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BackgroundFerrous iron (Fe) and zinc (Zn) at high concentration in the soil cause heavy metal toxicity and greatly affect rice yield and quality. To improve rice production, understanding the genetic and molecular resistance mechanisms to excess Fe and Zn in rice is essential. Genome-wide association study (GWAS) is an effective way to identify loci and favorable alleles governing Fe and Zn toxicty as well as dissect the genetic relationship between them in a genetically diverse population.ResultsA total of 29 and 31 putative QTL affecting shoot height (SH), root length (RL), shoot fresh weight (SFW), shoot dry weight (SDW), root dry weight (RDW), shoot water content (SWC) and shoot ion concentrations (SFe or SZn) were identified at seedling stage in Fe and Zn experiments, respectively. Five toxicity tolerance QTL (qSdw3a, qSdw3b, qSdw12 and qSFe5 / qSZn5) were detected in the same genomic regions under the two stress conditions and 22 candidate genes for 10 important QTL regions were also determined by haplotype analyses.ConclusionRice plants share partial genetic overlaps of Fe and Zn toxicity tolerance at seedling stage. Candidate genes putatively affecting Fe and Zn toxicity tolerance identified in this study provide valuable information for future functional characterization and improvement of rice tolerance to Fe and Zn toxicity by marker-assisted selection or designed QTL pyramiding.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4221-5) contains supplementary material, which is available to authorized users.

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Low night and high day temperatures during sensitive reproductive stages cause spikelet sterility in rice. Phenotyping of tolerance traits in the field is difficult because of temporal interactions with phenology and organ temperature differing from ambient. Physiological models can be used to separate these effects. A 203-accession indica rice diversity panel was phenotyped for sterility in ten environments in Senegal and Madagascar and climate data were recorded. Here we report on sterility responses while a companion study reported on phenology. The objectives were to improve the RIDEV model of rice thermal sterility, to estimate response traits by fitting model parameters, and to link the response traits to genomic regions through genome-wide association studies (GWAS). RIDEV captured 64% of variation of sterility when cold acclimation during vegetative stage was simulated, but only 38% when it was not. The RIDEV parameters gave more and stronger quantitative trait loci (QTLs) than index variables derived more directly from observation. The 15 QTLs identified at P<1 × 10-5 (33 at P<1 × 10-4) were related to sterility effects of heat, cold, cold acclimation, or unexplained causes (baseline sterility). Nine annotated genes were found on average within the 50% linkage disequilibrium (LD) region. Among them, one to five plausible candidate genes per QTL were identified based on known expression profiles (organ, stage, stress factors) and function. Meiosis-, development- and flowering-related genes were frequent, as well a stress signaling kinases and transcription factors. Putative epigenetic factors such as DNA methylases or histone-related genes were frequent in cold-acclimation QTLs, and positive-effect alleles were frequent in cold-tolerant highland rice from Madagascar. The results indicate that epigenetic control of acclimation may be important in indica rice genotypes adapted to cool environments.

Phenology and time of flowering are crucial determinants of rice adaptation to climate variation. A previous study characterized flowering responses of 203 diverse indica rices (the ORYTAGE panel) to ten environments in Senegal (six sowing dates) and Madagascar (two years and two altitudes) under irrigation in the field. This study used the physiological phenology model RIDEV V2 to heuristically estimate component traits of flowering such as cardinal temperatures (base temperature (Tbase) and optimum temperature), basic vegetative phase, photoperiod sensitivity and cold acclimation, and to conduct a genome-wide association study for these traits using 16 232 anonymous single-nucleotide polymorphism (SNP) markers. The RIDEV model after genotypic parameter optimization explained 96% of variation in time to flowering for Senegal alone and 91% for Senegal and Madagascar combined. The latter was improved to 94% by including an acclimation parameter reducing Tbase when the crop experienced low temperatures during early vegetative development. Eighteen significant (P<1.0 × 10-5) quantitative trait loci (QTLs) were identified, namely ten for RIDEV parameters and eight for climatic index variables (difference in time to flowering between key environments). Co-localization of QTLs for different traits were rare. RIDEV parameters gave QTLs that were mostly more significant and distinct from QTLs for index variables. Candidate genes were investigated within the estimated 50% linkage disequilibrium regions of 39 kB. In addition to several known flowering network genes, they included genes related to thermal stress adaptation and epigenetic control mechanisms. The peak SNP for a QTL for the crop parameter Tbase (P=2.0 × 10-7) was located within HD3a, a florigen that was recently identified as implicated in flowering under cool conditions.