Orthologs from maxmer sequence context

TL;DR

This paper introduces a fast, efficient method using short-range maximal matches to identify orthologs across whole genomes, matching known orthologs and discovering new ones with high accuracy.

Contribution

It presents a novel approach leveraging non-embedded maximal matches for ortholog detection, reducing computational time and improving ortholog identification accuracy.

Findings

Recapitulates most exact matches of traditional alignment methods.

Recovers high-confidence orthologs with high sensitivity and specificity.

Identifies putatively novel orthologs not found in existing databases.

Abstract

Context-dependent identification of orthologs customarily relies on conserved gene order or whole-genome sequence alignment. It is shown here that short-range context--as short as single maximal matches--also provides an effective means to identify orthologs within whole genomes. On pristine (un-repeatmasked) mammalian whole-genome assemblies we perform a genome "intersection" that in general consumes less than one thirtieth of the computation time required by commonly used methods for whole-genome alignment, and we extract "non-embedded maximal matches," maximal matches that are not embedded into other maximal matches, as potential orthologs. An ortholog identified via non-embedded maximal matches is analogous to a "positional ortholog" or a "primary ortholog" as defined in previous literature; such orthologs constitute homologs derived from the same direct ancestor whose ancestral positions in the genome are conserved. At the nucleotide level, non-embedded maximal matches recapitulate most exact matches identified by a Lastz net alignment. At the gene level, reciprocal best hits of genes containing non-embedded maximal matches recover one-to-one orthologs annotated by Ensembl Compara with high selectivity and high sensitivity; these reciprocal best hits additionally include putatively novel orthologs not found in Ensembl (e.g. over two thousand for human/chimpanzee). The method is especially suitable for genome-wide identification of orthologs.