Denis C. Shields

The genetic code is degenerate, but alternative synonymous codons are generally not used with equal frequency. Since the pioneering work of Grantham's group it has been apparent that genes from one species often share similarities in codon frequency; under the "genome hypothesis" there is a species-specific pattern to codon usage. However, it has become clear that in most species there are also considerable differences among genes. Multivariate analyses have revealed that in each species so far examined there is a single major trend in codon usage among genes, usually from highly biased to more nearly even usage of synonymous codons. Thus, to represent the codon usage pattern of an organism it is not sufficient to sum over all genes as this conceals the underlying heterogeneity. Rather, it is necessary to describe the trend among genes seen in that species. We illustrate these trends for six species where codon usage has been examined in detail, by presenting the pooled codon usage for the 10% of genes at either end of the major trend. Closely-related organisms have similar patterns of codon usage, and so the six species in Table 1 are representative of wider groups. For example, with respect to codon usage, Salmonella typhimurium closely resembles E. coli, while all mammalian species so far examined (principally mouse, rat and cow) largely resemble humans.

The conventional wisdom is that certain classes of bioactive peptides have specific structural features that endow their particular functions. Accordingly, predictions of bioactivity have focused on particular subgroups, such as antimicrobial peptides. We hypothesized that bioactive peptides may share more general features, and assessed this by contrasting the predictive power of existing antimicrobial predictors as well as a novel general predictor, PeptideRanker, across different classes of peptides.We observed that existing antimicrobial predictors had reasonable predictive power to identify peptides of certain other classes i.e. toxin and venom peptides. We trained two general predictors of peptide bioactivity, one focused on short peptides (4-20 amino acids) and one focused on long peptides (> 20 amino acids). These general predictors had performance that was typically as good as, or better than, that of specific predictors. We noted some striking differences in the features of short peptide and long peptide predictions, in particular, high scoring short peptides favour phenylalanine. This is consistent with the hypothesis that short and long peptides have different functional constraints, perhaps reflecting the difficulty for typical short peptides in supporting independent tertiary structure.We conclude that there are general shared features of bioactive peptides across different functional classes, indicating that computational prediction may accelerate the discovery of novel bioactive peptides and aid in the improved design of existing peptides, across many functional classes. An implementation of the predictive method, PeptideRanker, may be used to identify among a set of peptides those that may be more likely to be bioactive.

The patterns of synonymous codon usage in 91 Drosophila melanogaster genes have been examined. Codon usage varies strikingly among genes. This variation is associated with differences in G+C content at silent sites, but (unlike the situation in mammalian genes) these differences are not correlated with variation in intron base composition and so are not easily explicable in terms of mutational biases. Instead, those genes with high G+C content at silent sites, resulting from a strong "preference" for a particular subset of the codons that are mostly C-ending, appear to be the more highly expressed genes. This suggests that G+C content is reduced in sequences where selective constraints are weaker, as indeed seen in a pseudogene. These and other data discussed are consistent with the effects of translational selection among synonymous codons, as seen in unicellular organisms. The existence of selective constraints on silent substitutions, which may vary in strength among genes, has implications for the use of silent molecular clocks.