Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice

Comparing Yield Monitors with Weigh Wagons for On-farm Corn Hybrid Evaluation

For many years, on-farm yield evaluations of corn (Zea mays L.) hybrids were done with weigh wagons, handheld moisture testers, and measuring wheels. Today, most combines have continuous flow yield and moisture sensors. Published research results comparing the accuracy of combine-mounted sensor systems with that of weigh wagons are limited for on-farm corn hybrid evaluation. This study examined the accuracy of combine-mounted yield sensors with traditional weigh wagon methodology in on-farm corn hybrid strip trials. Data from combine-mounted sensors for plot weight, moisture percentage, and yield were compared with weigh wagon weight, handheld moisture testers, and calculated yield in six nonreplicated strip trials in 2012, 2013, and 2014 in east-central South Dakota. A total of 195 total entries were compared. Pearson correlation coefficients and linear regressions for weight, moisture percentage, and yield were calculated for each environment and for all environments combined. The Pearson correlation coefficients across all environments were 0.998 for weight of grain in pounds, 0.928 for grain moisture content percentage, and 0.983 for yield in bushels per acre corrected for moisture content. The probability of nonsignificance for weight, moisture percentage, and yield was P \u3c 0.0001. Linear regression models predicting combine-mounted sensor of sample weight, sample moisture, and yield with the traditional system were significant at P \u3c 0.0001 for all three measurements. Yield monitors can be used successfully for on-farm hybrid evaluations, replacing traditional methods that use weigh wagons, measuring wheels, and handheld moisture testers