Inferring Clusters of Orthologous and Paralogous Transcripts.

The alternative processing of eukaryote genes allows producing multiple distinct transcripts from a single gene, thereby contributing to the transcriptome diversity. Recent studies suggest that more than 90% of human genes are concerned, and the transcripts resulting from alternative processing are highly conserved between orthologous genes. In this paper, we first present a model to define orthology and paralogy relationships at the transcriptome level, then we present an algorithm to infer clusters of orthologous and paralogous transcripts. Gene-level homology relationships are used to define different types of homology relationships between transcripts and a Reciprocal Best Hits approach is used to infer clusters of isoorthologous and recent paralogous transcripts. We applied the method to transcripts of gene families from the Ensembl-Compara database. The results are agreeing with those from previous studies comparing orthologous gene transcripts. The results also provide evidence that searching for conserved transcripts beyond orthologous genes will likely yield valuable information. The results obtained on the Ensembl-Compara gene families are available at https://github.com/UdeS-CoBIUS/TranscriptOrthology . Supplementary material can be found at https://doi.org/10.5281/zenodo.7750949 .