BackgroundGenetic diversity is the main source of variability in any crop improvement program. It serves as a reservoir for identifying superior alleles controlling key agronomic and quality traits through allele mining/association mapping. Association mapping based on LD (Linkage dis-equilibrium), non-random associations between causative loci and phenotype in natural population is highly useful in dissecting out genetic basis of complex traits. For any successful association mapping program, understanding the population structure and assessing the kinship relatedness is essential before making correlation between superior alleles and traits. The present study was aimed at evaluating the genetic variation and population structure in a collection of 192 rice germplasm lines including local landraces, improved varieties and exotic lines from diverse origin.ResultsA set of 192 diverse rice germplasm lines were genotyped using 61 genome wide SSR markers to assess the molecular genetic diversity and genetic relatedness. Genotyping of 192 rice lines using 61 SSRs produced a total of 205 alleles with the PIC value of 0.756. Population structure analysis using model based and distance based approaches revealed that the germplasm lines were grouped into two distinct subgroups. AMOVA analysis has explained that 14 % of variation was due to difference between with the remaining 86 % variation may be attributed by difference within groups.ConclusionsBased on these above analysis viz., population structure and genetic relatedness, a core collection of 150 rice germplasm lines were assembled as an association mapping panel for establishing marker trait associations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-015-0062-5) contains supplementary material, which is available to authorized users.

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212-RM302-RM8085-RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.

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Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.

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