MIR1868 negatively regulates rice cold tolerance at both the seedling and booting stages

Abstract

Low temperature causes rice yield losses of up to 30%–40%, therefore increasing its cold tolerance is a breeding target. Few genes in rice are reported to confer cold tolerance at both the vegetative and reproductive stages. This study revealed a rice-specific 24-nt miRNA, miR1868, whose accumulation was suppressed by cold stress. Knockdown of MIR1868 increased seedling survival, pollen fertility, seed setting, and grain yield under cold stress, whereas its overexpression conferred the opposite phenotype. Knockdown of MIR1868 increased reactive oxygen species (ROS) scavenging and soluble sugar content under cold stress by increasing the expression of peroxidase genes and sugar metabolism genes, and its overexpression produced the opposite effect. Thus, MIR1868 negatively regulated rice cold tolerance via ROS scavenging and sugar accumulation.

Headnote

ABSTRACT

Low temperature causes rice yield losses of up to 30%–40%, therefore increasing its cold tolerance is a breeding target. Few genes in rice are reported to confer cold tolerance at both the vegetative and reproductive stages. This study revealed a rice-specific 24-nt miRNA, miR1868, whose accumulation was suppressed by cold stress. Knockdown of MIR1868 increased seedling survival, pollen fertility, seed setting, and grain yield under cold stress, whereas its overexpression conferred the opposite phenotype. Knockdown of MIR1868 increased reactive oxygen species (ROS) scavenging and soluble sugar content under cold stress by increasing the expression of peroxidase genes and sugar metabolism genes, and its overexpression produced the opposite effect. Thus, MIR1868 negatively regulated rice cold tolerance via ROS scavenging and sugar accumulation.

Keywords:

Rice

Cold tolerance

miRNA

ROS scavenging

Soluble sugar accumulation

1. Introduction

Rice (Oryza sativa L.), a staple grain of half of the world's popu-lation, originates in temperate and tropical regions and is sensitive to low temperatures, thus its production and geographic distribu-tion are restricted by cold stress. Low temperature occurring at the seedling stage (< 4 C) usually results in seedling growth retarda-tion and even death [1]. Cold stress at the booting stage (< 15 C) represses the meiosis of pollen mother cells and leads to reduced numbers of mature pollen grains and increased proportions of male sterility, reducing seed setting and grain yield [2–5]. There-fore, improving the cold tolerance is a major breeding target for rice.

It is desirable to identify genes that regulate rice cold tolerance at various developmental stages. Several QTL and genes regulate rice cold tolerance at the seedling stage: COLD1 (CHILLING-TOLERANCE DIVERGENCE 1) [6], HAN1 ("han" means "chilling" in Chinese) [7], LTG1 (Low Temperature Growth 1) [8], bZIP73 (Basic Leucine Zipper 73) [9], and MAPK3 (Mitogen-Activated Protein Kinases 3) [10]. Because it is difficult to evaluate cold tolerance at the booting stage, only a few QTL and genes have been character-ized [1]. Among them, only bZIP73 and MAPK3 conferred cold toler-ance at the seedling and booting stages [4,5,9,10].

ding RNAs [11], function in abiotic stress response. Rice harbors 689 known and 1664 predicted miRNAs [12]. They influence plant height [13–15], tiller [13,16,17], grain size [18–20], and the toler-ance to saline and alkaline [21–23], drought [24,25] and cold [26–28] stresses. The miRNAs functionally characterized to date are mostly 20–22-nt miRNAs, which post-transcriptionally regu-late target genes through mRNA cleavage and/or translational repression [11]. 24-nt miRNAs modulated the expression of target genes via the RNA-directed DNA methylation pathway [11,29]. sRNA-seq identified 24-nt miRNAs differentially expressed under biotic and abiotic stresses, including cold, drought, heat, and blast disease [30]. Only miR1871 [31], miR1873 [32], miR1875 [33], and miR1876 [34] have been reported to regulate rice immunity to blast. It is desirable to identify the biological function of abiotic stress responses mediated by 24-nt miRNA.

In a previous study [35], we identified 18 cold-responsive miR-NAs: fifteen 21-nt and three 24-nt miRNAs. Five of the 21-nt miR-NAs: miR156k [26], miR319 [27], miR408 [24], miR535 [36], and miR1320 [28], have been shown to regulate cold tolerance. In this study, we identified a 24-nt rice-specific miR1868 whose accumu-lation is suppressed by cold stress. We showed that MIR1868 negatively regulated rice cold tolerance at both the seedling and booting stages. Our studies uncovered a previously uncharacterized "miR1868-ROS/soluble sugar-cold tolerance" sig-naling module that well explains the negative role of MIR1868 in rice cold tolerance.

2. Materials and methods

2.1. Generation of transgenic rice lines

For overexpression of MIR1868 (MIR1868-OE), DNA sequences of pre-miR1868 were cloned and inserted into the pCAM-BIA330035Su vector under the control of the CaMV35S promoter. For knockdown of MIR1868 (MIR1868-KD), an STTM (Short Tan-dem Target Mimic) fragment that contained two imperfect miR1868 target sites with a CAT trinucleotide bulge linked by a 48-nt short spacer was artificially synthesized and inserted into the pCAMBIA330035Su vector. The sequences of all primers and synthetic DNA fragments used for vector construction are listed in Table S1.

The wild-type (WT) rice cultivar Kongyu 131 (O. sativa L. subsp. japonica) was used for Agrobacterium-mediated transformation. After identification of glyphosate-resistant plants, PCR and qRT-PCR were performed to screen MIR1868 overexpression or knock-down lines. Transgenic lines with a 3:1 genetic segregation ratio of progeny were selected, and homologous T3 generation seeds were used for phenotypic, physiological and biochemical assays under cold stress.

2.2. Cold stress tolerance assays

To test cold tolerance at the seedling stage, three-leaf seedlings were treated at 4 C for 4 d until the leaves began to curl, and then recovered under normal conditions for 7 d. The proportion of sur-viving seedlings was calculated. At least three independent exper-iments were performed, and 90 seedlings from each line were used in each experiment.

To test cold tolerance at the booting stage, rice plants were grown in cylindrical plastic pots (33 cm in height and 28 cm in diameter). Tillers were labeled when the auricular spacing between the flag leaf and the penultimate leaf was –6 cm to –2 cm (between the meiotic stage and the uninucleate pollen stage) [2]. The labeled plants were moved to a 15 C greenhouse for 7 d and then grown under normal conditions until maturity. When anthers elongated to 2/3 of the glumes, anthers were collected and crushed to release pollen grains for I2-KI staining. Pollen grains stained blue were counted under a light microscope. After harvest, main panicle weight, thousand-grain weight, seed setting (the ratio of filled kernels to the total number of kernels per panicle), grain length, grain width, and grain thickness were measured. More than 30 tillers from 15 plants per line were used for the cold tolerance test at the booting stage.

2.3. Measurement of physiological and biochemical parameters

Physiological parameters were measured by using three-leaf seedlings treated at 4 C for 0 and 2 d. The contents of malondi-aldehyde (MDA) were measured with a spectrophotometer as described [30]. The activities of superoxide dismutase (SOD), per-oxidase (POD), and catalase (CAT) were measured as described [37]. Nitro blue tetrazolium (NBT) and 3,30 -diaminobenzidine (DAB) staining were performed as described [38]. At least 15 sam-ples per line were determined for each index.

2.4. Rna-sequencing assays

Three-leaf seedlings of WT, MIR1868-OE-2, and MIR1868-KD-1 lines were treated at 4 C for 0 and 0.5 h. Leaves were sampled from three individual seedlings, respectively, and subjected to RNA-seq by Biomarker Biotechnology Corporation (Beijing, China). The sequence data were filtered, and clean data were mapped to the rice genome-MSU Release 7.0. The mapped data was used for a library quality assessment such as the insert fragment length test and randomness test. The DEGs with FDR - 0.05 and |log2FoldChange| 1 were selected and used for KEGG enrichment analysis.

2.5. RNA extraction and qRT-PCR analysis

To detect gene expression under cold stress, three-leaf seedlings were treated at 4 C for 0, 0.5, 1, 3, 6, 9, 12, and 24 h, respectively. To exclude the potential circadian alternation of gene expression, cold treatment was started at multiple time points and samples were collected at the same time point. Total RNAs were extracted from rice leaves using the TRIzol reagent (Invitrogen Life Technolo-gies, 15596026, USA) and treated with DNase I (Thermo Fisher Sci-entific, EN0521, USA) to remove genomic DNA contamination. cDNA was synthesized by using the Transcriptor First Strand cDNA Synthesis Kit (Roche, 04379012001, USA) with miR1868 stem-loop primer, U6-specific primer, and oligo dT primer for other genes. cDNA (10 dilutions) was amplified using the TransStart TopGreen qPCR SuperMix (TransGen Biotech, AQ131, China) on a CFX96 Real-Time System (Bio-Rad). The OsU6 (XR_003241666, for miR1868) and OsElf1-a (LOC_Os03g08010, for others) genes were used as internal reference genes. Three biological replicates and three tech-nological repeats were performed, and relative expression levels were calculated using the DDCT method [28]. The sequences of all primers used for qRT-PCR assays are listed in Table S1.

3. Results

3.1. miR1868, a rice-specific 24-nt miRNA, is downregulated by cold stress

Our previous microarray data revealed an obvious decrease in miR1868 accumulation under cold stress [35]. In this study, we confirmed that the accumulation of miR1868 rapidly decreased after cold treatment for 0.5 h to half of that under normal condi-tions. Along with the cold treatment period, MIR1868 displayed a fluctuating expression pattern, but showed down-regualted expression except at 9 h (Fig. 1A).

Based on the keyword "MIR1868" search against the miRbase database, the MIR1868 gene was found only in rice, suggesting that MIR1868 is a rice-specific MIRNA (Fig. S1A). MIR1868 was located in the third intron of a ribosomal protein-encoding gene Os04g32710, whose expression was suppressed by cold stress (Figs. S1B, S2). After transcription, the third intron of Os04g32710 is cleaved and processed to form a 24 nt miR1868 (Fig. S1C, D). These findings indicate that miR1868 is a rice-specific 24-nt miRNA and is downregulated by cold stress.

3.2. MIR1868 negatively regulates rice cold tolerance at the seedling stage

To investigate the role of MIR1868 in cold response, we gener-ated MIR1868 overexpression (MIR1868-OE) rice in which pre-miR1868 expression was driven by the CaMV35S promoter (Fig. S3A). The T3 generation from two independent MIR1868-OE lines, MIR1868-OE-2 and MIR1868-OE-4, was subjected toquantitative real-time PCR analysis. Mature miR1868 accumula-tion was increased by about 40 and 63 folds in these two MIR1868-OE lines (Fig. 1B). MIR1868 knockdown (MIR1868-KD) lines were also generated by using the STTM technology (Fig. S3B, C). The accumulation of mature miR1868 was decreased to less than half in the MIR1868-KD lines (MIR1868-KD-1 and MIR1868-KD-5) (Fig. 1C).

To test the effect of MIR1868 on rice cold tolerance, we first per-formed the phenotypic assays by exposing the 3-leaf seedlings of the MIR1868-OE and MIR1868-KD lines to 4 C for 2 d. After recov-ery from cold treatment, the MIR1868-OE seedlings displayed more withered leaves and lower survival rates than WT (Fig. 1D, F), while seedlings from the MIR1868-KD lines displayed better performance and higher survival rates (Fig. 1E, G). This finding sug-gests that MIR1868 negatively regulates cold tolerance at the seed-ling stage.

3.3. MIR1868 modulates pollen viability and grain yields under cold stress at the booting stage

We further determined the cold tolerance of MIR1868 trans-genic lines at the booting stage. Pollen staining showed no differ-ence in pollen fertility among WT, MIR1868OE, and MIR1868KD lines under normal growth conditions. After cold treatment, the fertile pollen rates of the MIR1868-OE lines were significantly lower than that of WT, while the MIR1868-KD lines displayed higher rates of fertile pollen grains than WT (Fig. 2A, C). Consis-tently, the MIR1868-OE lines showed lower seed setting rates than WT, while higher seed setting rates were observed for the MIR1868-KD lines under cold treatment (Fig. 2B, D). Thousand-grain weight was decreased in the MIR1868-OE lines but increased in the MIR1868-KD lines after cold treatment (Fig. 2E). Grain length and width did not differ among the WT, MIR1868-OE, and MIR1868-KD lines either before or after cold treatment (Fig. S4A, B). Grain thickness was smaller in the MIR1868-OE lines than in the WT after cold treatment, whereas it was greater in the MIR1868-KD lines (Fig. 2F). Collectively, these results indicate that MIR1868 functions as a negative regulator of rice cold tolerance at the booting stage.

3.4. MIR1868 targets prediction and expression analysis

miRNAs recognize target genes via complementary base pairing to regulate gene expression [28]. To investigate the regulatory mechanism of MIR1868, we first used the rice transcript sequence as a library to predict potential targets of miR1868 via the psRNATarget website. A total of 33 genes were predicted as miR1868 potential targets (Table S2). We analyzed their cold stress expression patterns by using the public transcriptome database [37] and found that six were induced by cold stress (Table S3). Based on the functional annotation and the threshold of psRNATar-get prediction (Expectation values < 3.5), we selected four of these six genes to measure their expression in the MIR1868 transgenic lines. The expression of all these four genes was not altered in either the MIR1868-OE or MIR1868-KD lines compared with WT (Fig. S5).

To further analyze whether the expression of all potential tar-gets is altered by miR1868, we performed the RNA-seq analysisof the WT, MIR1868-OE-2, and MIR1868-KD-1 lines before and after cold treatment. Analysis of clean read numbers, percentages of reads with average quality > Q30, and GC contents (Table S4), as well as the expression density and the number of FPKMs (Fig. S6) indicated that the sequencing data were high quality. Moreover, the the Pearson correlation coefficient among different samples also showed better reproducibility between biological replicates (Fig. S7). Based on the RNA-seq data, 21 of the above 33 predicted target genes could be detected (Fig. S8). However, none of these genes were differentially expressed in the MIR1868 transgenic lines under normal conditions. After cold treatment, Os07g46670 was down-regulated in both the MIR1868-OE-2 and MIR1868-KD-1 lines, and Os06g06670 expression was elevated in the MIR1868-OE-2 line. These data suggest transcript levels of these predicted target genes are not regulated by miR1868.

3.5. Rna-seq analysis of MIR1868-regulated metabolic pathways in response to cold stress

Based on the RNA-seq data, 247 (112 up and 135 down) and 194 (84 up and 110 down) differentially expressed genes (DEGs, FDR - 0.05, |log2FoldChange| 1) were identified in the MIR1868OE-2 and MIR1868-KD-1 lines under normal conditions. After cold treatment, the DEG numbers were greatly increased, with 1797 DEGs in MIR1868-OE-2 and 894 in MIR1868-KD-1, indicating the activation of numerous cold-responsive genes (Fig. 3A).

Subsequently, we screened the DEGs that showed a negative correlation in the MIR1868-OE-2 and MIR1868-KD-1 lines. Under normal conditions, three genes were negatively correlated. Os05g32690 encodes a 107-amino acid protein without function-ally annotated structural domains, and its expression was down-regulated in MIR1868-OE-2 and up-regulated in MIR1868-KD-1. Os12g15340 encodes a retrotransposon protein, and Os04g41640 encodes a chitin recognition protein. These two genes were up-regulated in the MIR1868-OE-2 line and down-regulated in the MIR1868-KD-1 line (Fig. S9). After cold treatment, the number of down-regulated DEGs (481) in MIR1868-KD-1 is roughly compa-rable to that of up-regualted DEGs (6 05) in MIR1868-OE-2, how-ever only 11 genes showed up-regulation in MIR1868-OE-2 but down-regulation in MIR1868-KD-1 (Fig. 3B). The number (1192) of down-regulated DEGs in MIR1868-OE-2 is much bigger than that (413) of up-regulated DEGs in MIR1868-KD-1, and 125 DEGs showed down-regulation in MIR1868-OE-2 but up-regulation in MIR1868-KD-1 (Fig. 3C). We further predicted the recognition sequences of miR1868 in both the genomic and promoter sequences of these negatively correlated genes; however, no recog-nition sites were observed.

To reveal the metabolism pathways mediated by MIR1868, we performed KEGG-pathway annotation of these 136 negatively cor-related DEGs (Fig. 3D). As a consequence, 63 DEGs were enriched in 26 KEGG pathways, including four DEGs in two cellular processes, one DEG in plant hormone signaling transduction, and 58 DEGs enriched in 23 metabolism pathways. Eleven DEGs were enriched in the starch and sucrose metabolism pathway and seven DEGs were enriched in the phenylpropanoid biosynthesis pathway. Therefore, MIR1868 functions in cold stress response by modifying these two metabolic pathways.

3.6. MIR1868 regulates ROS homeostasis under cold stress

Seven of DEGs in the phenylpropanoid biosynthesis pathway (Fig. 3C) encode peroxidases, which are key antioxidant enzymesunder cold stress. As shown in Fig. 4A, no difference was observed in their expression among different lines under normal growth conditions. After cold treatment, their expression levels were lower in the MIR1868-OE line and higher in the MIR1868-KD line than WT. We selected Os05g04380 (Peroxidase 2), Os03g13200 (Peroxi-dase A2), OsPOX1, and Os03g22010 (Peroxidase 70) for qRT-PCR val-idation. After cold treatment, their expression was significantly down-regulated in the MIR1868-OE lines while up-regulated in the MIR1868-KD lines compared with WT (Fig. 4B–E). Consistently, after cold stress, POD activity was higher in the MIR1868-KD lines but lower in the MIR1868-OE lines (Fig. 4F). Enzyme activity of SOD and CAT was also up-regulated in the MIR1868-KD lines and down-regulated in the MIR1868-OE lines (Fig. 4G, H). The accumu-lation of H2O2 and O2 was further detected by DAB and NBT stain-ing, respectively. As shown in Fig. 4I and J, the MIR1868-OE lines accumulated more H2O2 and O2 than WT, while ROS accumulation was much less in the MIR1868-KD lines under cold stress. We also measured the content of MDA, an indicator of oxidative damage in plant cells. Expectedly, compared with WT, the MIR1868-KD lines showed less accumulation of MDA, while the MIR1868-OE lines displayed increased MDA contents (Fig. 4K). Taken together, these results suggest that MIR1868 regulates ROS scavenging under cold stress.

3.7. MIR1868 modifies sucrose and starch metabolism under cold stress

Based on RNA-seq analysis, eleven genes belonging to the sucrose and starch metabolism pathway were differentially expressed in the MIR1868 transgenic lines (Fig. 3C). As shown in Fig. 5A, the expression of these genes showed no difference among the WT, MIR1868-OE, and MIR1868-KD lines under normal growth conditions. After cold treatment, their expression levels were significantly decreased in the MIR1868-OE line and increased in the MIR1868-KD line compared with WT. The differential expression of four genes, including OsSUS1 (Os03g28330), OsGH9A3(Os03g52630), Os3BGlu7 (Os03g49600), and Os4BGlu12 (Os04g39880), was further verified by real-time PCR. Consistent with the RNA-seq data, their expression levels were significantly lower in the MIR1868-OE lines but higher in the MIR1868-KD lines than WT under cold stress (Fig. 5B–E).

According to the KEGG database annotation, these genes were involved mainly in sucrose and cellulose catabolism (Fig. S10; Table S5). Therefore, we measured the content of soluble sugars in the MIR1868 transgenic lines. As expected, compared with WT, the MIR1868-KD lines showed an obvious increase in soluble sugar accumulation, while the MIR1868-OE lines displayed less soluble sugars (Fig. 5F). In summary, MIR1868 suppresses the sugar meta-bolism in rice under cold stress.

4. Discussion

MiRNAs play essential roles in regulating rice growth and devel-opment, as well as the adaptation to environmental stresses [11]. Rice miR1868 is a species-specific 24-nt miRNA. Recent studies showed that MIR1868 expression was suppressed under drought, cold, and heat treatments but elevated after inoculation with rice blast [30,38]. However, the biological function of MIR1868 is still unclear. In this study, we illustrate that MIR1868 regulates rice cold tolerance by modulating ROS homeostasis and sucrose metabolism.

Currently, few genes are reported to control cold tolerance at both the seedling and booting stages [4,5,9,10]. In this study, we showed that miR1868 accumulation was decreased under cold stress (Fig. 1A). Genetic evidence suggests that knockdown of MIR1868 improves seedlings survival (Fig. 1D, G), pollen fertility (Fig. 2A, C), seed setting rates (Fig. 2B, D), thousand-grain weight and grain thickness (Fig. 2E, F) under cold stress; in contrast, over-expression of MIR1868 has the opposite phenotype. Notably, over-expression and knockdown of MIR1868 did not affect rice plants growth and seed development under normal growth conditions (Fig. S4). The evidence suggests that MIR1868 is a negative regula-tor of cold tolerance at both the seedling and booting stages with-out affecting rice yields. Therefore, MIR1868 is a suitable candidate target for CRISPR-mediated gene editing for breeding new rice varieties with improved cold tolerance.

The cold tolerance in rice is closely related to the capability of ROS scavenging and osmotic regulation. For example, bZIP73 improved rice cold tolerance by activating peroxidase gene expres-sion to scavenge excess ROS [9], and by facilitating the transport of soluble sugars from anthers to pollen [4]. OsTMF negatively regu-lated cold tolerance by inhibiting peroxidase activity [12], and the MAPK3-ICE1-TPP1 module positively regulated rice cold toler-ance by increasing trehalose accumulation [5,10]. In this study, we showed that MIR1868 affected ROS scavenging and soluble sugar accumulation under cold stress at the seedling stage (Figs. 3–5). Although the targets of MIR1868 could not be successfully identified in the current study, we suppose MIR1868, as a regulatory gene, could recognize different targets to affect different physio-logical processes. Several MIRNAs, like miR319 [16,27], miR528 [39,40], and miR1848 [41,42] also participated different processes by targeting different genes. Therefore, it will be important to iden-tify MIR1868 targets in future work. Besides, considering the regu-lation of MIR1868 on cold tolerance at the booting stage, further analysis is need to clarify the MIR1868-mediated physiological changes at the booting stage.

In addition to ROS scavenging, peroxidases also catalyze the synthesis of lignin, which plays important roles in the composition of cell wall and stress response [43]. Therefore, we hypothesized that MIR1868 may modify cell wall composition under cold treat-ment, which needs further verification by determining the cell wall composition of MIR1868 transgenic lines. Moreover, cell wall integ-rity maintenance is important for activating and monitoring the pathogenic defense responses [43]. Previous sRNA-seq data indi-cated that MIR1868 expression was significantly increased after inoculation with rice blast [38]. The function of MIR1868 in regulat-ing rice blast resistance is worth further investigation.

MiRNAs control the expression of target genes by recognizing their targets through base complementary pairing. 24-nt miRNAs could recognize the promoter [33], transcript [32], and intron [31] of target genes to regulate their expression via RNA-mediated DNA methylation [29]. Identification of MIR1868 targets is of great significance to illustrate the signal transduction medi-ated by MIR1868 in cold stress response. Unfortunately, we could not successfully identify MIR1868 targets based on target predic-tion and RNA-seq analysis. No gene harboring the miR1868 recog-nition sequences was found to show perfectly opposite expression patterns in the MIR1868 overexpression and knockdown lines. We hypothesized that due to unknown feedback regulation, target genes might be only differentially expressed in either MIR1868OE or MIR1868-KD lines. This phenomenon was also found for other 24-nt miRNAs [31,32]. For example, expression of MFAP1, the target of miR1871, was only up-regulated in the miR1871 knockdown lines, but not reduced in the overexpression lines [31]. Another reasonable speculation is that MIR1868 controls the protein translation process of targets through an unknown mecha-nism. Future work should focus on the experimental identification of MIR1868 targets, and identify how MIR1868 tie ROS scavenging and soluble sugar accumulation in cold stress response.

5. Conclusions

MIR1868 negatively regulates rice cold tolerance at both the seedling and booting stage. A miR1868-ROS/soluble sugar-cold tol-erance signaling module explains the negative role of MIR1868 in rice cold tolerance at the molecular level. This study provides can-didate targets for breeding new cold-tolerant rice varieties through CRISPR-mediated gene editing

CRediT authorship contribution statement

Yang Shen: Methodology, Writing – original draft, Data cura-tion, Formal analysis. Xiaoxi Cai: Data curation, Formal analysis, Methodology. Yan Wang: Methodology, Data curation. Wanhong Li: Data curation. Dongpeng Li: Data curation, Formal analysis. Hao Wu: Data curation. Weifeng Dong: Formal analysis. Bowei Jia: Writing – review & editing, Methodology. Mingzhe Sun: Con-ceptualization, Funding acquisition, Project administration, Writ-ing – review & editing. Xiaoli Sun: Writing – review & editing, Funding acquisition, Project administration, Supervision.

Declaration of competing interest

The authors declare that they have no known competing finan-cial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was supported by grants from the National Natural Science Foundation of China (U20A2025, 32101672, 31971826), the National Key Research and Development Plan of China (2021YFF1001100), Natural Science Foundation of Heilongjiang province (YQ2023C035), Double First-class Innovation Achieve-ment Program of Heilongjiang Province (LJGXCG2023-072), and the Graduate Student Scientific Research Innovation Projects of Heilongjiang Bayi Agricultural University (YJSCX2022-Z01).

Appendix A. Supplementary data

Supplementary data for this article can be found online at https://doi.org/10.1016/j.cj.2024.02.005.

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ARTICLE INFO

Article history:

Received 26 December 2023

Revised 30 January 2024

Accepted 3 February 2024

Available online 13 March 2024

Footnote

* Corresponding authors.

E-mail addresses: [email protected] (M. Sun), [email protected]. cn (X. Sun).

References

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