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Abstract Increasing trends in the occurrence of diabetes underline the need to develop low glycemic index (GI) rice with preferred grain quality. In the current study, a diverse set of 3 K sub-panel of rice consisting of 150 accessions was evaluated for resistant starch and predicted glycemic index, including nine other quality traits under transplanted situation. Significant variations were noticed among the accessions for the traits evaluated. Trait associations had shown that amylose content possess significant positive and negative association with resistant starch and predicted glycemic index. Genome-wide association studies with 500 K SNPs based on MLM model resulted in a total of 41 marker-trait associations (MTAs), which were further confirmed and validated with mrMLM multi-locus model. We have also determined the allelic effect of identified MTAs for 11 targeted traits and found favorable SNPs for 8 traits. A total of 11 genes were selected for haplo-pheno analysis to identify the superior haplotypes for the target traits where haplotypes ranges from 2 (Os10g0469000-GC) to 15 (Os06g18720-AC). Superior haplotypes for RS and PGI, the candidate gene Os06g11100 (H4-3.28% for high RS) and Os08g12590 (H13-62.52 as intermediate PGI). The identified superior donors possessing superior haplotype combinations may be utilized in Haplotype-based breeding to developing next-generation tailor-made high quality healthier rice varieties suiting consumer preference and market demand.

The genetic improvement of any crop mainly depends on the amount of genetic variability present in the population. To explore this variability, an effort was made to classify, understand the nature and magnitude of genetic variability and diversity among 112 rice genotypes for 16 quantitative traits using Mahalanobis D2 statistics. Analysis of variance revealed a wide and significant variation for all the 16 traits studied. A slight difference between PCV and GCV was found, suggesting that genetic control of traits is higher than environmental influence. Characters such as harvest index, days to first flowering, days to 50% flowering, and plant height showed high heritability coupled with high genetic advance as per cent of mean suggesting that selection for the improvement of these traits may be rewarding. Cluster analysis indicated that the 112 rice genotypes were grouped into 7 clusters, wherein cluster I had the highest number of genotypes (73) followed by cluster III with 22 genotypes. The maximum inter-cluster distance was recorded between clusters V and VII with a D2 value of 58981.07, followed by clusters II and V (51875.13). The number of spikelets per panicle (52.17%) and the number of grains per panicle (27.26%) were found to be the most contributing traits towards total genetic diversity. Hence, information on the nature and degree of divergence would help the plant breeder in the selection and hybridization procedure for choosing the right type of parents to improve yield and other traits.