Using all gene families vastly expands data available for phylogenomic inference

Abstract

Traditionally, single-copy orthologs have been the gold standard in phylogenomics. Most phylogenomic studies identify putative single-copy orthologs by using clustering approaches and retaining families with a single sequence from each species. However, this approach can severely limit the amount of data available by excluding larger families. Recent methodological advances have suggested several ways to include data from larger families. For instance, tree-based decomposition methods facilitate the extraction of orthologs from large families. Additionally, several popular methods for species tree inference appear to be robust to the inclusion of paralogs, and hence could use all of the data from larger families. Here, we explore the effects of using all families for phylogenetic inference using genomes from 26 primate species. We compare single-copy families, orthologs extracted using tree-based decomposition approaches, and all families with all data (i.e., including orthologs and paralogs). We explore several species tree inference methods, finding that across all nodes of the tree except one, identical trees are returned across nearly all datasets and methods. As in previous studies, the relationships among Platyrrhini remain contentious; however, the tree inference methods matter more than the dataset used. We also assess the effects of each dataset on branch length estimates, measures of phylogenetic uncertainty and concordance, and in detecting introgression. Our results demonstrate that using data from larger gene families drastically increases the number of genes available for phylogenetic inference and leads to consistent estimates of branch lengths, nodal certainty and concordance, and inferences of introgression.

OrthoSNAP: a tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

“…Inclusion of SNAP-OGs increased the size of all seven datasets, sometimes substantially. We note that our results are qualitatively similar to those reported recently by Smith et al [37], which retrieved SC-OGs nested within larger families from 26 primates and examined their performance in gene tree and species tree inference. Three noteworthy differences are that we also conduct species-specific inparalog trimming, provide a user-friendly command-line software for SNAP-OG identification, and evaluated the phylogenetic information content of SNAP-OGs and SC-OGs across seven diverse phylogenomic datasets.…”

“…Notably, these software are also different from sequence similarity graph-based inferences of subgroups of single-copy orthologous genes—such as the algorithm implemented in OMA [21]. Finally, our results, together with other studies, demonstrate the utility of SC-OGs that are nested within larger families [15,20,37,38].…”

“…Thus, OrthoSNAP allows for greater user flexibility and accounts for more diverse scenarios, leading to, at least in some instances, the identification of more loci for downstream analyses (S8 Fig) . Notably, these software are also different from sequence similarity graph-based inferences of subgroups of single-copy orthologous genes-such as the algorithm implemented in OMA [21]. Finally, our results, together with other studies, demonstrate the utility of SC-OGs that are nested within larger families [15,20,37,38].…”

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

“…Inclusion of SNAP-OGs increased the size of all 7 datasets, sometimes substantially. We note that our results are qualitatively similar to those reported recently by Smith and colleagues [37], which retrieved SC-OGs nested within larger families from 26 primates and examined their performance in gene tree and species tree inference. Three noteworthy differences are that we also conduct species-specific inparalog trimming, provide a user-friendly command-line software for SNAP-OG identification, and evaluated the phylogenetic information content of SNAP-OGs and SC-OGs across 7 diverse phylogenomic datasets.…”

“…Moreover, examination of evolutionary histories facilitates the identification of species-specific inparalogs. Finally, our results, together with other studies, demonstrate the utility of SC-OGs that are nested within larger families [ 15 , 20 , 37 , 38 ].…”