Julius B. Lucks/Meetings and Notes/20070523

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Protein Evolutionary Rates

  • dS = # synonymous changes per site
  • dN = # non-synonymous changes per site
  • calculate these quantities by comparing coding sequences of similar organisms that have diverged (S. ceriviciae and S. bayanus diverged 20 million years ago)
  • Drummond, PNAS, 2005 [1]
    • dN has a range of several orders of magnitude
    • what is known is that highly expressed proteins evolve slowly (small dN)
    • expression level, CAI, abundance, # interactions, length, network centrality, fitness of knockout - all correlate with dN
  • Drummond, MBE, 2006 [2]
    • principal axis when do Principle Component Regression is: expression level, CAI, abundance - no other relevant axis
      • Principle Component Regression - take axes that find with Principle Component Analysis (PCA), and regress these with an outcome variable (here dN)
    • the problem is protein interaction data is very unreliable [3]
  • Plotkin and Fraser, MBE, 2007, [4]
    • make all variables on equal footing by adding noise to them to equal the noise in the protein interaction data
      • find that the principle component found above drastically reduced
    • hidden variable analysis to see if can extract anything from the noisy data
    • contentious because protein interaction data is biased towards picking up interactions between highly abundant proteins, and thus slowly evolving proteins - conflation

Side Note

  • how does PCA deal with variables that have different scales?
    • 2 options
      • normalize all variables to have an internal variance of 1 (and 0-mean)
      • do PCA on the rank of the variables (non-parametric)

Bibliography

  1. Drummond DA, Bloom JD, Adami C, Wilke CO, and Arnold FH. Why highly expressed proteins evolve slowly. Proc Natl Acad Sci U S A. 2005 Oct 4;102(40):14338-43. DOI:10.1073/pnas.0504070102 | PubMed ID:16176987 | HubMed [Drummond-PNAS-2005]
  2. Drummond DA, Raval A, and Wilke CO. A single determinant dominates the rate of yeast protein evolution. Mol Biol Evol. 2006 Feb;23(2):327-37. DOI:10.1093/molbev/msj038 | PubMed ID:16237209 | HubMed [Drummond-MBE-2006]
  3. von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, and Bork P. Comparative assessment of large-scale data sets of protein-protein interactions. Nature. 2002 May 23;417(6887):399-403. DOI:10.1038/nature750 | PubMed ID:12000970 | HubMed [vonMering-Nature-2002]
  4. Plotkin JB and Fraser HB. Assessing the determinants of evolutionary rates in the presence of noise. Mol Biol Evol. 2007 May;24(5):1113-21. DOI:10.1093/molbev/msm044 | PubMed ID:17347158 | HubMed [Plotkin-Fraser-MBE-2007]
All Medline abstracts: PubMed | HubMed