Codon Bias

Codon usage bias refers to differences in the frequency of occurrence of synonymous codons in coding DNA. A codon is a series of three nucleotides (a triplet) that encodes a specific amino acid residue in a polypeptide chain or for the termination of translation (stop codons).

There are 64 different codons (61 codons encoding for amino acids plus 3 stop codons) but only 20 different translated amino acids. The overabundance in the number of codons allows many amino acids to be encoded by more than one codon. Because of such redundancy it is said that the genetic code is degenerate. Different organisms often show particular preferences for one of the several codons that encode the same amino acid- that is, a greater frequency of one will be found than expected by chance. How such preferences arise is a much debated area of molecular evolution.

Weak Selection and codon bias in Drosophila.

Synonymous, or "silent", DNA changes were considered good candidates for neutral evolution because they do not alter the amino acid sequence of encoded proteins.  However, a number of species show preferential usage of codons recognized by abundant tRNA's.  This pattern suggests "major codon preference"; natural selection may discriminate among synonymous codons to enhance the speed

or the accuracy of protein synthesis (Figure 1)                           .<img src="/17c259e3-20ac-5f83-b570-ce7ecdffe37c.png"/>

Figure 1. Schematic depiction of protein synthesis.

Under major codon preference, codon usage and tRNA pools are co-adapted to enhance the efficiency of translation. During protein synthesis, the translational apparatus waits at a given codon for the appropriate tRNA to arrive, then links the (yellow) amino acid to the elongating polypeptide. The waiting time is shorter at major codons which are recognized by abundant (unshaded) tRNAs. Shorter waiting times increase the rate of elongation of the polypeptide and decrease the probability that an incorrect amino acid will be incorporated into the protein.

The fitness effects of mutations can be determined by examining patterns of evolution on different time scales.  We have developed a statistical method that examines both the frequency spectrum of polymorphisms within populations and the numbers of mutations fixed between species.  Computer simulations show that comparisons of such patterns provide a powerful approach to detect even very weak selection (Figure 2).  Under major codon preference, silent DNA mutations fall into two fitness classes: "preferred" mutations that increase the number of major codons and "unpreferred" changes in the opposite direction.  Frequency distribution and divergence patterns for silent changes in Drosophila simulans are strikingly similar to those predicted by major codon preference; preferred mutations are found at higher frequencies within populations and are more often fixed between species than unpreferred changes (Figure 3).  Maximum likelihood estimates support that selection acts at its limit of efficacy in the face of stochastic processes to maintain codon bias in this species.

Figure 2. Statistical power to detect weak selection.

The proportion of statistical tests which reject fitness equivalence between preferred and unpreferred mutations simulated under major codon preference are plotted on the y-axis. FD refers to frequency distribution, PD to polymorphism and divergence, SID to singletons, intermediate frequency, and divergence, and FDD to frequency distribution and divergence tests. Data are show for sample sizes of l sites in m alleles.

Figure 3. Frequency distributions and divergence of nearly neutral mutations.

a) Expected frequency distributions and divergence under weak selection. For a sample of m = 5 alleles from a population, the expected proportionof mutations found in 1 to 5 of the sequences. b) Observed frequency distributions and divergence of preferred and unpreferred silent DNA mutations among 5 alleles of each of 8 D. simulans genes. The difference between the distributions is significant (Mann-Whitney U-test, P < 0.001).

Codon Bias

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