WGDI: A user-friendly toolkit for evolutionary analyses of whole-genome duplications and ancestral karyotypes
Evidence of whole-genome duplications (WGDs) and subsequent karyotype changes has been detected in most major lineages of living organisms on Earth. To clarify the complex resulting multi-layered patterns of gene collinearity in genome analyses, there is a need for convenient and accurate toolkits....
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Veröffentlicht in: | Molecular plant 2022-12, Vol.15 (12), p.1841-1851 |
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Zusammenfassung: | Evidence of whole-genome duplications (WGDs) and subsequent karyotype changes has been detected in most major lineages of living organisms on Earth. To clarify the complex resulting multi-layered patterns of gene collinearity in genome analyses, there is a need for convenient and accurate toolkits. To meet this need, we developed WGDI (Whole-Genome Duplication Integrated analysis), a Python-based command-line tool that facilitates comprehensive analysis of recursive polyploidization events and cross-species genome alignments. WGDI supports three main workflows (polyploid inference, hierarchical inference of genomic homology, and ancestral chromosome karyotyping) that can improve the detection of WGD and characterization of WGD-related events based on high-quality chromosome-level genomes. Significantly, it can extract complete synteny blocks and facilitate reconstruction of detailed karyotype evolution. This toolkit is freely available at GitHub (https://github.com/SunPengChuan/wgdi). As an example of its application, WGDI convincingly clarified karyotype evolution in Aquilegia coerulea and Vitis vinifera following WGDs and rejected the hypothesis that Aquilegia contributed as a parental lineage to the allopolyploid origin of core dicots.
This work reports an integrated and user-friendly toolkit, WGDI,for polyploid inference, hierarchical inference of genomic homology, and ancestral chromosome karyotyping. WGDI can improve the detection of whole-genome duplication and facilitates dynamic illumination of karyotype evolution. |
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ISSN: | 1674-2052 1752-9867 |
DOI: | 10.1016/j.molp.2022.10.018 |