Designating eukaryotic orthology via processed transcription units

Abstract

Orthology is a widely used concept in comparative and evolutionary genomics. In addition to prokaryotic orthology, delineating eukaryotic orthology has provided insight into the evolution of higher organisms. Indeed, many eukaryotic ortholog databases have been established for this purpose. However, unlike prokaryotes, alternative splicing (AS) has hampered eukaryotic orthology assignments. Therefore, existing databases likely contain ambiguous eukaryotic ortholog relationships and possibly misclassify alternatively spliced protein isoforms as in-paralogs, which are duplicated genes that arise following speciation. Here, we propose a new approach for designating eukaryotic orthology using processed transcription units, and we present an orthology database prototype using the human and mouse genomes. Currently existing programs cover less than 69% of the human reference sequences when assigning human/mouse orthologs. In contrast, our method encompasses up to 80% of the human reference sequences. Moreover, the ortholog database presented herein is more than 92% consistent with the existing databases. In addition to managing AS, this approach is capable of identifying orthologs of embedded genes and fusion genes using syntenic evidence. In summary, this new approach is sensitive, specific and can generate a more comprehensive and accurate compilation of eukaryotic orthologs.

Gene-oriented ortholog database: a functional comparison platform for orthologous loci

“…Because GOOD emphasizes the interference caused by AS events which is more abundant in higher order eukaryotes, we first considered mammals. In addition, the algorithm we applied ( 13 ) is sensitive to the quality of genome assembly and transcript annotations. Therefore, species are sequentially included by their annotation levels.…”

“…Examining other species with sequenced vertebrate genomes, zebrafish is also well studied. We eliminated it because the algorithm we used ( 13 ) has a limitation to apply directly to such a far distant species to all other chosen species. We further included chimpanzee to demonstrate that the GO annotation from a well-annotated gene can benefit to its un-annotated orthologous gene.…”

“…GOOD contains generated regions, 18 373 in human, 18 858 in mouse, 17 681 in chimpanzee and 9311 in cow. Each region has its own unique transcriptional representative, the processed transcription unit (PTU) ( 13 ). That is, AS information is analyzed to generate PTUs which are DNA sequences of genes without absolute introns.…”

“…Most of them, however, consider orthology from the aspect of protein sequences individually, including HomoloGene ( http://www.ncbi.nlm.nih.gov/homologene ), EnsemblCompara ( 6 ), Inparanoid ( 7 , 8 ), Roundup ( 9 ), OrthoMCL ( 10 , 11 ) and OrthoDB ( 12 ). There exist ambiguous and incomplete ortholog assignments because of the interference mediated by alternative splicing (AS) ( 13 ). Isoforms of one gene might be assigned to different orthologous clusters.…”

Refining orthologue groups at the transcript level

“…EnsemblCompara [ 2 ], for example, selects the longest transcript of a gene. Recently the “GOOD” database [ 16 , 17 ] was constructed to define orthologue groups by examining the “processed transcription units” of a gene (the genomic region that encompasses all exons of a gene whether alternate or constitutive). This method provided better coverage of orthologue groups and distinction between orthologues and paralogues [ 16 , 17 ].…”