ArticlePloS one2022
Population structure and genetic diversity characterization of soybean for seed longevity.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Development and characterization of biparental mapping population for the properties of seed and seed coat applicable to seed longevity in soybean (Glycine max (L.) Merrill).BMC plant biology · 2025Article
- Genome-wide association study reveals the QTLs and candidate genes associated with seed longevity in soybean (Glycine max (L.) Merrill).BMC plant biology · 2025Article
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- Population Structure and Genetic Diversity of the 175 Soybean Breeding Lines and Varieties Cultivated in West Siberia and Other Regions of Russia.Plants (Basel, Switzerland) · 2023Article
- Insights into mechanisms of seed longevity in soybean: a review.Frontiers in plant science · 2023Review
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3 authors.
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Abstract
Seed longevity is an important trait in the context of germplasm conservation and economics of seed production. The identification of populations with high level of genetic variability for seed longevity and associated traits will become a valuable resource for superior alleles for seed longevity. In this study, Genotyping-by-sequencing (GBS)-single nucleotide polymorphism (SNP) approach, simple sequence repeats (SSR) markers and agro-morphological traits have been explored to investigate the diversity and population structure of assembled 96 genotypes. The GBS technique performed on 96 genotypes of soybean (Glycine max (L.) Merrill) resulted in 37,897 SNPs on sequences aligned to the reference genome sequence. The average genome coverage was 6.81X with a mapping rate of 99.56% covering the entire genome. Totally, 29,955 high quality SNPs were identified after stringent filtering and most of them were detected in non-coding regions. The 96 genotypes were phenotyped for eight quantitative and ten qualitative traits by growing in field by following augmented design. The STRUCTURE (Bayesian-model based algorithm), UPGMA (Un-weighed Pair Group Method with Arithmetic mean) and principal component analysis (PCA) approaches using SSR, SNP as well as quantitative and qualitative traits revealed population structure and diversity in assembled population. The Bayesian-model based STRUCTURE using SNP markers could effectively identify clusters with higher seed longevity associated with seed coat colour and size which were subsequently validated by UPGMA and PCA based on SSR and agro-morphological traits. The results of STRUCTURE, PCA and UPGMA cluster analysis showed high degree of similarity and provided complementary data that helped to identify genotypes with higher longevity. Six black colour genotypes, viz., Local black soybean, Kalitur, ACC Nos. 39, 109, 101 and 37 showed higher seed longevity during accelerated ageing. Higher coefficient of variability observed for plant height, number of pods per plant, seed yield per plant, 100 seed weight and seed longevity confirms the diversity in assembled population and its suitability for quantitative trait loci (QTL) mapping.
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