Sherill-Rofe, D. | bioRxiv Science

bioRxiv2025

CladeOScope-GSA: A Tool for Predicting Functional Gene Interactions via Phylogenetic Profiling

Understanding gene function and protein network dynamics is a key challenge in biology and human health. In the light of the exponential growth in genomic data, phylogenetic profiling methods became more powerful in analysing thousands of genomes to uncover evolutionary associations and predict functional interactions [1,2,4,13,14,16,18,23,24,26]. It is based on the well-supported hypothesis that genes that work together are subject to similar evolutionary pressures and therefore their conservation patterns across phylogeny are correlated. We introduce CladeOScope-GSA, a web-based tool designed for phylogeny-aware analysis of gene sets across extensive comparative genomics datasets. By integrating clade-focused normalized phylogenetic profiling (NPP) with interactive visualization, CladeOScope-GSA enables researchers to identify evolutionary patterns within user-defined gene sets. Building upon the infrastructure of the original CladeOScope visualization platform, the addition of statistical gene set analysis, expanded phylogenetic and genomic data, enhanced visualization, and improved statistical tools represent a significant advancement in the tools capabilities. We demonstrate its utility through case studies spanning 1905 species, showcasing how CladeOScope-GSA empowers researchers to extract biological insights from complex comparative datasets. The web tool is accessible at https://tabachlab.shinyapps.io/CladeOScope

evolutionary biology↗

bioRxiv2020

Conservation motifs - a novel evolutionary-based classification of proteins

Cross-species protein conservation patterns, as directed by natural selection, are indicative of the interplay between protein function, protein-protein interaction and evolution. Since the beginning of the genomic era, proteins were characterized as either conserved or not conserved. This simple classification became archaic and cursory once data on protein orthologs became available for thousands of species. To enrich the language used to describe protein conservation patterns, and to understand their biological significance, we classified 20,294 human proteins against 1096 species. Analyses of the conservation patterns of human proteins in different eukaryotic clades yielded extremely variable and rich patterns that had never been characterized or studied before. Using mathematical classifications, we defined seven conservation motifs: Steps, Critical, Lately Developed, Plateau, Clade Loss, Trait Loss and Gain, which describe the evolution of human proteins. Overall, our work offers novel terms for conservation patterns and defines a new language intended to comprehensively describe protein evolution. This novel terminology enables the classification of proteins based on evolution, reveals aspects of protein evolution, and improves the understanding of protein functions.

evolutionary biology↗