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For CMLM, the relatedness matrix, measured as the genetic similarity between individuals and IBS (identical by state) values, was used to estimate random effects. The kinship matrix (K) estimated from SNP genotyping data was used jointly with population structure (Q value) to improve statistical power of association. For fixed effects, PCs through PCA analysis and Q-matrix through STRUCTURE were used as covariates for association analysis. Scree plot of PCA analysis suggested first three components as most informative, which were used as covariate matrix in K + P (kinship + PCA) model. For K + Q (kinship + Q-matrix) model, a file generated through run K = 3 in STRUCTURE program was used as covariate matrix. The critical P-values for assessing the significance of SNPs were calculated based on a false discovery www.selleckchem.com/products/Lapatinib-Ditosylate.html rate (FDR) separately for each trait,50 which was found to be highly stringent. An FDR cut-off of 0.05 was used for determining significance. 3. Results S6 Kinase 3.1. Success of genotyping array The array designed with 5,246 SNPs in our study was successfully used to genotype all the 220 rice accessions. The data generated through Illumina Infinium platform were loaded in Genome Studio software where, after cluster refinement with optimum GenTrain (>0.7) and GenCall score (>0.3), 4,929 polymorphic SNPs (?94%) were identified. After excluding the SNPs with MAF Selleck LY294002 most of the genetic variation (66%) in the accessions was explained by first two PCs. Based on 4,191 SNPs, the first PC explained almost 52% of genetic variation, whereas PC II explained 14%. The scree plot generated through GAPIT recommended the first three components as informative, where descent changes gradually (Fig.?3A). When we plotted the first two components against each other, three subpopulations were identified. A total of 130 accessions were clustered as a single large subpopulation (I) (Fig.?3B). For inferring the most likely number of populations among 220 accessions in STRUCTURE, the transformation method51 was used, and similar to PCA, three subpopulations were identified (Fig.?3C). Forty-four per cent of the accessions (97/220) did not show any admixture, 46% accessions (101/220) showed up to 20% admixture, while the remaining 10% (22/220) were found to be highly admixed. Figure?3. Population structure of current association panel which consisted mostly of the indica accessions. (A) Scree plot from GAPIT showing the selection of PCs for association study.