Abstract Elevated nighttime temperatures resulting from climate change significantly impact the rice crop worldwide. The rice ( Oryza sativa L.) plant is highly sensitive to high nighttime temperature (HNT) during grain-filling (reproductive stage). HNT stress negatively affects grain quality traits and has a major impact on the value of the harvested rice crop. In addition, along with grain dimensions determining rice grain market classes, the grain appearance and quality traits determine the rice grain market value. During the last few years, there has been a major concern for rice growers and the rice industry over the prevalence of rice grains opacity and the reduction of grain dimensions affected by HNT stress. Hence, the improvement of heat-stress tolerance to maintain grain quality of the rice crop under HNT stress will bolster future rice value in the market. In this study, 185 F 12 - recombinant inbred lines (RILs) derived from two US rice cultivars, Cypress (HNT-tolerant) and LaGrue (HNT-sensitive) were screened for the grain quality traits grain length (GL), grain width (GW), and percent chalkiness (%chalk) under control and HNT stress conditions and evaluated to identify the genomic regions associated with the grain quality traits. In total, there were 15 QTLs identified; 6 QTLs represented under control condition explaining 3.33% to 8.27% of the phenotypic variation, with additive effects ranging from − 0.99 to 0.0267 on six chromosomes and 9 QTLs represented under HNT stress elucidating 6.39 to 51.53% of the phenotypic variation, with additive effects ranging from − 8.8 to 0.028 on nine chromosomes for GL, GW, and % chalk. These 15 QTLs were further characterized and scanned for natural genetic variation in a japonica diversity panel (JDP) to identify candidate genes for GL, GW, and %chalk. We found 6160 high impact single nucleotide polymorphisms (SNPs) characterized as such depending on their type, region, functional class, position, and proximity to the gene and/or gene features, and 149 differentially expressed genes (DEGs) in the 51 Mbp genomic region comprising of the 15 QTLs. Out of which, 11 potential candidate genes showed high impact SNP associations. Therefore, the analysis of the mapped QTLs and their genetic dissection in the US grown Japonica rice genotypes at genomic and transcriptomic levels provide deep insights into genetic variation beneficial to rice breeders and geneticists for understanding the mechanisms related to grain quality under heat stress in rice.
more »
« less
Evaluating metabolic and genomic data for predicting grain traits under high night temperature stress in rice
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.
more » « less- Award ID(s):
- 1736192
- PAR ID:
- 10506425
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- G3: Genes, Genomes, Genetics
- Volume:
- 13
- Issue:
- 5
- ISSN:
- 2160-1836
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Summary 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
Fie1 , a component of the FIS‐PRC2 complex. Our results suggest that the allelic difference controlling grain width under HNT is a result of differential transcript‐level response ofFie1 in grains developing under HNT stress.We present evidence to support the role of
Fie1 in grain size regulation by testing overexpression (OE) and knockout mutants under heat stress. The OE mutants were either unaltered or had a positive impact on mature grain size under HNT, while the knockouts exhibited significant grain size reduction under these conditions. -
more » « less
Abstract Background Wheat grain development in the first few days after pollination determines the number of endosperm cells that influence grain yield potential and is susceptible to various environmental conditions, including high night temperatures (HNTs). Flag leaves and seed-associated bracts (glumes, awn, palea, and lemma) provide nutrients to the developing seed. However, the specific metabolic roles of these tissues are uncertain, especially their dynamics at different developmental stages and the time in a day. Tissue- and time-dependent metabolite profiling may hint at the metabolic roles of tissues and the mechanisms of how HNTs affect daytime metabolic status in early grain development.
Results The metabolite profiles of flag leaf, bract, seed (embryo and endosperm), and entire spike were analyzed at 12:00 (day) and 23:00 (night) on 2, 4, and 6 days after fertilization under control and HNT conditions. The metabolite levels in flag leaves and bracts showed day/night oscillations, while their behaviors were distinct between the tissues. Some metabolites, such as sucrose, cellobiose, and succinic acid, showed contrasting oscillations in the two photosynthetic tissues. In contrast, seed metabolite levels differed due to the days after fertilization rather than the time in a day. The seed metabolite profile altered earlier in the HNT than in the control condition, likely associated with accelerated grain development caused by HNT. HNT also disrupted the day/night oscillation of sugar accumulation in flag leaves and bracts.
Conclusions These results highlight distinct metabolic roles of flag leaves and bracts during wheat early seed development. The seed metabolite levels are related to the developmental stages. The early metabolic events in the seeds and the disruption of the day/night metabolic cycle in photosynthetic tissues may partly explain the adverse effects of HNT on grain yield.
-
more » « less
Abstract Rapid increases in minimum night temperature than in maximum day temperature is predicted to continue, posing significant challenges to crop productivity. Rice and wheat are two major staples that are sensitive to high night‐temperature (HNT) stress. This review aims to (i) systematically compare the grain yield responses of rice and wheat exposed to HNT stress across scales, and (ii) understand the physiological and biochemical responses that affect grain yield and quality. To achieve this, we combined a synthesis of current literature on HNT effects on rice and wheat with information from a series of independent experiments we conducted across scales, using a common set of genetic materials to avoid confounding our findings with differences in genetic background. In addition, we explored HNT‐induced alterations in physiological mechanisms including carbon balance, source–sink metabolite changes and reactive oxygen species. Impacts of HNT on grain developmental dynamics focused on grain‐filling duration, post‐flowering senescence, changes in grain starch and protein composition, starch metabolism enzymes and chalk formation in rice grains are summarized. Finally, we highlight the need for high‐throughput field‐based phenotyping facilities for improved assessment of large‐diversity panels and mapping populations to aid breeding for increased resilience to HNT in crops.
-
more » « less
Abstract High night air temperature (HNT) stress negatively impacts both rice (
Oryza sativa L) yield and grain quality and has been extensively investigated because of the significant yield loss observed (10%) for every increase in air temperature (1°C). Most of the rice HNT studies have been conducted under greenhouse conditions, with limited information on field‐level responses for the major rice sub‐populations. This is due to a lack of a field‐based phenotyping infrastructure that can accommodate a diverse set of accessions representing the wider germplasm and impose growth stage‐specific stress. In this study, we built six high‐tunnel greenhouses and screened 310 rice accessions from the Rice Diversity Panel 1 (RDP1) and 10 commercial hybrid cultivars in a replicated design. Each greenhouse had heating and a cyber–physical system that sensed ambient air temperature and automatically increased night air temperature to about 4°C relative to ambient temperature in the field for two cropping seasons. The system successfully imposed HNT stress of 4.0 and 3.94°C as recorded by Raspberry Pi sensors for 2 weeks in 2019 and 2020, respectively. HOBO sensors (Onset Computer Corporation) recorded a 2.9 and 2.07°C temperature differential of ambient air between control and heated greenhouses in 2019 and 2020, respectively. These greenhouses were able to withstand constant flooding, heavy rains, strong winds (140 mph), and thunderstorms. Selected US rice cultivars showed an average of 24% and 15% yield reduction under HNT during the 2019 and 2020 cropping seasons, respectively. Our study highlights the potential of this computer‐based infrastructure for accurate implementation of HNT or other abiotic stresses under field‐growing conditions.
