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: As first shown in Shah and Gilchrist(2011), the relationship between codon usage and protein synthesis rate can range from simple and monotonic to complex. Figure 6 illustrates how codon usage changesacross approximately 2 orders of magnitudes of for each of the multicodon amino acids. Both ROC SEMPPR’swith and without model fits accurately predict how CUB changes withprotein synthesis rates (fig. 6). Indeed,the predicted changes in CUB between the with andwithout ROC SEMPPR model fits are almost indistinguishablefrom one another, reflecting the strong agreement between their estimates ofΔM and Δη across models as discussed above. Fig. 6.—
Affiliation: Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee email@example.com.