Identifying genetically redundant accessions in the world's largest cassava collection

Area of Science:

• Agricultural Science
• Genetics
• Bioinformatics

Background:

• Crop genebanks are crucial for conserving genetic diversity, essential for developing improved crop varieties with enhanced yields, nutrition, and resilience.
• Cassava (Manihot esculenta) is a vital carbohydrate source for millions globally, necessitating effective conservation of its genetic resources.
• Efficient management of large genebank collections requires the identification and removal of genetic redundancy to optimize resource allocation.

Purpose of the Study:

• To optimize the identification of genetic redundancy within the International Center for Tropical Agriculture (CIAT) cassava genebank collection.
• To establish empirical distance thresholds for assessing genetic redundancy using molecular markers.
• To identify a subset of genetically distinct cassava accessions for efficient genebank management.

Main Methods:

• Applied single-nucleotide polymorphism (SNP) and SilicoDArT molecular markers to 5,302 Manihot esculenta accessions.
• Implemented quality filters for marker selection and DNA sample exclusion.
• Analyzed genetic distances to identify clusters of redundant accessions, comparing with passport data.

Main Results:

• Identified 47% of accessions as genetically redundant, with 2,518 (SNP) and 2,526 (SilicoDArT) distinct genotypes found.
• A significant portion of accessions (2,776 SNP, 2,785 SilicoDArT) belonged to clusters containing up to 87 individuals.
• Comparison with passport and historical data supported the identification of redundant accession clusters.

Conclusions:

• Provides valuable guidance for genebank curators on setting genetic distance thresholds to assess redundancy.
• Aids in identifying distinct accessions, prioritizing management activities like cryopreservation.
• Offers insights for future studies and potential removal of duplicate accessions to improve genebank efficiency.