In the present study, we tested rice genotypes that included un(der)exploited landraces of Tamil Nadu along with indica and japonica test cultivars to ascertain their genetic diversity structure. Highly polymorphic microsatellite markers were used for generating marker segregation data. A novel measure, allele discrimination index, was used to determine subpopulation differentiation power of each marker. Phenotypic data were collected for yield and component traits. Pattern of molecular differentiation separated indica and japonica genotypes; indica genotypes had two subpopulations within. Landraces were found to have indica genome, but formed a separate subgroup with low linkage disequilibrium. The landraces further separated into distinct group in both hierarchical clustering analysis using neighbour-joining method as well as in the model based population structure analysis. Japonica and the remaining indica cultivars formed two other distinct groups. Linkage disequilibrium observed in the whole population was considerably reduced in subpopulations. Low linkage disequilibrium of landforms suggests their narrow adaptation in local geographical niche. Many population specific alleles could be identified particularly for japonica cultivars and landraces. Association analysis revealed nine marker–trait associations with three agronomic traits, of which 67% were previously reported. Although the testing landraces together with known cultivars had permitted genomewide association mapping, the experiment offers scope to study more landraces collected from the entire geographical region for drawing more reliable information.

Assessment of genetic diversity in a crop germplasm is a vital part of plant breeding. DNA markers such as microsatellite or simple sequence repeat markers have been widely used to estimate the genetic diversity in rice. The present study was carried out to decipher the pattern of genetic diversity in terms of both phenotypic and genotypic variability, and to assess the efficiency of random vis-à-vis QTL linked/gene based simple sequence repeat markers in diversity estimation. A set of 88 rice accessions that included landraces, farmer’s varieties and popular Basmati lines were evaluated for agronomic traits and molecular diversity. The random set of SSR markers included 50 diversity panel markers developed under IRRI’s Generation Challenge Programme (GCP) and the trait-linked/gene based markers comprised of 50 SSR markers reportedly linked to yield and related components. For agronomic traits, significant variability was observed, ranging between the maximum for grains/panicle and the minimum for panicle length. The molecular diversity based grouping indicated that varieties from a common centre were genetically similar, with few exceptions. The trait-linked markers gave an average genetic dissimilarity of 0.45 as against that of 0.37 by random markers, along with an average polymorphic information constant value of 0.48 and 0.41 respectively. The correlation between the kinship matrix generated by trait-linked markers and the phenotype based distance matrix (0.29) was higher than that of random markers (0.19). This establishes the robustness of trait-linked markers over random markers in estimating genetic diversity of rice germplasm.