Assisted transcriptome reconstruction and splicing orthology

Abstract

BackgroundTranscriptome reconstruction, defined as the identification of all protein isoforms that may be expressed by a gene, is a notably difficult computational task. With real data, the best methods based on RNA-seq data identify barely 21 % of the expressed transcripts. While waiting for algorithms and sequencing techniques to improve — as has been strongly suggested in the literature — it is important to evaluate assisted transcriptome prediction; this is the question of how alternative transcription in one species performs as a predictor of protein isoforms in another relatively close species. Most evidence-based gene predictors use transcripts from other species to annotate a genome, but the predictive power of procedures that use exclusively transcripts from external species has never been quantified. The cornerstone of such an evaluation is the correct identification of pairs of transcripts with the same splicing patterns, called splicing orthologs.ResultsWe propose a rigorous procedural definition of splicing orthologs, based on the identification of all ortholog pairs of splicing sites in the nucleotide sequences, and alignments at the protein level. Using our definition, we compared 24 382 human transcripts and 17 909 mouse transcripts from the highly curated CCDS database, and identified 11 122 splicing orthologs. In prediction mode, we show that human transcripts can be used to infer over 62 % of mouse protein isoforms. When restricting the predictions to transcripts known eight years ago, the percentage grows to 74 %. Using CCDS timestamped releases, we also analyze the evolution of the number of splicing orthologs over the last decade.ConclusionsAlternative splicing is now recognized to play a major role in the protein diversity of eukaryotic organisms, but definitions of spliced isoform orthologs are still approximate. Here we propose a definition adapted to the subtle variations of conserved alternative splicing sites, and use it to validate numerous accurate orthologous isoform predictions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3103-6) contains supplementary material, which is available to authorized users.

Evolution of the human cold/menthol receptor, TRPM8

“…Values related to the alignments. While considering the retained alignments and applying a comparative genomics approach (Blanquart, et al 2016), we evaluated the presence or absence of the following functional sites observed in human exons: the motifs "AG" of the acceptor splice site (A value) and the "GT" of the donor splice site ( D value), the start codon "ATG" (T value) and the stop codons "TAA", "TAG" or "TGA" (P value). Occurrences of putative orthologous stop codons were also assessed to appear in the same frame as observed for the human stop codon.…”

“…In 2016, GenBank and Refseq cDNA databases referenced 152,726 and 110,720 human mRNAs, respectively, with an average number of mRNA isoforms per gene ranging from 4 to 8 in humans (Pan, et al 2008). Moreover, in the same year, another study reported that the number of orthologous coding isoforms discovered in humans and mice has grown constantly over the past ten years (Blanquart, et al 2016). However, the coverage bias at the 5'-and 3'-ends of mRNA sequencing results in underrepresentation of mRNA extremities (Kukurba and Montgomery 2015).…”

“…This consequently impairs the search for alternative transcripts generated by alternative transcription: initiated by alternative promoters and/or terminated by alternative polyadenylation sites. In addition, shotgun mRNA-seq methods suffer from artifacts at the step of sequence reconstruction, even though statistical inference (Conesa, et al 2016) and the use of orthologous pairs of splicing sites (Blanquart, et al 2016) have greatly improved them in recent years. As a consequence, an astonishing proportion of isoforms remains unknown, which impairs our understanding of genes involved in adaptive traits.…”

SplicedFamAlign: CDS-to-gene spliced alignment and identification of transcript orthology groups

“…For instance, in Figure 9, the spliced alignment of g[c 1 ] against g is A = { (1,4,9,12), (5,16,18,29), (17,24,49,56)} (see Figure 10 for more general examples of spliced alignments with conserved and deleted blocks ). A spliced alignment A induces a set of putative gene intron segments.…”

“…Identifying orthologous isoforms at transcript level is a prerequisite to describing evolutionary relationships between genes in terms of splicing structure and sets of splice variants [5,17]. Here, we focus on the spliced alignment of full CDS against gene sequences within a gene family, which allows to identify splicing orthologous CDS with similar sequences and splicing structures from genes that have evolved from a common ancestral gene [26,1]. Splicing orthologs are supposed to have retained the same function in the course of evolution.…”