Orthologybased

Orthology-based methods are analyses that rely on orthologous genes—genes in different species that originated from a single gene in the last common ancestor and diverged through speciation. Because orthologs frequently conserve function, orthology-based inference is widely used to transfer functional information between organisms and to compare gene content across taxa. The approach contrasts with paralogy-based analyses, which focus on gene copies created by duplication within a lineage.

Identifying orthologs involves sequence comparison, phylogenetic reconstruction, and gene order (synteny) information. Common computational strategies include reciprocal best hits, tree reconciliation, and graph-based clustering. Several public resources assemble large-scale orthology relationships, such as OrthoDB, eggNOG, OrthoMCL, InParanoid, and OMA, each with different coverage and confidence metrics.

Applications include functional annotation transfer, where the function of an uncharacterized gene is inferred from its ortholog; comparative genomics and evolutionary studies; reconstruction of pathways and networks across species; and prioritization of model organisms or drug targets based on conserved biology.

Limitations include functional divergence after speciation, where orthologs no longer share identical roles; paralogs formed by gene duplication can masquerade as orthologs in some methods; errors in genome annotations or incomplete genomes reduce accuracy; and different evolutionary rates can mislead orthology inference. Consequently, results are typically integrated with additional evidence.

Orthology-based approaches inform a broad range of fields and underpin many annotation pipelines, but are part of a broader comparative genomics toolkit. Researchers continually improve methods to handle complex gene histories, lineage-specific events, and meta-analytic confidence scoring.