Dataset Information

Synonymous codon usage bias is correlative to intron number and shows disequilibrium among exons in plants.

ABSTRACT:

Background

Evidence has been assembled to suggest synonymous codon usage bias (SCUB) has close relationship with intron. However, the relationship (if any) between SCUB and intron number as well as exon position is at present rather unclear.

Results

To explore this relationship, the sequences of a set of genes containing between zero and nine introns was extracted from the published genome sequences of three algal species, one moss, one fern and six angiosperms (three monocotyledonous species and three dicotyledonous species). In the algal genomes, the frequency of synonymous codons of the form NNG/NNC (codons with G and C at the third position) was positively related to intron number, but that of NNA/NNT was inversely correlated; the opposite was the case in the land plant genomes. The frequency of NNC/NNG was higher and that of NNA/NNT lower in two terminal exons than in the interstitial exons in the land plant genes, but the rule showed to be opposite in the algal genes. SCUB patterns in the interstitial and two terminal exons mirror the different evolutionary relationships between these plant species, while the first exon shows the highest level of conservation is therefore concluded to be the one which experiences the heaviest selection pressure. The phenomenon of SCUB may also be related to DNA methylation induced conversion of CG to AT.

Conclusions

These data provide some evidence of linkage between SCUB, the evolution of introns and DNA methylation, which brings about a new perspective for understanding how genomic variation is created during plant evolution.

SUBMITTER: Qin Z

PROVIDER: S-EPMC3576282 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundSynonymous codon usage is typically biased towards translationally superior codons in many organisms. In Drosophila, genomic data indicates that translationally optimal codons and splice optimal codons are mostly mutually exclusive, and adaptation to translational efficiency is reduced in the intron-exon boundary regions where potential exonic splicing enhancers (ESEs) reside. In contrast to genomic scale analyses on large datasets, a refined study on a well-controlled set of samples can be effective in demonstrating the effects of particular splice-related factors. Down syndrome cell adhesion molecule (Dscam) has the largest number of alternatively spliced exons (ASEs) known to date, and the splicing frequency of each ASE is accessible from the relative abundance of the transcript. Thus, these ASEs comprise a unique model system for studying the effect of splicing regulation on synonymous codon usage.ResultsCodon Bias Indices (CBI) in the 3' boundary regions were reduced compared to the rest of the exonic regions among 48 and 33 ASEs of exon 6 and 9 clusters, respectively. These regional differences in CBI were affected by splicing frequency and distance from adjacent exons. Synonymous divergence levels between the 3' boundary region and the remaining exonic region of exon 6 ASEs were similar. Additionally, another sensitive comparison of paralogous exonic regions in recently retrotransposed processed genes and their parental genes revealed that, in the former, the differences in CBI between what were formerly the central regions and the boundary regions gradually became smaller over time.ConclusionAnalyses of the multiple ASEs of Dscam allowed direct tests of the effect of splice-related factors on synonymous codon usage and provided clear evidence that synonymous codon usage bias is restricted by exonic splicing signals near the intron-exon boundary. A similar synonymous divergence level between the different exonic regions suggests that the intensity of splice-related selection is generally weak and comparable to that of translational selection. Finally, the leveling off of differences in codon bias over time in retrotransposed genes meets the direct prediction of the tradeoff model that invokes conflict between translational superiority and splicing regulation, and strengthens the conclusions obtained from Dscam.