Identification and validation of functional markers in a global rice collection by association mapping

Abstract

Recent results indicate that marker-assisted selection is an effective approach to reduce the cost and to improve the efficacy and accuracy of selection in plant breeding. This study was conducted to identify and validate molecular markers linked to important breeding traits by association mapping. The association was evaluated between 81 molecular markers (STS, SSR, Indel, CAPS, and PCR-based SNP) and 15 morphological traits in a global panel of 100 rice (Oryza sativa) accessions. The population structure analysis identified three main subpopulations. Obvious kinship relationships were also detected between the rice accessions. Association analysis was performed based on the mixed linear model by considering population structure and family relatedness. In addition, the false discovery rate method was used to correct the multiple testing. A total of 47 marker-trait associations were identified, including 22 markers for 14 traits. Among all, the polymorphism at the loci DDR-GL was highly associated with grain characters (grain length, grain width, and length/width ratio). In addition, marker RM3148 was responsible for five important traits simultaneously. Results demonstrated that such informative markers can be very useful for rice breeding programs using marker-assisted selection. Moreover, the diverse populations of rice accessions are a valuable resource for association mapping of morphological traits.

Identification of functional pathways associated with the conditional ablation of serum response factor in Dstncorn1 mice

“…The linear models for microarray data (limma) version 3.28.17 (11) in R-software package () were applied to identify the DEGs among the three mouse groups. The log 2 -fold change (log 2 FC) and the false discovery rate (FDR) (12) were calculated. Genes with log 2 FC>1 and an FDR <0.05 were considered to be DEGs and were used for subsequent analysis.…”