SSR-BASED GENETIC STRUCTURE STUDY OF SEVENTY-EIGHT COWPEA ( Vigna unguiculata (L.) Walp) GENOTYPES

Seventy-eight cowpea accessions were studied using short sequence repeats (SSR) technique. Genetic structure of these accessions was studied using three SSR polymorphic primers, SSR-6206, SSR-6218 and SSR-6219. A total of eight loci were scored for the three primers with a total of ten alleles. Bayesian clustering method grouped the cowpea genotypes into 4 sub-populations. Ancestral allele frequencies ranged between 0.128 and 0.802, while allele frequencies within sub-populations ranged from 0.001 and 0.997. Allele frequency divergence among sub-populations ranged from 0.145 to 0.406. Expected heterozygosity between individuals in the same sub-population ranged from 0.084 and 0.26, Mean genetic differentiation among sub-populations ranged from 0.374 and 0.687, with a mean geneflow ranging from 0.228 and 0.837. There was relative uniformity within the sub-populations which can be accounted for by independent random genetic drift.


Introduction
Natural populations are structured into subpopulations which do not permit total random mating making them genetically distinct from each other. This therefore would result in a set of individuals characterized by some measure of genetic distinction. Such genetic differences may be due to geographic ancestry. Structure in this sense refers to any deviation from random-mating, including inbreeding and assortative mating. It is important to know how much variation exists within each level of structure relative to other levels. Wright (1951) developed the F-statistics, a set of measures for departures from Hardy-Weinberg equilibrium in sub-divided populations. Fixation index (F) a measure of increased homozygosity; Inbreeding coefficient (F IS ) a correlation of uniting gametes relative to gametes drawn at random from within a sub-population (Individual within the Sub-population) and F ST a measure of population sub-structure which is beneficial for analysing the overall genetic divergence amongst sub-populations. Elements of population structure assessment include similarity and dissimilarity measure, genetic distances between individuals, clustering and differentiation among sub-populations (Panda et al., 2015).
Genetic diversity plays a key role in the continued existence of species. An insight of the dynamics of genetic diversity within and among populations of species is key to the development of optimum genetic resource management strategies towards conservation, sustainable utilization and genetic improvement (Panda et al., 2015). Genetic diversity assessment is very vital to mitigate threats of environmental fluctuations. For the maximum exploitation of genetic resources in breeding programmes, knowledge about genetic diversity is paramount. Availability of genetic diversity within plant species aids in the selection of superior lines for crop improvement (Ali et al., 2007). Genetic differentiation in populations may be due to a lot of factors, among which are the following suggested by Falconer (1988): random genetic drift occurring independently in different sub-populations, uniformity within sub-populations due to progressive reduction in genetic variation within each sub-population, geographical or ecological causes under natural conditions or from controlled breeding in domesticated or laboratory breeding, genetic drift (Mettler and Gregg, 1969), occurring populations that become small periodically (that is "bottle-neck effect") and populations established by a few emigrants ("founders principle") carrying a small sample of genetic variation from a large population. The study was conducted to study the genetic structure of Ghanaian cowpeas at three SSR gene loci. Such a study will be useful to the cowpea breeders and cowpea germplasm curators.

SSR analysis
Fifty cowpeas derived SSR primers were screened and three of them, SSR-6206, SSR-6218 and SSR-6219 (Table 1), which produced consistent, reproducible and polymorphic bands were used for DNA amplification.

Collection of leaf samples
The first trifoliate leaves of one plant per accession was harvested two weeks after planting and stored at -80 o prior to DNA extraction.

DNA extraction
The Doyle and Doyle (1990) method with modification was used for genomic DNA extraction. Genomic DNA was extracted from one gram of young cowpea leaves harvested on ice. The leaf tissues were ground in liquid nitrogen using a micropestle. The ground leave sample was transferred into Eppendorf tubes and 500 µl of prewarmed (60 o C) cetyltrimethyl ammonium bromide (CTAB) extraction buffer was added. The solution was vortexed and incubated at 65 o C for one hour. A solution of phenol/chloroform was added. DNA was precipitated by adding equal volumes of cold isopropanol and NaOAc. DNA pellets were washed using EtOH. The washed DNA pellets were allowed to dry at room temperature. The dried DNA pellets were then dissolved in 1xTE buffer (10 MM Tris (pH 8.0); 0.1 MM EDTA) and treated with RNase (5 µg/µl) at 37 o C for 30 minutes. DNA quality and quantity were checked using Nano-drop spectrophotometer. DNA was stained with a blue dye and run using 1.5% agarose gel electrophoresis.

TABLE 1 List of three cowpea SSR markers
ACAATGCACAAAATGTGAATCTC GGGAAGCTTAGGAAAAGTTTGA

PCR amplification
The three primers were used to carry out PCR amplification. The cocktail prepared for amplification contained the following: 2 µl template DNA, 6.25 µl master mix, 0.5 µl of primer (forward and backward), and 3.25 µl of double distilled water. The PCR tubes were placed in a thermocycler and programmed for initial denaturation at 95°C for 3 minutes, followed by 30 cycles for 30 seconds at 94°C, 30 seconds at 53°C, 2 minutes at 72°C, and final extension for 15 minutes at 72°C .

Electrophoresis
The PCR product was electrophoresed in 1.5% agarose gel in TAE buffer at a voltage of 100 V for 2 hours 30 minutes. The agarose gel was stained with ethidium bromide and visualized and scored under UV.

Statistical analysis
Band (allele) positions for each cowpea genotype were scored by micro-satellite repeat score approach, where each allele at a given locus was coded by a unique integer and missing allele coded as -999. Marker genotype data was prepared in Microsoft excel and the file saved in Text (tab delimited) type. The software STRUCTURE version 2.2. (Pritchard et al., 2000) was used for data analysis. To determine memberships of cowpea genotypes, number and membership of clusters, allele frequency distribution in the clusters, allele frequency divergence among clusters and gene flow.

Membership probabilities of genotypes
Membership probabilities of each genotype in each of the four sub-populations are shown in Table 5 to Table 8

Nei's nucleotide distance among subpopulations
Results for Nei's nucleotide distance among sub-populations are shown in Table 9. The distances represent allele-frequency divergence among the sub-populations. The distance ranged from 0.145 (sub-populations 2 and 4) to 0.466 (between sub-populations 1 and 3) with an average distance of 0.274.

Average distance (expected heterozygosity) between individual in the same cluster
Results for average distance between individual cowpea genotypes in the same subpopulation are presented in Table 10. Average distance ranged from 0.084 (in sub-population 4) to 0.26 (in sub-population 3).  The four sub-populations represent 4 major gene pools of the 78 cowpea genotypes. These sub-populations differed in the distribution of the 8 SSR loci. There was differential allele frequency distribution within the four sub-populations. Allele frequencies for the sub-populations were either lower or higher than their corresponding ancestral allele frequencies. There was therefore an indication of some alleles approaching either extinction or fixation in the respective sub-populations. Allele SSR1-1 is approaching extinction in sub-population 2 with a frequency of 0.005in sub-populations 2, 3 and 4 allele SSR2-2 is approaching extinction with frequencies of 0.001, 0.012 and 0.001 respectively. Similarly, alleles SSR7-2 is approaching extinction in all of the four sub-populations. Allele SSR3-1 is approaching fixation in sub-populations 2 and 4 with frequencies of 0.994 and 0.992, respectively, while allele SSR4-1 is also approaching fixation in subpopulations 1 and 4 with frequencies of 0.978 and 0.995, respectively. Allele SSR5-1 is also approaching fixation in sub-populations 1, 2 and 4 with frequencies of 0.984, 0.998 and 0.997, respectively. In sub-populations 1 and 2, allele SSR6-1is approaching fixation with frequencies of 0.952 and 0.993, respectively. Allele SSR7-2 is also approaching fixation in sub-population 1. Allele SSR8-1 is approaching fixation in sub-populations 1, 2 and 4 with allele frequencies 0.995, 0.998 and 0.970, respectively. Different levels of genetic differentiation were observed for the 4 gene pools. The levels of genetic differentiation for the 4 sub-populations imply that 31.3% of genetic differentiation resided within genotypes for sub-population 2 and sub-population 4, respectively. In sub-population 1 and subpopulation 3 36.8% and 62.6% of genetic differentiation resided within the genotypes. A relatively high level of geneflow of about 85.0% occurred in sub-population 3, while relatively low levels occurred in the remaining three sub-populations. The observations for the current study were at variance with those of Asante et al. (2003) who observed 92.5% of genetic differentiation within cowpea genotypes and a geneflow of 100.0% in a study of genetic structure at the isocitrate dehydrogenase and malate dehydrogenase enzyme gene loci of Ghanaian cowpea accessions. These differences could be due to differences in the cowpea genotype and also the genetic markers used. In the current study, there is relative uniformity within the subpopulations which can be accounted for by independent random genetic drift.