Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana

Abstract

Soybean [Glycine max (L.) Merrill] is an important oilseed crop worldwide and it has recently become the crop of interest in Ghana. In this study, 142 soybean accessions were genotyped with 34 SSR markers and concurrently evaluated for five quantitative and two qualitative phenotypic traits. Twenty‐nine of the SSR markers were polymorphic with mean allele number of 5.3, polymorphic information content (PIC) of 0.51 and gene diversity of 0.55. Molecular analysis based on unweighted paired group arithmetic mean (UPGMA) clustering and principal coordinate analysis (PCoA) was similar in explaining the extent of diversity within the accessions. Structure analysis placed most of the accessions into two subpopulations with 18 (12.7%) as admixtures. Principal component analysis (PCA) based on phenotypic traits revealed two clusters. Both UPGMA clustering‐based SSR data and PCA from phenotypic data showed similar results. The assembled germplasm is genetically diverse with high variation in flowering and maturity period, and key yield components which could be exploited in developing superior varieties well adapted to Ghana and West Africa.

Genetic diversity and population structure of groundnut (Arachis hypogaea L.) accessions using phenotypic traits and SSR markers: implications for rust resistance breeding

“…Pod yield, kernel yield and, late leaf spot, rust scored, and shelling percent are important yield components that can be used for indirect selection for yield due to their significantly correlation with yield. The correlations found in this study were in concurrence with Denwar et al ( 2019 ), who also found that disease ratings were negatively correlated with yield while selection for number of pods and seeds per pod increased grain yield in soybean. The positive correlation between rust and late leaf spot shown in this study were confirmed in the previous reports (Narasimhulu et al .…”

“…This showed that most genotypes were more inclined towards susceptibility rather than resistance. Similarly, (Denwar et al 2019 ) found that trait contribution to different PCs differed depending on the extent of variation for the particular trait among test genotypes. Pod yield, kernel yield and, late leaf spot, rust scored, and shelling percent are important yield components that can be used for indirect selection for yield due to their significantly correlation with yield.…”

“…3 and 4 ). The optimal number of clusters in the population structure was based on the Evanno method (Earl and VonHoldt 2012 ), which has been widely used to confirm number of clusters in populations of different crops including cereals and legumes (Van Inghelandt et al 2010 ; Ren et al 2014 ; Denwar et al 2019 ). The two identified clusters grouped the released varieties separately from the landraces while genotypes with similar genetic background were correctly placed in closely linked cluster and sub-clusters.…”

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

“…The mean gene diversity of 0.42 recorded in this study is higher than that of Liu et al [30] who reported a mean gene diversity of 0.35 using 5195 SNP markers to screen 577 soybean accessions. Nonetheless, it is lower compared to the 0.78 and 0.55 reported by Abe et al [31] and Denwar et al [32], respectively, in soybean using microsatellite (SSR) markers. The lower gene diversity with SNP markers is due to their bi-allelic nature when compared with multi-allelic markers such as SSR, as theoretically, maximum gene diversity observable with biallelic markers is 0.5.…”

Genetic Diversity and Population Structure of Tomato (<i>Solanum lycopersicum</i>) Germplasm Developed by Texas A&M Breeding Programs

“…Genetic heritable variability is indispensable in plant breeding aimed at developing new cultivars that express desirable characteristics generation after generation [13]. Furthermore, the development of improved varieties is enhanced when parents are selected based on genetic heterogeneity [14], making genetic variation estimation necessary in breeding programs to allow the selection of parental lines either to increase breeding population variation or to develop hybrids for cultivar release [15].…”