title: Assessing the determinants of evolutionary rates in the presence of noise.
abstract: Although protein sequences are known to evolve at vastly different rates, little is known about what determines their rate of evolution. However, a recent study using principal component regression (PCR) has concluded that evolutionary rates in yeast are primarily governed by a single determinant related to translation frequency. Here, we demonstrate that noise in biological data can confound PCRs, leading to spurious conclusions. When equalizing noise levels across 7 predictor variables used in previous studies, we find no evidence that protein evolution is dominated by a single determinant. Our results indicate that a variety of factors--including expression level, gene dispensability, and protein-protein interactions--may independently affect evolutionary rates in yeast. More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution.
authors.affiliation: Department of Biology, The University of Pennsylvania, USA. jplotkin@sas.upenn.edu
authors.forename: Joshua B
authors.initials: JB
authors.lastname: Plotkin
authors.forename: Hunter B
authors.initials: HB
authors.lastname: Fraser
mesh_terms: D003062:Codon; D019143:Evolution, Molecular; D005800:Genes, Fungal; D008957:Models, Genetic; D012044:Regression Analysis; D012441:Saccharomyces cerevisiae / Q000235:genetics*; D012641:Selection, Genetic
chemical_list: D003062:Codon