Comparison of paralog identification methods with target capture phylogenomics of the Sindora clade (Detarioideae, Leguminosae)
Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because the evolutionary history of paralogs may differ from the divergence history of species. Here, we compare existing approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, Putative Paralog Detection and the Yang & Smith orthology inference approach. We use as a case study a target enrichment dataset of 89 species of Detarioideae (Fabaceae) with a focus on the Sindora clade. We verify the performance of these paralog handling tools using BLAST mapping against a reference genome sequence of Sindora glabra and compare their impacts on final species tree topologies. Our results show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs, followed by the built-in paralog identification functions of HybPiper and CAPTUS. However, the results we recovered for the Sindora clade suggest that correct identification, removal or incorporation of paralogs does not lead to significant changes in the resulting species tree topology. The topological differences we recovered were largely due to biological reasons such as hybridisation and introgression. Our study highlights the importance of careful inspection of sequencing alignments and provides a roadmap for workers to establish the best approach for their dataset to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for their study group.
Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because the evolutionary history of paralogs may differ from the divergence history of species. Here, we compare existing approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, Putative Paralog Detection and the Yang & Smith orthology inference approach. We use as a case study a target enrichment dataset of 89 species of Detarioideae (Fabaceae) with a focus on the Sindora clade. We verify the performance of these paralog handling tools using BLAST mapping against a reference genome sequence of Sindora glabra and compare their impacts on final species tree topologies. Our results show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs, followed by the built-in paralog identification functions of HybPiper and CAPTUS. However, the results we recovered for the Sindora clade suggest that correct identification, removal or incorporation of paralogs does not lead to significant changes in the resulting species tree topology. The topological differences we recovered were largely due to biological reasons such as hybridisation and introgression. Our study highlights the importance of careful inspection of sequencing alignments and provides a roadmap for workers to establish the best approach for their dataset to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for their study group.