Genetic effect of a new allele for the flowering time locus Ghd7 in rice

Modelling and Using Spatial Effects in Nationwide Historical Data Improve Genomic Prediction of Rice Heading Date in Japan

Genomic prediction is a promising strategy for enhancing crop breeding efficiency. Historical data of breeding and cultivation tests from geographically wide regions presumably contain rich information for training genomic prediction models. Therefore, it is essential to explore methodologies to effectively handle such data. To improve the prediction accuracy of models using historical data, we incorporated a spatial model to account for spatial structures among field stations, in addition to conventional genomic prediction models. Targeting the rice heading date from historical data across Japan, we first constructed conventional genomic prediction models using genomic and/or meteorological elements as predictors. Next, we obtain the residual terms. Assuming that the residual terms were partly explained by the spatial effects assigned to each field station, a spatial model was applied to the residual terms and the spatial effects were calculated. Our genomic prediction models performed best when the genome, meteorological elements, and genome-meteorology interactions were included (model 3), and they performed second best when the genome and meteorological elements were included (model 2). For these genomic prediction models, residual terms were spatially biased and corrected for spatial effects. For the best model (model 3), the root mean squared errors (RMSE) of genomic prediction combined with spatial effects were approximately 3.6 days under tenfold cross-validation and approximately 5.1 days under leave-one-line-out cross-validation. The inclusion of the spatial effects improved the RMSEs by approximately 15% and 9% for the former and latter, respectively. Lines with highly improved predictions of the spatial effects were developed, mainly in the northern Tohoku region. The spatial effects were heterogeneous and regional patterns were detected. These findings imply that spatial effects are important not only for improving prediction performance but also for dissecting the model itself to identify the factors contributing to model improvement.

Allelic combinations of Hd1, Hd16, and Ghd7 exhibit pleiotropic effects on agronomic traits in rice

Heading date is a critical agronomic trait that significantly affects grain yield and quality in rice. As early heading is typically associated with reduced yield due to shorter growth duration, it is essential to harness optimum heading date genes and their allelic combinations to promote heading while minimizing yield penalties. In this study, we identified quantitative trait loci (QTLs) for heading date and other major agronomic traits in a recombinant inbred line (RIL) population derived from a cross between Koshihikari and Baegilmi. Analyses on 3 major QTLs for heading date and their underlying genes (Hd1, Hd16, and Ghd7) revealed their pleiotropic effects on culm length, panicle length, and head rice percentage. Additionally, Ghd7 exhibited pleiotropic effects on panicle number and grain size. Among 8 different types of allelic combinations of the 3 heading date genes, RILs carrying a single nonfunctional hd16 or ghd7 under the functional background of the other 2 genes (Hd1hd16Ghd7 and Hd1Hd16ghd7) showed potential for maintaining yield and quality-related traits while accelerating heading. These results provide valuable insights for fine-tuning heading dates in rice breeding programs.

Artificial selection in the expansion of rice cultivation

Gene distributions and population genomics suggest artificial selection of ghd7 osprr37, for extremely early heading date of rice, in the Tohoku region of Japan. The ranges of cultivated crops expanded into various environmental conditions around the world after their domestication. Hokkaido, Japan, lies at the northern limit of cultivation of rice, which originated in the tropics. Novel genotypes for extremely early heading date in Hokkaido are controlled by loss-of-function of both Grain number, plant height and heading date 7 (Ghd7) and Oryza sativa Pseudo-Response Regulator 37 (OsPRR37). We traced genotypes for extremely early heading date and analyzed the phylogeny of rice varieties grown historically in Japan. The mutations in Ghd7 and OsPRR37 had distinct local distributions. Population genomics revealed that varieties collected from the Tohoku region of northern Japan formed three clusters. Mutant alleles of Ghd7 and OsPRR37 appear to have allowed rice cultivation to spread into Hokkaido. Our results show that the mutations of two genes might be occurred in the process of artificial selection during early rice cultivation in the Tohoku region.

Characterization of QTLs and Candidate Genes for Days to Heading in Rice Recombinant Inbred Lines

Understanding the gene mechanisms controlling days to heading (DH) is important in rice breeding for adaption in the target environment. Using a recombinant inbred line population derived from the cross between two japonica rice cultivars, Koshihikari and Baegilmi, we identified three consistent quantitative trait loci (QTLs) for DH for two years, qDH3, qDH6, and qDH7 on chromosomes 3, 6, and 7, respectively. While Baegilmi contributed the allele for early heading at qDH6 and qDH7 with the additive effect of five days each, Koshihikari contributed the allele for early heading at qDH3 with the additive effect of three days. Notably, pyramiding two or more alleles for early heading at these QTLs accelerated heading effectively. Sequencing of Hd16, Hd1, and Ghd7, the previously known heading date genes underlying qDH3, qDH6, and qDH7, respectively, revealed that Baegilmi and Koshihikari carry different alleles at the three genes. Molecular markers were developed to screen the allelic compositions of the three genes among 295 Korean commercial rice cultivars. The results showed that few cultivars carry alleles for early heading at the three genes, highlighting that DH can be further accelerated and fine-tuned in breeding programs by combining the desirable alleles of Hd16, Hd1, and Ghd7.