Validation of Yield Component Traits Identified by Genome-Wide Association Mapping in a tropical japonica × tropical japonica Rice Biparental Mapping Population.

The Rice Diversity Panel 1 (RDP1) was developed for genome-wide association (GWA) studies to explore five rice ( L.) subpopulations (, , , , and ). The RDP1 was evaluated for over 30 traits, including agronomic, panicle architecture, seed, and disease traits and genotyped with 700,000 single nucleotide polymorphisms (SNPs). Most rice grown in the southern United States is and thus the diversity in this subpopulation is interesting to U.S. breeders. Among the RDP1 accessions, 'Estrela' and 'NSFTV199' are both phenotypically and genotypically diverse, thus making them excellent parents for a biparental mapping population. The objectives were to (i) ascertain the GWA QTLs from the RDP1 GWA studies that overlapped with the QTLs uncovered in an Estrela × NSFTV199 recombinant inbred line (RIL) population evaluated for 15 yield traits, and (ii) identify known or novel genes potentially controlling specific yield component traits. The 256 RILs were genotyped with 132 simple sequence repeat markers and 70 QTLs were found. Perl scripts were developed for automatic identification of the underlying candidate genes in the GWA QTL regions. Approximately 100 GWA QTLs overlapped with 41 Estrela × NSFTV199 QTL (RIL QTL) regions and 47 known genes were identified. Two seed trait RIL QTLs with overlapping GWA QTLs were not associated with a known gene. Segregating SNPs in the overlapping GWA QTLs for RIL QTLs with high values will be evaluated as potential DNA markers useful to breeding programs for the associated yield trait.

Genetic dissection of yield and its component traits using high-density composite map of wheat chromosome 3A: bridging gaps between QTLs and underlying genes.

Earlier we identified wheat (Triticum aestivum L.) chromosome 3A as a major determinant of grain yield and its component traits. In the present study, a high-density genetic linkage map of 81 chromosome 3A-specific markers was developed to increase the precision of previously identified yield component QTLs, and to map QTLs for biomass-related traits. Many of the previously identified QTLs for yield and its component traits were confirmed and were localized to narrower intervals. Four novel QTLs one each for shoot biomass (Xcfa2262-Xbcd366), total biomass (wPt2740-Xcfa2076), kernels/spike (KPS) (Xwmc664-Xbarc67), and Pseudocercosporella induced lodging (PsIL) were also detected. The major QTLs identified for grain yield (GY), KPS, grain volume weight (GVWT) and spikes per square meter (SPSM) respectively explained 23.2%, 24.2%, 20.5% and 20.2% of the phenotypic variation. Comparison of the genetic map with the integrated physical map allowed estimation of recombination frequency in the regions of interest and suggested that QTLs for grain yield detected in the marker intervals Xcdo549-Xbarc310 and Xpsp3047-Xbarc356 reside in the high-recombination regions, thus should be amenable to map-based cloning. On the other hand, QTLs for KPS and SPSM flanked by markers Xwmc664 and Xwmc489 mapped in the low-recombination region thus are not suitable for map-based cloning. Comparisons with the rice (Oryza sativa L.) genomic DNA sequence identified 11 candidate genes (CGs) for yield and yield related QTLs of which chromosomal location of two (CKX2 and GID2-like) was confirmed using wheat aneuploids. This study provides necessary information to perform high-resolution mapping for map-based cloning and for CG-based cloning of yield QTLs.

Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa.

Asian rice, Oryza sativa is a cultivated, inbreeding species that feeds over half of the world's population. Understanding the genetic basis of diverse physiological, developmental, and morphological traits provides the basis for improving yield, quality and sustainability of rice. Here we show the results of a genome-wide association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa collected from 82 countries that were systematically phenotyped for 34 traits. Using cross-population-based mapping strategies, we identified dozens of common variants influencing numerous complex traits. Significant heterogeneity was observed in the genetic architecture associated with subpopulation structure and response to environment. This work establishes an open-source translational research platform for genome-wide association studies in rice that directly links molecular variation in genes and metabolic pathways with the germplasm resources needed to accelerate varietal development and crop improvement.

Molecular mapping of QTLs for resistance to Gibberella ear rot, in corn, caused by Fusarium graminearum.

Gibberella ear rot, caused by the fungus Fusarium graminearum Schwabe, is a serious disease of corn (Zea mays) grown in northern climates. Infected corn is lower yielding and contains toxins that are dangerous to livestock and humans. Resistance to ear rot in corn is quantitative, specific to the mode of fungal entry (silk channels or kernel wounds), and highly influenced by the environment. Evaluations of ear rot resistance are complex and subjective; and they need to be repeated over several years. All of these factors have hampered attempts to develop F. graminearum resistant corn varieties. The aim of this study was to identify molecular markers linked to the genes for resistance to Gibberella ear rot. A recombinant inbred (RI) population, produced from a cross between a Gibberella ear rot resistant line (CO387) and a susceptible line (CG62), was field-inoculated and scored for Gibberella ear rot symptoms in the F4, F6, and F7 generations. The distributions of disease scores were continuous, indicating that resistance is probably conditioned by multiple loci. A molecular linkage map, based on segregation in the F5 RI population, contained 162 markers distributed over 10 linkage groups and had a total length of 2237 cM with an average distance between markers of 13.8 cM. Composite interval mapping identified 11 quantitative trait loci (QTLs) for Gibberella ear rot resistance following silk inoculation and 18 QTLs following kernel inoculation in 4 environments that accounted for 6.7%-35% of the total phenotypic variation. Only 2 QTLs (on linkage group 7) were detected in more than 1 test for silk resistance, and only 1 QTL (on linkage group 5) was detected in more than 1 test for kernel resistance, confirming the strong influence of the environment on these traits. The majority of the favorable alleles were derived from the resistant parent (CO387). The germplasm and markers for QTLs with significant phenotypic effects may be useful for marker-assisted selection to incorporate Gibberella ear rot resistance into commercial corn cultivars.