High-throughput markers, such as SNPs, along with different methodologies were used to evaluate the applicability of the Bayesian approach and the multivariate analysis in structuring the genetic diversity in cassavas. The objective of the present work was to evaluate the diversity and genetic structure of the largest cassava germplasm bank in Brazil. Complementary methodological approaches such as discriminant analysis of principal components (DAPC), Bayesian analysis and molecular analysis of variance (AMOVA) were used to understand the structure and diversity of 1,280 accessions genotyped using 402 single nucleotide polymorphism markers. The genetic diversity (0.327) and the average observed heterozygosity (0.322) were high considering the bi-allelic markers. In terms of population, the presence of a complex genetic structure was observed indicating the formation of 30 clusters by DAPC and 34 clusters by Bayesian analysis. Both methodologies presented difficulties and controversies in terms of the allocation of some accessions to specific clusters. However, the clusters suggested by the DAPC analysis seemed to be more consistent for presenting higher probability of allocation of the accessions within the clusters. Prior information related to breeding patterns and geographic origins of the accessions were not sufficient for providing clear differentiation between the clusters according to the AMOVA analysis. In contrast, the F ST was maximized when considering the clusters suggested by the Bayesian and DAPC analyses. The high frequency of germplasm exchange between producers and the subsequent alteration of the name of the same material may be one of the causes of the low association between genetic diversity and geographic origin. The results of this study may benefit cassava germplasm conservation programs, and contribute to the maximization of genetic gains in breeding programs.
ABSTRACT. Single nucleotide polymorphism (SNP) markers were used in the largest cassava (Manihot esculenta Crantz) germplasm collection from Brazil to develop core collections based on the maximization strategy. Subsets with 61, 64, 84, 128, 256, and 384 cassava accessions were selected and named PoHEU, MST64, PoRAN, MST128, MST256, and MST384, respectively. All the 798 alleles identified by 402 SNP markers in the entire collection were captured in all core collections. Only small alterations in the diversity parameters were observed for the different core collections compared with the complete collection. Because of the optimal adjustment of the validation parameters representative of the complete collection, the absence of genotypes with high genetic similarity and the maximization of the genetic distances between accessions of the PoHEU core collection, which contained 4.7% of the accessions of the complete collection, maximized the genetic conservation of this important cassava collection. Furthermore, the development of this core collection will allow concentrated efforts toward future characterization and agronomic evaluation of accessions to maximize the diversity and genetic gains in
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations鈥揷itations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.