Seforta, an integrated tool for detecting the signature of selection in coding sequences

Abstract

BackgroundThe majority of amino acid residues are encoded by more than one codon, and a bias in the usage of such synonymous codons has been repeatedly demonstrated. One assumption is that this phenomenon has evolved to improve the efficiency of translation by reducing the time required for the recruitment of isoacceptors. The most abundant tRNA species are preferred at sites on the protein which are key for its functionality, a behavior which has been termed “translational accuracy”. Although observed in many species, as yet no public domain software has been made available for its quantification.FindingsWe present here Seforta (Selection for Translational Accuracy), a program designed to quantify translational accuracy. It searches for synonymous codon usage bias in both conserved and non-conserved regions of coding sequences and computes a cumulative odds ratio and a Z-score. The specification of a set of preferred codons is desirable, but the program can also generate these. Finally, a randomization protocol calculates the probability that preferred codon combinations could have arisen by chance.ConclusionsSeforta is the first public domain program able to quantify translational accuracy. It comes with a simple graphical user interface and can be readily installed and adjusted to the user's requirements.

An analysis of codon bias in six red yeast species

“…The second method involves the computation of the codons that are preferentially used in the highly expressed genes as compared with the lesser expressed ones. EST data were used to quantify the transcript abundance for each species according to the following pipeline: (a) EST sequences were aligned to the transcripts by using the software Burrows–Wheeler Aligner (Li & Durbin, ) with default parameters; (b) the number of aligned sequences was computed by the software eXpress (Roberts & Pachter, ) with default parameters and used as a proxy of the transcripts expression level; and (c) based on the expression distribution, the 5% extreme values were used to select highly and lesser expressed genes and, for each codon, optimality was investigated by a chi‐squared contingency test with the software Seforta (Camiolo, Melito, Milia, & Porceddu, ).…”

Peer Review #3 of "corseq: fast and efficient identification of favoured codons from next generation sequencing reads (v0.1)"

“…We then used a chi square test to compare the codon usage of the 5% most highly and most lowly expressed transcripts, i.e. a method that is implemented in the software Seforta (Camiolo et al, 2014). At this stage, 2x2 contingency tables were created similar to those discussed in the previous section.…”

corseq: fast and efficient identification of favoured codons from next generation sequencing reads

“…Briefly, RNAseq sequences were aligned to the coding sequences with bwa ( Li & Durbin, 2010 ) (default parameters) and transcript abundance were quantified by the tool express ( Roberts & Pachter, 2013 ) (default parameters). We then used a chi-square test to compare the codon usage of the 5% most highly and most lowly expressed transcripts, i.e., a method that is implemented in the software Seforta ( Camiolo et al, 2014 ). At this stage, 2 × 2 contingency tables were created similar to those discussed in the previous section.…”