Keynote talk at "Society for General Microbiology" meeting in March, 2001 by Jonathan Eisen

transcript

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“Nothing in biology makes senseexcept in the light of evolution.”

T. H. Dobzhansky (1973)

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Talk Outline

• Complete Genome Projects - history and current status

• What have we learned about evolutionary history and processes from recent genome projects

• Two main themes - completeness and closeness• Coming attractions• Why we need more genomes

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The Institute for Genomic Research

• A not for profit institution, staff ~230

• Departments:– Eukaryotic Genomics– Microbial Genomics– Functional Genomics– Bioinformatics– Sequencing Core

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Whole Genome Shotgun Sequencing

shotgunshotgun

sequencesequenceWarner Brothers, Inc.Warner Brothers, Inc.

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Assemble Fragments

sequencer sequencer outputoutput

assemble assemble fragmentsfragments

Closure &Closure &

AnnotationAnnotation

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General Steps in Analysis of Complete Genomes

• Identification/prediction of genes

• Characterization of gene features

• Characterization of genome features

• Prediction of gene function

• Prediction of pathways

• Integration with known biological data

• Comparative genomics

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Haemophilusinfluenzae

Mycoplasmagenitalium

Synechocystissp.

Methanococcusjannaschii

Mycoplasmapneumoniae

Saccharomyces cerevisiae

Helicobacterpylori

Escherichiacoli

Archaeoglobus fulgidus

Borrelia burgdorferi

Aquifexaeolicus

Pyrococcushorikoshii

Treponemapallidum

Rickettsia prowazekii

Aeropyrumpernix

Thermotoga maritima

Deinococcusradiodurans

Helicobacterpylori

Neisseriameningitidis

Campylobacterjejuni Pseudomonas

aeruginosa

Xylellafastidiosa

Vibrio cholerae

Bacillus subtilis

Methanobacteriumthermoautotrophicum

Mycobacteriumtuberculosis

Chlamydiatrachomatis

Chlamydia pneumoniae

Neisseriameningitidis

Chlamydiatrachomatis

Chlamydia pneumoniae

1996 2000199919981997

Microbial Genomes Sequenced

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Complete Genome/Chromosome Progress

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rRNA Tree for Species with Complete Genomes (~August 2000)

Methanobacterium thermoautotrophicumArchaeoglobus fulgidusPyrococcus horikoshiiMethanococcus jannaschiiAeropyrum pernix0.05 changesArchaeaMycobacterium tuberculosisBacillus subtilisSynechocystis sp.Aquifex aeolicusThermotoga maritimaDeinococcus radioduransTreponema pallidumBorrelia burgdorferiHelicobacter pyloriCampylobacter jejuniNeisseria meningitidisEscherichia coliVibrio choleraeHaemophilus influenzaeRickettsia prowazekiiMycoplasma pneumoniaeMycoplasma genitaliumChlamydia trachomatisChlamydia pneumoniaeBacteriaCaenorhabditis elegansDrosophila melanogasterSaccharomyces cerevisiaeEukarya

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rRNA Tree - Complete/In ProgressEuryarchaeotaCrenarchaeotaAlphaProteobacteriaEpsilonProteobacteriaDeltaProteobacteriaSpirochetesGreen Sulfur bacteriaChlamydiaCyanobacteriaThermotogalesThermophilic O2 reducersDeinococcus/ThermusBetaProteobacteriaGammaProteobacteriaLow GC Gram-positive bacteriaHigh GCGram-positive bacteriaGreen Non-Sulfur bacteria

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Limitations of Genome Analysis• Functional predictions are PREDICTIONS• Need to follow up all predictions with

experimental work• Each genome sequence is a snapshots of one clone• Genome analysis is not able to identify novel

processes• Annotation needs to be updated• Assembly can be wrong• Some parts of genome may be missed (e.g., low

copy plasmids)

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Genome sequences and evolution

• Origin of new gene function• Gene loss• Genome degradation• Gene and genome duplication• Rates and patterns of mutation,

recombination• Gene transfer• Species evolution

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Evolution and Complete Genomes I:Gene Loss

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EuksArchBacteriaLossEvolutionary Origin of GeneMTMJSCHSAADRTABSMGMPBBTPHPHIECSSMTPresence ( ) or Absence of GeneSpecies AbbreviationKingdom

Example of Tracing Gene Loss

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Why Identify Gene Loss

• Indicates that gene is not absolutely required for survival

• Parallel loss of same gene in different species may indicate selective advantage of loss of that gene

• Correlated loss of genes in a pathway indicates a conserved association among those genes (important for phylogenetic profiles)

• Loss in organellar genomes frequently accompanied by gain in nuclear genome

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Duplication and Loss of Mismatch Repair Genes

51234*E. coliH. influenzaeN. gonorrhoaeaH. pyloriSyn. spB. subtilisS. pyogenesM. pneumoniaeM. genitaliumA. aeolicusD. radioduransT.pallidumB.burgdorferiSyn. spB. subtilisS. pyogenesA. aeolicusD. radioduransB. burgdorferiMutS1MutS-I lineageMutS-II lineageSpecies TreeGene loss*Gene Duplications1-5Gene LossA.B.A. aeolicusS pyogenesB. subtilisSyn. spD. radioduransMutS2B.burgdorferi

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Buchnera

• Extensive gene loss relative to E. coli

• Surprising loss of some genes– UvrABCD– RecA– Very different than many pathogens (frequently

loss MutS, MutL)

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Evolution and Complete Genomes II:Gene and Genome Duplication

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Why Duplications Are Useful to Identify

• Allows division into orthologs and paralogs

• Improves functional predictions

• Helps identify mechanisms of duplication

• Can be used to study mutation processes in different parts of a genome

• Lineage specific duplications may be indicative of species’ specific adaptations

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Expansion of MCP Family in V. choleraeE.coli gi1787690B.subtilis gi2633766Synechocystis sp. gi1001299Synechocystis sp. gi1001300Synechocystis sp. gi1652276Synechocystis sp. gi1652103H.pylori gi2313716H.pylori99 gi4155097C.jejuni Cj1190cC.jejuni Cj1110cA.fulgidus gi2649560A.fulgidus gi2649548B.subtilis gi2634254B.subtilis gi2632630B.subtilis gi2635607B.subtilis gi2635608B.subtilis gi2635609B.subtilis gi2635610B.subtilis gi2635882E.coli gi1788195E.coli gi2367378E.coli gi1788194E.coli gi1789453C.jejuni Cj0144C.jejuni Cj0262cH.pylori gi2313186H.pylori99 gi4154603C.jejuni Cj1564C.jejuni Cj1506cH.pylori gi2313163H.pylori99 gi4154575H.pylori gi2313179H.pylori99 gi4154599C.jejuni Cj0019cC.jejuni Cj0951cC.jejuni Cj0246cB.subtilis gi2633374T.maritima TM0014T.pallidum gi3322777T.pallidum gi3322939T.pallidum gi3322938B.burgdorferi gi2688522T.pallidum gi3322296B.burgdorferi gi2688521T.maritima TM0429T.maritima TM0918T.maritima TM0023T.maritima TM1428T.maritima TM1143T.maritima TM1146P.abyssi PAB1308P.horikoshii gi3256846P.abyssi PAB1336P.horikoshii gi3256896P.abyssi PAB2066P.horikoshii gi3258290P.abyssi PAB1026P.horikoshii gi3256884D.radiodurans DRA00354D.radiodurans DRA0353D.radiodurans DRA0352P.abyssi PAB1189P.horikoshii gi3258414B.burgdorferi gi2688621M.tuberculosis gi1666149V.cholerae VC0512V.cholerae VCA1034V.cholerae VCA0974V.cholerae VCA0068V.cholerae VC0825V.cholerae VC0282V.cholerae VCA0906V.cholerae VCA0979V.cholerae VCA1056V.cholerae VC1643V.cholerae VC2161V.cholerae VCA0923V.cholerae VC0514V.cholerae VC1868V.cholerae VCA0773V.cholerae VC1313V.cholerae VC1859V.cholerae VC1413V.cholerae VCA0268V.cholerae VCA0658V.cholerae VC1405V.cholerae VC1298V.cholerae VC1248V.cholerae VCA0864V.cholerae VCA0176V.cholerae VCA0220V.cholerae VC1289V.cholerae VCA1069V.cholerae VC2439V.cholerae VC1967V.cholerae VCA0031V.cholerae VC1898V.cholerae VCA0663V.cholerae VCA0988V.cholerae VC0216V.cholerae VC0449V.cholerae VCA0008V.cholerae VC1406V.cholerae VC1535V.cholerae VC0840V.cholerae VC0098V.cholerae VCA1092V.cholerae VC1403V.cholerae VCA1088V.cholerae VC1394V.cholerae VC0622NJ*******************************************************************************

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C. pneumoniae Paralogs by Position

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C. pneumoniae Paralogs - Lineage Specific

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Evolution and Complete Genomes III:Genome Rearrangements

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X-files

Eisen et al. 2000. Genome Biology 1(6): 11.1-11.9

Also see Tillier and Collins. 2000. Nature Genetics 26(2):195-7.

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V. cholerae vs. E. coliBest Matching Proteins by Location

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M. leprae vs. M. tuberculosis Whole Genome Alignment

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Duplication and Gene Loss Model

E’F’

E. coliE. coli

V. cholerae

E’F’

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39Origin

Terminus

C. trachomatis vs C. pneumoniae Dot Plot

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B1A1B2A2B3A3B3B22423222120191817161514131211109672582627282930123453132 B131326789101112131415161718192021222324252627282930123453132 B32423222120191817161514131211109672582627282933231304521 A131326789101112131415161718192021222324252627282930123453132 A231326789101112131918171615142021222324252627282930123453132 A32678910111213191817161514202122232425262754331302928132B2Inversion Around Terminus (*)

Inversion Around Terminus (*)

Inversion AroundOrigin (*)

******** Common Ancestor of

A and B

31326789101112131415161718192021222324252627282930123453132A2A1A2A3B2B1

Symmetric Inversion Model

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Why are Inversions Symmetrical Around Origin

• Genetic studies in Salmonella and E. coli suggest that there may be strong selection against other inversions

– Mahan, Segall, Schmid and Roth– Liu and Sanderson– Rebollo, Francois, and, Louarn

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Evolution and Complete Genomes IV:Gene Transfer

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Examples of Horizontal Transfers

• Antibiotic and toxin resistance genes on plasmids

• Pathogenicity islands

• Agrobacterium Ti plasmid

• Viruses

• Organelle to nucleus transfers

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Why Gene Transfers Are Useful to Identify

• Laterally transferred genes frequently involved in environmental adaptations and/or pathogenicity

• Helps identify transposons, integrons, and other vectors of gene transfer

• Helps identify species associations in the environment

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Tree of Life or Web of Life?

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Most ‘Evidence’ for Gene Transfer has Alternative Explanations

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How to Infer Gene Transfers

• Unusual distribution patterns

• Unusual nucleotide composition

• High sequence similarity to supposedly distantly related species

• Unusual gene trees

• Observe transfer events

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100s of DNA Islands in O157:H7 vs. K12: Gene Loss or Transfer?

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Lateral Transfer Inference Based on Complete Genome Analysis I:

Organellar to Nuclear Transfers in A. thaliana

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Mitochondrial Genome Integration into A. thaliana chrII

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A. thaliana Nuclear Proteins:Best Matches to Complete Genomes

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Best Matches vs. Prokaryotes

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Best Matches Per ORF

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Lateral Transfer Inference Based on Complete Genome Analysis II:

Bacterial to Vertebrate Transfers Based on Analysis of the Human

Genome

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Lander et al. ‘Evidence’

• Genes match bacteria not non-vertebrate eukaryotes

• Or, genes have stronger match to bacteria than non-vertebrates

• A set of ~120 of these genes found in many bacterial species

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Alternative explanations

• Gene loss from non-vertebrate eukaryotes

• Rapid divergence in non-vertebrate eukaryotes

• Incomplete genomes (e.g., D. melanogaster)

• Bad annotation/gene finding

• Contamination

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Evolutionary Rate Variation

231456

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Trees Don’t Support TransferParamecium bursaria Chlorella virus 1Homo sapiens HAS1Mus musculus HAS1Xenopus laevisXenopus laevis Danio rerio Homo sapiens Mus musculus Danio rerio Xenopus laevis Gallus gallus Bos taurus Homo sapiens Mus musculus Rattus norvegicus Bradyrhizobium sp SNU001Rhizobium leguminosarumRhizobium spRhizobium lotiRhizobium tropiciRhizobium sp. NodCMesorhizobium sp 7653RSinorhizobium melilotiRhizobium melilotiRhizobium leguminosarumRhizobium galegaeAzorhizobium caulinodansStigmatella aurantiacaStreptomyces coelicolorStreptococcus uberisStreptococcus equisimilisStreptococcus pyogenes HASAStreptococcus pneumoniae0.2BacteriaVertebratesVirusIIIIII

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Number of pBVTs is Dependent on # of Genomes Analyzed

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Birney et al, same issue of Nature as complete genome

“The unfinished human genomic DNA may contain contamination, particularly from bacteria but also from other sources. Contaminating DNA is routinely removed from finished sequence, but some is still present in unfinished sequence. If the predicted gene matches a bacterial gene more closely than any vertebrate gene then it will almost always be a contaminant.”

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Evolution and Complete Genomes V:Species Evolution

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Whole Genome “Phylogeny”

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Whole Genome vs. rRNA

Methanobacterium thermoautotrophicumArchaeoglobus fulgidusPyrococcus horikoshiiMethanococcus jannaschiiAeropyrum pernix0.05 changesArchaeaMycobacterium tuberculosisBacillus subtilisSynechocystis sp.Aquifex aeolicusThermotoga maritimaDeinococcus radioduransTreponema pallidumBorrelia burgdorferiHelicobacter pyloriCampylobacter jejuniNeisseria meningitidisEscherichia coliVibrio choleraeHaemophilus influenzaeRickettsia prowazekiiMycoplasma pneumoniaeMycoplasma genitaliumChlamydia trachomatisChlamydia pneumoniaeBacteriaCaenorhabditis elegansDrosophila melanogasterSaccharomyces cerevisiaeEukarya

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Deinococcus radiodurans2a) RecA2b) SS-rRNAErwinia carotovaraEscherichia coliShigella flexneriEnterobacter agglomeransYersinia pestisSerratia marcescensProteus vulgarisProteus mirabilisVibrio anguilarrumVibrio choleraeHaemophilus influenzaeArabidopsis thaliana CPSTAcetobacter polyoxogenesMethylobacillus flagellatumMethylomonas claraMethylophilus methylotrophusMagnetispirillum magnetotacticumRhizobium phaseoliRhizobium viciaeCorynebacterium glutamicumStreptomyces violaceusMycobacterium lepraeMycobacterium tuberculosisStreptomyces ambofaciensStreptomyces lividansBorrelia burgdorferiBacteroides fragilisChlamydia trachomatisThermus aquaticusThermus thermophilusAquifex pyrophilusThermotoga maritimaLactococcus lactisStreptococcus pneumoniaeBacillus subtilisStaphylococcus aureusAcholeplasma laidlawiiSynechococcus sp. PCC7002Synechococcus sp. PCC7942Anabaena variabilisCampylobacter jejuniHelicobacter pyloriAgrobacterium tumefaciensRhizobium melilotiRhodobacter sphaeroidesRhodobacter capsulatusRickettsia prowazekiiMyxococcus xanthus2Myxococcus xanthus1Xanthomonas oryzaeThiobacillus ferrooxidansAcidiphilium facilisBrucella abortusNeisseria gonorrhoeaePseudomonas fluorescencsPseudomonas aeruginosaAzotobacter vinelandiiPseudomonas putidaAcinetobacter calcoaceticusLegionella pneumophilaBurkholderia cepaciaBordetella pertussisMycoplasma mycoidesMycoplasma pulmonisErwinia carotovaraEscherichia coliEnterobacter agglomeransYersinia pestisSerratia marcescensProteus vulgarisArsenophonus nasoniaeVibrio anguilarrumVibrio choleraeHaemophilus influenzae"Flavobacterium" lutescensNicotiana tabacum CPSTAcetobacter pasterianusMethylobacillus flagellatumMethylomonas methylovoraMethylophilus methylotrophusMagnetispirillum magnetotacticumRhizobium phaseoliRhizobium viciaeCorynebacterium glutamicumStreptomyces coelicolorMycobacterium lepraeMycobacterium tuberculosisStreptomyces ambofaciensStreptomyces lividansBorrelia burgdorferiBacteroides fragilisChlamydia trachomatisThermus aquaticusThermus thermophilusDeinococcus radioduransAquifex pyrophilusThermotoga maritimaLactococcus lactisStreptococcus salivariusBacillus subtilisStaphylococcus aureusAcholeplasma laidlawiiSynechococcus sp. PCC6301Phormidium minutumAnabaena sp . PCC7120Campylobacter jejuniHelicobacter pyloriAgrobacterium tumefaciensRhizobium melilotiRhodobacter sphaeroidesRhodobacter capsulatusRickettsia prowazekiiMyxococcus xanthusXanthomonas oryzaeThiobacillus caldusAcidiphilium facilisBrucella abortusNeisseria gonorrhoeaePseudomonas flavescensPseudomonas aeruginosaPseudomonas putidaAcinetobacter calcoaceticusLegionella pneumophilaBurkholderia cepaciaBordetella pertussisMycoplasma mycoidesMycoplasma pulmonisγ1γ2βαLowGCHighGCδεCyano/D T

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Coming Attractions I: Phylogenetic Profiles

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Phylogenetic Profile - E.coliFlagellar Genes

fhiAfliMfliPfliGflgGfliFflgIflhAflhBgcpE

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PG Profile. C. tepidum Chlorophyll Synthesis

CbiGCbiPDsrNCbiACbiJHCobNBchH1BchH2CobN2BchH3ChlIChlI2ChlI3

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Coming Attractions II:Uncultured Environmental Species

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Genomics does not require initial culturing step.

• Isolate, by filtration, all bacteria in a water sample• Extract total DNA in very large pieces• Clone those pieces as BACs into E.coli to get enough.• Sequence the BACs like a bacterial genome.

Natural Water

Filterconcentrate

ExtractDNA

CloneInto BACs

SequenceGeneList

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Bacterial Rhodopsin: a new photosynthesis system in the oceans

SAR86, anuncultured

bacteria

BAC Sequenced and

Analyzed

Beja O, et.al., Science 2000 289:1902-6

Bacterial rhodopsin: evidence for a new type of phototrophy in the sea.

Rhodopsinfound

H+ADP ATP

Cloned into E. coli E. coli pumps

protons in thelight

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80 m750 m

Proteobacteria

Archaea

Best Matches of Bac Ends

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RecA-Bacteroides/Cytophaga in Monterey Bay BACs

Chlorobium tepidum

Cytophaga hutchinsonii

Prevotella ruminocola

Bacteroides fragilis

Porphyromonas gingivalis

MBBAD68TR

MBBAD65TR

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Wither Genomics? Not yet.

• Despite limitations, a great deal can still be learned from genome sequence analysis.

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Evolutionary Diversity Still Poorly Represented in Complete Genomes

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Limited Ecological and Physiological Diversity

• All genomes from cultured species or pathogens/symbionts

• Limited ecological diversity– most are from pathogens or thermophiles

• Limited physiological diversity– need whole range for particular physiologies,

not just extremes

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Why Completeness is Important

• Improves characterization of genome features– Gene order, replication origins

• Better comparative genomics– Genome duplications, inversions

• Presence and absence of particular genes can be very important (e.g., gene loss)

• Missing sequence might be important (e.g., centromere)

• Allows researchers to focus on biology not sequencing• Facilitates large scale correlation studies

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Acknowledgements

• Genome inversions: S. Salzberg, J. Heidelberg, O. White, A. Stoltzfus, J. Peterson, H. Ochman

• Genome sequences and analysis: J. Heidelberg, T. Read, H. Tettelin, K. Nelson, J. Peterson, R. Fleischmann, D. Bryant

• Horizontal transfers: K. Nelson, W. F. Doolittle

• TIGR: C. Fraser, J. Venter, M-I. Benito, S. Kaul, Seqcore

• $$$: NSF, NIH, ONR, DOE

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Close Relatives vs Year0510152025303540199519961997199819992000Solo generaMultiple species

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Evolutionary Studies Improve Most Aspects of Genome Analysis• Phylogeny of species places comparative data in perspective• Evolution of genes and gene families

– Functional predictions– Identification of orthologs and paralogs– Species specific mutation patterns

• Evolution of pathways– Convergence– Prediction of function

• Evolution of gene order/genome rearrangements• Phylogenetic distribution patterns• Identification of novel features

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Genome Information and Analysis Improves Studies of Evolution

• Complete genome information particularly useful

• Unbiased sampling

• More sequences of genes

• Presence/absence information needed to infer certain events (e.g., gene loss, duplication)

• Genome wide mutation and substitution patterns (e.g., strand bias)

• Diversification and duplication

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Tracing Gene Loss

• Need presence and absence information of orthologous genes from different species

• Determining absence requires a complete genome

• May still miss some homologs (e.g., due to rapid divergence)

• Helps to have closely related species

• Use standard character state reconstruction methods to infer gene gain and loss

Keynote talk at "Society for General Microbiology" meeting in March, 2001 by Jonathan Eisen

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