1. MOLECULAR EVOLUTION Molecular evolution examines DNA and proteins, addressing two types of questions: How do DNA and proteins evolve? How are genes and organisms evolutionarily related?

2. Applications Reveal dynamics of evolutionary processes. Indicate chronology of change. Identify phylogenetic relationships.

3. Alignment of two sequences Number of aligned positions = 23

4. Sequence Alignments Matching nucleotides are interpreted as unchanged since a common ancestor. Substitutions, insertions, and deletions can be identified. Gaps inserted to maximize the similarity between aligned sequences indicate occurrence of insertions and deletions (indels).

5. Optimal alignment Many alignments are possible between sequences, and algorithms typically maximize the matching number of amino acids or nucleotides, invoking the smallest possible number of indel events.

6. Substitutions When DNA sequences diverge, they begin to collect mutations. The number of substitutions (P) found in an alignment is widely used in molecular evolution analysis.

7. An exemplary alignment Number of aligned positions = 23 Number of different positions (P) = 8

8. Number of substitutions If the alignment shows few substitutions, a simple count is used. If many substitutions occurred, it is likely that a simple count will underestimate the substitution events, due to the probability of multiple changes at the same site.

9. Jukes and Cantor Model They assumed that each nucleotide is equally likely to change into any other nucleotide, and created a mathematical model to describe multiple base substitutions. What other models could be developed?

10. Jukes and Cantor model K= -(3/4)*ln (1-(4/3)*P) P= observed number of substitutions over the total number of sites. K=distance between sequence x and sequence y expressed as the number of changes per site corrected for multiple substitutions at the same site natural log (ln) corrects for the underestimation of substitutions). ¾ and 4/3 are terms reflect that there are four types of nucleotides and three ways in which a second nucleotide may be substituted with.

11. P = 8/23 = 0.348 K = -(3/4)*ln(1-4/3*P) = 0.467 Observed distance P = 0.348 increases when Jukes Cantor Model is used to correct for the multiple substitutions. Calculation of distance (K) between sequences

12. Correction for multiple substitutions If two sequences are 95% identical, then P = 0.05; and K = 0.0517-0.05 = 0.0017 If two sequences are only 50% identical, then P = 0.5; and K = 0.824 – 0.5 = 0.324

13. Rates of nucleotide substitutions Substitutions accumulate independently and simultaneously in different sequences. Substitution rate, R, can be calculated by dividing the distance (K) between two homologous sequences by 2T, where T is the divergence time. R = K/(2T).

14. Example The following sequences represent an optimum alignment of the first 50 nucleotides of human and sheep preproinsulin genes, which last shared a common ancestor 80 million years ago: Human: ATGGCCTGT GGATGCGCCT CCTGCCCCTG CTGGCGCTGC TGGCCCTCTG Sheep: ATGGCCTGT GGACACGCCT GGTGCCCCTG CTGGCCCTGC TGGCACTCTG

15. Example Human: ATGGCCTGT GGATGCGCCT CCTGCCCCTG CTGGCGCTGC TGGCCCTCTG Sheep: ATGGCCTGT GGACACGCCT GGTGCCCCTG CTGGCCCTGC TGGCACTCTG P = 6/50 = 0.12 (observed) K = -(3/4)ln(1-(4/3)(0.12)) = 0.1308 Estimated number of substitutions = 50 x 0.1308 = 6.56 R = K/(2T) = 0.1308/(2 x 80 x 10 6 ) = 8.175 x 10 - 10 /year

16. Degenerate Code Codons are degenerate. Of 20 amino acids, 18 are encoded by more than one codon. Met (AUG) and Trp (UGG) are the exceptions; all other correspond to a set of two or more codons. Codon sets often show a pattern in their sequences; variation at the third position is most common.

17. Degenerate Code The code has start and stop signals. AUG, the start signal for protein synthesis. Stop codons have no corresponding tRNA (UAG, amber; UAA, ochre; UGA, opal). Wobble occurs in the anticodon. The 3 rd base in the codon is able to base-pair less specifically, because it is less constrained three dimensionally.

18. Patterns and Modes of Substitutions Patterns of variation within homologous genes show that some amino acid substitutions are found more frequently than others.

19. Patterns and Modes of Substitutions Substitutions often involve amino acids with similar chemical characteristics, supporting two evolutionary principles: Mutations are rare events Most dramatic changes are removed by natural selection.

20. Patterns and Modes of Substitutions Chemically similar amino acids tend to have similar codons, and so may result from a single mutation. Natural selection acting on this variation produces proteins optimized for role and environment. More substantial alterations of protein structure are likely to be deleterious and removed from gene pool.

21. Synonymous and non- synonymous sites Synonymous changes, which do not alter the amino acids in the protein, are found five times more often than non-synonymous changes.

22. Synonymous and non- synonymous sites –Both types of change are equally likely to occur, but non-synonymous changes are usually detrimental to fitness, and are eliminated by natural selection. Mutations are changes in nucleotide sequences due to errors in replication or repair. Substitutions are mutations that have passed through the filter of selection.

23. Mutations vs. substitutions Would the mutation rate would be greater or less than the observed substitution rate, for example 8.175 x 10 -10 is for preproinsulin gene. YES Why?

24. Variation in evolutionary rates within genes Studies show that different regions of genes evolve at different rates. Distinctions are seen between and within coding and non-coding regions. Examples of non-coding regions include introns, leaders, non-transcribed flanking regions, pseudogenes.

25. Relative rates of evolutionary change in mammals SequenceR (x 10 -9 ) Functional genes 5’ flanking region2.36 CDS, synonymous4.65 CDS, nonsynonymous0.88 Intron3.70 3’ flanking region4.46 Pseudogenes4.85

26. Flanking regions and introns Changes in 3’ sequences have no known effect on the amino acid sequence; so most substitutions are tolerated. Rate of substitutions are high in introns but not as high as in synonymous of CDS. 5’ untranslated regions have low rates: they contain regulatory regions for transcription.

27. Pseudogenes Highest rate of evolution is that of nonfunctional pseudogenes, which no longer code for proteins. What advantage pseudogenes provide for evolution of multiple gene families?

28. Coding sequences with high rates of nonsynonymous substitution Major histocompatibility complex (MHC) in mammals If there is evolutionary pressure for diversity, substitutions become advantageous. MHC is involved in immune function where diversity favors fewer individuals vulnerable to an infection by any single virus. Viruses utilize error-prone replication coupled with diversifying selection. Both viruses and MHC complex rapidly evolves due to natural selection for diversification.

29. Ribosomal RNAs Sequences of rRNA regions that interact and provide for ribosomal function by pairing will be subject to mutation at the same rates as sequences that do not pair. However, mutations that disrupt pairing will be selected against, since such mutations will alter ribosomal function and become detrimental to fitness.

30. Mitochondrial DNA (mtDNA) Mammalian mitochondrial genome contains a circular, double-stranded mtDNA about 15000 bp long (1/10000 of the nuclear genome, encoding 2 rRNAs, 22 tRNAs, and 13 proteins). The average synonymous substitution rate in mammalian mitochondria is 5.7 x 10- 8/site/year, 10 times higher than the synonymous substitutions in nuclear genes.

31. Mitochondrial DNA (mtDNA) The higher rates of mutation in mtDNA are likely to be due to: The higher error rate during mtDNA replication and repair. mtDNA polymerases have no proofreading ability. Higher concentrations of mutagens such as free radicals resulting from metabolic processes. Less selective pressure because there are many of them within the cell; changes are less detrimental.

32. Maternal transmission Clonal inheritance from mother, when the mother’s egg contributes to the zygote. So no meiosis occurs, all offspring will have the same mtDNA from the same mother. Study matriarchal lineages can be traced allowing examination of family structure. Example: geographic variation in mtDNA sequences of pocket gophers in south eastern USA.

33. Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Letters are different mtDNA types grouped according to similarity, and are superimposed on a geographic map of the collection sites. The tick marks across connecting lines are the number of mutations. Lineage relationships among mtDNA types in pocket gophers

34. mtDNA or nuclear DNA Suppose you are studying human migrational patterns? Would you use mtDNA or nuclear genes to estimate how long ago humans moved from a particular place to another?

35. mtDNA or nuclear DNA? Since the time scale is on the order of tens of thousands years, and mtDNA accumulate more mutations than nuclear DNA, mtDNA will provide more information about the differences between human populations geographically separated. What about if you want to study the phylogenetic relationships of mammalian species that diverged 80 million years ago? (HINT: multiple substitutions)

36. Molecular Clock Suggests that rates of molecular evolution for loci with similar functional constraints are uniform during the time period after divergence from a common ancestor (Fossil record).

37. The molecular clock for alpha- globin

38. Rates of amino acid replacement in proteins

39. Peter J. Russell, iGenetics: Copyright © Pearson Education, Inc., publishing as Benjamin Cummings. Fig. 24.3 The molecular clock runs at different rates in different proteins

40. Molecular Phylogeny Organisms are similar at the molecular level are expected to be more closely related than dissimilar organisms. Phylogenetic relationships among living things are inferred from molecular similarity.