Identifying genetically redundant accessions in the world's largest cassava collection.
Front Plant Sci
; 14: 1338377, 2023.
Article
em En
| MEDLINE
| ID: mdl-38304449
ABSTRACT
Crop diversity conserved in genebanks facilitates the development of superior varieties, improving yields, nutrition, adaptation to climate change and resilience against pests and diseases. Cassava (Manihot esculenta) plays a vital role in providing carbohydrates to approximately 500 million people in Africa and other continents. The International Center for Tropical Agriculture (CIAT) conserves the largest global cassava collection, housing 5,963 accessions of cultivated cassava and wild relatives within its genebank. Efficient genebank management requires identifying and eliminating genetic redundancy within collections. In this study, we optimized the identification of genetic redundancy in CIAT's cassava genebank, applying empirical distance thresholds, and using two types of molecular markers (single-nucleotide polymorphism (SNP) and SilicoDArT) on 5,302 Manihot esculenta accessions. A series of quality filters were applied to select the most informative and high-quality markers and to exclude low-quality DNA samples. The analysis identified a total of 2,518 and 2,526 (47 percent) distinct genotypes represented by 1 to 87 accessions each, using SNP or SilicoDArT markers, respectively. A total of 2,776 (SNP) and 2,785 (SilicoDArT) accessions were part of accession clusters with up to 87 accessions. Comparing passport and historical characterization data, such as pulp color and leaf characteristic, we reviewed clusters of genetically redundant accessions. This study provides valuable guidance to genebank curators in defining minimum genetic-distance thresholds to assess redundancy within collections. It aids in identifying a subset of genetically distinct accessions, prioritizing collection management activities such as cryopreservation and provides insights for follow-up studies in the field, potentially leading to removal of duplicate accessions.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Observational_studies
/
Prognostic_studies
Idioma:
En
Revista:
Front Plant Sci
Ano de publicação:
2023
Tipo de documento:
Article