ArticlePloS one2026
Morphological and molecular characterization of Nepalese Common Bean (Phaseolus vulgaris L.) Landraces.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Nepalese common bean landraces constitute valuable yet underexplored genetic reservoirs for crop improvement. However, integrated morphological and molecular characterization of this germplasm remains limited. This experiment was conducted at 2023 and 2024 to evaluate the morphological and molecular traits of 58 Nepalese common bean landraces collected from 21 districts of the Nepal via an augmented block design. Twenty-three quantitative and twenty-four qualitative traits were measured and analyzed via descriptive and multivariate methods. The Shannon-Weaver diversity indices (H') ranged from 0.085-0.99 for qualitative traits and 0.46-0.92 for quantitative traits. The five principal components (PCs) explained 70.86% of the total phenotypic variation, with two PCs explaining 46.27% of the variation. Phenotypic cluster analysis grouped the 58 accessions into 5 distinct groups. Molecular analysis via 15 SSR markers revealed 38 alleles, with an average of 3.16 alleles per marker. The PIC value ranged from 0.16 to 0.46. The genotypic dendrogram grouped the 58 landraces into 3 clusters. The first two molecular principal coordinates accounted for 43.27% of the variation among the accessions. The analysis of molecular variance revealed a maximum variation of 93% within the population and only 7% variation among the populations. Population structure analysis revealed three genetic clusters, with most accessions showing admixture with moderate heterozygosity and a high fixation index. The accessions NGRCO4168 and NGRCO9516 were identified as promising accessions for traits including days to 50% flowering, days to 50% fruiting, maturity, and yield (t/ha). These accessions should be further evaluated across diverse environments to assess their stability and adaptability. Additionally, expanded SSR or SNP analyses integrated with phenotypic data could facilitate marker-trait association studies aimed at identifying genomic regions linked to key agronomic traits.
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