Two rice genotypes, wild type MangShuiDao (MSD) and its mutant osseh1, were selected for use in this study. MSD is a cold tolerant temperate Japonica landrace from Yangtze River region, China. The mutant osseh1 lines were generated by CRISPR/Cas9 previously. The mutation sites in the osseh1 knock-out lines were showed in Supplementary Figure 1 .

Seeds were surface sterilized with 5% (w/v) sodium hypochlorite for 3 min and then soaked in the water at 28°C for 5 days in the dark. The germinated seeds were transferred to 96-well plates and then grown hydroponically in the solution of International Rice Research Institute (IRRI). The 96-well plates were placed in a plant growth chamber (14h-light/10h-dark conditions) with temperatures of 28°C and 25°C for the light and dark conditions, respectively.

For cold stress at the seedling stage, the seedlings of wild type and osseh1 mutants were used to test the cold tolerance. The seedlings were transferred to a growth chamber at 4°C for 7 days after knowing which plants were able to recover at 28°C for 7 days, and the survival rates were calculated. Cold treatment was treated at the 16^th days of rice seedling growth. The sampling time of physiological indicators was 0 h and 48 h after cold stress.

For the germination assay, sterilized seeds were put in the 0 µM, 1 µM, 10 µM, 100 µM or 150 µM ABA. The germination rates were assessed at 0, 36, 48, 60, 72, 84, 96 h. Three replicate assays were conducted with at least 200 seeds each time.

The soluble sugar content was measurement was performed according to the previous study (Yoshida et al., 1971) with some modification. Briefly, leaf sample (0.2 g fresh weight) was fixed in 4 ml 80% ethanol. After centrifugation at 5000 × g for 10 min, added 2.5 ml of anthrone to the supernatant (0.5 ml) and kept in a water bath at 40°C for 30 min. After cooling, measure the optical density of the mixture at 625 nm.

The proline content was determined according to the previous study (Bates et al., 1973) with some modification. Leaf samples (0.5 g) were boiled in 10ml 3% sulfosalicylic acid and then the cooling homogenate was centrifuged at 3000×g for 10 min. The supernatant (1 ml) was treated with 1 ml acetic acid and 2 ml 2.5% ninhydrin, boiled for 1 h, and absorbance was determined at 520 nm.

The ROS content was determined by plant ROS enzyme-linked immunity kit (Jiangsu Meimian Industrial Co., Ltd., Yancheng, China) according to the manufacturer’s protocol. Double antibody sandwich method was used in the kit to determine the content of plant ROS in the leaves sample. Purified plant ROS antibodies were placed in the microporous plate to form solid-phase antibodies. Use purified ROS antibody to coat the microplate to prepare solid phase antibody. Add ROS to the microplate coated with monoclonal antibody in turn, and then combine with HRP (horse radish peroxidase) labeled ROS antibody to form antibody antigen enzyme labeled antibody complex. After thorough washing, add substrate TMB (3, 3′,5,5′-Tetramethylbenzidine) for color development. TMB is catalyzed by HRP enzymes to turn blue and converted to the final yellow color by acid. The shade of color was positively correlated with ROS in the sample. The absorbance (OD) was measured at 450nm and the concentration of ROS was calculated by standard curve.

Fresh leaves (about 0.2 g) were ground in cold 2 mL 50 mM PBS solution. Centrifuged homogenate at 8000 r/min for 20 min at 4°C. The supernatant was kept measure the antioxidant enzyme activity. For SOD activity measurement, 50 μL supernatant was added to 5 mL nitroblue tetrazolium (NBT) reaction buffer and then the reaction mixture was kept under 4000 lux lights for 20 min and analyzed at 560 nm using a spectrophotometer (Polle et al., 1989). For POD activity measurement, 50 μL supernatant was added to 5 mL guaiacol reaction buffer and analyzed at 470 nm using a spectrophotometer (Fecht-Christoffers et al., 2006). For CAT activity measurement, 50 μL supernatant was added to 5 mL reaction buffer in the presence of H₂O₂ and analyzed at 240 nm using a spectrophotometer (Verma and Dubey, 2003). For APX activity measurement, 50 μL supernatant was added to 5 mL ascorbate reaction buffer and analyzed at 290 nm using a spectrophotometer (Vanacker et al., 1998). All treatments had three biological and three technical replicates.

Metabolomic profiling was performed using a widely targeted metabolome technology with three independent biological replicates at MetWare Biotechnology Co., Ltd. (Wuhan, China) (Li et al., 2022a). Briefly, the leaves samples were ground using the MM 400 Mixer Mill (Retsch Technology, Haan, Germany) with a zirconia bead for 1.5 min. Then, 100 mg freeze-dried powder was weighted for metabolites extraction with 500 μL of 80% aqueous methanol containing 0.1 mg/L lidocaine at 4°C for 8h. Following centrifugation at 10000g for 15 min, the supernatant was filtered via a syringe filter (SCAA-104, 0.22-μm pore size; ANPEL, Shanghai, China) before LC-MS/MS analysis. Quality Control (QC) samples were mixed with all samples to test the reproducibility of the entire experiment. Differentially accumulated metabolites (DAMs) were identified using the t-test < 0.05 and variable importance in projection (VIP) ≥ 1.

RNA-Seq sequencing and analyses were performed by Gene Denovo Biotechnology Co., (Guangzhou, China) as described previously (Li et al., 2022b; Yan et al., 2022). Briefly, total RNA was extracted from the four-leaf stage seedlings using the Trizol Reagent Kit (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol, with three biological replicates each containing 50 plants. RNA quality and integrity were assessed on the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA). Gene Denovo Biotechnology Co. (Guangzhou, China) performed RNA-Seq sequencing and analyses using the Illumina HiSeq2500 platform. Differentially expressed genes (DEGs) between the osseh1 mutants and the wild type were identified with false discovery rate (FDR) < 0.05 and absolute fold change ≥ 2. DEGs were then analyzed by Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway.

Total RNA was extracted from the rice seedling leaves using the TransZol Up Plus RNA kit (TransGen Biotech, China) according to the manufacturer’s protocol. RNA quality and concentration were quantified using a NanoDrop 8000 spectrophotometer (Thermo Fisher Scientific). Total RNA was reverse-transcribed to cDNA using One-Step gDNA Removal and cDNA Synthesis SuperMix (TransGen Biotech, China). RT-qPCR was carried out using the PerfectStart Green qPCR SuperMix (TransGen Biotech, China) protocol and the QuantStudio 3 System (Applied Biosystems, USA). Rice ACTIN1 gene was used as the internal control. Data were analyzed following the relative quantification method (Livak and Schmittgen, 2001). Primer used for RT-qPCR are listed in Supplementary Table 9 . The experiments were repeated at least three times.

Hormone treatments were conducted by spraying the leaves of 12-day old seedlings with 1 μM, 10 μM, 100 μM and 150 μM ABA containing 0.1% (v/v) Tween 20 as the surfactant. The seedlings were sprayed with the mixture of different concentration of ABA at 9 a.m. for 3 days and then transferred to a growth chamber at 4°C for 2 days. ABA (Sigma) was dissolved in methanol. The identical volume of the blank methanol containing 0.1% (v/v) Tween20 was used as a mock treatment.

The ABA content was determined by plant ABA enzyme-linked immunity kit (Jiangsu Meimian Industrial Co., Ltd., Yancheng, China) according to the manufacturer’s protocol. Double antibody sandwich method was used in the kit to determine the content of plant ABA in the leaves sample.

A two-tailed Student’s t-test was used to compare the difference of data from two groups, and analysis of variance (ANOVA) one-way comparison followed by Duncan’s tests (p<0.05) was used to compare the difference of data from multiple groups, using SPSS version 26 ((IBM Corp., Armonk, NY, USA).

In order to dissect the function of OsSEH1 in rice, we examined the cold tolerance of wild type (WT) and osseh1lines. After 7-day cold treatment and a 7-day recovery, only 41.67% of the osseh1 seedlings survived, in contrast to 87.5% of the WT plants ( Figures 1A, B ). Further, we measured the physiological parameters of WT plants and osseh1 knock-out lines before and after cold treatment. The growth performance was assessed by evaluating plant height, root length, shoot fresh and dry weight, root fresh and dry weight. We sampled and measured the parameters at three time points and the first sampling point is the 14^th day of the rice seedling ( Supplementary Figure 2A ). For both WT and osseh1 lines, shoot fresh weight, root fresh weight, shoot dry weight and root dry weight showed similar rising tendency during cold treatment compared with that during normal condition ( Supplementary Figures 2B–E ). However, the plant height and root length of osseh1 lines was significantly inhibited under cold stress compared with that of WT ( Supplementary Figure 2F, G ).

In addition, we measured soluble sugar content, proline content, ROS content, superoxide dismutase (SOD) activity, peroxidase (POD) activity, ascorbate peroxidase (APX) activity and catalase (CAT) activity in the leaves of WT and osseh1 lines under normal and cold condition. Compared with the WT lines, the soluble sugar content of osseh1 lines decreased significantly under normal condition, while there was no significant difference between them under cold stress ( Figure 1C ). The proline content of both WT and osseh1 lines were increased after cold stress, while there was no significant difference between them under normal and cold condition ( Figure 1D ). Our results also revealed that the ROS content in osseh1 knock-out lines was significantly higher than that in WT plants, suggesting that osseh1 lines were subjected to more severe oxidative stress under cold stress ( Figure 1E ). After 2-day 4°C cold stress, the SOD activity in the leaves of osseh1 is significantly lower than that of WT ( Figure 1F ). The POD activity was no difference between WT and osseh1 lines under normal and cold condition ( Figure 1G ). The CAT activity of osseh1 was lower compared to that of WT under normal condition, while there was no significant difference between them under cold condition ( Figure 1H ). The APX activity of osseh1 lines was significantly higher than that of WT under both normal and cold condition ( Figure 1I ). These results indicated that OsSEH1 play a role in regulating rice development and physiological characteristics.

To reveal the role of OsSEH1 underlying cold treatment at the metabolic profile, we performed widely targeted metabolomics assay for wild type plants and osseh1 knock-out mutants. We used an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) method to identify changes in metabolite levels. Principal component analysis (PCA) indicated that the metabolites of different genotypes and treatments were significantly different ( Figure 2A ). Cluster analysis was also performed, and 12 samples were clearly divided into four groups, indicating significant differences in metabolites among four experiment groups ( Figure 2B ). A total of 806 metabolites were detected with this approach, including 31 different types of substances, among these metabolites, 110 were phenolic acids, 108 were flavonoid metabolites, 75 were organic acids, 73 were amino acids and derivatives, and 54 were free fatty acids ( Supplementary Table 1 ; Supplementary Figure 3 ). In positive ion mode, the metabolites were categorized into 12 classes, while in negative ion mode, the metabolites were categorized into 11 classes ( Figure 2C ).

A total of 102 differently accumulated metabolites (DAMs) (32 upregulated and 70 downregulated metabolites) were identified between WT under normal condition and osseh1 under normal condition (WT vs osseh1; variable importance (VIP) scores ≥1 and T-test P<0.05; Figure 2D ; Supplementary Table 2 ). 81 DAMs (53 upregulated and 28 downregulated metabolites) were identified between the WT under normal condition and WT under cold stress (WT vs WT-C; variable importance (VIP) scores ≥1 and T-test P<0.05; Figure 2D ; Supplementary Table 3 ). 59 DAMs (54 upregulated and 5 downregulated metabolites) were identified between the osseh1 under normal condition and osseh1 under cold stress (osseh1 vs osseh1-C; variable importance (VIP) scores ≥1 and T-test P<0.05; Figure 2D ; Supplementary Table 4 ). 100 DAMs (47 upregulated and 53 downregulated metabolites) were identified between WT and osseh1under cold stress (WT-C vs osseh1-C; variable importance (VIP) scores ≥1 and T-test P<0.05; Figure 2D ; Supplementary Table 5 ). These results suggested that OsSEH1 regulate a broad range of the metabolite accumulation.

The DAMs between WT and osseh1 lines under normal and cold condition were analyzed further. As expected, the metabolites expression patterns were similar between the biological replicates but differed significantly between the WT and osseh1 mutant lines ( Figures 3A, C ). We detected the different accumulation pattern of a wide range of the amino acids, flavonoids, organic acids, alkaloids, phenolic acids and lipids between WT and osseh1 mutants ( Figures 3A, C ). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that glyoxylate and dicarboxylate metabolism, citrate cycle (TCA cycle) and biosynthesis of antibiotics were the most significantly changed pathways in the noncold treatment WT vs osseh1 comparison ( Figure 3B ). However, the DAMs participating in citrate cycle (TCA cycle), 2-Oxocarboxylic acid metabolism, Pyruvate metabolism were mainly enriched under cold stress ( Figure 3D ). Further, some primary metabolic pathway that are essential for plant growth and development were also significantly enriched under cold stress, including biosynthesis of amino acids, flavone and flavonol biosynthesis and carbon metabolism. Flavonoids serve as ROS scavengers by locating and neutralizing radicals before they damage the cell thus important for plants (Agati et al., 2012). The contents of large-scale flavonoids were lower in osseh1 mutants compared to WT plants under cold treatment ( Figure 3C ), suggesting that the OsSEH1 may be involved in the regulation of flavone and flavonol biosynthesis.

We also performed a transcriptome assay using WT plants and osseh1 mutants, in parallel with metabolomics. Under normal condition, we depicted 683 differently expressed genes (DEGs) that were up-regulated and 496 down-regulated (fold change > 2 or < 0.5, FDR<0.05; Supplementary Figure 4A ; Supplementary Table 6 ) in the WT vs. osseh1 comparison. Gene ontology (GO) analyses revealed that these DEGs were enriched in defense response, regulation of hormone levels, benzene-containing compound metabolic process, response to stimulus and oxidation-reduction process biological processes ( Figure 4A ). KEGG pathway analysis showed that photosynthesis (ko00195), flavonoid biosynthesis (ko00941) and stilbenoid, diarylheptanoid and gingerol biosynthesis (ko00945) were the most significantly changed pathways ( Figure 4B ).

Under cold condition, we depicted 514 differently expressed genes (DEGs) that were up-regulated and 429 down-regulated (fold change>2 or < 0.5, FDR<0.05; Supplementary Figure 4B ; Supplementary Table 7 ) in the WT-C vs osseh1-C comparison. GO analyses revealed that these DEGs were enriched in multiple biological process, including defense response, photosynthetic electron transport chain, toxin metabolic process, zinc ion transmembrane transport and oxidation-reduction process ( Figure 4C ). KEGG pathway analysis demonstrated that photosynthesis (ko00195), metabolic pathways (ko01100) and flavonoid biosynthesis (ko00941) were the most significantly changed pathways in the WT-C vs osseh1-C comparison ( Figure 4D ). These results are consistent with our proposed role for OsSEH1 in the regulation of cold stress tolerance.

To further understand the regulatory network of OsSEH1 in the cold stress, we conducted transcription factor analysis on the differently expression genes between WT and osseh1 lines. The results showed that significant changes in the expression level of many different types of transcription factors, including bHLH family, ERF family, NAC family, C2H2 family and MYB family ( Figure 4E ). The results indicated that OsSEH1 may regulate the expression of a large number transcription factors.

In view of the differences in physiological characteristics between WT and osseh1 lines, we also focused on the term of oxidation-reduction process. We found that a total of 59 DEGs involved in oxidation-reduction process, including multiple genes encoding oxidoreductase ( Figure 5A ; Supplementary Table 8 ). The result indicated a role of OsSEH1 in the control of redox homeostasis. To confirm this possibility, we analyzed the expression levels of 14 genes by RT-qPCR (six genes in the DEGs analysis and eight other ROS-related genes) in WT and osseh1 lines under normal condition and cold stress ( Figure 5B ). Of the 14 tested genes, FeSOD, SODcc1, POD1, POX22.3, LOX10, ANS, Prx30, OPR1 and GRL8 were significantly lower in osseh1 lines than in WT plants under cold stress, while the expression of APx1, APx8, CATB and OPR8 were significantly higher in the osseh1 lines than WT plants and the expression of Perox4 was not significantly different between the osseh1 lines and WT plants.

To better characterize the role of OsSEH1 in regulating genes and metabolites under cold stress, we conducted Pearson’s correlation analysis based on the transcriptomic and metabolomic data. The KEGG analysis of the correlated DEGs and DAMs showed that phenylpropanoid biosynthesis, metabolic pathways and flavonoid biosynthesis were the most enriched pathway under cold treatment ( Figure 6A ). Further, we performed an integrated Two-way Orthogonal Partial Least Squares (O2PLS) analysis of the transcriptome and metabolome Tables ( Figure 6B ). Consistent with the result of KEGG analysis, 11 of the top 25 metabolites were highly correlated with phenylpropanoid biosynthesis and flavonoid biosynthesis, including Isovitexin-2’’-O-(6’’’-p-coumaroyl) glucoside (Zmhp003322), Isovitexin-2’’-O-(6’’’-feruloyl) glucoside (Zmhp003186), Swertiajaponin (pmp000233), 4’-Hydroxy-5,7-dimethoxyflavanone (pmc1990), Tricin-4’-O-(guaiacylglycerol) ether-7-O-glucoside (pmb1312), Tricin-7-O-Glucoside (pmb0736), Tricin-4’-O-(syringyl alcohol) ether-5-O-glucoside (pmb0719), Isoorientin-7-O-(6’’-p-coumaroyl) glucoside (pmb0660), Tricin-4’-O-glucoside (Lmhp206353), L-Phenylalanine (pme0021) ( Figure 6B ).

Moreover, we screened DEGs and DAMs in relation to their corresponding positions in the phenylpropanoid biosynthesis pathway. Metabolite analysis showed that (S)-alpha-Amino-beta-phenylpropionic acid (pme0021), Tyrosine (mws0250), 5-O-Caffeoylshikimic acid (Hmln002806), Apigenin 8-C-glucoside (mws0048) and 5,7,3’,4’-Tetrahydroxyflavone (pme0088) were all down-regulated in the osseh1 lines compared with that of WT plants under cold treatment ( Figure 7 ). Then, a total of 31 DEGs were identified in the phenylpropanoid biosynthesis pathway between the WT and osseh1 lines under cold treatment. 16 genes encoding core players in the phenylpropanoid biosynthesis pathway, such as PAL (Os04g0518400), ANS (Os01g0372500), 4CL (Os01g0901600), prx30 (Os02g0240100), prx38 (Os03g0235000), prx45 (Os03g0368900), prx58 (Os04g0656800), prx72 (Os05g0162000), prx115 (Os07g0677600) and prx117 (Os08g0113000) were significantly down-regulated in osseh1 lines compared with that in WT plants under cold stress ( Figure 7 ). These evidences supported the conclusion that OsSEH1 may play an essential role in the phenylpropanoid biosynthesis pathway in response to cold stress.

The growth and adaptation to stress of plants are commonly regulated by multiple phytohormones. Meanwhile, we noticed that the DEGs between WT and osseh1 knock-out lines were significantly enriched in regulation of hormone levels and hormone metabolic process ( Figure 4A ) and we thus speculated that OsSEH1 may play a role in regulation of phytohormones. To verify our speculation, we separately sprayed exogenous indole-3-acetic acid (IAA), 2, 4-Epibrassinolide and abscisic acid (ABA) onto the leaves of WT and osseh1 knock-out lines under cold stress. The cold tolerance of WT plants and osseh1 knock-out lines sprayed with ABA was significantly improved compared with that without exogenous hormone, but not with IAA or 2, 4-Epibrassinolide. To test a potential connection between OsSEH1 and ABA, we further determined that the survival of WT plants increased by 0.70%, 5.56%, 11.11%, -1.39% in the 1 μM, 10 μM, 100 μM and 150 μM ABA treatments, respectively, compared with that of the 0 μM ABA treatment, while those of osseh1 lines were 12.5%, 18.06%, 21.54%, 11.81% respectively ( Figures 8A, B ). To further verify the sensitivity of WT and osseh1 lines to exogenous ABA, we calculated the germination rates of seeds grown on 0 μM, 1 μM or 10 μM ABA. In the absence of ABA, there was no significant difference between osseh1 mutants and WT plants ( Figures 8C, D ). However, the germination rates of osseh1 seeds treated with 1 μM and 10 μM ABA were significantly inhibited compared with that of WT plants ( Figures 8C, D ). These results indicated that osseh1 knock-out lines had ABA hypersensitive phenotypes compared with that WT lines.

Further, we measured soluble sugar content, proline content, ROS content, SOD activity, POD activity, APX activity and CAT activity in the leaves treated with different ABA concentrations of WT and osseh1 lines. We measured the endogenous ABA content in the osseh1 knock-out lines and WT plants to verify the effectiveness of exogenous ABA application. The endogenous ABA content of osseh1 knock-out lines was significantly higher than that of WT plants before and after treatment ( Supplementary Figure 5A ). The content of soluble sugar in WT plants was increased as the ABA concentrations was increased, while it was almost no difference in osseh1 lines under cold stress ( Figure 8E ). The trends of the proline content in both WT and osseh1 lines showed no difference with the increase in ABA concentration ( Figure 8F ). The content of ROS in WT plants was increased as the ABA concentrations was increased, while it decreased significantly at the concentration of 1 μM and 10 μM in osseh1 lines ( Figure 8G ). The activity of SOD in WT increased slowly as the ABA concentrations was increased, reaching a maximum with the spraying of 150 µM*L^-1 ABA. In contrast, the activity of SOD in osseh1 lines increase to a maximum with the spraying of 10 µM*L^-1 ABA ( Supplementary Figure 5B ). Interestingly, in WT plants, the activity of POD was decreased as the ABA concentration was increased under cold stress, while it increased in osseh1 plants ( Supplementary Figure 5C ). The activity of CAT and APX in both WT and osseh1 plants increased with the increase in ABA concentration under cold stress ( Supplementary Figures 5D, E ). These results suggested that WT and osseh1 knock-out plants differ in the sensitivity to exogenous ABA.