MSOAR

MSOAR identifies ortholog groups across multiple genomes to support evolutionary and functional genomic analyses.

Key Features:

• Ortholog Group Identification: Constructs gene families via sequence similarity searches and clustering, applies MSOAR 2.0 for pairwise orthology assignments, and partitions each gene family into super ortholog groups (SOGs) with at most one gene per genome.
• Tree of Ortholog Groups (TOGs): For each SOG, labels species-tree leaves with binary presence/absence indicators and infers internal node labels using parsimony and biological constraints to produce fully labeled TOGs.
• Comparative Performance: Reports higher prediction accuracy than MultiParanoid, the Roundup multi-ortholog repository, and the Ensembl ortholog database when validated against gene symbols in real data, and outperforms Notung in inferring evolutionary events on simulated datasets.
• Evolutionary Event Analysis: Infers gene births, duplications, and losses across species to characterize genomic evolutionary dynamics.

Scientific Applications:

• Evolutionary studies: Identification of ortholog groups and inferred gene birth/duplication/loss events to analyze genome evolution.
• Functional genomics: Cross-species ortholog mapping to support analyses of gene function conservation and divergence.
• Phylogenetic reconstruction: Use of labeled TOGs to trace phylogenetic relationships and reconstruct evolutionary histories.

Methodology:

Construct gene families by sequence similarity searches and clustering, apply MSOAR 2.0 for pairwise ortholog assignments, partition families into SOGs, and construct TOGs with node labels inferred by parsimony and biological constraints.