Orthology and Paralogy Relationships at Transcript Level.

Eukaryotic genes undergo a mechanism called alternative processing, resulting in transcriptome diversity by allowing the production of multiple distinct transcripts from a gene. More than half of human genes are affected, and the resulting transcripts are highly conserved among orthologous genes of distinct species. In this work, we present the definition of orthology and paralogy between transcripts of homologous genes, together with an algorithm to compute clusters of conserved orthologous and paralogous transcripts. Gene-level homology relationships are utilized to define various types of homology relationships between transcripts originating from the same ancestral transcript. A Reciprocal Best Hits approach is employed to infer clusters of isoorthologous and recent paralogous transcripts. We applied this method to transcripts from simulated gene families as well as real gene families from the Ensembl-Compara database. The results are consistent with those from previous studies that compared orthologous gene transcripts. Furthermore, our findings provide evidence that searching for conserved transcripts between homologous genes, beyond the scope of orthologous genes, is likely to yield valuable information.