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The phylogenetics project data revealed! October 4, 2010 OEB 192.

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Presentation on theme: "The phylogenetics project data revealed! October 4, 2010 OEB 192."— Presentation transcript:

1 The phylogenetics project data revealed! October 4, 2010 OEB 192

2 Geographic Distribution Pathogen = Salmonella Typhi

3 Why so little turnover? Letters indicate antibiotic resistant haplotypes Selection less effective due to “carriers” with no symptoms!

4 Codon Usage Bias & Selection October 4, 2010 OEB 192

5 Degenerate Code

6 Codon Usage Bias Non-random usage of codons Rickettsia (bacteria) - Winkler 1988 Percent codon usage in family Codons for each amino acid Preferred arginine codon Unpreferred arginine codon

7 Why non-random codon usage?

8 Codons correspond to anticodons on tRNAs

9 Unequal numbers of tRNAs There are six leucine codons So, there are six corresponding tRNAs tRNA copy number differences E. Coli - Ikemura 1981

10 Species differ in codon usage bias Without considering selection, why might different species have different codon usage patterns? Massey 2003 6 Leucine Codons

11 Different GC content alters codon usage Mutational Bias 232 Eubacterial genomes - Guchte 2006

12 Is there selection on codon bias? Four levels of evidence: 1.Genome level 2.Species level 3.Tissue level 4.Gene level Evidence: Non-random patterns of codon usage that are difficult to explain without selection

13 Selection on codons 1.Throughout genomes Same organism, so not explained by differences in tRNA abundance or mutational bias 2. Between species Why does the pattern decrease from E. coli to Human? Drummond and Wilke 2008 expression optimal codons High Expression level genes have high codon bias

14 Selection on codons 3. Within tissues Plotkin et al 2004 Red = selectively expressed in human testes Blue – selectively expressed In human ovaries

15 Selection on codons 4. Within genes Conserved sites more likely to use preferred codons Likely to find Preferred codon Likely to find Unpreferred codon Species in alignemnt: Os = Oryza sativa, Pp = Physcomitrella patens, Dd = Dictyostelium discoideum, Hs = Homo sapiens, Dr = Danio reiro, Dm = Drosophila melanogaster, Sc = Saccharomyces cerevisiae, Sp = Schizosaccharomyces pombe, Pf = Plasmodium falciparumGene = ubiquitin/SUMO-1 like protein Wang et. al. 2001

16 Why is there selection on codons? Movie of Translation: http://www.youtube.com/watch?v=Jml8CFBWcDs&p=22FC96CD697EBE40

17 Process of Translation Translational Speed Faster, so allows more protein to be made Translational Accuracy Incorrect translation is a waste of resources Discuss evidence:

18 Protein Folding Translational Speed Speed tuned to protein folding pace Translational Accuracy Mistranslation induced misfolding Translational Robustness Protein folds even with errors Discuss evidence:

19 Selection on synonymous sites Other general reasons for selection on synonymous sites (not specifically codon bias): Aberrant splicing mRNA instability secondary structure

20 Weak selection Is population size dependent – WHY? Smaller populations are more stochastic: 7 heads and 3 tails in 10 coin flips - possible vs. 70,000 heads and 30,000 tails in 100,000 coin flips – rare!

21 Weak selection Is population size dependent Other possible types of weak selection: Do humans and mammals have selection on codons? Much stronger in microbes! Allow us to study these patterns -ascertain mechanistic basis for selection -determine average effect of mutation Genome size Number of introns Urrutia & Hurst 2003

22 1.Could effect dN/dS (or other measures of selection)...but, It’s very weak selection that doesn’t effect all genes 1.Useful to detect HGT 2.Helpful to consider when building genetically modified organisms 4.Medical applications – Coleman et al. 2008 Implications of selection on synonymous sites Pride et al 2006

23 How is codon bias measured? Measure tRNA abundance CAI (Codon adaptation index): measures codon composition relative to reference set (usually highly expressed genes from same genome) Fop (frequency of optimal codons): Measures the number of preferred codons over the total number of amino acids with synonymous codons Akashi’s test: Tests how strong the correlation is between conserved sites and preferred codons Still more: ENC (Effective number of codons) MCB (Maximum Likelihood codon bias


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