ScGOclust: leveraging gene ontology to find functionally analogous cell types between distant species

Basic biological processes are shared across animal species, yet their cellular mechanisms are profoundly diverse. Comparing cell-type gene expression between species reveals conserved and divergent cellular functions. However, as phylogenetic distance increases, gene-based comparisons become less informative. The gene ontology (GO) knowledgebase offers a solution by serving as the most comprehensive resource of gene functions across a vast diversity of species, providing a bridge for distant species comparisons.

Here, we present scGOclust, a computational tool that constructs de novo cellular functional profiles using GO terms, facilitating systematic and robust comparisons within and across species. We applied scGOclust to analyse and compare the heart, gut, and kidney between mouse and fly, and whole-body data from Caenorhabditis elegans and Hydra vulgaris. We show that scGOclust effectively recapitulates the function spectrum of different cell types, characterizes functional similarities between homologous cell types, and reveals functional convergence between unrelated cell types. Additionally, we identified subpopulations within the fly crop that show circadian rhythm-regulated secretory properties and hypothesize an analogy between fly principal cells from different segments and distinct mouse kidney tubules. We envision scGOclust as an effective tool for uncovering functionally analogous cell types or organs across distant species, offering fresh perspectives on evolutionary and functional biology.

ScGOclust is publicly available on CRAN: https://cran.r-project.org/web/packages/scGOclust/index.html and development versions are available on GitHub: github.com/Papatheodorou-Group/scGOclust/.