ArticleBMC genomic data2024
Comprehensive analysis of the genetic variation dataset among wild soybean (Glycine soja) in Shandong Province, China.
Article in BMC genomic data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Comprehensive Method for Soybean Cultivar Identification Using MGIseq, VCF2GENOME, and REST API.Methods in molecular biology (Clifton, N.J.) · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
objectivesWild soybean (Glycine soja), the ancestor of domesticated soybean, retains a higher level of genetic diversity and adaptability to harsh environments, making it highly valuable for breeding. Here, we re-sequenced 69 wild soybean individuals collected by the Shandong Academy of Agricultural Sciences and identified 1,613,162 high-quality SNPs which not only enriches our understanding of the genetic structure of wild soybean, but also provides valuable resources for further genomic research and genetic improvement of soybean. DATA DESCRIPTION: In this study, we collected 69 wild soybean accessions from Shandong Province, China, and performed re-sequencing on the DNBSEQ platform, followed by SNPs identification. We then integrated ADMIXTURE, neighbor-joining tree, and principal component analysis to illustrate population characteristics. The results showed that these wild soybean accessions could be divided into three distinct subpopulations, exhibiting significant genetic differences.
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