Metabolic Dynamics of Developing Rice Seeds Under High Night-Time Temperature Stress

Abstract

High temperature stress during rice reproductive development results in yield losses. Reduced grain yield and grain quality has been associated with high temperature stress, and specifically with high night-time temperatures (HNT). Characterizing the impact of HNT on the phenotypic and metabolic status of developing rice seeds can provide insights into the mechanisms involved in yield and quality decline. Here, we examined the impact of warmer nights on the morphology and metabolome during early seed development in six diverse rice accessions. Seed size was sensitive to HNT in four of the six genotypes, while seed fertility and seed weight were unaffected. We observed genotypic differences for negative impact of HNT on grain quality. This was evident from the chalky grain appearance due to impaired packaging of starch granules. Metabolite profiles during early seed development (3 and 4 days after fertilization; DAF) were distinct from the early grain filling stages (7 and 10 DAF) under optimal conditions. We observed that accumulation of sugars (sucrose, fructose, and glucose) peaked at 7 DAF suggesting a major flux of carbon into glycolysis, tricarboxylic acid cycle, and starch biosynthesis during grain filling. Next, we determined hyper (HNT > control) and hypo (HNT < control) abundant metabolites and found 19 of the 57 metabolites to differ significantly between HNT and control treatments. The most prominent changes were exhibited by differential abundance of sugar and sugar alcohols under HNT, which could be linked to a protective mechanism against the HNT damage. Overall, our results indicate that combining metabolic profiles of developing grains with yield and quality parameters under high night temperature stress could provide insight for exploration of natural variation for HNT tolerance in the rice germplasm.

Divergent phenotypic response of rice accessions to transient heat stress during early seed development

“…Extensive work has been carried out regarding the impact of HS on different phases of plant development (Bokszczanin & Fragkostefanakis, ; Cheng, Sakai, Yagi, & Hasegawa, ; Hasanuzzaman, Nahar, Alam, Roychowdhury, & Fujita, ; Jagadish et al, ; Prasad, Bheemanahalli, & Jagadish, ). Both reproductive development and grain filling phases in rice have been documented as sensitive to environmental perturbations (Prasad et al, ; Jagadish et al, ; Prasad et al, ; Jagadish et al, ; Coast, Ellis, Murdoch, Quiñones, & Jagadish, ; Arshad et al, ; Ali et al, ; Dhatt et al, ). However, genotypic variation in rice germplasm for heat stress responses during early seed development remains largely unexplored.…”

MADS78 and MADS79 Are Essential Regulators of Early Seed Development in Rice

“…For SEM, mature rice grains were transversely cut, placed on conductive tape attached to aluminum SEM stubs, and vacuum dried in a sample drying oven at 40°C for 1 week. Afterward, samples were sputter coated with chromium using a Denton Vacuum Desk V sputter coater and imaged with the Hitachi-S4700 Field-Emission SEM device at 503, 2003, and 2,0003 (Dhatt et al, 2019). Three independent biological replicates were used for the observations.…”

Enhanced N‐metabolites, ABA and IAA‐conjugate in anthers instigate heat sensitivity in spring wheat

“…Dried metabolite pellets were subjected to derivatization by methoxyamine hydrochloride (Sigma) and N ‐Methyl‐ N ‐(trimethylsilyl) trifluoroacetamide (Sigma) as described in Lisec et al (). Metabolite profiling was performed by 5977A GC/MSD (Agilent) with parameters following Dhatt et al (). Peaks in the reference sample, which is the mixture of equal volume of all samples, were annotated to metabolites by MassHunter Unknown software (Agilent) to generate batch specific library.…”

“…Peaks in the reference sample, which is the mixture of equal volume of all samples, were annotated to metabolites by MassHunter Unknown software (Agilent) to generate batch specific library. Peak area of representative ion was quantified by MassHunter Quantitation software (Agilent) using the batch specific library (Dhatt et al ). The parameters used for peak annotation are shown in Tables S1 and S2, following the recommended reporting format (Fernie et al ).…”