P-GRe : an efficient pipeline to maximised pseudogene prediction in plants/eucaryotes

Abstract

Formerly considered as part of "junk DNA", pseudogenes are nowadays known for their role in the post-transcriptional regulation of functional genes. In addition, their identification allows a better understanding of gene evolution in the frame of multigenic families. Despite this, there is, to our knowledge, no fully automatic user-friendly software allowing the annotation of pseudogenes on a whole genome. Here, we present Pseudo-Gene Retriever (P-GRe), a fully automated pseudogene prediction software requiring only a genome sequence and its corresponding GFF annotation file. P-GRe detects the sequences of the pseudogenes on a whole genome and returns to the user all their genomic sequences and their pseudo-coding sequences. The ability of P-GRe to finely reconstruct the structure of pseudogenes also allow to obtain a set of proteins virtually encoded by the predicted pseudogenes. We show here that in 70% of the cases, virtual proteins constructed by P-GRe from Arabidopsis thaliana proteome and genome aligned better to their parent protein than their annotated counterpart.