Discovering New Orthologous Groups with P-COGs

Biochemical Genetics. 2026.

Bug D. S., Kuzovenkova D. A., Tishkov A. V., Porozova N., Petukhova N. V.

Deciphering the evolutionary history of genes is foundational for biomedical research, enabling the identification of compensatory mutations in disease-associated genes and the selection of evolutionarily relevant model organisms. However, challenges of multi-isoform handling, the presence of incomplete genomes/proteomes initial datasets, and problems of evolutionary history representation are still present. To address these issues, we introduce a novel framework based on the Clusters of Orthologous Groups (COG) method, primarily designed for improving phylogenetic tree clustering in studying evolutionary history of eukaryotes, P-COGs (Pavlov's COGs). It encourages the use of a single sequence dataset for both constructing phylogenetic trees and inferring COGs. We demonstrate the tool's utility through an evolutionary study of the voltage-dependent chloride channel genes family (CLCN). Moreover, P-COGs allowed us to observe multiple clusters of orthologous genes in CLCN that were not identified by other COG-based tools. Additionally, we resolved the evolutionary history of hundreds of cancer-associated genes with P-COGs to support accurate evolution-based variant effect prediction. The resulting COG graphs are accessible via our interactive web application ( https://epicenter.1spbgmu.ru/shiny/pavlovscogs/ ). P-COGs is openly available at https://github.com/bugds/Pavlovs_COGs. 

Keywords: эволюция, концепция, framework, tool, Phylogeny, Филогения, использование инстументов искусственного интеллекта в исследованиях, Evolution, Clusters of orthologous groups, Кластеры ортологических групп

Publication based on the results of: Рациональный дизайн низкомолекулярных ингибиторов PD-1 для терапии злокачественных новообразований с резистентностью к химиотерапии (2025)