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. 2024 Oct 25;15(11):1373.
doi: 10.3390/genes15111373.

Genetic Diversity and Population Structure Analysis of Soybean [ Glycine max (L.) Merrill] Genotypes Using Agro-Morphological Traits and SNP Markers

Felicity Kido Chiemeke  1 , Bunmi Olasanmi  2 , Paterne A Agre  3 , Hapson Mushoriwa  3 , Godfree Chigeza  4 , Abush Tesfaye Abebe  3
Affiliations

Genetic Diversity and Population Structure Analysis of Soybean [ Glycine max (L.) Merrill] Genotypes Using Agro-Morphological Traits and SNP Markers

Felicity Kido Chiemeke et al. Genes (Basel). .

Abstract

Background/Objectives: Understanding the genetic diversity of soybean genotypes can provide valuable information that guides parental selection and the design of an effective hybridization strategy in a soybean breeding program. In order to identify genetically diverse, complementary, and prospective parental lines for breeding, this study set out to ascertain the genetic diversity, relationships, and population structure among 35 soybean genotypes based on agro-morphological traits and Single Nucleotide Polymorphic (SNP) marker data. Methods/Results: Cluster analysis, based on agro-morphological traits, grouped the studied genotypes into four clusters. The first two principal components accounted for 62.8% of the total phenotypic variation, where days to 50% flowering, days to 95% maturity, grain yield, shattering score, and lodging score had high and positive contributions to the total variation. Using the SNP marker information, mean values of 0.16, 0.19, 0.067, and 0.227 were obtained for minor allele frequency (MAF), polymorphic information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He), respectively. Using different clustering approaches (admixture population structure, principal component scatter plot, and hierarchical clustering), the studied genotypes were grouped into four major clusters. Conclusions:The agro-morphological and molecular analysis results indicated the existence of moderate genetic diversity among the studied genotypes. The traits identified to be significantly related to yield provide valuable information for the genetic improvement of soybeans for yield.

Keywords: SNP Marker; genetic diversity; grain yield; soybean.

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Conflict of interest statement

The authors declare there are no conflicts of interest.

Figures

Figure 1
Figure 1
Cluster dendrogram of thirty-five soybean genotypes evaluated across three locations in Nigeria in 2022 based on agro-morphological traits.
Figure 2
Figure 2
Biplot of the first two principal components showing the 35 genotypes and their association with the seven phenotypic traits. In this figure, GY: grain yield in kg/ha, HSW: hundred seed weight in g, PHT: plant height, D50f: days to fifty percent flowering, DTM: 95% days to maturity, Lsco: lodging score, Ssco: shattering score.
Figure 3
Figure 3
Hierarchical clustering dendrogram of thirty-three soybean genotypes based on 10,630 SNP markers generated using the Ward D2 method and Jaccard’s dissimilarity matrix.
Figure 4
Figure 4
Population structure based on admixture analysis of thirty-three soybean genotypes. Subpopulations were set at k = 4. The colors represent the four clusters: Cluster 1 (red), cluster 2 (blue), cluster 3 (green), and cluster 4 (black) based on a membership coefficient of ≥60%, admixed membership based on a coefficient of <60%.
Figure 5
Figure 5
Silhouette width optimum clustering.
Figure 6
Figure 6
Scatter plot of individuals on the first two principal components analysis of thirty-three soybean genotypes using 10,630 SNP markers.
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