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Estimating Gene Expression and Codon-Specific Translational Efficiencies, Mutation Biases, and Selection Coefficients from Genomic Data Alone.

Gilchrist MA, Chen WC, Shah P, Landerer CL, Zaretzki R - Genome Biol Evol (2015)

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee mikeg@utk.edu.

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Comparison of with and without ROC SEMPPR estimates for codon-specificdifferences in mutation biases terms ΔM which areunitless. Specifically,  equals the natural logarithm of the ratio ofthe frequencies of synonymous codon 1 to i in the absenceof natural selection. To improve legibility of the plots, the two codonamino acids have been combined into two plots and all of the amino acidswith greater than two codons into separate plots. The dashed blue linerepresents the 1:1 line between axes and error bars indicate the 95%posterior CIs for each parameter. For both the with andwithout fits of ROC SEMPPR, all codons have CIs that donot overlap with 0. As illustrated in the last plot, a linear regressionbetween estimates of  for all codons produces a correlationcoefficient .
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evv087-F2: Comparison of with and without ROC SEMPPR estimates for codon-specificdifferences in mutation biases terms ΔM which areunitless. Specifically, equals the natural logarithm of the ratio ofthe frequencies of synonymous codon 1 to i in the absenceof natural selection. To improve legibility of the plots, the two codonamino acids have been combined into two plots and all of the amino acidswith greater than two codons into separate plots. The dashed blue linerepresents the 1:1 line between axes and error bars indicate the 95%posterior CIs for each parameter. For both the with andwithout fits of ROC SEMPPR, all codons have CIs that donot overlap with 0. As illustrated in the last plot, a linear regressionbetween estimates of for all codons produces a correlationcoefficient .

Mentions: Briefly, when fitted to the S. cerevisiae S288c genome, we findnearly perfect agreement between ROC SEMPPR’s with andwithout estimates for codon-specific protein synthesistranslational inefficiencies, Δη, and mutation bias,ΔM (Pearson correlation for both sets of parameters, see figs. 1 and 2).We note that, with the exception Arginine’s , the central 95% credibility intervals (CIs)for ROC SEMPPR’s Δη and ΔM parameters do notoverlap with zero (see supplementary tables S1–S4, Supplementary Material online). These results indicate thatinformation on the genome scale parameters, and are robustly encoded and estimable from CUB patternsand that provides little additional information. Fig. 1.—


Estimating Gene Expression and Codon-Specific Translational Efficiencies, Mutation Biases, and Selection Coefficients from Genomic Data Alone.

Gilchrist MA, Chen WC, Shah P, Landerer CL, Zaretzki R - Genome Biol Evol (2015)

Comparison of with and without ROC SEMPPR estimates for codon-specificdifferences in mutation biases terms ΔM which areunitless. Specifically,  equals the natural logarithm of the ratio ofthe frequencies of synonymous codon 1 to i in the absenceof natural selection. To improve legibility of the plots, the two codonamino acids have been combined into two plots and all of the amino acidswith greater than two codons into separate plots. The dashed blue linerepresents the 1:1 line between axes and error bars indicate the 95%posterior CIs for each parameter. For both the with andwithout fits of ROC SEMPPR, all codons have CIs that donot overlap with 0. As illustrated in the last plot, a linear regressionbetween estimates of  for all codons produces a correlationcoefficient .
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4494061&req=5

evv087-F2: Comparison of with and without ROC SEMPPR estimates for codon-specificdifferences in mutation biases terms ΔM which areunitless. Specifically, equals the natural logarithm of the ratio ofthe frequencies of synonymous codon 1 to i in the absenceof natural selection. To improve legibility of the plots, the two codonamino acids have been combined into two plots and all of the amino acidswith greater than two codons into separate plots. The dashed blue linerepresents the 1:1 line between axes and error bars indicate the 95%posterior CIs for each parameter. For both the with andwithout fits of ROC SEMPPR, all codons have CIs that donot overlap with 0. As illustrated in the last plot, a linear regressionbetween estimates of for all codons produces a correlationcoefficient .
Mentions: Briefly, when fitted to the S. cerevisiae S288c genome, we findnearly perfect agreement between ROC SEMPPR’s with andwithout estimates for codon-specific protein synthesistranslational inefficiencies, Δη, and mutation bias,ΔM (Pearson correlation for both sets of parameters, see figs. 1 and 2).We note that, with the exception Arginine’s , the central 95% credibility intervals (CIs)for ROC SEMPPR’s Δη and ΔM parameters do notoverlap with zero (see supplementary tables S1–S4, Supplementary Material online). These results indicate thatinformation on the genome scale parameters, and are robustly encoded and estimable from CUB patternsand that provides little additional information. Fig. 1.—

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology & Evolutionary Biology, University of Tennessee, Knoxville National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee mikeg@utk.edu.

Show MeSH
Related in: MedlinePlus