Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools - Correa Abondano, Miguel; Ospina, Jessica Alejandra; Wenzl, Peter; Carvajal-Yepes, Monica (Frontiers in Plant Science, 2024)
Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions. A panel of 44 common bean (Phaseolus vulgaris L.) landraces from the Alliance Bioversity and CIAT gene bank, was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping (in silico-pool), and by pooling tissue from 25 individual plants per accession (seq-pool). Sampling strategies were compared to assess technical aspects of the samples, marker information content and genetic composition of the panel. The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 SNPs) than the in silico-pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico-pool genotyping were consistent, but results suggest that the difference between pools depends on population heterogeneity. Principal Coordinate Analysis (PCoA), Hierarchical Clustering, and the estimation of admixture coefficients derived from a single plant, in silico- and seq-pools successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets. In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits.