1. Molecular Evolution, Part 2 Everything you didn’t want to know… and more! Everything you didn’t want to know… and more!

2. Average Rates of Substitution

3. Similarity Profiles

4. What influences determine rates of change & levels of similarity? Mutation – stochastic changes Natural selection – organismal survival and reproductive success Genetic drift – random fixation of selectively neutral alleles

5. Detecting Positive Selection Protein coding regions only K A /K S Codon-degeneracy model (CDM) Selection on Amino Acid Properties (TreeSAAP) Case study paper

6. K A /K S Ratios

7. MEGA3 Molecular Evolutionary Genetics Analysis www.megasoftware.net/mega3/ 1. Constructing Trees from Distance Data 2. Computing Statistical Quantities for Nucleotide Sequences 3, Estimating Evolutionary Distances from Nucleotide Sequences 4. Constructing Trees and Selecting OTUs from Nucleotide Sequences 5. Tests of the Reliability of a Tree Obtained 6. Test of Positive Selection 7. Creating Multiple Sequence Alignments 8. Working With Genes and Domains 9. Managing Taxa With Groups Application Description

8. MEGA and Positive Selection

9. Results

10. Codon Degeneracy

11. CDM Uses the degeneracy structure of codons to predict patterns of nucleotide substitution expected under neutral expectations Expectations are statistically compared to observations inferred from a well-resolved phylogenetic tree Deviations from neutral expectations indicates a significant historical influence by natural selection on the protein

12. Patterns of Codon-degeneracy

13. Patterns Applied to the Standard Genetic Code

14. The Model Application Descriptions: 1, 2, 3123 (See pg. 395 of #3) Patterns of codon degeneracy Counting sites Counting codons with certain patterns of degeneracy Transition bias Evolvability – codon architecture

15. Central Equations

16. Nested Newick Trees

17. Transition Bias

18. Sliding Window

19. Results

20. Amino Acid Properties

21. Log odds ratio

22. The.doc format is much clearer..doc format i BLOSUM62 Substitution Matrix CSTPAGNDEQHRKMILVFYW C9 -30 -4-3 -2 S41 101000 0 -2 -3 T141 101000 0 -2 -3 P 17 -2 -2 -2-3 -2-4-3-4 A01 40 -2 -2 -2 -3 G 01-206 -2 -3-4 0-3 -2 N-310-2 0610000-2-3 -2-4 D-301-21620 -2-3 -4-3 -4 E 00 -20252001 -3 -2-3 Q 00 -200250110-3-2 -3-2 H-30-2 110080-2-3 -22-2 R-3 -2-20 01052-3-2-3 -2-3 K 00 -2011 25 -3-2-3 -2-3 M -2-3-2-3-20 512-20 I -2 -3-4-3 14210-3 L-2 -3-4-3-4-3-2-3-2 22430-2 V-2 0-3 -2 -3 -21314 -3 F-2 -4-2-3 -3 000631 Y-2 -3-2-3-2-3-22-2 372 W-2-3 -4-3-2-4 -3-2 -3 -3-2-3121 BLOSUM62 Substitution Matrix

23. Venn Diagram

24. Grantham Index Composition Polarity Molecular volume

25. Physicochemical Distances Composition, Polarity, Molecular Weight 20 Mammalian proteins

26. TreeSAAP Assumes that all possible changes are equally likely to construct a discrete probability distribution of magnitudes of biochemical change for alternative physicochemical amino acid properties Statistically compares these expectations with observed biochemical changes Deviations from constrained randomness indicate positive or negative selection

27. The Model Application Description (see pg. 919) Evolutionary pathways Counting codons obs/exp proportions

28. Amino Acid Properties

29. Magnitude Categories

30. Sliding Window

31. Results