Annotation-free delineation of prokaryotic homology groups

PLoS Comput Biol. 2022 Jun 8;18(6):e1010216. doi: 10.1371/journal.pcbi.1010216. eCollection 2022 Jun.

Abstract

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Gene Transfer, Horizontal
  • Genome, Bacterial* / genetics
  • Phylogeny
  • Prokaryotic Cells*
  • Sequence Alignment

Grants and funding

This work was funded in part by National Science Foundation (https://nsf.gov/) grants DBI 2030604, CCF 1514177, CCF 1800723 and EF 2126387(to L.N.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.