Author(s): Pawan Kumar Yadav, Ravi S Singh, Prakash Singh, Chandan Kisore, Tushar Ranjan, Chanda Kushwaha, Kumari Rashmi, Sanjeev Kumar and PK Singh

Abstract: Indian mustard (Brassica juncea L. Czern & Coss.) is an important oilseed crop of rapeseed-mustard group. Understanding the nature and magnitude of genetic variation in conjunction with genetic gain of the traits is pertinent for a breeding programme aimed at developing high yielding stable varieties. Yield and oil content decreases progressively with the delay in planting from optimum time of sowing due to terminal heat during the reproductive phase. So, it is important to screen out the potential genetically diverse genotypes which will perform well during the late sown condition using molecular diversity analysis. We employed long non coding-RNA (LncRNA)-SSR markers, as these are highly polymorphic and useful in genetic diversity analysis. We analysed total thirty six genotypes of Indian mustard including four checks (NRCHB-101, Kranti, CS-56 and RGN-73) using LncRNA-SSR markers. Out of twenty five of these markers, fourteen were found to be polymorphic with an average PIC value 0.28 and maximum 0.56. The Jaccard’s coefficient (similarity matrix), showed maximum similarity (1.0) between NRCHB101 and Kranti, followed by (0.94) between BRRM119 and BRRM 116, BRRM119 and BRRM 117, BRRM120 and BRRM-117, BRRM120 and BRRM 118, and the least similarity (0.17) was found between CMCNL22-14 and Kranti, followed by (0.24) BRRM118 and CMCNL22-15. Dendrogram prepared on the basis of molecular data showed two major clusters, I (sub-cluster IA and IB) and II (sub-cluster IIA and IIB), containing 29 and 7 genotypes, respectively. The genotypes like CMCNL22-14 and Kranti, BRRM118 and CMCNL22-15, and others having a large cluster distance could provide good heterotic combination and there is also possibility of getting desired transgressive segregants in the advance generations. The present study led to identification of suitable genotypes that could be used in future breeding programme.

DOI: 10.33545/26174693.2024.v8.i4Sb.914