Deciphering phenotyping, DNA barcoding, and RNA secondary structure predictions in eggplant wild relatives provide insights for their future breeding strategies.

Eggplant or aubergine (Solanum melongena L.) and its wild cousins, comprising 13 clades with 1500 species, have an unprecedented demand across the globe. Cultivated eggplant has a narrow molecular diversity that hinders eggplant breeding advancements. Wild eggplants need resurgent attention to broaden eggplant breeding resources. In this study, we emphasized phenotypic and genotypic discriminations among 13 eggplant species deploying chloroplast-plastid (Kim matK) and nuclear (ITS2) short gene sequences (400-800 bp) at DNA barcode region followed by ITS2 secondary structure predictions. The identification efficiency at the Kim matK region was higher (99-100%) than in the ITS2 region (80-90%). The eggplant species showed 13 unique secondary structures with a central ring with various helical orientations. Principal component analysis (PCoA) provides the descriptor-wise phenotypic clustering, which is essential for trait-specific breeding. Groups I and IV are categorized under scarlet complexes S. aethiopicum, S. trilobatum, and S. melongena (wild and cultivated). Group II represented the gboma clade (S. macrocarpon, S. wrightii, S. sisymbriifolium, and S. aculeatissimum), and group III includes S. mammosum, and S. torvum with unique fruit shape and size. The present study would be helpful in genetic discrimination, biodiversity conservation, and the safe utilization of wild eggplants.