The action of selection on codon bias in the human genome is related to frequency, complexity, and chronology of amino acids.

BACKGROUND: The question of whether synonymous codon choice is affected by cellular tRNA abundance has been positively answered in many organisms. In some recent works, concerning the human genome, this relation has been studied, but no conclusive answers have been found. In the human genome, the variation in base composition and the absence of cellular tRNA count data makes the study of the question more complicated. In this work we study the relation between codon choice and tRNA abundance in the human genome by correcting relative codon usage for background base composition and using a measure based on tRNA-gene copy numbers as a rough estimate of tRNA abundance. RESULTS: We term major codons to be those codons with a relatively large tRNA-gene copy number for their corresponding amino acid. We use two measures of expression: breadth of expression (the number of tissues in which a gene was expressed) and maximum expression level among tissues (the highest value of expression of a gene among tissues). We show that for half the amino acids in the study (8 of 16) the relative major codon usage rises with breadth of expression. We show that these amino acids are significantly more frequent, are smaller and simpler, and are more ancient than the rest of the amino acids. Similar, although weaker, results were obtained for maximum expression level. CONCLUSION: There is evidence that codon bias in the human genome is related to selection, although the selection forces acting on codon bias may not be straightforward and may be different for different amino acids. We suggest that, in the first group of amino acids, selection acts to enhance translation efficiency in highly expressed genes by preferring major codons, and acts to reduce translation rate in lowly expressed genes by preferring non-major ones. In the second group of amino acids other selection forces, such as reducing misincorporation rate of expensive amino acids, in terms of their size/complexity, may be in action. The fact that codon usage is more strongly related to breadth of expression than to maximum expression level supports the notion, presented in a recent study, that codon choice may be related to the tRNA abundance in the tissue in which a gene is expressed.

Codon bias as a factor in regulating expression via translation rate in the human genome.

We study the interrelations between tRNA gene copy numbers, gene expression levels and measures of codon bias in the human genome. First, we show that isoaccepting tRNA gene copy numbers correlate positively with expression-weighted frequencies of amino acids and codons. Using expression data of more than 14,000 human genes, we show a weak positive correlation between gene expression level and frequency of optimal codons (codons with highest tRNA gene copy number). Interestingly, contrary to non-mammalian eukaryotes, codon bias tends to be high in both highly expressed genes and lowly expressed genes. We suggest that selection may act on codon bias, not only to increase elongation rate by favoring optimal codons in highly expressed genes, but also to reduce elongation rate by favoring non-optimal codons in lowly expressed genes. We also show that the frequency of optimal codons is in positive correlation with estimates of protein biosynthetic cost, and suggest another possible action of selection on codon bias: preference of optimal codons as production cost rises, to reduce the rate of amino acid misincorporation. In the analyses of this work, we introduce a new measure of frequency of optimal codons (FOP'), which is unaffected by amino acid composition and is corrected for background nucleotide content; we also introduce a new method for computing expected codon frequencies, based on the dinucleotide composition of the introns and the non-coding regions surrounding a gene.

Gene prediction by spectral rotation measure: a new method for identifying protein-coding regions.

A new measure for gene prediction in eukaryotes is presented. The measure is based on the Discrete Fourier Transform (DFT) phase at a frequency of 1/3, computed for the four binary sequences for A, T, C, and G. Analysis of all the experimental genes of S. cerevisiae revealed distribution of the phase in a bell-like curve around a central value, in all four nucleotides, whereas the distribution of the phase in the noncoding regions was found to be close to uniform. Similar findings were obtained for other organisms. Several measures based on the phase property are proposed. The measures are computed by clockwise rotation of the vectors, obtained by DFT for each analysis frame, by an angle equal to the corresponding central value. In protein coding regions, this rotation is assumed to closely align all vectors in the complex plane, thereby amplifying the magnitude of the vector sum. In noncoding regions, this operation does not significantly change this magnitude. Computing the measures with one chromosome and applying them on sequences of others reveals improved performance compared with other algorithms that use the 1/3 frequency feature, especially in short exons. The phase property is also used to find the reading frame of the sequence.