Estimating Gene Expression and Codon-Specific Translational Efficiencies, Mutation Biases, and Selection Coefficients from Genomic Data Alone.
Bottom Line: We also observe strong agreement between our parameter estimates and those derived from alternative data sets.Our estimates of codon-specific translational inefficiencies and tRNA copy number-based estimates of ribosome pausing time ([Formula: see text]), and mRNA and ribosome profiling footprint-based estimates of gene expression ([Formula: see text]) are also highly correlated, thus supporting the hypothesis that selection against translational inefficiency is an important force driving the evolution of CUB.In conclusion, our method demonstrates that an enormous amount of biologically important information is encoded within genome scale patterns of codon usage, accessing this information does not require gene expression measurements, but instead carefully formulated biologically interpretable models.
Affiliation: Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee firstname.lastname@example.org.Show MeSH
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Mentions: Given the strong correlation between ROC SEMPPR’s with andwithout estimates of the codon-specific mutation biases and translational inefficiencies, it is not surprising that with andwithout estimates of from ROC SEMPPR are highly correlated(, fig.5a). More importantly, the without based estimates of show substantial correlation with the mRNA abundancebased estimates of values from Yassour et al. (2009) (, fig.5b). To be clear, these values are the same values used as inputs to thewith model fits. Fig. 5.—
Affiliation: Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee email@example.com.