The asymmetric increase in average nighttime temperatures relative to increase in average daytime temperatures due to climate change is decreasing grain yield and quality in rice. Therefore, a better genome-level understanding of the impact of higher night temperature stress on the weight of individual grains is essential for future development of more resilient rice. We investigated the utility of metabolites obtained from grains to classify high night temperature (HNT) conditions of genotypes, and metabolites and single-nucleotide polymorphisms (SNPs) to predict grain length, width, and perimeter phenotypes using a rice diversity panel. We found that the metabolic profiles of rice genotypes alone could be used to classify control and HNT conditions with high accuracy using random forest or extreme gradient boosting. Best linear unbiased prediction and BayesC showed greater metabolic prediction performance than machine learning models for grain-size phenotypes. Metabolic prediction was most effective for grain width, resulting in the highest prediction performance. Genomic prediction performed better than metabolic prediction. Integrating metabolites and genomics simultaneously in a prediction model slightly improved prediction performance. We did not observe a difference in prediction between the control and HNT conditions. Several metabolites were identified as auxiliary phenotypes that could be used to enhance the multi-trait genomic prediction of grain-size phenotypes. Our results showed that, in addition to SNPs, metabolites collected from grains offer rich information to perform predictive analyses, including classification modeling of HNT responses and regression modeling of grain-size-related phenotypes in rice.
A higher minimum (night‐time) temperature is considered a greater limiting factor for reduced rice yield than a similar increase in maximum (daytime) temperature. While the physiological impact of high night temperature (HNT) has been studied, the genetic and molecular basis of HNT stress response remains unexplored. We examined the phenotypic variation for mature grain size (length and width) in a diverse set of rice accessions under HNT stress. Genome‐wide association analysis identified several HNT‐specific loci regulating grain size as well as loci that are common for optimal and HNT stress conditions. A novel locus contributing to grain width under HNT conditions colocalized with We present evidence to support the role of
- Award ID(s):
- 1736192
- PAR ID:
- 10450765
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- New Phytologist
- Volume:
- 229
- Issue:
- 1
- ISSN:
- 0028-646X
- Page Range / eLocation ID:
- p. 335-350
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Heat stress occurring during rice (
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