Julius B. Lucks/Meetings and Notes/20070523

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 |
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 |
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 |
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 |