In trypanosomatids, bias in codon usage correlates with tRNA gene copy number and with expression level. This provides strong evidence for a major impact of translational selection on gene expression. Thus, translational selection facilitates the generation of differential protein abundance from genes embedded within polycistrons. Since translation rates are likely retarded by codons with low-abundance cognate tRNAs, natural selection of tRNA gene numbers and codon bias allows optimization of translation rate and efficiency across the genome. Many of the most highly expressed genes use a dual strategy to enhance expression; increased gene dosage combined with a high proportion of codons with more abundant cognate tRNAs. This dual strategy allows for an increase in overall transcription and translation.
In S. cerevisiae, although the value of codon bias as a predictor of protein levels is disputed, proteins encoded by genes with low bias are not detected on two-dimensional gels and protein abundance does correlate when only genes with high bias are considered [29, 30]. Thus, translational selection may be a pervasive mechanism in the control of gene expression but its impact may be obscured in many cell-types due to the impact of other regulatory mechanisms. I propose that translational selection makes a more substantial contribution to gene expression control in trypanosomatids due to the paucity of regulated transcription. Initial ribosome assembly on mRNA may also be largely unregulated since trans-splicing leads to the attachment of an identical spliced-leader sequence to every mRNA [4]. Thus, differential translation efficiency may be the dominant level of gene expression control in trypanosomatids. Translational selection may have emerged in primitive cells that lacked mechanisms for differential mRNA expression and the emergence of differential transcription in other cell types may have obscured or partially replaced this mode of control.
Many trypanosomatid proteins are differentially expressed during the cell-cycle and the life-cycle and additional controls must clearly determine such differential expression. A number of mRNA un-translated regions, particularly at the 3′ end, may modulate mRNA maturation, transport, turnover and translation for example and protein turnover may also vary [4]. When these additional controls operate, codon bias should fail to predict expression level. Prominent examples of differential regulation include the variant surface glycoprotein gene, abundantly expressed in bloodstream form T. brucei, and procyclins, expressed in insect stage T. brucei. Expression of these proteins is regulated using an unusual mechanism involving differential transcription by RNA polymerase I which is restricted to RRNA genes in other eukaryotes [31]. mRNA turnover [32] and protein turnover [33] also contribute to controlling variant surface glycoprotein expression and, as expected, codon bias fails to predict relative expression when these controls operate (CAI for variant surface glycoprotein genes = 0.54 +/-0.01. n = 4). Thus, codon analysis in combination with high-throughput proteome analysis may allow identification of proteins subject to the alternative expression control strategies described above. In addition, orthologous genes that show poor correspondence in relative codon bias among trypanosomatids may be those that display species-specific expression differences. If this is the case, genome-wide codon-usage analysis will facilitate the identification of these genes.
Protein coding sequences are relatively easy to predict in trypanosomatids due to high density, intron poverty and organisation into directional clusters. New annotation tools are under development, however [34], and gene annotation could be refined. The findings reported here indicate that algorithms incorporating codon sampling could facilitate the annotation of current and future trypanosomatid genome sequence data.
