Estimation of genetic diversity and relatedness in a mango germplasm collection using SNP markers and a simplified visual analysis methodExport / Share PlumX View Altmetrics View AltmetricsKuhn, D. N., Dillon, N. L., Bally, I. S.E., Groh, A., Rahaman, J., Warschefsky, E., Freeman, B., Innes, D. J. and Chambers, A. H. (2019) Estimation of genetic diversity and relatedness in a mango germplasm collection using SNP markers and a simplified visual analysis method. Scientia Horticulturae, 252 . pp. 156-168. ISSN 0304-4238
Article Link: https://doi.org/10.1016/j.scienta.2019.03.037 Publisher URL: http://www.sciencedirect.com/science/article/pii/S0304423819302110 AbstractMango is a globally important tropical fruit but lacks genomic tools to support cultivar identification and to enable breeding efforts. Assessing the genetic diversity and relatedness of mango germplasm is essential for identifying genetically distant parents with favorable agronomic traits to produce hybrid populations enabling selection of improved cultivars. We thus genotyped 1915 mango accessions from the United States, Senegal, Thailand, and Australia with 272 single nucleotide polymorphism (SNP) markers identifying over 520,000 genotypes. These accessions represent the available diversity from both public and private germplasm collections in these countries, as well as accessions from smaller international collections. The study included Mangifera indica, other Mangifera species, and accessions from half sibling populations. Genotype data were analyzed using an affinity propagation method to define 258 groups. Using a simple visual method, no more than 30 SNPs are needed to distinguish a single cultivar of interest from all other cultivars in the dataset enabling the accurate identification of important commercial cultivars. As these SNP markers provided accurate genotype data for accessions from different genera as well as half siblings, the majority of the genetic diversity of the mango germplasm and related species that were genotyped has been captured. The dataset contains a large collection of open-pollinated half siblings from known maternal parents. A simple visual method can also be used to identify self-pollinated individuals among the half siblings of known maternal parents and, in some cases, to infer likely candidates for the paternal parent. Identification of self-pollinated individuals is particularly important in terms of selection of improved cultivars, as due to high levels of heterozygosity, self-pollinated progeny are likely to uncover deleterious recessive alleles. Genotyping of progeny at the seedling stage and removal of self-pollinated progeny can increase the efficiency and decrease the costs of selection of improved cultivars from open-pollinated populations.
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