Dataset Information

CBDB: the codon bias database.

ABSTRACT: BACKGROUND: In many genomes, a clear preference in the usage of particular codons exists. The mechanisms that induce codon biases remain an open question; studies have attributed codon usage to translational selection, mutational bias and drift. Furthermore, correlations between codon usage within host genomes and their viral pathogens have been observed for a myriad of host-virus systems. As such, numerous studies have investigated codon usage and codon bias in an effort to better understand how species evolve. Numerous metrics have been developed to identify biases in codon usage. In addition, a few data repositories of codon bias data are available, differing in the metrics reported as well as the number and taxonomy of strains examined. DESCRIPTION: We have created a new web resource called the Codon Bias Database (CBDB) which provides information regarding the codon bias within the set of highly expressed genes for 300+ bacterial genomes. CBDB was developed to provide a resource for researchers investigating codon bias in bacteria, facilitating comparisons between strains and species. Furthermore, the site was created to serve those studying adaptation in phage; the genera selected for this first release of CBDB all have sequenced, annotated bacteriophages. The annotations and sequences for the highly expressed gene set are available for each strain in addition to the strain's codon bias measurements. CONCLUSIONS: Comparing species and strains provides a comprehensive look at how codon usage has been shaped over evolutionary time and can elucidate the putative mechanisms behind it. The Codon Bias Database provides a centralized repository of look-up tables and codon usage bias measures for a wide variety of genera, species and strains. Through our analysis of the variation in codon usage within the strains presently available, we find that most members of a genus have a codon composition most similar to other members of its genus, although not necessarily other members of its species.

SUBMITTER: Hilterbrand A

PROVIDER: S-EPMC3463423 | biostudies-other | 2012

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

CBDB: the codon bias database.

Hilterbrand Adam A Saelens Joseph J Putonti Catherine C

BMC bioinformatics 20120426

<h4>Background</h4>In many genomes, a clear preference in the usage of particular codons exists. The mechanisms that induce codon biases remain an open question; studies have attributed codon usage to translational selection, mutational bias and drift. Furthermore, correlations between codon usage within host genomes and their viral pathogens have been observed for a myriad of host-virus systems. As such, numerous studies have investigated codon usage and codon bias in an effort to better unders ...[more]

PMID: 22536831

Similar Datasets

Project description:BACKGROUND:In spite of extensive research on the effect of mutation and selection on codon usage, a general model of codon usage bias due to mutational bias has been lacking. Because most amino acids allow synonymous GC content changing substitutions in the third codon position, the overall GC bias of a genome or genomic region is highly correlated with GC3, a measure of third position GC content. For individual amino acids as well, G/C ending codons usage generally increases with increasing GC bias and decreases with increasing AT bias. Arginine and leucine, amino acids that allow GC-changing synonymous substitutions in the first and third codon positions, have codons which may be expected to show different usage patterns. PRINCIPAL FINDINGS:In analyzing codon usage bias in hundreds of prokaryotic and plant genomes and in human genes, we find that two G-ending codons, AGG (arginine) and TTG (leucine), unlike all other G/C-ending codons, show overall usage that decreases with increasing GC bias, contrary to the usual expectation that G/C-ending codon usage should increase with increasing genomic GC bias. Moreover, the usage of some codons appears nonlinear, even nonmonotone, as a function of GC bias. To explain these observations, we propose a continuous-time Markov chain model of GC-biased synonymous substitution. This model correctly predicts the qualitative usage patterns of all codons, including nonlinear codon usage in isoleucine, arginine and leucine. The model accounts for 72%, 64% and 52% of the observed variability of codon usage in prokaryotes, plants and human respectively. When codons are grouped based on common GC content, 87%, 80% and 68% of the variation in usage is explained for prokaryotes, plants and human respectively. CONCLUSIONS:The model clarifies the sometimes-counterintuitive effects that GC mutational bias can have on codon usage, quantifies the influence of GC mutational bias and provides a natural null model relative to which other influences on codon bias may be measured.

Project description:Codon usage bias (CUB)-preferential use of one of the synonymous codons, has been described in a wide range of organisms from bacteria to mammals, but it has not yet been studied in marine phytoplankton. CUB is thought to be caused by weak selection for translational accuracy and efficiency. Weak selection can overpower genetic drift only in species with large effective population sizes, such as Drosophila that has relatively strong CUB, while organisms with smaller population sizes (e.g., mammals) have weak CUB. Marine plankton species tend to have extremely large populations, suggesting that CUB should be very strong. Here we test this prediction and describe the patterns of codon usage in a wide range of diatom species belonging to 35 genera from 4 classes. We report that most of the diatom species studied have surprisingly modest CUB (mean Effective Number of Codons, ENC = 56), with some exceptions showing stronger codon bias (ENC = 44). Modest codon bias in most studied diatom species may reflect extreme disparity between astronomically large census and modest effective population size (Ne), with fluctuations in population size and linked selection limiting long-term Ne and rendering selection for optimal codons less efficient. For example, genetic diversity (pi ~0.02 at silent sites) in Skeletonema marinoi corresponds to Ne of about 10 million individuals, which is likely many orders of magnitude lower than its census size. Still, Ne ~107 should be large enough to make selection for optimal codons efficient. Thus, we propose that an alternative process-frequent changes of preferred codons, may be a more plausible reason for low CUB despite highly efficient selection for preferred codons in diatom populations. The shifts in the set of optimal codons should result in the changes of the direction of selection for codon usage, so the actual codon usage never catches up with the moving target of the optimal set of codons and the species never develop strong CUB. Indeed, we detected strong shifts in preferential codon usage within some diatom genera, with switches between preferentially GC-rich and AT-rich 3rd codon positions (GC3). For example, GC3 ranges from 0.6 to 1 in most Chaetoceros species, while for Chaetoceros dichaeta GC3 = 0.1. Both variation in selection intensity and mutation spectrum may drive such shifts in codon usage and limit the observed CUB. Our study represents the first genome-wide analysis of CUB in diatoms and the first such analysis for a major phytoplankton group.

Dataset Information

CBDB: the codon bias database.

Publications

CBDB: the codon bias database.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure