Molecular Characterization of Kenyan Common Bean Germplasm Using Ssr and Peroxidase Gene Markers

Abstract

Common bean (Phaseolus vulgaris) is a legume of high nutritional value and the most important legume worldwide for direct human consumption. It serves as a principal source of protein, starch, vitamins, folate and minerals (iron, potassium, phosphorus, magnesium, manganese and to a lesser extent zinc and calcium). There is limited information on the genetic diversity and population structure of common bean genotypes grown in Kenya. The objective of this study was to determine the genetic diversity and population structure of common bean genotypes from different growing regions (Eastern, Central, Rift Valley, Nyanza and Western) in Kenya using molecular markers. Seeds of 46 cultivars were collected from different regions and three seeds of each genotype were established in plastic pots containing sterile soil in the screenhouse. Young leaves from two-week-old plants were used for DNA extraction followed by PCR amplification using simple sequence repeat (SSR) and peroxidase gene (POX) molecular markers. A total of 366 alleles were amplified using five SSR primers across 40 genotypes, with an average of 4.5 alleles per locus. The polymorphism information content (PIC) of the SSR markers ranged from 0.48 to 0.74 with an average of 0.60. The pair wise genetic similarity between common bean genotypes ranged from 0.15 to 1.0 with an average of 0.54. A dendrogram based on the unweighted pair-group method with arithmetic mean (UPGMA) grouped the 40 genotypes into two major clusters. It was notable that the first major cluster was further divided into two-separate sub-clusters, representing genotypes from each of the regions. Principal component analysis (PCA) of the SSR markers showed that the first two principal components (PCs) explained a total of 28.79% of the genetic variation and failed to cluster the genotypes into distinct groups. Analysis of molecular

variance (AMOVA) revealed high levels of genetic variation (87%) within population, compared to the variation that exists among the populations. Using five POX markers, a total of 624 alleles were amplified ranging from 3 to 9 on every locus, with an average of 7.20. The PIC of the POX markers varied from 0.6204 (POX11) to 0.9110 (POX8), with an average of 0.7677. The range of the observed heterozygosity was from 0.6667 (POX 8) to 0.9150 (POX 12) with a mean of 0.7945, while the values of the mean genetic diversity obtained ranged from 0.3072 (POX11) to 0.4425 (POX8), having a mean of 0.3972. Un-weighted pair group method with arithmetic mean (UPGMA) was used to cluster the genotypes into two main genetic clusters, and the genotypes showed no grouping by geographical origins. The highest value of genetic variation was observed between the genotypes obtained from Western, Rift valley and Central regions of Kenya. Population structure analysis using the Bayesian model-based approach grouped the germplasms into 7 gene pools and showed a high genetic admixture within individual genotypes. Furthermore, population structure analysis showed that these 7 gene pools coexisted in genotypes belonging to different geographic regions. AMOVA revealed higher genetic diversity (99%) within population than among population (1%) and offers a reliable base for the design of genetic improvement schemes. This study demonstrates the existence of considerable genetic diversity in common bean genotypes cultivated in Kenya. The wider genetic diversity is important to future generations so that it copes with unpredictable climate changes and human needs. Therefore, these genotypes can be used as a foundation for future breeding programs to produce hybrids of desirable agronomical traits.