Multiple DNA marker-assisted diversity analysis of Indian mango (Mangifera indica L.) populations

Arbitrary (65 RAPD, 25 ISSR, 23 DAMD), gene-targeted (22 SCoT, 33 CBDP) and co-dominant sequence specific (40 SSR) markers were used individually, or in combinations, to examine the genetic variability within and among 70 selected Indian mango genotypes based on geographic origin (East India, West India, North India, South India) and fruit status (Selection, Hybrid, Landrace). The highest genetic variability was demonstrated by the East Indian populations, followed by those from South India, West India, and North India, when measured in terms of Na, Ne, H, I, PB%, Ht and Hs. Interestingly, the local genotypes of Odisha, which forms a part of East Indian populations, showed the highest diversity compared to hybrid or selection groups, suggesting that the indigenous genotypes hold a greater potential for exploiting the unique and favourable alleles. The maximum genetic variability was detected in geographical/fruit status populations with SSRs (Na-1.76/1.88, Ne-1.48/1.51, H-0.28/0.30, I-0.41/0.45, PB%-76.1/86.9, Ht-0.31/0.32 and Hs-0.28/0.30), followed by CBDPs and SCoTs, reflecting their preeminence for examining the level of genetic polymorphism and diversity. Outcome of AMOVA based analyses as well as low-to-moderate coefficient of genetic differentiation (Gst) and high gene flow (Nm) indicated a greater amount of intra-population genetic variation compared to heterogeneity at inter-population level. Information generated through this investigation could facilitate conservation and further exploitation of mango germplasm including genetic improvement through breeding.

Automated summary

Genetic variability was examined among 70 Indian mango genotypes based on geographic origin and fruit status using various markers. East Indian populations showed the highest genetic variability, while local genotypes from Odisha demonstrated the highest diversity. SSR markers were most effective in detecting genetic variability within geographical/fruit status populations, followed by CBDPs and SCoTs, highlighting their importance in studying genetic polymorphism and diversity levels.