Deciphering allelic variability and population structure in buckwheat: An analogy between the efficiency of ISSR and SSR markers

Food and nutritional security continue to be the issues of concern in developing countries like ours. Exploring the reservoir of high potential unexplored genetic resources could address the world's food and nutritional insecurity. The availability of diverse data and the population structure of any crop germ plasm is a valuable genetic resource for discovering genes that can help achieve food and nutritional stability. We used seven ISSR and seven SSR markers to investigate diversity among 63 buckwheat genotypes, including landraces from India's northwestern Himalayas. Various parameters such as percent polymorphism, PIC, resolving power, and marker index was used to evaluate the inequitable efficacy of these markers. We foundthat both marker systems are effective in detecting polymorphism in buckwheat germplasm. Seven ISSRs produced 55 polymorphic bands, while seven SSRs produced 32bands. When compared to ISSRs, SSRs had a greater average PIC value (0.43) than that of (0.36). ISSRs, on the other hand, had a resolving power of (4.38) compared to (1.42) for SSRs. The hierarchical cluster analysis dendrogram divided genotypes into three major clusters. We found that both marker systems were equally accurate in grouping buckwheat genotypes according to their geographical origins. Using 7 ISSR and 7 SSR markers, the model-based STRUCTURE analysis established a population with two sub-populations that correspond to species-based groupings. Within the population, there was a high level of genetic diversity. These results have consequences for both buckwheat breeding and conservation efforts. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

The study showed that both ISSR and SSR markers were effective in detecting polymorphism in buckwheat germplasm, with SSRs having a higher average PIC value and ISSRs having a higher resolving power. Hierarchical cluster analysis divided genotypes into three major clusters, with both marker systems accurately grouping buckwheat genotypes by their geographical origins.