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Selection on codon bias in yeast: a transcriptional hypothesis.

Trotta E - Nucleic Acids Res. (2013)

Bottom Line: We show that the most used codons in highly expressed genes can be predicted by mRNA structural data and that the codon choice at each synonymous site within an mRNA is not random with respect to the local secondary structure.Consistent with this, we report evidence supporting the adaptation of the tRNA pool to the codon profile of the most expressed genes rather than vice versa.We show that the correlation of codon usage with the gene expression level also includes the stop codons that are normally not decoded by aminoacyl-tRNAs.

View Article: PubMed Central - PubMed

Affiliation: Institute of Translational Pharmacology, Consiglio Nazionale delle Ricerche (CNR), Roma 00133, Italy.

ABSTRACT
Codons that code for the same amino acid are often used with unequal frequencies. This phenomenon is termed codon bias. Here, we report a computational analysis of codon bias in yeast using experimental and theoretical genome-wide data. We show that the most used codons in highly expressed genes can be predicted by mRNA structural data and that the codon choice at each synonymous site within an mRNA is not random with respect to the local secondary structure. Because we also found that the folding stability of intron sequences is strongly correlated with codon bias and mRNA level, our results suggest that codon bias is linked to mRNA folding structure through a mechanism that, at least partially, operates before pre-mRNA splicing. Consistent with this, we report evidence supporting the adaptation of the tRNA pool to the codon profile of the most expressed genes rather than vice versa. We show that the correlation of codon usage with the gene expression level also includes the stop codons that are normally not decoded by aminoacyl-tRNAs. The results reported here are consistent with a role for transcriptional forces in driving codon usage bias via a mechanism that improves gene expression by optimizing mRNA folding structures.

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Frequency distribution and synonymous fraction of GCA and GCT. Frequency distribution (triangles) and synonymous fraction (circles) of GCA (open markers) and GCT (closed markers) with categories of transcript level. GCA and GCT are synonymous codons of the 4-fold degenerate amino acid alanine.
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gkt740-F2: Frequency distribution and synonymous fraction of GCA and GCT. Frequency distribution (triangles) and synonymous fraction (circles) of GCA (open markers) and GCT (closed markers) with categories of transcript level. GCA and GCT are synonymous codons of the 4-fold degenerate amino acid alanine.

Mentions: To exclude the possibility that the transcript levels associated with codons could be compatible with a neutral model in which mutational biases are the only active forces, we simulated 5000 yeast genomes with the codon probabilities at each synonymous site equal to their relative frequencies in the whole genome, but we left unchanged the transcript level assigned to each gene. The frequency distribution of the codon transcript level in simulated sequences showed that the levels of transcription in native codons is statistically incompatible with a neutral model (/Z-score/ ranging from 7.6 to 77.5) (Supplementary Figure S1). We also verified that such a spread was not caused by outliers. This is illustrated in the graph in Figure 2 (triangles) that shows the frequency distribution of the transcription levels for the synonymous codons GCT and GCA. GCT is the preferred codon of the 4-fold degenerate alanine in the highly transcribed genes (major codon). Its distribution is asymmetric with respect to its synonymous minor codon (GCA). The asymmetry consists in an excess of the major codon (GCT) in the classes of genes with an average of >0.5 transcripts per cell. Because the two codons present an equal GC-content, which should minimize the possible biases due to mutational forces, this result suggests that selection on codon bias acts positively by favoring major codons in highly expressed genes rather than negatively by inhibiting the use of minor codons. The result is more apparent when the relative frequencies of synonymous codons are plotted as a function of the transcription level category (Figure 2, circles). The graph distinguishes three different classes of genes:


Selection on codon bias in yeast: a transcriptional hypothesis.

Trotta E - Nucleic Acids Res. (2013)

Frequency distribution and synonymous fraction of GCA and GCT. Frequency distribution (triangles) and synonymous fraction (circles) of GCA (open markers) and GCT (closed markers) with categories of transcript level. GCA and GCT are synonymous codons of the 4-fold degenerate amino acid alanine.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814355&req=5

gkt740-F2: Frequency distribution and synonymous fraction of GCA and GCT. Frequency distribution (triangles) and synonymous fraction (circles) of GCA (open markers) and GCT (closed markers) with categories of transcript level. GCA and GCT are synonymous codons of the 4-fold degenerate amino acid alanine.
Mentions: To exclude the possibility that the transcript levels associated with codons could be compatible with a neutral model in which mutational biases are the only active forces, we simulated 5000 yeast genomes with the codon probabilities at each synonymous site equal to their relative frequencies in the whole genome, but we left unchanged the transcript level assigned to each gene. The frequency distribution of the codon transcript level in simulated sequences showed that the levels of transcription in native codons is statistically incompatible with a neutral model (/Z-score/ ranging from 7.6 to 77.5) (Supplementary Figure S1). We also verified that such a spread was not caused by outliers. This is illustrated in the graph in Figure 2 (triangles) that shows the frequency distribution of the transcription levels for the synonymous codons GCT and GCA. GCT is the preferred codon of the 4-fold degenerate alanine in the highly transcribed genes (major codon). Its distribution is asymmetric with respect to its synonymous minor codon (GCA). The asymmetry consists in an excess of the major codon (GCT) in the classes of genes with an average of >0.5 transcripts per cell. Because the two codons present an equal GC-content, which should minimize the possible biases due to mutational forces, this result suggests that selection on codon bias acts positively by favoring major codons in highly expressed genes rather than negatively by inhibiting the use of minor codons. The result is more apparent when the relative frequencies of synonymous codons are plotted as a function of the transcription level category (Figure 2, circles). The graph distinguishes three different classes of genes:

Bottom Line: We show that the most used codons in highly expressed genes can be predicted by mRNA structural data and that the codon choice at each synonymous site within an mRNA is not random with respect to the local secondary structure.Consistent with this, we report evidence supporting the adaptation of the tRNA pool to the codon profile of the most expressed genes rather than vice versa.We show that the correlation of codon usage with the gene expression level also includes the stop codons that are normally not decoded by aminoacyl-tRNAs.

View Article: PubMed Central - PubMed

Affiliation: Institute of Translational Pharmacology, Consiglio Nazionale delle Ricerche (CNR), Roma 00133, Italy.

ABSTRACT
Codons that code for the same amino acid are often used with unequal frequencies. This phenomenon is termed codon bias. Here, we report a computational analysis of codon bias in yeast using experimental and theoretical genome-wide data. We show that the most used codons in highly expressed genes can be predicted by mRNA structural data and that the codon choice at each synonymous site within an mRNA is not random with respect to the local secondary structure. Because we also found that the folding stability of intron sequences is strongly correlated with codon bias and mRNA level, our results suggest that codon bias is linked to mRNA folding structure through a mechanism that, at least partially, operates before pre-mRNA splicing. Consistent with this, we report evidence supporting the adaptation of the tRNA pool to the codon profile of the most expressed genes rather than vice versa. We show that the correlation of codon usage with the gene expression level also includes the stop codons that are normally not decoded by aminoacyl-tRNAs. The results reported here are consistent with a role for transcriptional forces in driving codon usage bias via a mechanism that improves gene expression by optimizing mRNA folding structures.

Show MeSH
Related in: MedlinePlus