Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 May 8;20(5):e0312079.
doi: 10.1371/journal.pone.0312079. eCollection 2025.

Genetic diversity and population structure of soybean (Glycine max (L.) Merril) germplasm

Affiliations

Genetic diversity and population structure of soybean (Glycine max (L.) Merril) germplasm

Tenena Silue et al. PLoS One. .

Abstract

Soybean (Glycine max (L.) Merril) is a significant legume crop for oil and protein. However, its yield in Africa is less than half the global average resulting in low production, which is inadequate for satisfying the continent's needs. To address this disparity in productivity, it is crucial to develop new high-yielding cultivars by utilizing the genetic diversity of existing germplasms. Consequently, the genetic diversity and population structure of various soybean accessions were evaluated in this study. To achieve this objective, a collection of 147 soybean accessions was genotyped using the Diversity Array Technology Sequencing method, enabling high-throughput analysis of 7,083 high-quality single-nucleotide polymorphisms (SNPs) distributed across the soybean genome. The average values observed for polymorphism information content (PIC), minor allele frequency, expected heterozygosity and observed heterozygosity were 0.277, 0.254, 0.344, and 0.110, respectively. The soybean genotypes were categorized into four groups on the basis of model-based population structure, principal component analysis, and discriminant analysis of the principal component. Alternatively, hierarchical clustering was used to organize the accessions into three distinct clusters. Analysis of molecular variance indicated that the genetic variance (77%) within the populations exceeded the variance (23%) among them. The insights gained from this study will assist breeders in selecting parental lines for genetic recombination. The present study demonstrates that soybean improvement is viable within the IITA breeding program, and its outcome will help to optimize the genetic enhancement of soybeans.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Distribution and density of filtered SNPs across 20 soybean chromosomes.
The horizontal axis represents the chromosome length, the SNP density in each region is indicated at the bottom right.
Fig 2
Fig 2. Population structure of 147 soybean breeding lines from the IITA breeding program, Ibadan on the basis of ADMIXTURE analysis with the subpopulations set at K = 4 via 7,083 high-quality SNPs.
The colors correspond to the four subpopulations: Subpopulation 1 (red), Subpopulation 2 (blue), Subpopulation 3 (green) and Subpopulation 4 (cyan), determined by a membership coefficient greater than70%.
Fig 3
Fig 3. Summary of discriminant analysis of principal component (DAPC) for 147 soybean accessions, illustrating the ordination plot of DAPC for the four groups.
Eigenvalues are displayed in the upper-left inset. Genetic groups or clusters are represented by distinct colors and inertia ellipses, with individual genotypes indicated by dots.
Fig4
Fig4. Hierarchical clustering analysis based on 7,083 DArT-SNP markers, depicting the genetic relationships among 147 soybean accessions from the IITA, Ibadan breeding programme.
Fig 5
Fig 5. Principal component analysis plot showing the clustering of 147 soybean breeding accessions into four clusters.
Each cluster is represented by a distinct color: Cluster 1 (red), Cluster 2 (yellow), Cluster 3 (green), Cluster 4 (blue), and admixed individuals (pink).

Similar articles

References

    1. Shete R, Borale S, Andhale G, Girase V. Screening of soybean genotypes for pod-shattering tolerance and association of different traits with seed yield. The Pharma Innovation Journal. 2023;12:1548–51.
    1. Abebe AT, Kolawole AO, Unachukwu N, Chigeza G, Tefera H, Gedil M. Assessment of diversity in tropical soybean (Glycine max (L.) Merr.) varieties and elite breeding lines using single nucleotide polymorphism markers. Plant Genet Resour. 2021;19(1):20–8. doi: 10.1017/s1479262121000034 - DOI
    1. Dean F, Science H, Ranga A. Soyabean the miracle golden bean in Indian foods. Acta Scientific Nutritional Health. 2019;3:44–9.
    1. Alfred O, Shaahu A, Ochigbo A, Amon T, Vange T, Msaakpa T. Soybean: A major component of livestock feed (Fish). Journal of Agriculture and Veterinary Science. 2020;13:38–43.
    1. Tolorunse K, Joseph E, Gana A, Azuh V. Molecular characterization of soybean (Glycine max (L.) Merrill) genotypes using SSR markers. Nigeria Journal of Plant Breeding. 2022;1:12–7.

LinkOut - more resources