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Genome Evolution © Amos Tanay, The Weizmann Institute
Genome evolution 2012
Lecture 1: evolutionary ideas
Amos Tanay, Ziskind 204, ext 3579 עמוס תנאי
amos.tanay@weizmann.ac.il
http://www.wisdom.weizmann.ac.il/~atanay/GenomeEvo/
Genome Evolution © Amos Tanay, The Weizmann Institute
Linnaeus - SpeciesSwedish (1708-1777)
Developed hierarchical taxonomy (and pioneered scientific classification)
Even though his classification scheme included mythic monsters, Goethe said he is comparable only to Shakespeare and Spinoza
Genome Evolution © Amos Tanay, The Weizmann Institute
Lemarck - adaptation
Jean Baptiste Lamarck
French (1744-1829)
First specializing in invertebrate zoology, collecting samples for museums-gardens
1 paper in first 6 years as professor
Controversial (geophysics, chemistry..)
The “first” evolutionary theorist
Complexification force Adaptive force
“Forming order”
Genome Evolution © Amos Tanay, The Weizmann Institute
Darwin – natural selection
Darwin
English (1809-1882)
Dislike surgeon studies Famous Beagle tripMaltussian growthSurvival of the fittest
Wallace“Origin of species” (1859)
First print: 1250 copies
The Descent of Man, and Selection in Relation to Sex
Genome Evolution © Amos Tanay, The Weizmann Institute
Fischer,Haldane,Wright – Population genetics
Fischer
Haldane
Wright
Sewall Wright: (American 1889-1988)Geneticist (Guinea pigs)Genetic drift, inbreeding..
Ronald Fisher: (English 1890-1962)Start by studying crop variationInvented ANOVA, Max likelihood, non parametric statistics, Fisher information Quantitative genetics, diffusion approximation
J.B.S Haldane: (English 1892-1964)Aristocrat familyBriggs-haldane kinetics (Michaelis-Mentel Alternative)Gene frequenciesPopular author and communicator
Genome Evolution © Amos Tanay, The Weizmann Institute
Models of population genetics
A
a
A
a
Generations/time
Modeling the dynamics of allele frequencies
Blue allele
Yellow allele
AA
aa
AaGenerations/time AA
aa
Aa
Modeling the dynamics of allele frequencies
Genome Evolution © Amos Tanay, The Weizmann Institute
Modeling evolution
A
a
A
a
Generations/time
Modeling the dynamics of allele frequencies
Blue allele
Yellow allele
t t+1
Genome Evolution © Amos Tanay, The Weizmann Institute
DobzhanskyMayr
0.717
0.573
0.504
0.302
0.657
0.3390.008
0.007
0.032
0.005
0.009
0.000
0.000
0.000
0.000
0.005
0.010
0.000
0.000
0.126
0.068
0.004
0.002
0.000
0.000
0.000
0.014
0.224
0.411
0.106
1589.0SRF
3299.0RTF
4995.0H
0272.0H
3062.0H
Frequency of recessive allele (blue flower color) in “desert snow” flowers (Lynanthus parruae)
Mayr,Dobzhansky – Synthesis
The modern synthesis
DarwinMendel
Ernst Mayr: German/American (1904-2005)
Tropical explorations: birds
SpeciationBiogeographyPhilosophy of Science: rejected reductionism
Theodosius Dobzhansky (Ukrainan/American 1900-1975)
Genetics and the origin of species
Flies/plants field studies
Genome Evolution © Amos Tanay, The Weizmann Institute
The code – Genomic sequences
The machine – Protein networks in cells
…ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…
Watson,Crick - Code
Jacob
Monod
Crick
Genome Evolution © Amos Tanay, The Weizmann Institute
Kimura: Stochasticity, Neutrality
Kimura
…ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…
…ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…
…ACGAATAGCAAAAGGGCAGATGGCATTCTAGATCGAAAGCATGAAACTAGATAGCAT…
…ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…
…ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…
Selectionists: Mutations are occurring by chance - some get selected and these are the changes we see between genomes
Kimura et al.: Most of the changes between genomes are neutral - not a result of selection
Genome Evolution © Amos Tanay, The Weizmann Institute
Neutral Evolution
Kimura’s analytic achievement was the solution of a certain class of Partial Differential Equations that describe the dynamic of allele frequencies under neutral evolution
),()(2
1),()(),(
2txxV
xtxxM
xtx
t
But we can try and understand the essence of neutral evolution even without fancy mathematics:
t=1 t=n
Last common ancestor
Neutral changesAlong the path are fixated
Coalescent time
Genome Evolution © Amos Tanay, The Weizmann Institute
Felsenstein (and many others): Phylogenetics, probability
Computational methods for sequence analysis
Construct phylogenies from genomes
Tree of life? Origin of early forms?
Gould-Eldrege:Punctuated equilibrium
Better and better fossil record
Evolution/speciation rate: bursts
Joe Felsenstein
Genome Evolution © Amos Tanay, The Weizmann Institute
Ohno: duplication
Susumo Ohno – (1928-2000)
Genome evolution is facilitated by duplications
Underlying concept: modularity
Based on protein families at start
(Can you think of the challenges in explaining protein duplication?)
Genome Evolution © Amos Tanay, The Weizmann Institute
Yeast Genome duplication
• The budding yeast S. cerevisiae genome have extensive duplicates
• We can trace a whole genome duplication by looking at yeast species that lack the duplicates (K. waltii, A. gosypii)
• Only a small fraction (5%) of the yeast genome remain duplicated
Genome Evolution © Amos Tanay, The Weizmann Institute
• How can an organism tolerate genome duplication and massive gene loss?
• Is this critical in evolving new functionality?
Genome Evolution © Amos Tanay, The Weizmann Institute
Jacob/Monod-> Evolving programs
F. Jacob(b 1920)
J. Monod(1910-1976)
Regulation
Development
Evo-Devo
Davidson..Gould..Lewis..
Genome Evolution © Amos Tanay, The Weizmann Institute
Maynard-Smith: interaction
1920-2004
Interaction between individuals inside a species: different strategies
Introducing game theoretic ideas to evolution
What is the basic unit of evolution?
Genes may compete and interact in a population
Genome Evolution © Amos Tanay, The Weizmann Institute
The Genomics revolution
Mouse chromosomes colors overlaid on the human chromosomes – From the mouse genome paper
Genome Evolution © Amos Tanay, The Weizmann Institute
From hundreds to billions loci….
Protein analysis
1960
1970
1980
1990
2000
2010
x1 x2 x3 x4 x5 x6
Phylogenetic reconstruction
Multiple copies of the same Markov process
Universal Q
Genome = many independent nucleotides
Genome Evolution © Amos Tanay, The Weizmann Institute
From hundreds to billions loci….
1960
1970
1980
1990
2000
2010
x1 x2 x3 x4 x5 x6
Multiple copies of the same Markov process
Universal Q
Genome = many independent nucleotides
Genome Evolution © Amos Tanay, The Weizmann Institute
Humans and Chimps
• Where are the “important” differences?• How did they happen?
~5-7 million years
3X109
{ACGT}3X109
}ACGT{
Genome alignment
Genome Evolution © Amos Tanay, The Weizmann Institute
Ma
rmo
se
t
Ma
ca
qu
e
Ora
ng
uta
n
Ch
imp
Hu
ma
n
Bab
oo
n
Gib
bo
n
Gor
illa
0.5%0.5%
0.8%
1.5%
3%
9%
1.2%
Where are the “important” differences?
How did new features were gained?
Genome Evolution © Amos Tanay, The Weizmann Institute
“Junk” and ultraconservation
12MB ~6000 genes
100MB ~20,000 genes
3GB ~27,000 genes
Baker’s yeast
The worm c.elegans
Humans
1 cell
~1000 cells
~50 trillions cells
Genome Evolution © Amos Tanay, The Weizmann Institute
Archeological genomics reveal sequences of extinct species!
Genome Evolution © Amos Tanay, The Weizmann Institute
From: Lynch 2007
Genome Evolution © Amos Tanay, The Weizmann Institute
ENCODE Data
exon exon exon exonintron intergenicintergenic intronintron
Genome Evolution © Amos Tanay, The Weizmann Institute
Antibiotic resistance: Staphylococcus aureus
Timeline for the evolution of bacterial resistance in an S. aureus patient (Mwangi et al., PNAS 2007)
•Skin based•killed 19,000 people in the US during 2005 (more than AIDS)•Resistance to Penicillin: 50% in 1950, 80% in 1960, ~98% today•2.9MB genome, 30K plasmid
How do bacteria become resistant to antibiotics?Can we eliminate resistance by better treatment protocols, given understanding of the evolutionary process?
Genome Evolution © Amos Tanay, The Weizmann Institute
Vanco. Rifampi Oxacili Dapto.
20/7 1 0.012 0.75 0.01
20/9 4 16 25 0.05
1/10 6 16 0.75 0.05
6/10 8 16 1.5 1.0
13/10 8 16 0.75 1.0
Mutations
1 2 3 4-6 7 8 9 10 11 12 13 14 15…18Resistance to Antibiotics
S. Aureus found just few “right” mutations and survived multi-antibiotics
Ultimate experiment: sequence the entire genome of the evolving S. aureus
Genome Evolution © Amos Tanay, The Weizmann Institute
Toprak et al. 2012
Evolving E.coli in the lab given antibiotic pressure
Independent lines develop resistance by playing with one critical protein in multiple ways
Genome Evolution © Amos Tanay, The Weizmann Institute
Course duties
•Exercises – 70% of the grade – (Evolutionary simulations/Theory)
•Project
Topics:
Population genetics: models, drift, selectionSpecies, phylogeniesProbabilistic models for sequence evolutionComparative genomics: inferring selectionQuantitative traits evolutionEvolution of transcription regulationCancer evolution
Mathematics: Markov processes, algorithms for probabilistic inference, some statisticsIntroduced without assuming much prior knowledge, buy may require work to understand..