Genetic Diversity and Population Structure of Soybean Lines Adapted to Sub-Saharan Africa Using Single Nucleotide Polymorphism (SNP) Markers

Abstract

Soybean productivity in sub-Saharan Africa (SSA) is less than half of the global average yield. To plug the productivity gap, further improvement in grain yield must be attained by enhancing the genetic potential of new cultivars that depends on the genetic diversity of the parents. Hence, our aim was to assess genetic diversity and population structure of elite soybean genotypes, mainly released cultivars and advanced selections in SSA. In this study, a set of 165 lines was genotyped with high-throughput single nucleotide polymorphism (SNP) markers covering the complete genome of soybean. The genetic diversity (0.414) was high considering the bi-allelic nature of SNP markers. The polymorphic information content (PIC) varied from 0.079 to 0.375, with an average of 0.324 and about 49% of the markers had a PIC value above 0.350. Cluster analysis grouped all the genotypes into three major clusters. The model-based STRUCTURE and discriminant analysis of principal components (DAPC) exhibited high consistency in the allocation of lines in subpopulations or groups. Nonetheless, they presented some discrepancy and identified the presence of six and five subpopulations or groups, respectively. Principal coordinate analysis revealed more consistency with subgroups suggested by DAPC analysis. Our results clearly revealed the broad genetic base of TGx (Tropical Glycine max) lines that soybean breeders may select parents for crossing, testing and selection of future cultivars with desirable traits for SSA.

Predictive genotype-phenotype relations using genetic diversity in African yam bean (Sphenostylis stenocarpa (Hochst. ex. A. Rich) Harms)

“…In this study, the PIC values were much lower than previously reported studies in AYB [ 1 , 19 , 21 – 23 ] which are mainly attributed to the type of markers used because RAD-SNP markers are bi-allelic in nature when compared with multi-allelic markers [ 32 ]. Furthermore, such discrepancy in genetic diversity could also be due to the differences in the studied material and number of applied genotypes as well as markers [ 32 – 34 ]. However, the PIC values obtained in present study are similar to ones obtained from DArT SNP markers in maize [ 24 ] and sugar beet [ 35 ].…”

Genome-wide association analysis of chickpea germplasms differing for salinity tolerance based on DArTseq markers

“…The SNP and DArT markers demonstrated a moderate rate of PIC values from 0.01 to 0.375 and 0.0106 to 0.58, respectively. Other crop species, such as maize and soybean, have generated similar values of moderate PIC scores for genome-wide markers such as SNP and DArT [ 35 , 36 ].…”

Introgression of QTLs for Drought Tolerance into Farmers’ Preferred Sorghum Varieties

“…Undoubtedly, drought is a major environmental threat to agriculture sustainability in the world which affects physiological plant growth and performance [1,2]. Nonetheless, both pre-and post-flowering drought stress limits crop yield, though post-flowering drought stress is a major concern for sorghum farmers in Tanzania where it occurs when plants are at the grain filling stage and critical for the determination of yield performance [3,4].…”

“…Among the diverse DNA-based markers, SNPs markers clearly detect the existing polymorphism among genotypes, including in sorghum [20,21]. Compared with electrophoresis systembased traditional SNP markers, Kompetitive allele-specific PCRs (KASP) are useful because of low genotyping error rate and amenability to automation that may complement direct phenotyping under field conditions resulting in short breeding cycles in complement with conventional breeding method [2,22]. Additionally, codominant nature of KASP markers facilitates identification of favourable alleles in heterozygous conditions for the introgression of traits through MABC which are either governed by dominant or recessive gene action [23][24][25].…”