High salinity is one of the major abiotic stresses limiting rice production. Melatonin has been implicated in the salt tolerance of rice. However, the molecular basis of melatonin-mediated salt tolerance in rice remains unclear. In the present study, we performed an integrated transcriptome and metabolome profiling of rice seedlings treated with salt, melatonin, or salt + melatonin. The application of exogenous melatonin increased the salt tolerance of rice plants by decreasing the sodium content to maintain Na⁺/K⁺ homeostasis, alleviating membrane lipid oxidation, and enhancing chlorophyll contention. A comparative transcriptome analysis revealed that complex molecular pathways contribute to melatonin-mediated salt tolerance. More specifically, the AP2/EREBP–HB–WRKY transcriptional cascade and phytohormone (e.g., auxin and abscisic acid) signaling pathways were activated by an exogenous melatonin treatment. On the basis of metabolome profiles, 64 metabolites, such as amino acids, organic acids, nucleotides, and secondary metabolites, were identified with increased abundances only in plants treated with salt + melatonin. Several of these metabolites including endogenous melatonin and its intermediates (5-hydroxy-L-tryptophan, N¹-acetyl-N²-formyl-5-methoxykynuramine), gallic acid, diosmetin, and cyanidin 3-O-galactoside had antioxidant functions, suggesting melatonin activates multiple antioxidant pathways to alleviate the detrimental effects of salt stress. Combined transcriptome and metabolome analyses revealed a few gene–metabolite networks related to various pathways, including linoleic acid metabolism and amino acid metabolism that are important for melatonin-mediated salt tolerance. The data presented herein may be useful for further elucidating the multiple regulatory roles of melatonin in plant responses to abiotic stresses.

Ferrous 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. A 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. Rice 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.

Gibberellin 2-oxidase (GA2ox) plays an important role in the GA catabolic pathway and the molecular function of the OsGA2ox genes in plant abiotic stress tolerance remains largely unknown. In this study, we functionally characterized the rice gibberellin 2-oxidase 8 (OsGA2ox8) gene. The OsGA2ox8 protein was localized in the nucleus, cell membrane, and cytoplasm, and was induced in response to various abiotic stresses and phytohormones. The overexpression of OsGA2ox8 significantly enhanced the osmotic stress tolerance of transgenic rice plants by increasing the number of osmotic regulators and antioxidants. OsGA2ox8 was differentially expressed in the shoots and roots to cope with osmotic stress. The plants overexpressing OsGA2ox8 showed reduced lengths of shoots and roots at the seedling stage, but no difference in plant height at the heading stage was observed, which may be due to the interaction of OsGA2ox8 and OsGA20ox1, implying a complex feedback regulation between GA biosynthesis and metabolism in rice. Importantly, OsGA2ox8 was able to indirectly regulate several genes associated with the anthocyanin and flavonoid biosynthetic pathway and the jasmonic acid (JA) and abscisic acid (ABA) biosynthetic pathway, and overexpression of OsGA2ox8 activated JA signal transduction by inhibiting the expression of jasmonate ZIM domain-containing proteins. These results provide a basis for a future understanding of the networks and respective phenotypic effects associated with OsGA2ox8.

Background: Chilling stress is a major factor limiting rice production. Rice genotypes differ greatly in their seedling chilling tolerance (CT), which is known to involve differential expression of large numbers of genes and proteins. To further understand the metabolomic responses of rice to chilling stress, profiles of the 106 primary metabolites of a CTjaponicavariety, Lijiangxintuanhegu (LTH) and a chilling sensitiveindicaline, IR29, were investigated under a time-series of chilling stress and non-stress control conditions at the seedling stage.Results: We identified 106 primary metabolites that were temporally and genotype-dependently regulated in LTH and IR29 under the time-series chilling stress and subsequent recovery. Three major groups of primary metabolites, amino acids (AAs), organic acids (OAs) and sugars, showed distinct change patterns in both genotypes in response to the chilling stress: a more general accumulation of most AAs, more dramatic decreased levels of most OAs, and greatly reduced levels for most sugars at early time points of stress but increased levels of specific sugars at the later time points of stress. Compared to IR29, LTH had more metabolites showing chilling induced changes, greater levels of these metabolomic changes and a greater ability to recover after stress, implying that LTH used a positive energy-saving strategy against chilling stress. During subsequent recovery, more metabolites were significantly and exclusively up-regulated in LTH, indicating their positive role in chilling tolerance. A comparative analysis of these metabolites data and differentially expressed genes data allowed identification of 7 AAs and related genes that were both chilling responsive and contributed greatly to the CT of LTH.Conclusions: The metabolomic responses of rice to chilling stress at the seedling stage were dynamic and involved large numbers of the metabolites. The chilling induced changes of three major groups of metabolites, AAs, OAs and sugars, in rice were well coordinated. The high level seedling CT of LTH was apparently attributed to its increased levels of most AAs and reduced energy consumption that resulted in increased glycolysis and strong resilience on recovery. The results of this study extend our understanding of molecular mechanisms of chilling stress tolerance in rice.

A 1D/2D genome-wide association study strategy was adopted to investigate the genetic systems underlying the reciprocal adaptation of rice (Oryza sativa) and its bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo) using the whole-genome sequencing and large-scale phenotyping data of 701 rice accessions and 23 diverse Xoo strains. Forty-seven Xoo virulence-related genes and 318 rice quantitative resistance genes (QR-genes) mainly located in 41 genomic regions, and genome-wide interactions between the detected virulence-related genes and QR genes were identified, including well-known resistance genes/virulence genes plus many previously uncharacterized ones. The relationship between rice and Xoo was characterized by strong differentiation among Xoo races corresponding to the subspecific differentiation of rice, by strong shifts toward increased resistance/virulence of rice/Xoo populations and by rich genetic diversity at the detected rice QR-genes and Xoo virulence genes, and by genome-wide interactions between many rice QR-genes and Xoo virulence genes in a multiple-to-multiple manner, presumably resulting either from direct protein–protein interactions or from genetic epistasis. The observed complex genetic interaction system between rice and Xoo likely exists in other crop–pathogen systems that would maintain high levels of diversity at their QR-loci/virulence-loci, resulting in dynamic coevolutionary consequences during their reciprocal adaptation.