ScGOclust: leveraging gene ontology to compare cell types across distant species using scRNA-seq data

Abstract

AbstractBasic biological processes are shared among animal species, yet their cellular mechanisms are profoundly diverse. Comparing cell type expression profiles across species reveals the conservation and divergence of cellular functions. With the increase of phylogenetic distance between species of interest, a gene-based comparison becomes limited. The Gene Ontology (GO) knowledgebase is the most comprehensive resource of gene functions, providing a bridge for comparing cell types between remote species. Here, we present scGOclust, a computational tool to construct cellular functional profiles using GO terms and facilitates systematic, robust comparisons within and across species. We use scGOclust to analyse and compare the heart, gut and kidney between mouse and fly. We show that scGOclust recapitulates the function spectrum of different cell types, characterises functional similarities between homologous cell types, and reveals functional convergence between unrelated cell types. Furthermore, we identify subpopulations in the fly crop by cross-species comparison of GO profiles. Finally, scGOclust resolved the analogy between Malpighian tubule and kidney segments.