HybPhaser: a workflow for the detection and phasing of hybrids in target capture data sets

Nauheimer, Lars, Weigner, Nicholas, Joyce, Elizabeth, Crayn, Darren, Clarke, Charles, and Nargar, Katharina (2021) HybPhaser: a workflow for the detection and phasing of hybrids in target capture data sets. Applications in Plant Sciences, 9 (7). e11441.

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PREMISE: Hybrids contain divergent alleles that can confound phylogenetic analyses but can provide insights into reticulated evolution when identified and phased. We developed a workflow to detect hybrids in target capture data sets and phase reads into parental lineages using a similarity and phylogenetic framework.

METHODS: We used Angiosperms353 target capture data for Nepenthes, including known hybrids to test the novel workflow. Reference mapping was used to assess heterozygous sites across the data set and to detect hybrid accessions and paralogous genes. Hybrid samples were phased by mapping reads to multiple references and sorting reads according to similarity. Phased accessions were included in the phylogenetic framework.

RESULTS: All known Nepenthes hybrids and nine additional samples had high levels of heterozygous sites, had reads associated with multiple divergent clades, and were phased into accessions resembling divergent haplotypes. Phylogenetic analysis including phased accessions increased clade support and confirmed parental lineages of hybrids.

DISCUSSION: HybPhaser provides a novel approach to detect and phase hybrids in target capture data sets, which can provide insights into reticulations by revealing origins of hybrids and reduce conflicting signal, leading to more robust phylogenetic analyses.

Item ID: 70290
Item Type: Article (Research - C1)
ISSN: 2168-0450
Keywords: alleles, Angiosperm353, HybPiper, introgression, Nepenthes, paralogs, polyploidy, reticulation
Copyright Information: © 2021 Nauheimer et al. Applications in Plant Sciences published by Wiley Periodicals LLC on behalf of Botanical Society of America. This is an open access article under the terms of the Creative Commons Attribution- NonCommercial- NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non- commercial and no modifications or adaptations are made.
Date Deposited: 24 Nov 2021 23:43
FoR Codes: 31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310201 Bioinformatic methods development @ 50%
31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310203 Computational ecology and phylogenetics @ 50%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 100%
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