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Molecular Evolution Molecular Evolution Justin Fay Center for Genome Sciences Department of Genetics 4515 McKinley Ave. Rm 4305 [email protected] Molecular evolution is the study of the cause and effects of evolutionary changes in molecules Species 1 GGCAGTGACATTTTCTAACGCGAAGGTACTT Species 2 GGCAGCGCCATTTTCTAATGCGAGGGTACTT Species 3 GGCAGCGCCATTGTCTAATGCGAGGGTACTT ***** * **** ***** **** ******* Phylogenetics Archea Divergence times Human-chimp-neanderthal Comparative Genomics Ultraconserved sequences (mutation and selection) ENCODE Fox2p Phylogenetics Methods Table 1. Number of possible rooted and unrooted trees. Table 2. Distance matrix. Sequence A B C Number of Number of rooted Number of A sequences trees unrooted trees B d(AB) 2 1 1 C d(AC) d(BC) 3 3 1 D d(AD) d(BD) d(CD) 4 15 3 Each d is the distance (substitution rate) 5 954 105 between pairs of sequences 10 34,459,425 2,027,025 Taxonomists have long debated phylogenetic methods. D C There are many types of methods: Character state methods (also called cladistic methods), like A B parsimony. Distance or similarity based methods (also called phenetic Software: methods), like UPGMA. PAUP Maximum likelihood and Bayesian Methods. PHYLIP MEGA Parsimony (non-parametric) and Maximum likelihood MrBayes (parametric) are both used when phylogeny is critical. Gene trees vs Species trees 1. Orthology 2. Independence (no concerted evolution or horizontal transfer) Orthologs are genes created by speciation events. Paralogs are genes created by duplication events. Homologs are genes that are similar because of shared ancestry. Duplication Orthologues and paralogues can be distinguished by i) synteny or ii) phylogeny. Speciation Species 1 Species 2 Gene Conversion and Horizontal Gene Transfer Locus 1 Chr02 HHF1 HHT1 Species tree Locus 2 Chr14 HHT2 HHF2 Vertebrate to Bacteria Bacteria to Vertebrate No conversion Gene Conversion (true phylogeny) Molecular Evolution (Comparative Genomics) 1. Conservation Annotation of genes, regulatory sequences and other functional elements Functional sequences will remain conserved across distantly related species whereas non-functional sequences will accumulate changes 2. Divergence Evolution of genes, regulatory sequences and other functional elements Species-specific functional sequences Functional sequences with new or modified functions Origins of Molecular Evolution Insulin was the first protein sequenced in 1955 for which Fred Sanger received the Nobel prize. Cytochrome C protein sequence (Margoliash et al. 1961). The sequencing of the same proteins from different species established a number of key principles of molecular evolution: 1. Most proteins are highly conserved and changes that do occur are not found within functionally important sites. For example human diabetics were treated with insulin purified from pigs and cows. 2. The rate of amino acid substitution is constant across phylogenetic lineages. Molecular clock - the rate of amino acid or nucleotide substitution is constant per year across phylogenetic lineages (Zuckerkandl and Pauling 1962). Controversial but revolutionized phylogenetics and set the stage for the neutral theory. Neutral theory or neutral mutation random drift hypothesis - the vast majority of mutations that become polymorphic in a population and fixed between species are not driven by Darwinian selection but are neutral or nearly neutral with respect to fitness (Kimura 1968; King and Jukes 1969). The neutral theory is dead; long live the neutral theory. Difference between between mutation rate Difference Fixation probability depends on selection on depends probability Fixation time * probability * fixation rate = rate mutation Substitution selection) on (depends population rate Substitution onselection) depend NOT (does division cell rate Mutation and and substitution rate. the chance of a mutation occurring in each generation or generation each in occurring ofamutation chance the the frequency at which mutations become fixed within a a within fixed become mutations at which frequency the Population frequency Time Nucleotide Substitution Models Jukes and Cantor (JC69) Model (1969) A G Purines C T Pyrimidines Assumptions of JC model. 1) Equal base frequencies Nucleotide substitution models 2) Equal mutation rates between the bases correct for multiple hits 3) Constant mutation rate 4) No selection Jukes Cantor Model p = 3/31 = 0.097 K = 0.104 substitutions per site Other nucleotide substitution models Model Assumption Free Reference Parameters JC69 A=G=C=T 1 Jukes & Cantor ts=tv 1969 K80 A=G=C=T 2 Kimura 1980 F81 ts=tv 4 Felsenstein 1980 HKY85 5 Hasegawa, Kishino & Yano GTR unequal rates 9 Tavare 1986 Substitution Rates with Selection Substitution rate = mutation rate * fixation probability * time The substitution rate for neutral mutations = 2Nµ * 1/2N * t = µt The substitution rate for adaptive mutations = 2Nµ * 2s * t = 4Nsµt for 4Ns > 1 No selection: The substitution rate between two species is K = 2t. −4N sq 1−e e P= Selection: −4N s 1−e e t S.cerevisiae S.paradoxus Conserved sequences Human-Mouse conservation Species Conserved* Conserved Noncoding Reference (non-repetitive aligned) Humans 3-8% 21% Waterston et al. (2002) Worms 18-37% 18% Shabalina & Kondrashov (1999) Flies 37-53% 40-70% Andolfatto (2005) Yeast 47-68% 30-40% Chin et al. (2005), Doniger et al. (2005) *Siepel et al. (2005) Deletion and expression assays of conserved noncoding sequences Pennacchio et al. 2006 Yun et al. 2012 Rapidly Evolving Genes (dN/dS) Detecting selection using the nucleotide substitution rate Synonymous change - mutation that does not change the amino acid sequence of a protein. Nonsynonymous change - mutation that changes the amino acid sequence of a protein. dN or Ka = the nonsynonymous substitution rate = # nonsynonymous changes / # nonsynonymous sites. dS or Ks = the synonymous substitution rate = # synonymous changes / # synonymous sites. Table 1. The genetic code. Codon AA Codon AA Codon AA Codon AA TTT Phe TCT Ser TAT Tyr TGT Cys TTC Phe TCC Ser TAC Tyr TGC Cys Interpretation of dN/dS ratios (assuming synonymous sites are TTA Leu TCA Ser TAA Stop TGA Stop TTG Leu TCG Ser TAG Stop TGG Trp neutral): dN/dS = 1No constraint on protein sequence, i.e. nonsynonymous CTT Leu CCT Pro CAT His CGT Arg CTC Leu CCC Pro CAC His CGC Arg changes are neutral. CTA Leu CCA Pro CAA Gln CGA Arg dN/dS < 1Functional constraint on the protein sequence, i.e. CTG Leu CCG Pro CAG Gln CGG Arg nonsynonymous mutations are deleterious. ATT Ile ACT Thr AAT Asn AGT Ser ATC Ile ACC Thr AAC Asn AGC Ser dN/dS > 1Change in the function of the protein sequence, i.e. ATA Ile ACA Thr AAA Lys AGA Arg nonsynonymous mutations are adaptive. ATG Met ACG Thr AAG Lys AGG Arg GTT Val GCT Ala GAT Asp GGT Gly GTC Val GCC Ala GAC Asp GGC Gly GTA Val GCA Ala GAA Glu GGA Gly GTG Val GCG Ala GAG Glu GGG Gly Rapidly Evolving Genes dN increased by positive selection dN decreased by negative selection Problem: dN may be influenced by both and still be less than dS Nayak et al. 2005 Branch Model (dN/dS) (rate heterogeneity) 15 copies in human Vary in copy in other primates Johnson et al. 2001 Site Model (dN/dS) ● Positive selection on the egg receptor (VERL) for abalone sperm lysin. ● VERL – lysin are a lock and key for fertilization. ● Co-evolution by sexual selection, conflict or microbial attack. Gilando et al. 2003 Sites – methods Maximum Parsimony (Suzuki) Maximum Likelihood (PAML, HyPhy) Models of molecular evolution Key Assumptions: ➔Alignments are correct ➔Sites are independent ➔Mutational & selection parameters Alignment Accuracy & Coverage No indels Indels No indels Indels No constraint Constraint Pollard et al. 2004 Alignment differences gp120 HIV/SIV ClustalW alignment PRANK alignment (phylogeny aware) Detection of positive selection depends on the alignment Markova-Raina and Petrov (2011) Mutation rate variation ● Transitions vs. Transversions – transitions occur twice as often as transversions ● CpG - Spontaneous deamination of 5- methylcytosine results in thymine and ammonia, 20x higher rate of transition ● 28% of mutations are transitions at CpG sites but only 3.5% of sites are CpG ● Genomic position (5-10%) ● Age, sex (2 – 10 fold) ● Repeats (polynucleotides, microsatellites) Types of Mutations - WGS Single nucleotide Transpositions Duplications Insertion/Deletion Rearrangement G/C to A/T 2.9-fold higher than reverse! Predicts 74% AT content Substitution rate as a function of GC content BRCA1 sliding window Ka/Ks analysis Codon Bias Measures of Codon Bias CAI – codon adaptive index based on relative usage of the codon to the most abundant codon for an amino acid Fop – frequency of the optimal codon ENC – effective number of codons based on the deviation from equal usage Explanation of Codon Bias Bias towards GC ending codons that is not found in adjacent noncoding regions Correlates with highly expressed genes Correlates with tRNA abundance Explanations: translational accuracy/speed, protein misfolding Codon Bias is correlated with Synonymous Substitution Rate Codon Bias correlation depends on distance Codon models αs = synonymous rate βs = nonsynonymous rate R = tv/ts πny = frequency of target nucleotide n in codon y Binding site models ● Sequence ~ binding affinity (Schneider et al. 1986, Berg and von Hippel 1987) ● Binding affinity ~ fitness (Gerland and Hwa 2002, Sengupta et al. 2002) ● Fitness ~ substitution rate (Moses et al. 2004) Kimura 1962 Bulmer 1991 Moses et al. 2004 Biased Gene Conversion AT to GC bias Recombination occurs in hotspots Recombination
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