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Accurate, automated taxonomic assignment of genebank accessions: a new method demonstrated using high-throughput marker data from 10,000 Capsicum spp. accessions

KEY MESSAGE: We demonstrate how an algorithm that uses cheap genetic marker data can ensure the taxonomic assignments of genebank samples are complete, intuitive, and consistent—which enhances their value. ABSTRACT: To maximise the benefit of genebank resources, accurate and complete taxonomic assig...

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Detalles Bibliográficos
Autores principales: Rabanus-Wallace, M. Timothy, Stein, Nils
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10495273/
https://www.ncbi.nlm.nih.gov/pubmed/37695370
http://dx.doi.org/10.1007/s00122-023-04441-8
Descripción
Sumario:KEY MESSAGE: We demonstrate how an algorithm that uses cheap genetic marker data can ensure the taxonomic assignments of genebank samples are complete, intuitive, and consistent—which enhances their value. ABSTRACT: To maximise the benefit of genebank resources, accurate and complete taxonomic assignments are imperative. The rise of genebank genomics allows genetic methods to be used to ensure this, but these need to be largely automated since the number of samples dealt with is too great for efficient manual recategorisation, however no clearly optimal method has yet arisen. A recent landmark genebank genomic study sequenced over 10,000 genebank accessions of peppers (Capsicum spp.), a species of great commercial, cultural, and scientific importance, which suffers from much taxonomic ambiguity. Similar datasets will, in coming decades, be produced for hundreds of plant taxa, affording a perfect opportunity to develop automated taxonomic correction methods in advance of the incipient genebank genomics explosion, alongside providing insights into pepper taxonomy in general. We present a marker-based taxonomic assignment approach that combines ideas from several standard classification algorithms, resulting in a highly flexible and customisable classifier suitable to impose intuitive assignments, even in highly reticulated species groups with complex population structures and evolutionary histories. Our classifier performs favourably compared with key alternative methods. Possible sensible alterations to pepper taxonomy based on the results are proposed for discussion by the relevant communities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-023-04441-8.