Genome Evolution Amos Tanay The Weizmann Institute Genome

Genome Evolution © Amos Tanay, The Weizmann Institute Genome evolution 2010 Lecture 1: evolutionary ideas Amos Tanay, Ziskind 204, ext 3579 עמוס תנאי amos. tanay@weizmann. ac. il http: //www. wisdom. weizmann. ac. il/~atanay/Genome. Evo/

Genome Evolution © Amos Tanay, The Weizmann Institute Linnaeus - Species Swedish (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 “Forming order” Complexification force Adaptive force

Genome Evolution © Amos Tanay, The Weizmann Institute Darwin – natural selection Darwin English (1809 -1882) Dislike surgeon studies Famous Beagle trip Maltussian growth Survival 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 Ronald Fischer: (English 1890 -1962) Start by studying crop variation Invented ANOVA, Max likelihood, non parameteric statistics, Fischer information Qunatitative genetics, diffussion approximation J. B. S Haldane: (English 1892 -1964) Aristocrat family Briggs-haldane kinetics (Michaelis-Mentel Alternative) Gene frequencies Popular author and communicator Fischer Haldane Sewall Wright: (American 1889 -1988) Geneticist (Guinea pigs) Genetic drift, inbreeding. . Wright

Genome Evolution © Amos Tanay, The Weizmann Institute Models of population genetics Blue allele A Generations/time a Yellow allele A a Modeling the dynamics of allele frequencies AA Aa aa Generations/time AA Aa aa Modeling the dynamics of allele frequencies

Genome Evolution © Amos Tanay, The Weizmann Institute Modeling evolution Blue allele A Generations/time a Yellow allele A a Modeling the dynamics of allele frequencies t t+1

Genome Evolution © Amos Tanay, The Weizmann Institute Mayr, Dobzhansky – Synthesis Frequency of recessive allele (blue flower color) in “desert snow” flowers (Lynanthus parruae) 0. 717 Mayr Ernst Mayr: German/American (1904 -2005) 0. 573 0. 005 0. 657 0. 000 0. 032 0. 009 0. 302 0. 000 0. 007 0. 339 Tropical explorations: birds 0. 005 0. 008 0. 000 0. 010 Theodosius Dobzhansky (Ukrainan/American 19001975) 0. 002 0. 004 0. 000 0. 504 Dobzhansky 0. 000 0. 126 0. 000 0. 106 0. 224 0. 068 0. 000 0. 014 0. 411 Speciation Biogeography Philosophy of Science: rejected reductionism Genetics and the origin of species Flies/plants field studies The modern synthesis Mendel Darwin

Genome Evolution © Amos Tanay, The Weizmann Institute Watson, Crick - Code The code – Genomic sequences …ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT… Monod Jacob Crick The machine – Protein networks in cells

Genome Evolution © Amos Tanay, The Weizmann Institute Kimura: Stochasticity, Neutrality 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 …ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT… …ACGAATAGCAAAAGGGCAGATGGCATTCTAGATCGAAAGCATGAAACTAGATAGCAT… …ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT… Kimura …ACGAATAGCAAATGGGCAGATGGCAGTCTAGATCGAAAGCATGAAACTAGATAGCAT…

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 But we can try and understand the essence of neutral evolution even without fancy mathematics: Neutral changes Along the path are fixated Last common ancestor t=1 Coalescent time t=n

Genome Evolution © Amos Tanay, The Weizmann Institute Felsenstein (and many others): Phylogenetics, probability Computational methods for sequence analysis Construct phylogenies from genomes Tree of live? 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 Genome evolution is facilitated by duplications Underlying concept: modularity Susumo Ohno – (1928 -2000) 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 Davidson. . Gould. . Lewis. . Evo-Devo

Genome Evolution © Amos Tanay, The Weizmann Institute Maynard-Smith: interaction Interaction between individuals inside a species: different strategies Introducing game theoretic ideas to evolution What is the basic unit of evolution? 1920 -2004 Genes may compete and interact in a population

Genome Evolution © Amos Tanay, The Weizmann Institute The Genomics revolution

Genome Evolution © Amos Tanay, The Weizmann Institute From hundreds to billions loci…. Genome = many independent nucleotides x 1 Universal x 2 x 3 x 4 x 5 x 6 Q 1960 Multiple copies of the same Markov process Protein analysis Phylogenetic reconstruction 1970 1980 1990 2000 2010

Genome Evolution © Amos Tanay, The Weizmann Institute From hundreds to billions loci…. Genome = many independent nucleotides x 1 Universal x 2 x 3 x 4 x 5 x 6 Q Multiple copies of the same Markov process 1960 1970 1980 1990 2000 2010

Humans and Chimps ~5 -7 million years 3 X 109 {ACGT} Genome alignment • Where are the “important” differences? • How did they happen? Genome Evolution © Amos Tanay, The Weizmann Institute

Genome Evolution © Amos Tanay, The Weizmann Institute 9% 1. 2% 0. 8% 3% 1. 5% 0. 5% Human Chimp Gorilla Orangutan Gibbon Baboon Macaque Where are the “important” differences? How did new features were gained? Marmoset 0. 5%

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. 9 MB genome, 30 K 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 Ultimate experiment: sequence the entire genome of the evolving S. aureus Mutations Resistance to Antibiotics 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 1 2 3 4 -6 7 8 9 10 11 12 13 14 15… 18 S. Aureus got found just few “right” mutations and survived multi-antibiotics

Genome Evolution © Amos Tanay, The Weizmann Institute “Junk” and ultraconservation Baker’s yeast 12 MB ~6000 genes The worm c. elegans 100 MB ~20, 000 genes Humans 3 GB ~27, 000 genes 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 intergenic exon intron ENCODE Data exon intergenic

Genome Evolution © Amos Tanay, The Weizmann Institute Course duties • Exercises – 70% of the grade • Submit on time • Present a paper Topics: Population genetics: models, drift, selection Species, phylogenies Probabilistic models for sequence evolution Comparative genomics: inferring selection Quantitative traits evolution Evolution of transcription regulation Mathematics: Markov processes, algorithms for probabilistic inference, some statistics Introduced without assuming much prior knowledge, buy may require work to understand. .