the past millennia could have caused thechanges in these pathways
We detected significant changes in a number of pathwaysresponsible for metabolism One of them pentose and glu-curonate interconversions is associated with carbohydratemetabolism In the human organism this pathway mainlydescribes the transformation of UDP-glucose a-D-glucose-1-phosphate and D-xylose (Du et al 2016) We suggest thatchanges in this pathway are the consequences of dramaticdiet modifications arising with the introduction of agriculturean important event that stimulated the Neolithic transitionand progressed during the Bronze Age One of three sub-strates entering the pentose and glucuronate interconver-sions pathway UDP-glucose comes from the galactosemetabolism pathway (Du et al 2016) The main source ofgalactose in the modern human diet is lactose from milk
minus2 minus1 0 1 2
minus6
minus4
minus2
0
Dimension 1
Dim
en
sio
n 2
Bronze Age Europe
Modern Europe
Africa
Asia
America
minus6 minus4 minus2 0 2 4
02
46
Dimension 1
Dim
en
sio
n 2
Bronze Age individuals n=150
Modern Europeans n=305
A
B
FIG 3 Principal component analysis (A) World groups and (B)European groups
00
02
04
06
08
10
English
Iberian
Toscani
Bronze Age
Early Neolithic
Western European hunterminusgatherers
Unassigned
FIG 4 Proportion of ancient genomes in modern Europeanindividuals
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
131
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
The earliest stages of human civilization are the LateNeolithic Age and the Bronze Age These were the epochsthat gave rise to our present lifestyle The 6000 years betweenthat period and modern times encompass the greater part ofhuman civilization events In this paper we study the geneticconsequences of these cultural events
Many different approaches are used to reveal and analyzepossible selection signals (Voight et al 2006 Sabeti et al 2007Tang et al 2007 Williamson et al 2007 Quach et al 2009Grossman et al 2013 Mathieson et al 2015 Field et al 2016)Most are based on modern human genome-wide data andtherefore represent indirect evidence of selection Objectiveinformation can be obtained by direct comparison of ancientand modern human genomes The first steps in this directionwere made relatively recently they became possible thanks towhole-genome next generation sequencing of ancient sam-ples These studies have revealed selection signatures in singlenucleotide polymorphisms (SNPs) associated with skin pig-mentation diet and immunity as well as with some complextraits that is human height (Olalde et al 2014 Allentoft et al2015 Mathieson et al 2015 Dannemann et al 2016 Fu et al2016)
Providing that natural selection should act through phe-notypes we assume that selection signals for multigenic traitsshould be analyzed not only at the level of individual SNPs butalso at the level of biological pathways where the influence ofindividual SNPs is aggregated into functional groups Thisapproach has been previously used for instance to studyselection signatures between human and chimpanzee line-ages (Somel et al 2013) In the present study we appliedpathway analysis to low-covered whole-genome ancientDNA sequence data We compared data on European LateNeolithicBronze Age individuals (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) with those from modern European individuals(httpwwwinternationalgenomeorg) supposedly ofBronze Age ancestry and occupying the same geographicalarea as their ancestors Our aims were 1) to reveal nonsynon-ymous SNPs in ancient and modern groups 2) to associatethese SNPs with biological pathways and 3) to calculate thedifferences in pathway enrichment between the ancient andmodern groups The revealed differences indicate the pro-cesses that we suppose have been shaped by introductionof human cultural practices during the past 6000 years
Results
Compatibility of the DataWe compared whole-genome data from 150 ancient samples(supplementary tables 1 and 2 Supplementary Material on-line) dated between 3500 and 1000 BCE (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al 2015)(fig 1) with data on 305 modern Europeans genotyped in theframework of the 1000 Genomes Project (Gibbs et al 2015)We analyzed 40573 synonymous and 48860 nonsynony-mous SNPs from the Bronze Age group versus 72558 synon-ymous and 96710 nonsynonymous SNPs from the moderngroup using the pipeline shown in figure 2
To test whether there is any genetic continuity betweenthe Bronze Age group and the modern group we applied twodifferent approaches First principal components analysis(PCA) demonstrated that the ancient and modernEuropean individuals are colocated within the same clusterand are separated from modern individuals from other geo-graphic regions (Africa America and Asia) (fig 3)
Second to test whether the analyzed modern individualspossess genetic ancestry of the Bronze Age individuals wemeasured the proportion of the Bronze Age individuals inmodern samples Figure 4 shows that the linear compositionof Bronze Age ancestry in the modern individuals is relativelyhigh and varies from 20 to 90
Therefore we can confidently consider the analyzed mod-ern Europeans to be genetic descendants of the Bronze AgeEuropeans this fact gives us the basis for studying microevo-lution changes that occurred during the past six millennia inEurope
Comparison of Ancient and Modern DataDue to the low coverage of each position on the genome inthe ancient data consideration of individual SNPs for directcomparison of ancient and modern data does not producebiologically or statistically significant results since variant callat each ancient genomic position has limited fidelityTherefore we considered one ancient merged genome andone modern merged genome The ancient merged genomewas assembled from compiling all SNPs of European BronzeAge individuals whereas the modern merged genome wasassembled from all SNPs of modern European individualsGrouping of the SNPs into KEGG biochemical pathways(see Materials and Methods) gave the additional robustnessto the calculations
We assumed that during neutral evolution the same bio-logical pathways in the ancient and in the modern groupsshould accumulate mutations at the same rate whereas un-der selection pressure the rate of accumulation of mutationsin the same pathways should be different Therefore wecalculated two types of enrichment scores for pathways1) differential synonymous SNP enrichment (DSSE) scoresbetween ancient and modern groups and 2) differential non-synonymous SNP enrichment (DNSE) scores for these groups(see Materials and Methods) The enrichment score for eachpathway was calculated as the deviation of the fraction ofancient SNPs in the given pathway from the expected fractionof SNPs in the ancient merged genome Therefore whenthere are more SNPs in the ancient merged genome com-pared with what is expected the enrichment score is positivewhen there are less SNPs in the ancient merged genomecompared with what is expected the enrichment score isnegative Hence a positive enrichment score indicates higherpathway enrichment in the ancient group a negative enrich-ment score indicates higher pathway enrichment in themodern group
Comparative analysis of DSSE scores revealed that none ofthe pathways show significant differences in synonymous SNPenrichment between the ancient and the modern groups(supplementary table 3 Supplementary Material online)
Chekalin et al doi101093molbevmsy201 MBE
128
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
This corresponds to the hypothesis of neutral evolution forthis type of mutations At the same time comparison ofDNSE scores revealed 15 pathways that were differentiallyenriched in nonsynonymous SNPs between the Bronze Ageand modern European individuals (fig 5 and table 1 supple-mentary tables 4 and 5 Supplementary Material online) Wealso normalized nonsynonymous SNPs on synonymous SNPsThe results (fig 6) showed that all P-values of the synonymoustest as well as most P-values of the nonsynonymous test areinside the area of nonsignificant differences (shaded rectan-gle) At the same time P-values of the nonsynonymous testfor 15 differently enriched pathways are outside the area ofnonsignificant differences This confirms the significance ofdifferences in these pathways between ancient and modernEuropeans
The significance of the differences of enrichment scoresbetween the ancient and the modern groups was assessedusing the Bonferroni correction with Plt 001 (table 1)Benjamin et al (2017) proposed to use the threshold ofPlt 0005 (see Materials and Methods) We suggest thatamong 15 revealed pathways the 2 pathways that didnot pass this threshold (pentose and glucuronate intercon-versions and PI3K-Akt signaling pathway) should beinterpreted with caution We also excluded two of thepathways metabolic pathways since this grouping is toogeneral and ascorbate and aldarate metabolism since it isvery reduced in humans and its functions are not unique(Ye and Doak 2009)
Therefore we have identified the following pathways to besignificantly different between the Bronze Age and moderngroups pentose and glucuronate interconversions drugmetabolism by cytochrome P450 chemical carcinogenesisABC transporters antigen processing and presentationgraft-versus-host disease autoimmune thyroid diseasehypertrophic cardiomyopathy olfactory transduction
oocyte meiosis long-term potentiation and dopaminergicsynapse
We also compared the distribution of regulatory SNPsbetween Bronze Age and modern individuals (see Materialsand Methods) A proportion test revealed no difference inenrichment of the KEGG pathways between the ancient andthe modern groups This result was expected since the func-tions of most of the revealed SNPs in the regulatory regionsare not yet known Nonfunctional SNPs contribute to noiseinterfering the detection of functional SNPs (the same situa-tion could happen if we analyzed synonymous and nonsy-nonymous SNPs together)
Verification of the ResultsAs an alternative hypothesis we considered the possibilitythat the obtained results can be explained by insufficientsequence coverage of pathways in Bronze Age individualsTo test this hypothesis we performed the following compu-tations First we calculated the Spearman correlation coeffi-cient between enrichment score and fraction of coveredlength (supplementary fig 1 Supplementary Material online)The coefficient of determination was R2 frac14 01 This impliesthat a change in the coverage can explain only 10 of thevariability of pathway SNP enrichment and cannot be theleading cause of the observed effect Second we analyzedthe median coverage and median length of genes in the path-ways (supplementary fig 2 Supplementary Material online)With the rare exception (three pathways) more than 50 ofindividual genes were covered in the studied pathways Therevealed enriched pathways were clustered together withunenriched pathways Third we calculated average coverageper base pair per sample per pathway and total coverage perbase pair per pathway (supplementary fig 3 SupplementaryMaterial online) In general there is no relationship betweenenrichment and coverage The only exception is olfactory
FIG 1 Location of ancient samples analyzed in the study Data from Allentoft et al (2015) Gamba et al (2014) Haak et al (2015) and Mathiesonet al (2015) (for details see supplementary tables 1 and 2 Supplementary Material online)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
129
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
transduction pathway (supplementary fig 3A SupplementaryMaterial online) whose average coverage per sample is a bitlower in comparison to other pathways However the totalcoverage for this pathway (supplementary fig 3BSupplementary Material online) though a bit lower in com-parison to most of other pathways is not an outlier (there aretwo other pathways with the same coverage which did notshow any difference in enrichment between ancient andmodern groups) For our calculations we used data from
total not average coverage Therefore there is no relationshipbetween enrichment and the genersquos size or coverage
The observed trend might also be the result of generalinterpopulation differences between the two groups Totest this hypothesis we calculated interpopulation differencesbetween modern European groups using the same pathwayenrichment analysis (supplementary table 6 SupplementaryMaterial online) No difference in enrichment in any pathwaywas revealed between present-day Europeans Therefore the
FIG 2 Principal pipeline of the study Analysis for nonsynonymous SNPs is presented All calculations for synonymous SNPs were performed in thesame manner Additional parameters and tool versions are listed in supplementary methods Supplementary Material online
Chekalin et al doi101093molbevmsy201 MBE
130
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
observed differences between the Bronze Age and moderngroups are the results of microevolution changes during thepast 6000 years
DiscussionSince the Late Neolithic the European lifestyle has changeddrastically The main factors determining the relationship be-tween environment and the human body have undergonesignificant alterations For example preagrarian and earlyagrarian populations were exposed to environmental influen-ces from a comparatively small geographical area (Gillingset al 2015) In contrast modern Europeans exist in a global-ized world where global travel (and corresponding environ-mental exposures) as well as different new types of foodclothes and other consumables are common Many newfactors have appeared such as dietary changes new patho-gens new medications as well as high population density andcloser connections between distant groups of people All of
these new conditions inevitably provoke responses from thehuman body
In this paper we studied how introduction of differentcultural practices during the past 6000 years could shapehuman genomes We traced the microevolution of modernEuropeans back to their ancestors carriers of the LateNeolithic and Bronze Age cultures We revealed 13 biologicalpathways that are significantly different between the BronzeAge and modern groups For most of them (except 3) thenumber of nonsynonymous mutations is higher in the mod-ern group than in the Bronze Age group which means theaccumulation of mutations during the past 6000 years In thenext paragraphs we attempt to explain what civilizationevents during the past millennia could have caused thechanges in these pathways
We detected significant changes in a number of pathwaysresponsible for metabolism One of them pentose and glu-curonate interconversions is associated with carbohydratemetabolism In the human organism this pathway mainlydescribes the transformation of UDP-glucose a-D-glucose-1-phosphate and D-xylose (Du et al 2016) We suggest thatchanges in this pathway are the consequences of dramaticdiet modifications arising with the introduction of agriculturean important event that stimulated the Neolithic transitionand progressed during the Bronze Age One of three sub-strates entering the pentose and glucuronate interconver-sions pathway UDP-glucose comes from the galactosemetabolism pathway (Du et al 2016) The main source ofgalactose in the modern human diet is lactose from milk
minus2 minus1 0 1 2
minus6
minus4
minus2
0
Dimension 1
Dim
en
sio
n 2
Bronze Age Europe
Modern Europe
Africa
Asia
America
minus6 minus4 minus2 0 2 4
02
46
Dimension 1
Dim
en
sio
n 2
Bronze Age individuals n=150
Modern Europeans n=305
A
B
FIG 3 Principal component analysis (A) World groups and (B)European groups
00
02
04
06
08
10
English
Iberian
Toscani
Bronze Age
Early Neolithic
Western European hunterminusgatherers
Unassigned
FIG 4 Proportion of ancient genomes in modern Europeanindividuals
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
131
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
This corresponds to the hypothesis of neutral evolution forthis type of mutations At the same time comparison ofDNSE scores revealed 15 pathways that were differentiallyenriched in nonsynonymous SNPs between the Bronze Ageand modern European individuals (fig 5 and table 1 supple-mentary tables 4 and 5 Supplementary Material online) Wealso normalized nonsynonymous SNPs on synonymous SNPsThe results (fig 6) showed that all P-values of the synonymoustest as well as most P-values of the nonsynonymous test areinside the area of nonsignificant differences (shaded rectan-gle) At the same time P-values of the nonsynonymous testfor 15 differently enriched pathways are outside the area ofnonsignificant differences This confirms the significance ofdifferences in these pathways between ancient and modernEuropeans
The significance of the differences of enrichment scoresbetween the ancient and the modern groups was assessedusing the Bonferroni correction with Plt 001 (table 1)Benjamin et al (2017) proposed to use the threshold ofPlt 0005 (see Materials and Methods) We suggest thatamong 15 revealed pathways the 2 pathways that didnot pass this threshold (pentose and glucuronate intercon-versions and PI3K-Akt signaling pathway) should beinterpreted with caution We also excluded two of thepathways metabolic pathways since this grouping is toogeneral and ascorbate and aldarate metabolism since it isvery reduced in humans and its functions are not unique(Ye and Doak 2009)
Therefore we have identified the following pathways to besignificantly different between the Bronze Age and moderngroups pentose and glucuronate interconversions drugmetabolism by cytochrome P450 chemical carcinogenesisABC transporters antigen processing and presentationgraft-versus-host disease autoimmune thyroid diseasehypertrophic cardiomyopathy olfactory transduction
oocyte meiosis long-term potentiation and dopaminergicsynapse
We also compared the distribution of regulatory SNPsbetween Bronze Age and modern individuals (see Materialsand Methods) A proportion test revealed no difference inenrichment of the KEGG pathways between the ancient andthe modern groups This result was expected since the func-tions of most of the revealed SNPs in the regulatory regionsare not yet known Nonfunctional SNPs contribute to noiseinterfering the detection of functional SNPs (the same situa-tion could happen if we analyzed synonymous and nonsy-nonymous SNPs together)
Verification of the ResultsAs an alternative hypothesis we considered the possibilitythat the obtained results can be explained by insufficientsequence coverage of pathways in Bronze Age individualsTo test this hypothesis we performed the following compu-tations First we calculated the Spearman correlation coeffi-cient between enrichment score and fraction of coveredlength (supplementary fig 1 Supplementary Material online)The coefficient of determination was R2 frac14 01 This impliesthat a change in the coverage can explain only 10 of thevariability of pathway SNP enrichment and cannot be theleading cause of the observed effect Second we analyzedthe median coverage and median length of genes in the path-ways (supplementary fig 2 Supplementary Material online)With the rare exception (three pathways) more than 50 ofindividual genes were covered in the studied pathways Therevealed enriched pathways were clustered together withunenriched pathways Third we calculated average coverageper base pair per sample per pathway and total coverage perbase pair per pathway (supplementary fig 3 SupplementaryMaterial online) In general there is no relationship betweenenrichment and coverage The only exception is olfactory
FIG 1 Location of ancient samples analyzed in the study Data from Allentoft et al (2015) Gamba et al (2014) Haak et al (2015) and Mathiesonet al (2015) (for details see supplementary tables 1 and 2 Supplementary Material online)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
129
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
transduction pathway (supplementary fig 3A SupplementaryMaterial online) whose average coverage per sample is a bitlower in comparison to other pathways However the totalcoverage for this pathway (supplementary fig 3BSupplementary Material online) though a bit lower in com-parison to most of other pathways is not an outlier (there aretwo other pathways with the same coverage which did notshow any difference in enrichment between ancient andmodern groups) For our calculations we used data from
total not average coverage Therefore there is no relationshipbetween enrichment and the genersquos size or coverage
The observed trend might also be the result of generalinterpopulation differences between the two groups Totest this hypothesis we calculated interpopulation differencesbetween modern European groups using the same pathwayenrichment analysis (supplementary table 6 SupplementaryMaterial online) No difference in enrichment in any pathwaywas revealed between present-day Europeans Therefore the
FIG 2 Principal pipeline of the study Analysis for nonsynonymous SNPs is presented All calculations for synonymous SNPs were performed in thesame manner Additional parameters and tool versions are listed in supplementary methods Supplementary Material online
Chekalin et al doi101093molbevmsy201 MBE
130
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
observed differences between the Bronze Age and moderngroups are the results of microevolution changes during thepast 6000 years
DiscussionSince the Late Neolithic the European lifestyle has changeddrastically The main factors determining the relationship be-tween environment and the human body have undergonesignificant alterations For example preagrarian and earlyagrarian populations were exposed to environmental influen-ces from a comparatively small geographical area (Gillingset al 2015) In contrast modern Europeans exist in a global-ized world where global travel (and corresponding environ-mental exposures) as well as different new types of foodclothes and other consumables are common Many newfactors have appeared such as dietary changes new patho-gens new medications as well as high population density andcloser connections between distant groups of people All of
these new conditions inevitably provoke responses from thehuman body
In this paper we studied how introduction of differentcultural practices during the past 6000 years could shapehuman genomes We traced the microevolution of modernEuropeans back to their ancestors carriers of the LateNeolithic and Bronze Age cultures We revealed 13 biologicalpathways that are significantly different between the BronzeAge and modern groups For most of them (except 3) thenumber of nonsynonymous mutations is higher in the mod-ern group than in the Bronze Age group which means theaccumulation of mutations during the past 6000 years In thenext paragraphs we attempt to explain what civilizationevents during the past millennia could have caused thechanges in these pathways
We detected significant changes in a number of pathwaysresponsible for metabolism One of them pentose and glu-curonate interconversions is associated with carbohydratemetabolism In the human organism this pathway mainlydescribes the transformation of UDP-glucose a-D-glucose-1-phosphate and D-xylose (Du et al 2016) We suggest thatchanges in this pathway are the consequences of dramaticdiet modifications arising with the introduction of agriculturean important event that stimulated the Neolithic transitionand progressed during the Bronze Age One of three sub-strates entering the pentose and glucuronate interconver-sions pathway UDP-glucose comes from the galactosemetabolism pathway (Du et al 2016) The main source ofgalactose in the modern human diet is lactose from milk
minus2 minus1 0 1 2
minus6
minus4
minus2
0
Dimension 1
Dim
en
sio
n 2
Bronze Age Europe
Modern Europe
Africa
Asia
America
minus6 minus4 minus2 0 2 4
02
46
Dimension 1
Dim
en
sio
n 2
Bronze Age individuals n=150
Modern Europeans n=305
A
B
FIG 3 Principal component analysis (A) World groups and (B)European groups
00
02
04
06
08
10
English
Iberian
Toscani
Bronze Age
Early Neolithic
Western European hunterminusgatherers
Unassigned
FIG 4 Proportion of ancient genomes in modern Europeanindividuals
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
131
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
transduction pathway (supplementary fig 3A SupplementaryMaterial online) whose average coverage per sample is a bitlower in comparison to other pathways However the totalcoverage for this pathway (supplementary fig 3BSupplementary Material online) though a bit lower in com-parison to most of other pathways is not an outlier (there aretwo other pathways with the same coverage which did notshow any difference in enrichment between ancient andmodern groups) For our calculations we used data from
total not average coverage Therefore there is no relationshipbetween enrichment and the genersquos size or coverage
The observed trend might also be the result of generalinterpopulation differences between the two groups Totest this hypothesis we calculated interpopulation differencesbetween modern European groups using the same pathwayenrichment analysis (supplementary table 6 SupplementaryMaterial online) No difference in enrichment in any pathwaywas revealed between present-day Europeans Therefore the
FIG 2 Principal pipeline of the study Analysis for nonsynonymous SNPs is presented All calculations for synonymous SNPs were performed in thesame manner Additional parameters and tool versions are listed in supplementary methods Supplementary Material online
Chekalin et al doi101093molbevmsy201 MBE
130
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
observed differences between the Bronze Age and moderngroups are the results of microevolution changes during thepast 6000 years
DiscussionSince the Late Neolithic the European lifestyle has changeddrastically The main factors determining the relationship be-tween environment and the human body have undergonesignificant alterations For example preagrarian and earlyagrarian populations were exposed to environmental influen-ces from a comparatively small geographical area (Gillingset al 2015) In contrast modern Europeans exist in a global-ized world where global travel (and corresponding environ-mental exposures) as well as different new types of foodclothes and other consumables are common Many newfactors have appeared such as dietary changes new patho-gens new medications as well as high population density andcloser connections between distant groups of people All of
these new conditions inevitably provoke responses from thehuman body
In this paper we studied how introduction of differentcultural practices during the past 6000 years could shapehuman genomes We traced the microevolution of modernEuropeans back to their ancestors carriers of the LateNeolithic and Bronze Age cultures We revealed 13 biologicalpathways that are significantly different between the BronzeAge and modern groups For most of them (except 3) thenumber of nonsynonymous mutations is higher in the mod-ern group than in the Bronze Age group which means theaccumulation of mutations during the past 6000 years In thenext paragraphs we attempt to explain what civilizationevents during the past millennia could have caused thechanges in these pathways
We detected significant changes in a number of pathwaysresponsible for metabolism One of them pentose and glu-curonate interconversions is associated with carbohydratemetabolism In the human organism this pathway mainlydescribes the transformation of UDP-glucose a-D-glucose-1-phosphate and D-xylose (Du et al 2016) We suggest thatchanges in this pathway are the consequences of dramaticdiet modifications arising with the introduction of agriculturean important event that stimulated the Neolithic transitionand progressed during the Bronze Age One of three sub-strates entering the pentose and glucuronate interconver-sions pathway UDP-glucose comes from the galactosemetabolism pathway (Du et al 2016) The main source ofgalactose in the modern human diet is lactose from milk
minus2 minus1 0 1 2
minus6
minus4
minus2
0
Dimension 1
Dim
en
sio
n 2
Bronze Age Europe
Modern Europe
Africa
Asia
America
minus6 minus4 minus2 0 2 4
02
46
Dimension 1
Dim
en
sio
n 2
Bronze Age individuals n=150
Modern Europeans n=305
A
B
FIG 3 Principal component analysis (A) World groups and (B)European groups
00
02
04
06
08
10
English
Iberian
Toscani
Bronze Age
Early Neolithic
Western European hunterminusgatherers
Unassigned
FIG 4 Proportion of ancient genomes in modern Europeanindividuals
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
131
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
observed differences between the Bronze Age and moderngroups are the results of microevolution changes during thepast 6000 years
DiscussionSince the Late Neolithic the European lifestyle has changeddrastically The main factors determining the relationship be-tween environment and the human body have undergonesignificant alterations For example preagrarian and earlyagrarian populations were exposed to environmental influen-ces from a comparatively small geographical area (Gillingset al 2015) In contrast modern Europeans exist in a global-ized world where global travel (and corresponding environ-mental exposures) as well as different new types of foodclothes and other consumables are common Many newfactors have appeared such as dietary changes new patho-gens new medications as well as high population density andcloser connections between distant groups of people All of
these new conditions inevitably provoke responses from thehuman body
In this paper we studied how introduction of differentcultural practices during the past 6000 years could shapehuman genomes We traced the microevolution of modernEuropeans back to their ancestors carriers of the LateNeolithic and Bronze Age cultures We revealed 13 biologicalpathways that are significantly different between the BronzeAge and modern groups For most of them (except 3) thenumber of nonsynonymous mutations is higher in the mod-ern group than in the Bronze Age group which means theaccumulation of mutations during the past 6000 years In thenext paragraphs we attempt to explain what civilizationevents during the past millennia could have caused thechanges in these pathways
We detected significant changes in a number of pathwaysresponsible for metabolism One of them pentose and glu-curonate interconversions is associated with carbohydratemetabolism In the human organism this pathway mainlydescribes the transformation of UDP-glucose a-D-glucose-1-phosphate and D-xylose (Du et al 2016) We suggest thatchanges in this pathway are the consequences of dramaticdiet modifications arising with the introduction of agriculturean important event that stimulated the Neolithic transitionand progressed during the Bronze Age One of three sub-strates entering the pentose and glucuronate interconver-sions pathway UDP-glucose comes from the galactosemetabolism pathway (Du et al 2016) The main source ofgalactose in the modern human diet is lactose from milk
minus2 minus1 0 1 2
minus6
minus4
minus2
0
Dimension 1
Dim
en
sio
n 2
Bronze Age Europe
Modern Europe
Africa
Asia
America
minus6 minus4 minus2 0 2 4
02
46
Dimension 1
Dim
en
sio
n 2
Bronze Age individuals n=150
Modern Europeans n=305
A
B
FIG 3 Principal component analysis (A) World groups and (B)European groups
00
02
04
06
08
10
English
Iberian
Toscani
Bronze Age
Early Neolithic
Western European hunterminusgatherers
Unassigned
FIG 4 Proportion of ancient genomes in modern Europeanindividuals
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
131
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
Humans are the only mammals who have the ability to utilizelactose in adulthood This ability is provided by a single mu-tation in an enhancer region of the lactase gene (LCT) whoseproduct lactase a participant in the galactose metabolismpathway breaks down lactose (Lewinsky et al 2005Enattah et al 2008) It is believed that in Europe the LCTmutation arose in the Bronze Age or somewhat earlier as aresult of milking (Holden and Mace 1997 Gamba et al 2014Allentoft et al 2015) In modern Europe the mutation fre-quency is up to 100 (Gerbault et al 2011) indicating strongpositive selection of this gene Apparently such a significant
change in the galactose metabolism pathway could stronglyaffect the product (UDP-glucose) yield which in turn couldmodify the next pathway pentose and glucuronate intercon-versions Other substrates for the pentose and glucuronateinterconversions pathway are a-D-glucose-1-phosphate theproduct of glycolysis and D-xylose entering from the starchand sucrose metabolism pathway (Du et al 2016) Glucoseand starch dairy intake has changed dramatically during thepast 6000 years As a result of agriculture the ratio ofcarbohydrate-rich food especially grain-based products hasincreased significantly in the human diet (Cordain et al 2005)This ratio further increased after the Industrial transition inthe 18ndash19th century after which industrially processed flourand sugar became commonly available (Cordain et al 2005Adler et al 2013) Therefore we suppose that changes innutrient consumption and thus in the metabolism of sub-strates for the pentose and glucuronate interconversionspathway have caused an accumulation of nonsynonymousmutations which could modify this pathway
Other metabolic pathways are associated with the trans-formation of xenobiotics They include drug metabolism bycytochrome P450 and chemical carcinogenesis (two closelyrelated pathways metabolism of xenobiotics by cytochromeP450 and drug metabolism by other enzymes have passedonly the BenjaminindashHochberg correction and not theBonferroni one (supplementary tables 3 and 4
minus1
0minus
50
51
0
DN
SE
sco
re p
er
pa
thw
ay
Metabolism
Immune system
Physical activity
Sensory transduction
Reproduction
Cognitive function
Pen
tose
an
d g
lucu
ron
ate
inte
rco
nve
rsio
ns
Dru
g m
eta
bo
lism
cyto
ch
rom
e P
45
0
Ch
em
ica
l ca
rcin
og
en
esis
AB
C tra
nsport
ers
An
tig
en
pro
ce
ssin
ga
nd
pre
se
nta
tio
n
PI3
Kminus
Akt
sig
na
ling
pa
thw
ay
Gra
ftminus
vers
usminus
ho
st
dis
ea
se
Au
toim
mu
ne
thyro
iddis
ease
Hyp
ert
rop
hic
ca
rdio
myo
pa
thy
Olfa
cto
ry t
ran
sd
uctio
n
Oo
cyte
me
iosis
Lo
ng
minuste
rm p
ote
ntia
tio
n
Do
pa
min
erg
ic s
yn
ap
se
FIG 5 Differential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathwaysthat have more SNPs in genomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes ofmodern Europeans
FIG 6 Relationship between the P-values for synonymous and non-synonymous SNPs in the studied pathways
Chekalin et al doi101093molbevmsy201 MBE
132
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
Supplementary Material online) These pathways are closelyconnected because they have partially overlapping mecha-nisms (Lang and Pelkonen 1999 Oliveira et al 2007) (indeedthe chemical carcinogenesis pathway shares approximately70 of genes with the cytochrome P450 metabolic pathway[supplementary table 7 Supplementary Material online])During the past several millennia substantial changes in hu-man lifestyle were accompanied by the introduction of largeamounts of different xenobiotics (including new types offood alcoholic beverages and microbial toxins) Some ofthem (such as medications plant fertilizers and food addi-tives) are supposed to improve the quality of human lifeOthers (such as heavy metals and other pollutants) are sideeffects of civilization activities All of these substances canshape human genomes by causing mutations (directly or in-directly) or by inducing natural selection Our results suggestthat new environmental factors in the form of xenobioticshave induced genomic responses via increasing gene variabil-ity and as a result modification of corresponding pathwaysUnfortunately we can see not only this adaptation but alsoan increase in the number of mutations in the chemical car-cinogenesis pathway
The ABC transporters pathway can be considered a partof the human metabolic system Human ABC transportergenes encode transmembrane pumps that transport varioussubstrates (including amino acids lipids proteins inorganicions drugs and other xenobiotics) against concentration gra-dients (Stefkova et al 2004 Pohl et al 2005 Vasiliou et al2009 Moitra and Dean 2011) Therefore changes in thequantity or quality of these substrates through diet mod-ifications or introduction of xenobiotics could also affectgenes encoding these transport proteins Interestingly
signals of positive selection were detected earlier insome genes associated with transport of vitamins andcofactors (Voight et al 2006 Tang et al 2007) In aggre-gate these data suggest that changes in lifestyle have in-duced genetic modifications in a system for transport ofnutrients and xenobiotics in the human body during thepast several millennia
Antigen processing and presentation is a very importantpart of the adaptive immune system which is evolutionarilyyoung and very reactive to environmental factors It is the firstline of host immune defense that recognizes and initiatesimmune responses to a broad range of alien agents Themajor histocompatibility complex (MHC) plays the most im-portant role in this process Due to a very specific mechanismof antigen interaction MHC proteins are highly diverse andthe genes encoding them (human leukocyte antigen genesHLA) are the fastest evolving genes in the human body (Blumet al 2013 Forni et al 2014) Unsurprisingly the antigenprocessing and presentation pathway has been shaped duringthe past 6000 years The introduction of farming which led toexposure to a huge variety of new pathogens as well as othercivilization factors such as urbanization (thus increasing pop-ulation density insufficient sanitation peridomestic animalsetc) and development of trading routes increasing the prob-ability of disease spread etc has changed the pathogenicenvironment drastically Major pandemics such as the plaguein Europe could have also played a very important role in theselection of immune system genes (Barnes et al 2011DeWitte 2014 Laayouni et al 2014) It is quite possible thatmodern medicine has also been modifying the genetic mech-anism of immune response This issue still needs extensiveresearch
Table 1 Biological Pathways Differently Enriched in Ancient and Modern Groups
Pathway ID Pathway Name AncientSNPs
Count
ModernSNPs
Count
DNSEScore
P-value P-value AdjustedBonferroni
EnrichedBonferroni 001
Threshold
EnrichedBonferroni 0005
Threshold
hsa00040 Pentose and glucuronateinterconversions
26 117 2429 175310205 505310203 Modern No
hsa00053 Ascorbate and aldaratemetabolism
20 99 2420 269310205 777310203 Modern No
hsa00982 Drug metabolismmdashcytochromeP450
84 259 2438 120310205 348310203 Modern Modern
hsa01100 Metabolic pathways 2512 4982 2469 276310206 798310204 Modern Modernhsa02010 ABC transporters 209 533 2444 893310206 258310203 Modern Modernhsa04114 Oocyte meiosis 298 337 558 241310208 697310206 Ancient Ancienthsa04151 PI3K-Akt signaling pathway 969 2019 2418 294310205 850310203 Modern Nohsa04612 Antigen processing and
presentation232 578 2437 127310205 366310203 Modern Modern
hsa04720 Long-term potentiation 202 215 513 291310207 841310205 Ancient Ancienthsa04728 Dopaminergic synapse 294 365 445 861310206 249310203 Ancient Ancienthsa04740 Olfactory transduction 756 1817 2709 135310212 389310210 Modern Modernhsa05204 Chemical carcinogenesis 101 305 2462 386310206 112310203 Modern Modernhsa05320 Autoimmune thyroid disease 181 482 2465 325310206 938310204 Modern Modernhsa05332 Graft-versus-host disease 166 444 2450 671310206 194310203 Modern Modernhsa05410 Hypertrophic cardiomyopathy
(HCM)347 843 2495 748310207 216310204 Modern Modern
NOTEmdashDifferential SNP enrichment of KEGG pathways between ancient and modern individuals Positive DNSE values correspond to pathways that have more SNPs ingenomes of ancient individuals whereas negative DNSE values correspond to pathways that have more SNPs in genomes of modern Europeans
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
133
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
Graft-versus-host disease is considered by clinicians to be adisorder but from the evolutionary point of view it representsa powerful system of immune response to alien agents Thisalloimmunity is evolutionarily ancient and seems to be anldquounavoidable consequencerdquo of a natural mechanism of anti-gen processing and presentation (Lakkis and Lechler 2013)Indeed graft-versus-host disease shares 71 of commongenes with the antigen processing and presentation pathway(most of them are HLA-genes) (supplementary table 7Supplementary Material online) Being an inseparable partof the human defense system alloimmunity should evolvetogether with it Therefore we suppose that all the above-mentioned factors that caused changes in the antigen proc-essing and presentation process should act similarly on thegraft-versus-host disease pathway
Another pathway connected with antigen processing andpresentation is connected to autoimmunity We revealed se-lection signals for autoimmune thyroid disease It shares 37of genes (all of them belong to HLA group) with the antigenprocessing and presentation pathway (supplementary table 7Supplementary Material online) Therefore the emergence ofthis autoimmune disease is probably a cost of the fast adapt-ing antigen processing and presentation system however webelieve that there are additional environmental factors thatcontributed to the intensive evolution of this particular dis-order Autoimmune thyroid disease is a syndrome character-ized by chronic inflammation of the thyroid It is believed tobe specific for Homo sapiens (Aliesky et al 2013) but it isunknown when this disease appeared in the human popula-tion Currently autoimmune thyroiditis is quite common inthe European population (Vanderpump 2011) It can proba-bly be connected with the increased carbohydrate uptakeafter introduction of agriculture which in turn has increasedthyroid hormone levels in the human body (Kopp 2004)Increased levels of thyroid hormone especially in combina-tion with inappropriate iodine supply cause several detri-mental systemic disorders (Motomura and Brent 1998Kopp 2004) Therefore we assume that the emergence ofnew nonsynonymous mutations is probably an organismalreaction to this new hormonal status Hypothetically thisreaction could be a kind of prevention mechanism or onthe contrary a consequence of thyroid hyperfunction
We revealed significant changes in the PI3K-Akt signalingpathway It is one of the universal signaling pathways whichare active in most of the human bodyrsquos cells It is responsiblefor a variety of fundamental processes such as apoptosiscellular growth proliferation cell survival metabolism andothers (Song et al 2005 Engelman et al 2006 Duronio 2008De Santis et al 2017) This pathway was shown to play animportant role in immunity cancer and long-term potenti-ation (Fresno Vara et al 2004 Hou and Klann 2004 Sui et al2008 Weichhart and Saemann 2008 Porta et al 2014 Chenet al 2017 Pons-Tostivint et al 2017) The PI3K-Akt signalingpathway is activated by different stimuli including antigensinflammation environmental toxicants and drugs (Song et al2005 Engelman et al 2006 Duronio 2008 De Santis et al2017) Therefore any of the factors described above (changesin diet pathogen environment xenobiotics) could affect this
pathway and stimulate accumulation of nonsynonymousmutations in it
The hypertrophic cardiomyopathy (HCM) pathway alsoshows signals of selection during the past 6000 years HCMis an autosomal dominant disease which is manifested as afunctional impairment of the heart It occurs in approxi-mately 02 of modern populations (Cirino and Ho 1993Marian 2010) The course of the disease is very often asymp-tomatic however in some cases especially with intensivephysical activity a sudden cardiac death can occur For ex-ample hypertrophic cardiomyopathy is the leading cause ofsudden cardiac death in young athletes (American College ofCardiology FoundationAmerican Heart Association TaskForce on Practice Guidelines et al 2011 Barsheshet et al2011) We suppose that the higher prevalence of nonsynon-ymous SNPs in the modern group in comparison to the an-cient group can be a consequence of the gradual change inEuropean lifestyle from pretechnological agrarians to modernpostindustrial societies a redistribution of physical load aswell as of balance between calorie uptake and physical activity(Lightfoot 2013) Genetic monitoring and adequate therapy(American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines et al 2011Cirino and Ho 1993) probably also play a role in the accumu-lation of HCM-associated mutations in modern Europeansand therefore one can expect an even higher frequency ofthese mutations in the future
Olfactory transduction the capacity to discriminate odorsshows the strongest signal of selection (table 1) As reportedbefore olfactory genes in primates have a tendency to pseu-dogenization (Gilad Man et al 2003 Pierron et al 2013Somel et al 2013) In humans approximately 60ndash70 ofolfactory genes are pseudogenes this probably reflects a de-creasing need for olfactory perception in great apes and es-pecially in humans (Rouquier et al 1998 Gilad Bustamanteet al 2003) Indeed relaxed selection has been described formost human olfactory genes (Gilad Bustamante et al 2003Somel et al 2013) leading to fast accumulation of mutationsin these genes (Miyata and Hayashida 1981 Gilad Man et al2003) According to our results this process has also beentaking place during recent human microevolution Mostlikely the process of pseudogenization of olfactory genes isstill ongoing At the same time we cannot exclude the pos-sibility that introduction of new cultural practices (new typesof food perfume etc) provides new directions for selectionat least for some olfactory genes
All the pathways described above have been accumulatingnonsynonymous mutations during the past 6000 years Atthe same time we revealed three pathways with the oppositepattern The modern group has significantly fewer mutationsthan the ancient one These pathways are described below
We revealed significant changes in a pathway associatedwith oocyte meiosis Oogenesis is the most important part offemale reproductive function It determines the timing ofpuberty and menopause as well as the effectiveness of repro-duction It has been shown that all these parameters arestrongly influenced by environmental factors (Gluckmanand Hanson 2006b Gold 2011 Henneberg and Saniotis
Chekalin et al doi101093molbevmsy201 MBE
134
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
2013) Retrospective analysis and direct data suggest signifi-cant fluctuations in menarche onset during the past severalmillennia (Gluckman and Hanson 2006a b Gillette andFolinsbee 2012 Henneberg and Saniotis 2013) a tendencyhas been reported for later menopause in modernEuropean women which is probably connected with lifestyleand overall quality of life (Gold 2011) Several hypothesesdiscuss the fluctuations in the number of childbirthsAlterations in nursing and dietary habits in early agricultur-alists might have caused a shortening of birth intervals(Kolata 1974 Hewlett and Lamb 2005 Gluckman andHanson 2006a b Gold 2011) and subsequent introductionof artificial childbirth reduction (including induced abortionsand later contraception) decreased the number of pregnan-cies In turn all these changes affected the number of men-strual cycles during a womanrsquos life Overall it is expected thatchanges in the duration of the reproductive period and inthe number of maturing oocytes might affect oocyte mei-osis The decrease in the number of nonsynonymousmutations in the oocyte meiosis pathway during thepast six millennia probably implies that despite all envi-ronmental changes in Europeans there was a tendency tokeep the organismrsquos homeostasis in such an importantprocess as reproduction The other possibility can be ashift in the mutation spectrum in order to adapt to thenew environmental conditions
Two more pathways (long-term potentiation and dopa-minergic synapse) for which the number of nonsynonymoussubstitutions in the modern group is significantly less than inthe ancient group are associated with cognitive functionsespecially memory and learning Information is probablythe most rapidly changing factor of our environmentDuring the past millennia ways of information presentationand perception have been completely altered Six thousandyears ago information was being accumulated from a rela-tively small geographic area and changed relatively slowlyWith the evolution of transport and transmission techniquesinformation capacity has expanded globally and the quantityand quality of data to process have been markedly enlargedMoreover the main cognitive tasks in Europe have also dra-matically changed during this time period (eg tool-makingvs car driving) This presumably affects such information per-ception systems as learning capability and memory Howevermutations in cognitive function genes can lead to detrimentalconsequences (indeed mutations in genes in long-term po-tentiation and dopaminergic synapse pathways can causeschizophrenia obsessive-compulsive disorder Parkinsonrsquos dis-ease drug addiction and many other neurological and neu-ropsychiatric disorders Bibb 2005 Centonze et al 2005 Kauerand Malenka 2007) These deleterious mutations should beeliminated through strong selection both directly and indi-rectly via sexual selection connected with behavioral reac-tions Data on molecular evolution of the human brain arestill controversial but most researchers suggest that codingregions of most human brain genes are subjects of negativeselection (Miyata et al 1994 Duret and Mouchiroud 2000 Hilland Walsh 2005 Tuller et al 2008 Huang et al 2013) Ourresults agree with this suggestion at the same time the
observed trend can indicate directional changes as a responseto the modified cognitive tasks
In summary we have revealed selection signatures in func-tional processes responsible for metabolic transformationsimmune responses including protection against pathogensalloimmune and autoimmune reactions signal transductionphysical activity sensory perception reproduction and cog-nitive functions Interestingly different environmental factorshave induced different types of natural selection An increasein the number of nonsynonymous mutations in modernhumans can indicate signs of either positive or relaxed selec-tion whereas a decrease suggests negative or on the contrarystrong positive selection For the identification of the exacttype of selection an additional analysis is required
The weakness of our approach is that it is impossible toidentify selection signals caused by modifications in a singlegene (like eg it was done in the work of Mathieson et al2015) Instead it is possible to reveal multiple modifications inpathways that are the result of many weak signals undetect-able by using other methods Therefore we believe that ourresults complement existing data on recent selection in theEuropean population Based on our results we suppose thatthe most important civilization events that have affectedadaptive reactions are changes in diet and the pathogenicenvironment the introduction of xenobiotics modificationsin lifestyle and in the information background To our knowl-edge our work is the first evidence for natural selection on thefunctional level Our results show that even during a relativelyshort period of time the human genome can be significantlyshaped by selection if the selection is induced by man
Our results raise a number of questions namely when didselection began to influence the revealed processes Howtheir subsequent evolution was affected To address theseissues further analyses on previous (EarlyMiddle NeolithicPaleolithic) and intermediate (Iron Age Middle Ages) timeperiods should be performed We are convinced that withthe emergence of new data we will better understand howdeeply and how rapidly biochemical and metabolic pathwayscan be affected by cultural and social changes
Materials and Methods
Ancient Data PreparationWe used published data from 159 European samples dated3500ndash1000 BCE (Gamba et al 2014 Allentoft et al 2015Haak et al 2015 Mathieson et al 2015) The focus of ourinvestigation was the Bronze Age however since the bordersbetween different archeological cultures and time periods areblurred we also used samples attributed to the Late Neolithic(supplementary table 1 Supplementary Material online)Selected individuals probably spoke Indo-European familylanguages that currently prevail in Europe (Haak et al2015) Most of the Late NeolithicBronze Age individualshave been previously shown to be genetically related toYamnaya culture (Lazaridis et al 2014 Allentoft et al 2015Haak et al 2015) and to most modern European ethnicgroups (Allentoft et al 2015 Haak et al 2015)
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
135
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
According to the authors (Allentoft et al 2015 Haak et al2015) genomic reads successfully passed quality controls onmitochondrial and bacterial DNA contamination To ensureauthenticity and remove batch effects we used a Bayesianapproach implemented in mapDamage 20 (Jonsson et al2013) We trimmed the past two nucleotides from each se-quence we further restricted our analyses to sites with basequality 20 To achieve statistical significance of the resultswe implemented the pipeline described in figure 2 and brieflyoutlined below SNPs were called independently in every sam-ple filtered by mapping quality (Qgt 30) and SNP quality(QUAL gt20) if possible alleles were supported by the samenumber of sequence reads we selected an allele at randomWe set the allele to ldquono callrdquo if the position was not coveredby sequence reads Genotypes for samples were called usingthe ldquocallrdquo command of bcftools (samtools bcftools) (Li et al2009) and filtered for quality score (QUAL 20) and thecoverage was required to be at least three per sample
We calculated the density and number of nonsynonymousSNPs per sample (supplementary table 6 SupplementaryMaterial online) We excluded eleven samples from analysisbased on 1) absence of genotypes in every position 2) out-grouping during PCA analysis shown in the original publica-tion (supplementary table 2 Supplementary Material online)or 3) due to enormous SNPs numbers compared with othersamples For this we computed the proportions of SNPs inthe samples through all the 305 pathways in the KEGG data-base To filter the samples we calculated the proportion ofSNPs in every sample for every pathway and then acquiredthe kernel density distribution for median proportions ofSNPs per sample per pathway The samples which were out-side the 99th percentile were rejected from further analysisThe 99th percentile for the median proportion of SNPs perpathway was 70 whereas the samples RISE98 RISE00 andRISE423 had average relative proportions of SNPs per path-way of 71 70 and 151 respectively Therefore thesesamples were rejected from further analysis The final BronzeAge subset consisted of 150 samples (supplementary table 2Supplementary Material online)
The resulting SNPs were annotated with the ANNOVAR(Wang et al 2010) tool using the hg19 human genome an-notation and the refGene database (httpvarianttoolssour-ceforgenetAnnotationRefGene) Synonymous andnonsynonymous SNPs were pooled into 2 separate singledata sets resulting in a collection of 40573 synonymousSNPs and 48860 nonsynonymous SNPs respectively Nextwe calculated the numbers of synonymous and nonsynon-ymous SNPs per KEGG pathway
Modern Data PreparationModern data were obtained from the latest release of theldquo1000 Genomes Projectrdquo database (Genomes Project) (httpwwwinternationalgenomeorg) We selected data only forEuropean populations with Indo-European roots Originallythe European subset includes British Finnish Spanish Italiansand Utah residents with Northern and Western Europeanancestry First we excluded the Utah residents Althoughthey have European ancestry the past several centuries
they have been living in different geographical and culturalconditions having different lifestyle different diet etc(Willett et al 2006) Next we excluded Finnish since theirpopulation history is different from other European popula-tions (Lao et al 2008) The Modern data set contained 305individuals 91 from the British population in England andScotland 107 from the Iberian peninsula (Spain) and 107individuals from Toscani (Italy) SNPs were functionally anno-tated with the ANNOVAR tool (Wang et al 2010) using thehg19 human genome annotation and the refGene database
Depth Files CorrectionDue to poor data sequence coverage even after aggregationof sequence reads from all the Bronze Age samples completegenome coverage had not been achieved Prior to calculatingthe distribution of nonsynonymous SNPs in the Bronze Ageand modern Europeans to avoid artificially high enrichmentscores we restricted our analysis of modern Europeans togenomic positions covered by the Bronze Age sequence readsSAMtools (Li et al 2009) was used for coverage calculationthen the results were filtered to keep coverage above 3 andmapping quality above 30 (Qgt 30) We generated a list ofcovered bases and used this list to select those SNPs in themodern human subsets that are covered in the Bronze Agesamples After this filtering the modern subsets contained72558 synonymous and 96710 nonsynonymous SNPs
KEGG Annotation and Preparation for EnrichmentAnalysisDistribution of SNPs in GenesA combined lists of 1) synonymous SNPs and 2) nonsynon-ymous SNPs from the Bronze Age individuals and present-dayEuropeans was mapped onto 305 KEGG pathways (Du et al2016) and counts of SNPs per pathway were computed Tominimize the false-positive rate we included only pathwayscontaining more than five genes with SNPs and with sumcovered pathway length more or equal to 50 in aggregatedancient data (table 1 and supplementary table 2Supplementary Material online)
Enrichment AnalysisTo analyze differences in numbers of SNPs per pathway be-tween the Bronze Age and present-day individuals we calcu-lated 1) DSSE scores and 2) DNSE scores The calculations forDSSE and DNSE were performed in a same way below wedescribe the calculations for DNSE
First we calculated the number of nonsynonymous SNPsin both the ancient and modern groups We assume thatduring neutral evolution similar pathways accumulate non-synonymous SNPs at the same rate and during enrichmentanalysis such pathways would fit a normal distributionwhereas pathways that are affected by evolutionary pressurewould be outliers from this distribution (supplementary fig 4Supplementary Material online) If Kfrac14 305 is the total num-ber of studied pathways and ifrac14 1 K number of the path-ways in Bronze Age and modern samples ni and mi denotethe number of nonsynonymous SNPs per ith pathway The
Chekalin et al doi101093molbevmsy201 MBE
136
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
expected (equilibrium) fraction of nonsynonymous SNPs inancient data is given by pfrac14 n(nthornm) where p is the fractionof ancient nonsynonymous SNPs in the whole analyzed sub-set n is the amount of ancient nonsynonymous SNPs inKEGG pathways m is the amount of modern nonsynony-mous SNPs in KEGG pathways The fraction pi of ancientnonsynonymous SNPs in the ith KEGG pathway is pi frac14 ni(nithornmi) where ni is the amount of ancient nonsynonymousSNPs in the ith pathway mi is amount of modern nonsynon-ymous SNPs in the ith pathway From acquired numbersenrichment DNSE scores were computed for every pathwaywith continuity correction (Fleiss et al 2003)
After computing the DNSE scores (distributed normallyShapirondashWilk test P-value gt001) we calculated P-values us-ing Bonferroni and BenjaminindashHochberg corrections andidentified the differentially enriched pathways The pathwayswere considered to be differentially enriched if absolute valueof the DNSE score gt4 and the adjusted P-value lt001However in 2017 in Nature Human Behavior (Benjaminet al 2017) the manuscript ldquoRedefine statistical significancerdquowas published where it was proposed to decrease the P-valuethreshold from 001 to 0005 We implemented the proposedthreshold on our data to avoid further false-positive enrich-ment signals resulting in alternative lists of enrichedpathways
In order to normalize nonsynonymous SNPs on synony-mous SNPs we performed the following procedureBonferroni-adjusted P-values were log-transformed (base10) and multiplied by the sign of the DNSE statistic so thatpositive scores correspond to enrichment in modern groupsand negative scores to enrichment in ancient groups respec-tively As a condition of significance we required the follow-ing The P-value of the nonsynonymous test was below theP-value of the synonymous test for each pathway In additionit was required for the Bonferroni-corrected P-value to bebelow 001 For each pathway the P-value of the synonymoustest was above the P-value of the corresponding nonsynon-ymous test
Validation of the MethodTo validate our method we compared it with the methodimplemented by Somel et al 2013 We calculated DNSEscores between chimpanzee and their ancestors (combinedgenomes from different species of primates data from Prado-Martinez et al 2013 httpswwwnaturecomarticlesna-ture12228) Our results confirmed the conclusions of Somelet al Olfactory transduction pathway demonstrated the sig-nature of relaxed selection in chimpanzee (enriched in com-parison with primates it is the only pathway enriched inchimpanzee) (supplementary table 8 SupplementaryMaterial online) As in Somel et al 2013 proteasome pathwaydid not demonstrate any signs of selection (no pathwayenrichment) (see Somel et al fig 2 and present study
supplementary table 8 Supplementary Material online) Wealso revealed several pathways which are enriched in primatesin comparison to chimpanzee This can indicate possible neg-ative or strong positive selection in chimpanzee Howeverthis suggestion requires additional thorough analysis whichis outside the scope of our paper
Comparison of Regulatory SNPs DistributionTo compare regulatory SNPs in Bronze Age and modernindividuals we extracted 10000 experimentally validated pro-moters and 50-UTRs from the DBTSS database (httpsdbtsshgcjp) Sequences [TSS 1000 TSSthorn 1000] were extractedand MATCH software with TRASNFAC database (httpswwwncbinlmnihgovpubmed12824369 with parametersset to minimize false-positive matches) was applied to iden-tify putative transcription factor binding sites (TFBS) in thosesequences A total of 61451840 putative TFBS were identifiedin these regions The TRANSFAC database is highly degener-ate with different entries having the same or similar matricestherefore producing overlapping predictions on a genomeSuch overlapping putative TBFS were merged into 88513contiguous regulatory sequences Furthermore we removedthose regions that were not fully covered by ancient DNAsequences leaving us with 31036 regulatory fragments Aproportion test was performed similarly to the calculationof enrichment scores in coding regions
PCA and reAdmixThe principal component analysis (PCA) was carried out in Rusing the ADMIXTURE vectors for Ancient and EuropeanWorldwide modern individuals The ADMIXTURE softwareimplements a model-based Bayesian approach that uses ablock-relaxation algorithm to compute a matrix of ancestralpopulation fractions in each individual (Q files) and infer allelefrequencies for each ancestral population (P files) (Alexanderet al 2009 Alexander and Lange 2011) We appliedADMIXTURE in unsupervised mode to the combined dataset of modern and ancient individuals We varied the numberof components between Kfrac14 6 and Kfrac14 17 recording thevalue of cross-validation (CV) error and picked Kfrac14 7 forthe PCA analysis as a sufficient number of components todistinguish subpopulations from each other
The PCA analysis was performed using the R packageprincomp with centering and scaling parameters and thenvisualized using the first two components cumulatively cor-responding to 60 of the variance among worldwide modernand ancient individuals
Additional ancient samples for reAdmix (Kozlov et al2015) analyses were obtained from (Gamba et al 2014Allentoft et al 2015 Haak et al 2015 Mathieson et al2015) This data set was combined with the modernEuropean samples from the 1000 Genomes database Theresulting data set contained 1) the Bronze age subset usedin this study (nfrac14 150) 2) early Neolithic data (nfrac14 32) and 3)Western European hunter-gatherers (nfrac14 12) A referencedata set was assembled from all ancient individuals and mod-ern individuals were represented as a linear combination of
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
137
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
ancient ones using the reAdmix algorithm Each modernpopulation was represented as
Modern Population frac14 w1BA thorn w2EN thorn w3WHG thorn e
where BA is ldquoBronze Agerdquo EN is ldquoEarly Neolithicrdquo WHG isldquoWestern Europe hunter-gatherersrdquo data e is an unassignedpart and coefficients were determined using the differentialevolution algorithm Modern individuals from 1000 genomes(British population [nfrac14 6] Toscani [nfrac14 6] and Iberian[nfrac14 5]) were clustered within self-reported ethnic groupsbased on similarity of their admixture vectors and the self-reported identity was validated using leave-one out proce-dure and Euclidian distance to the reference populationAverage contributions of ancient genomes to modernindividuals were computed for each cluster of modernindividuals
Data AccessSFTP access with ANNOVAR annotated vcf files for ancientman and filtered nonsynonymous and synonymous files frommodern samples
ip 8589112202
port 2203
username bronze_man
password bronze_man
Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online
AcknowledgmentsWe are grateful to Prof Maciej Henneberg (University ofAdelaide Australia) members of the Institute ofEvolutionary Medicine (University of Zurich Switzerland)and members of System Biology and ComputationalGenetics Seminar (Vavilov Institute of General GeneticsRussia) for valuable comments and fruitful discussion ofthe manuscript This work was supported by a Meuroaxi founda-tion grant (Zurich Switzerland awarded to FR) and by theNSF Division of Environmental Biology (1456634 to TT)
ReferencesAdams RM 1966 The evolution of urban society early Mesopotamia
and prehispanic Mexico Chicago (IL) Aldine Pub CoAdler CJ Dobney K Weyrich LS Kaidonis J Walker AW Haak W
Bradshaw CJA Townsend G Sołtysiak A Alt KW et al 2013Sequencing ancient calcified dental plaque shows changes in oralmicrobiota with dietary shifts of the Neolithic and Industrial revo-lutions Nat Genet 45(4) 450ndash455 455e1
Alexander DH Lange K 2011 Enhancements to the ADMIXTUREalgorithm for individual ancestry estimation BMC Bioinformatics12(1) 246
Alexander DH Novembre J Lange K 2009 Fast model-based esti-mation of ancestry in unrelated individuals Genome Res 19(9)1655ndash1664
Aliesky H Courtney CL Rapoport B McLachlan SM 2013 Thyroidautoantibodies are rare in nonhuman great apes and
hypothyroidism cannot be attributed to thyroid autoimmunityEndocrinology 154(12) 4896ndash4907
Allentoft ME Sikora M Sjogren KG Rasmussen S Rasmussen MStenderup J Damgaard PB Schroeder H Ahlstrom T Vinner Let al 2015 Population genomics of Bronze Age Eurasia Nature522(7555) 167ndash172
American College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines AmericanAssociation for Thoracic Surgery American Society ofEchocardiography American Society of Nuclear Cardiology HeartFailure Society of America Heart Rhythm Society Society forCardiovascular Angiography and Interventions Society ofThoracic Surgeons Gersh BJ Maron BJ et al 2011 2011ACCFAHA guideline for the diagnosis and treatment of hyper-trophic cardiomyopathy executive summary a report of theAmerican College of Cardiology FoundationAmerican HeartAssociation Task Force on Practice Guidelines J ThoracCardiovasc Surg 1421303ndash1338
Barnes I Duda A Pybus OG Thomas MG 2011 Ancient urbani-zation predicts genetic resistance to tuberculosis Evolution65(3) 842ndash848
Barsheshet A Brenyo A Moss AJ Goldenberg I 2011 Genetics of suddencardiac death Curr Cardiol Rep 13(5) 364ndash376
Beja-Pereira A Luikart G England PR Bradley DG Jann OC Bertorelle GChamberlain AT Nunes TP Metodiev S Ferrand N et al 2003Gene-culture coevolution between cattle milk protein genes andhuman lactase genes Nat Genet 35(4) 311ndash313
Benjamin DJ Berger JO Johannesson M Nosek BA Wagenmakers EJBerk R Bollen KA Brembs B Brown L Camerer C et al 2018Redefine statistical significance Nat Hum Behav 2 6ndash10
Bersaglieri T Sabeti PC Patterson N Vanderploeg T Schaffner SF DrakeJA Rhodes M Reich DE Hirschhorn JN 2004 Genetic signatures ofstrong recent positive selection at the lactase gene Am J Hum Genet74(6) 1111ndash1120
Bibb JA 2005 Decoding dopamine signaling Cell 122(2) 153ndash155Blum JS Wearsch PA Cresswell P 2013 Pathways of antigen processing
Annu Rev Immunol 31(1) 443ndash473Boyd R Richerson PJ 1985 Culture and the evolutionary process
Chicago (IL) University of Chicago PressCentonze D Siracusano A Calabresi P Bernardi G 2005 Long-term
potentiation and memory processes in the psychological works ofSigmund Freud and in the formation of neuropsychiatric symptomsNeuroscience 130(3) 559ndash565
Chen PH Yao H Huang LJ 2017 Cytokine receptor endocytosis newkinase activity-dependent and -independent roles of PI3K FrontEndocrinol (Lausanne) 878
Cirino AL Ho C 1993 Hypertrophic cardiomyopathy overview InAdam MP Ardinger HH Pagon RA Wallace SE Bean LJH MeffordHC Stephens K Amemiya A Ledbetter N editors GeneReviewsV
R
[Internet] Seattle (WA) University of Washington Seattle1993ndash2018
Cochran G Harpending H 2009 The 10000 year explosion how civili-zation accelerated human evolution New York Basic Books
Cordain L Eaton SB Sebastian A Mann N Lindeberg S Watkins BAOrsquoKeefe JH Brand-Miller J 2005 Origins and evolution of theWestern diet health implications for the 21st century Am J ClinNutr 81(2) 341ndash354
Dannemann M Andres AM Kelso J 2016 Introgression of Neandertal-and Denisovan-like haplotypes contributes to adaptive variation inhuman Toll-like receptors Am J Hum Genet 98(1) 22ndash33
De Santis MC Sala V Martini M Ferrero GB Hirsch E 2017 PI3Ksignaling in tissue hyper-proliferation from overgrowth syn-dromes to kidney cysts Cancers (Basel) 9 doi 103390cancers9040030
DeWitte SN 2014 Mortality risk and survival in the aftermath of themedieval Black Death PLoS One 9(5) e96513
Du J Li M Yuan Z Guo M Song J Xie X Chen Y 2016 A decisionanalysis model for KEGG pathway analysis BMC Bioinformatics17(1) 407
Chekalin et al doi101093molbevmsy201 MBE
138
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
Duret L Mouchiroud D 2000 Determinants of substitution rates inmammalian genes expression pattern affects selection intensitybut not mutation rate Mol Biol Evol 17(1) 68ndash74
Duronio V 2008 The life of a cell apoptosis regulation by the PI3KPKBpathway Biochem J 415(3) 333ndash344
Ehrlich PR 2000 Human natures genes cultures and the human pros-pect Washington (DC) Island Press for Shearwater Books
Enattah NS Jensen TG Nielsen M Lewinski R Kuokkanen M RasinperaH El-Shanti H Seo JK Alifrangis M Khalil IF et al 2008 Independentintroduction of two lactase-persistence alleles into human popula-tions reflects different history of adaptation to milk culture Am JHum Genet 82(1) 57ndash72
Engelman JA Luo J Cantley LC 2006 The evolution of phosphatidyli-nositol 3-kinases as regulators of growth and metabolism Nat RevGenet 7(8) 606ndash619
Field Y Boyle EA Telis N Gao Z Gaulton KJ Golan D Yengo LRocheleau G Froguel P McCarthy MI et al 2016 Detection of hu-man adaptation during the past 2000 years Science 354(6313)760ndash764
Fleiss JL Levin B Paik MC 2003 Statistical methods for rates and pro-portions Hoboken (NJ) John Wiley
Forni D Cagliani R Tresoldi C Pozzoli U De Gioia L Filippi G Riva SMenozzi G Colleoni M Biasin M et al 2014 An evolutionary analysisof antigen processing and presentation across different timescalesreveals pervasive selection PLoS Genet 10(3) e1004189
Fresno Vara JA Casado E de Castro J Cejas P Belda-Iniesta C Gonzalez-Baron M 2004 PI3KAkt signalling pathway and cancer CancerTreat Rev 30(2) 193ndash204
Fu Q Posth C Hajdinjak M Petr M Mallick S Fernandes D FurtwanglerA Haak W Meyer M Mittnik A et al 2016 The genetic history of IceAge Europe Nature 534(7606) 200ndash205
Galvani AP Slatkin M 2003 Evaluating plague and smallpox as historicalselective pressures for the CCR5-Delta 32 HIV-resistance allele ProcNatl Acad Sci U S A 100(25) 15276ndash15279
Gamba C Jones ER Teasdale MD McLaughlin RL Gonzalez-Fortes GMattiangeli V Domboroczki L Kovari I Pap I Anders A et al 2014Genome flux and stasis in a five millennium transect of Europeanprehistory Nat Commun 5 5257
Gibbs RA Boerwinkle E Doddapaneni H Han Y Korchina V Kovar CLee S Muzny D Reid JG Zhu Y et al Genomes Project Consortium2015 A global reference for human genetic variation Nature526(7571) 68ndash74
Gerbault P Liebert A Itan Y Powell A Currat M Burger J Swallow DMThomas MG 2011 Evolution of lactase persistence an example ofhuman niche construction Philos Trans R Soc Lond B Biol Sci366(1566) 863ndash877
Gilad Y Bustamante CD Lancet D Paabo S 2003 Natural selection onthe olfactory receptor gene family in humans and chimpanzees AmJ Hum Genet 73(3) 489ndash501
Gilad Y Man O Paabo S Lancet D 2003 Human specific loss of olfactoryreceptor genes Proc Natl Acad Sci U S A 100(6) 3324ndash3327
Gillette MT Folinsbee KE 2012 Early menarche as an alternative repro-ductive tactic in human females an evolutionary approach to re-productive health issues Evol Psychol 10(5) 830ndash841
Gillings MR Paulsen IT Tetu SG 2015 Ecology and evolution of thehuman microbiota fire farming and antibiotics Genes (Basel) 6(3)841ndash857
Gluckman PD Hanson MA 2006 Changing times the evolution ofpuberty Mol Cell Endocrinol 254ndash255 26ndash31
Gluckman PD Hanson MA 2006 Evolution development and timing ofpuberty Trends Endocrinol Metab 17(1) 7ndash12
Gold EB 2011 The timing of the age at which natural menopauseoccurs Obstet Gynecol Clin North Am 38(3) 425ndash440
Grossman SR Andersen KG Shlyakhter I Tabrizi S Winnicki S Yen APark DJ Griesemer D Karlsson EK Wong SH et al 2013Identifying recent adaptations in large-scale genomic data Cell152(4) 703ndash713
Haak W Lazaridis I Patterson N Rohland N Mallick S Llamas B BrandtG Nordenfelt S Harney E Stewardson K et al 2015 Massive migra-tion from the steppe was a source for Indo-European languages inEurope Nature 522(7555) 207ndash211
Hawks J Wang ET Cochran GM Harpending HC Moyzis RK 2007Recent acceleration of human adaptive evolution Proc Natl AcadSci U S A 104(52) 20753ndash20758
Henneberg M Saniotis A 2013 The future mismatch between bio-logical and social development of youths Int J Educ Res 1(2)online
Hewlett BS Lamb ME 2005 Hunter-gatherer childhoods evolutionarydevelopmental amp cultural perspectives New Brunswick (NJ) AldineTransaction
Hill RS Walsh CA 2005 Molecular insights into human brain evolutionNature 437(7055) 64ndash67
Holden C Mace R 1997 Phylogenetic analysis of the evolution of lactosedigestion in adults Hum Biol 69(5) 605ndash628
Hou L Klann E 2004 Activation of the phosphoinositide 3-kinase-Akt-mammalian target of rapamycin signaling pathway is required formetabotropic glutamate receptor-dependent long-term depressionJ Neurosci 24(28) 6352ndash6361
Huang Y Xie C Ye AY Li CY Gao G Wei L 2013 Recent adaptive eventsin human brain revealed by meta-analysis of positively selectedgenes PLoS One 8(4) e61280
Jonsson H Ginolhac A Schubert M Johnson PL Orlando L 2013mapDamage20 fast approximate Bayesian estimates of ancientDNA damage parameters Bioinformatics 29(13) 1682ndash1684
Kauer JA Malenka RC 2007 Synaptic plasticity and addiction Nat RevNeurosci 8(11) 844ndash858
Kimura M 1955 Stochastic processes and distribution of gene frequen-cies under natural selection Cold Spring Harb Symp Quant Biol2033ndash53
Kolata GB 1974 Kung hunter-gatherers feminism diet and birth con-trol Science 185932ndash934
Kopp W 2004 Nutrition evolution and thyroid hormone levelsmdasha linkto iodine deficiency disorders Med Hypotheses 62(6) 871ndash875
Kozlov K Chebotarev D Hassan M Triska M Triska P Flegontov PTatarinova TV 2015 Differential Evolution approach to detect re-cent admixture BMC Genomics 16(Suppl 8) S9
Laayouni H Oosting M Luisi P Ioana M Alonso S Ricano-Ponce ITrynka G Zhernakova A Plantinga TS Cheng SC et al 2014Convergent evolution in European and Rroma populations revealspressure exerted by plague on Toll-like receptors Proc Natl Acad SciU S A 111(7) 2668ndash2673
Lakkis FG Lechler RI 2013 Origin and biology of the allogeneicresponse Cold Spring Harb Perspect Med 3 doi 101101cshperspecta014993
Laland KN 2008 Exploring gene-culture interactions insights fromhandedness sexual selection and niche-construction case studiesPhilos Trans R Soc Lond B Biol Sci 363(1509) 3577ndash3589
Laland KN Odling-Smee J Myles S 2010 How culture shaped the hu-man genome bringing genetics and the human sciences togetherNat Rev Genet 11(2) 137ndash148
Lang M Pelkonen O 1999 Metabolism of xenobiotics and chemicalcarcinogenesis IARC Sci Publ 148 13ndash22
Lao O Lu TT Nothnagel M Junge O Freitag-Wolf S Caliebe ABalascakova M Bertranpetit J Bindoff LA Comas D et al 2008Correlation between genetic and geographic structure in EuropeCurr Biol 18(16) 1241ndash1248
Lazaridis I Patterson N Mittnik A Renaud G Mallick S Kirsanow KSudmant PH Schraiber JG Castellano S Lipson M et al 2014Ancient human genomes suggest three ancestral populations forpresent-day Europeans Nature 513(7518) 409ndash413
Lewinsky RH Jensen TG Moller J Stensballe A Olsen J Troelsen JT 2005T-13910 DNA variant associated with lactase persistence interactswith Oct-1 and stimulates lactase promoter activity in vitro HumMol Genet 14(24) 3945ndash3953
Li H Handsaker B Wysoker A Fennell T Ruan J Homer N Marth GAbecasis G Durbin R Genome Project Data Processing Subgroup
Changes in Biological Pathways During 6000 Years of Civilization in Europe doi101093molbevmsy201 MBE
139
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
msy201-TF1
2009 The sequence alignmentmap format and SAMtoolsBioinformatics 25(16) 2078ndash2079
Libert F Cochaux P Beckman G Samson M Aksenova M Cao A CzeizelA Claustres M de la Rua C Ferrari M et al 1998 The deltaccr5mutation conferring protection against HIV-1 in Caucasian popula-tions has a single and recent origin in Northeastern Europe HumMol Genet 7(3) 399ndash406
Lightfoot JT 2013 Why control activity Evolutionary selection pressuresaffecting the development of physical activity genetic and biologicalregulation Biomed Res Int 2013 821678
Marian AJ 2010 Hypertrophic cardiomyopathy from genetics to treat-ment Eur J Clin Invest 40(4) 360ndash369
Mathieson I Lazaridis I Rohland N Mallick S Patterson N RoodenbergSA Harney E Stewardson K Fernandes D Novak M et al 2015Genome-wide patterns of selection in 230 ancient Eurasians Nature528(7583) 499ndash503
Miyata T Hayashida H 1981 Extraordinarily high evolutionary rate ofpseudogenes evidence for the presence of selective pressure againstchanges between synonymous codons Proc Natl Acad Sci U S A78(9) 5739ndash5743
Miyata T Kuma K Iwabe N Nikoh N 1994 A possible link betweenmolecular evolution and tissue evolution demonstrated by tissuespecific genes Jpn J Genet 69(5) 473ndash480
Moitra K Dean M 2011 Evolution of ABC transporters by gene dupli-cation and their role in human disease Biol Chem 392(1ndash2) 29ndash37
Motomura K Brent GA 1998 Mechanisms of thyroid hormone actionImplications for the clinical manifestation of thyrotoxicosisEndocrinol Metab Clin North Am 27(1) 1ndash23
Olalde I Allentoft ME Sanchez-Quinto F Santpere G Chiang CWDeGiorgio M Prado-Martinez J Rodriguez JA Rasmussen SQuilez J et al 2014 Derived immune and ancestral pigmenta-tion alleles in a 7000-year-old Mesolithic European Nature507(7491) 225ndash228
Oliveira PA Colaco A Chaves R Guedes-Pinto H De-La-Cruz PL LopesC 2007 Chemical carcinogenesis An Acad Bras Cienc 79(4)593ndash616
Pierron D Cortes NG Letellier T Grossman LI 2013 Current relaxationof selection on the human genome tolerance of deleterious muta-tions on olfactory receptors Mol Phylogenet Evol 66(2) 558ndash564
Pohl A Devaux PF Herrmann A 2005 Function of prokaryotic andeukaryotic ABC proteins in lipid transport Biochim Biophys Acta1733(1) 29ndash52
Pons-Tostivint E Thibault B Guillermet-Guibert J 2017 Targeting PI3Ksignaling in combination cancer therapy Trends Cancer 3(6)454ndash469
Porta C Paglino C Mosca A 2014 Targeting PI3KAktmTOR signalingin cancer Front Oncol 464
Quach H Barreiro LB Laval G Zidane N Patin E Kidd KK Kidd JRBouchier C Veuille M Antoniewski C et al 2009 Signatures ofpurifying and local positive selection in human miRNAs Am JHum Genet 84(3) 316ndash327
Richerson PJ Boyd R 2005 Not by genes alone how culture transformedhuman evolution Chicago (IL) University of Chicago Press
Rouquier S Taviaux S Trask BJ Brand-Arpon V van den Engh GDemaille J Giorgi D 1998 Distribution of olfactory receptor genesin the human genome Nat Genet 18(3) 243ndash250
Sabeti PC Varilly P Fry B Lohmueller J Hostetter E Cotsapas C Xie XByrne EH McCarroll SA Gaudet R et al 2007 Genome-wide detec-tion and characterization of positive selection in human popula-tions Nature 449(7164) 913ndash918
Sabeti PC Walsh E Schaffner SF Varilly P Fry B Hutcheson HB Cullen MMikkelsen TS Roy J Patterson N et al 2005 The case for selection atCCR5-Delta32 PLoS Biol 3(11) e378
Somel M Wilson Sayres MA Jordan G Huerta-Sanchez E Fumagalli MFerrer-Admetlla A Nielsen R 2013 A scan for human-specific relax-ation of negative selection reveals unexpected polymorphism inproteasome genes Mol Biol Evol 30(8) 1808ndash1815
Song G Ouyang G Bao S 2005 The activation of AktPKB signalingpathway and cell survival J Cell Mol Med 9(1) 59ndash71
Stefkova J Poledne R Hubacek JA 2004 ATP-binding cassette (ABC)transporters in human metabolism and diseases Physiol Res 53(3)235ndash243
Stephens JC Reich DE Goldstein DB Shin HD Smith MW Carrington MWinkler C Huttley GA Allikmets R Schriml L et al 1998 Dating theorigin of the CCR5-Delta32 AIDS-resistance allele by the coalescenceof haplotypes Am J Hum Genet 62(6) 1507ndash1515
Sui L Wang J Li BM 2008 Role of the phosphoinositide 3-kinase-Akt-mammalian target of the rapamycin signaling pathway in long-termpotentiation and trace fear conditioning memory in rat medial pre-frontal cortex Learn Mem 15(10) 762ndash776
Tang K Thornton KR Stoneking M 2007 A new approach for usinggenome scans to detect recent positive selection in the humangenome PLoS Biol 5e171
Tuller T Kupiec M Ruppin E 2008 Evolutionary rate and gene expres-sion across different brain regions Genome Biol 9(9) R142
Vanderpump MP 2011 The epidemiology of thyroid disease Br MedBull 99(1) 39ndash51
Vasiliou V Vasiliou K Nebert DW 2009 Human ATP-binding cassette(ABC) transporter family Hum Genomics 3(3) 281ndash290
Voight BF Kudaravalli S Wen X Pritchard JK 2006 A map of recentpositive selection in the human genome PLoS Biol 4(3) e72
Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16) e164
Weichhart T Saemann MD 2008 The PI3KAktmTOR pathway ininnate immune cells emerging therapeutic applications AnnRheum Dis 67(Suppl 3) iii70ndashiii74
Willett K Jiang R Lenart E Spiegelman D Willett W 2006 Comparisonof bioelectrical impedance and BMI in predicting obesity-relatedmedical conditions Obesity (Silver Spring) 14(3) 480ndash490
Williamson SH Hubisz MJ Clark AG Payseur BA Bustamante CDNielsen R 2007 Localizing recent adaptive evolution in the humangenome PLoS Genet 3(6) e90
Ye Y Doak TG 2009 A parsimony approach to biological pathwayreconstructioninference for genomes and metagenomes PLoSComput Biol 5(8) e1000465
Chekalin et al doi101093molbevmsy201 MBE
140
Dow
nloaded from httpsacadem
icoupcomm
bearticle-abstract3611275146762 by Ann Nez user on 16 June 2019
