Elucidating the genetic control of rooting behavior under water-deficit stress is essential to breed climate-robust rice (Oryza sativa) cultivars. Using a diverse panel of 274 indica genotypes grown under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, mostly related to root morphology and anatomy, involving 45,000 root-scanning images and nearly 25,000 cross sections from the root-shoot junction. The phenotypic plasticity of these traits was quantified as the relative change in trait value under water-deficit compared with control conditions. We then carried out a genome-wide association analysis on these traits and their plasticity, using 45,608 high-quality single-nucleotide polymorphisms. One hundred four significant loci were detected for these traits under control conditions, 106 were detected under water-deficit stress, and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress), and 233 (plasticity) a priori candidate genes within linkage disequilibrium blocks for these loci. We identified key a priori candidate genes regulating root growth and development and relevant alleles that, upon validation, can help improve rice adaptation to water-deficit stress.
Climate change is increasing night temperature (NT) more than day temperature (DT) in rice-growing areas. Effects of combinations of NT (24−35°C) from microsporogenesis to anthesis at one or more DT (30 or 35°C) at anthesis on rice spikelet fertility, temperature within spikelets, flowering pattern, grain weight per panicle, amylose content and gel consistency were investigated in contrasting rice cultivars under controlled environments. Cultivars differed in spikelet fertility response to high NT, with higher fertility associated with cooler spikelets (P < 0.01). Flowering dynamics were altered by high NT and a novel high temperature tolerance complementary mechanism, shorter flower open duration in cv. N22, was identified. High NT reduced spikelet fertility, grain weight per panicle, amylose content and gel consistency, whereas high DT reduced only gel consistency. Night temperature >27°C was estimated to reduce grain weight. Generally, high NT was more damaging to grain weight and selected grain quality traits than high DT, with little or no interaction between them. The critical tolerance and escape traits identified, i.e. spikelet cooling, relatively high spikelet fertility, earlier start and peak time of anthesis and shorter spikelet anthesis duration can aid plant breeding programs targeting resilience in warmer climates.
Global warming causes night temperature (NT) to increase faster than day temperature in the tropics. According to crop growth models, respiration incurs a loss of 40-60% of photosynthate. The thermal sensitivity of night respiration (R(n)) will thus reduce biomass. Instantaneous and acclimated effects of NT on R(n) of leaves and seedlings of two rice cultivars having a variable level of carbohydrates, induced by exposure to different light intensity on the previous day, were investigated. Experiments were conducted in a greenhouse and growth chambers, with R(n) measured on the youngest fully expanded leaves or whole seedlings. Dry weight-based R(n) was 2.6-fold greater for seedlings than for leaves. Leaf R(n) was linearly related to starch (positive intercept) and soluble sugar concentration (zero intercept). Increased NT caused higher R(n) at a given carbohydrate concentration. The change of R(n) at NT increasing from 21 °C to 31 °C was 2.4-fold for the instantaneous response but 1.2- to 1.7-fold after acclimation. The maintenance component of R(n) (R(m)'), estimated by assimilate starvation, averaged 28% in seedlings and 34% in leaves, with no significant thermal effect on this ratio. The acclimated effect of increased NT on R(m)' across experiments was 1.5-fold for a 10 °C increase in NT. No cultivar differences were observed in R(n) or R(m)' responses. The results suggest that the commonly used Q10=2 rule overestimates thermal response of respiration, and R(n) largely depends on assimilate resources.
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