Cloning of rice chalkiness phenotype average value and plasticity major gene MPC5 and application of rice chalkiness phenotype average value and plasticity major gene MPC5 in rice quality improvement

Abstract

The invention relates to cloning of a rice chalkiness phenotype average value and plasticity major gene MPC5 and application of the rice chalkiness phenotype average value and plasticity major gene MPC5 in quality improvement. The major gene MPC5 capable of regulating and controlling the average value and plasticity of chalkiness phenotypes in an opposite mode is determined, and the verification of transgenic tests in a multi-point high-temperature and normal-temperature field for many years shows that after the MPC5 is knocked out, the chalkiness degree of grains is remarkably increased while the grain shape is remarkably widened, and the plasticity of the grains is reduced; overexpressed MPC5 grains are remarkably narrowed, the chalkiness is remarkably reduced, the plasticity is improved, and the expression level of the MPC5 is remarkably improved under a high-temperature condition. The major QTL for controlling the chalkiness phenotype average value and plasticity, the molecular breeding minimum SNPs combination of the major QTL and the molecular breeding minimum SNPs combination and the cloned major gene MPC5 for controlling the chalkiness phenotype average value and plasticity are important targets for cultivating high-temperature-resistant high-quality rice varieties and have wide application value.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of molecular breeding, and particularly relates to the discovery of the average value of the chalky phenotype of rice quality traits and the plasticity major gene MPC5 and application thereof in rice quality improvement. BACKGROUND

[0002] Rice is one of the most important crops in China and is the main food source for more than half of the world's population. In recent years, the main challenge for rice genetic breeding is how to rapidly improve yield and rice quality to enhance its market value. With the frequent occurrence of extreme weather, exploring the key genes affecting rice key quality and their interaction with the environment has become an important target for rice genetic breeding. The evaluation of rice grain quality mainly involves milling quality, appearance quality, nutritional quality, and eating and cooking quality. Among them, the chalky of rice kernel is defined as the opaque white part in the endosperm of rice, which is controlled by multiple genes and sensitive to environmental changes, and is an important indicator for evaluating the appearance and eating quality of rice. The chalky structure in rice will lead to a decrease in milled rice rate and reduce the hardness and toughness of cooked rice, thereby seriously affecting the appearance and taste. Existing studies have shown that there is a significant positive correlation between grain width and chalkiness of rice, and wide-grained rice has a faster filling speed during grain filling, which may lead to loose arrangement of starch granules, thereby forming a chalky phenotype. Therefore, elucidating the molecular mechanism of key genes regulating the chalky phenotype of rice, studying the relationship between genes and environmental adaptability, and exploring the correlation between grain width genes and the plasticity of chalky phenotype provide important gene resources and theoretical reference for the molecular design breeding of high-yield and high-quality rice.

[0003] Phenotypic plasticity, the variation of a genotype's traits under different environmental conditions, is a common phenomenon in nature. A significant feature of phenotypic plasticity is the trade-off between the mean value of a trait and its plasticity, i.e., an increase in the mean value of a trait often leads to a decrease in plasticity. The mean value, linear plasticity, and nonlinear plasticity of a crop's agronomic traits, based on the performance of a trait under different environmental conditions and genotype-by-environment interaction (G x E), reveal the complex relationship between genetic potential and environmental factors, and represent a trait's ability to adapt to environmental changes. To breed high-quality rice varieties with low chalkiness and high environmental adaptability, it is urgent to identify the major QTL genes controlling the trade-off between the mean value and plasticity of grain chalkiness and elucidate their underlying mechanisms, which will help to breed high-quality rice varieties that are adapted to local environments by exploiting the differences in plasticity among genotypes. Based on the method of genome-wide association study (GWAS), the genetic variation of complex traits and the identification of major genes in different rice varieties have been widely applied, and a series of genes affecting important agronomic traits have been identified in the rice genome. For example, genes controlling the grain chalkiness trait include OsbZIP60, OsCG5, PGC1.7, PGC8.6, PGC1.2, GS7, TUD, qGRL1.7, qPGWC3, qTGW2.4, qTGW1.12, qGL1.12, and qGL2.2, while genes controlling rice grain shape include GW5, OsSNB, GS3, and OsDER1. Previous studies have shown that environmental factors such as high temperature not only cause a significant decrease in rice yield but also significantly reduce grain quality, threatening global food security. Among them, the increase in rice chalkiness is the most important indicator of the deterioration of rice quality caused by high temperature and is sensitive to environmental changes. However, the mechanisms of these key chalkiness and grain shape genes forming different phenotypes under the influence of environmental fluctuations in different environmental conditions are still unclear.

[0004] GW5 is a major gene controlling grain width on chromosome 5 identified by Duan et al. using GWAS method. Research shows that a 1212 bp deletion exists in the 5' flanking region of GW5 gene in most japonica varieties, while the deletion is not found in most narrow-grained indica varieties. qRT-PCR and LUC-REN experimental results confirm that the deletion of the fragment reduces the expression level of GW5, which may lead to grain width. Further research shows that GW5 is located on the plasma membrane and encodes a calmodulin-binding protein, which is a new positive regulator in the brassinosteroid signaling pathway. Knocking out the GW5 gene in Kasalath can significantly increase grain width and weight. Existing research shows that GW5 plays an important role in regulating rice grain width, grain weight, participating in BR signaling pathway, and responding to salt stress. Although previous studies have confirmed the importance of GW5 in regulating rice grain type and yield and its potential role in abiotic stress, the research on the effect of GW5 gene on chalky quality and the molecular mechanism of regulating grain type and chalky quality have not been reported. SUMMARY

[0005] Based on the plasticity analysis and GWAS analysis of multi-year multi-point chalky phenotype data, the present application identifies a major gene MPC5 controlling the average value and plasticity of rice chalkiness, and analyzes its new function in regulating rice chalky quality, thereby providing a new genetic resource for genetic improvement of high-yield high-quality heat-tolerant rice varieties.

[0006] The present application provides the MPC5 gene, an expression cassette, an expression vector or a recombinant microorganism containing the same, and the use of the same in any of the following A1) to A6): A1) regulating the development of rice endosperm; A2) preparing a product for regulating the development of rice endosperm; A3) regulating the chalky rate, chalky area and / or chalkiness of rice grains; A4) preparing a product for regulating the chalky rate, chalky area and / or chalkiness of rice grains; A5) cultivating a high-quality heat-tolerant low-chalky rice variety; A6) preparing a product for cultivating a high-quality heat-tolerant low-chalky rice variety; The nucleotide sequence of the MPC5 gene is shown in SEQ ID NO: 1.

[0007] Further, overexpression of the MPC5 gene promotes normal development of rice endosperm, reduces the average value of chalky grains and grain width, and increases the plasticity, and under high temperature conditions, the chalkiness is relatively low; or knocking out the MPC5 gene in rice leads to abnormal development of rice endosperm, increases the average value of chalky grains and grain width, and reduces the plasticity.

[0008] The application also provides a method for promoting endosperm normal development of rice, inhibiting chalkiness formation of rice, improving grain quality of rice and / or cultivating high-temperature-tolerant rice varieties, wherein a MPC5 overexpression vector is constructed in rice or an allelic complementation vector is constructed by using allelic whole gene sequences, and the nucleotide sequence of the MPC5 gene is shown as SEQ ID NO:1.

[0009] Further, the method comprises the following steps: (1) constructing a MPC5 gene overexpression vector or an allelic complementation vector by using allelic whole gene sequences; (2) introducing the recombinant vector of step (1) into rice callus by means of agrobacterium-mediated method, and obtaining transgenic plants after culture; (3) obtaining positive transgenic plants by using hygromycin marker screening, and further obtaining positive plants overexpressing MPC5 by using RT-PCR method.

[0010] Further, the primers used in the RT-PCR are F: CCGACTACGACTGGTGCGC (SEQ ID NO:3) and R: CTCTGCGAACGCACCTTCGC (SEQ ID NO:4).

[0011] The application also provides application of the reagent for detecting MPC5 gene haplotype in any one of the following: B1) identifying or assisting in identifying endosperm development of rice seeds; B2) preparing products for identifying or assisting in identifying endosperm development of rice seeds; B3) identifying or assisting in identifying chalkiness rate, chalkiness area and / or chalkiness degree of rice seeds; B4) preparing products for identifying or assisting in identifying chalkiness rate, chalkiness area and / or chalkiness degree of rice seeds; B5) cultivating high-temperature-tolerant and / or high-quality rice varieties; B6) preparing products for cultivating high-temperature-tolerant and / or high-quality rice varieties; The MPC5 gene haplotype is divided according to the polymorphism of 22 common SNPs, and the reference genome is MSU version 6.0, and the physical positions are 505359498; 505359576; 505359659; 505361254; 505361872; 505363589; 505364539; 505364742; 505365234; 505368128; 505368197; 505368290; 505369089; 505369533; 505369780; 505370584; 505370884; 505371020; 505371694; 505373702; 505373728; 505374146, and when the nucleotides are AGCCGGTCGGACTTGGACATAA in turn, it is haplotype Hap1, when the nucleotides are GATTAAGTAAGAAAAAGTGCGG in turn, it is haplotype Hap2, and when the nucleotides are AGCCGATTAAGAAAAAGTGCGC in turn, it is haplotype Hap3.

[0012] Further, the rice plant of haplotype Hap2 or Hap3 has a lower MPC5 expression level, and further shows that the chalkiness and the average value of grain width are higher, and the plasticity is lower, and the tolerance to high temperature is poorer; the rice plant of haplotype Hap1 has a higher MPC5 expression level, and further shows that the chalkiness and the average value of grain width are lower, and the plasticity is higher, and the tolerance to high temperature is better.

[0013] Beneficial effects: the MPC5 gene identified in the application is a major gene for controlling the average value of chalkiness and plasticity found on the basis of a large number of QTLs and SNPs identified by using multi-year multi-point GWAS, and is an important target gene for breeding high-quality rice varieties with high temperature resistance, and has wide application value; the application discloses a unique molecular mechanism of MPC5 in regulating chalkiness plasticity, and provides important theoretical support for exploring the interaction between genotype and environment and its application in breeding. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiments will be briefly introduced below, and it should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0015] Figure 1 The technical flow chart of the application.

[0016] Figure 2Natural variation of 533 rice grain chalkiness under five-year environments. a-c: Natural variation of grain white belly rate (WBR), white core rate (WCR), white belly area (WBA), white core area (WCA), white belly degree (WBD), and white core degree (WCD); d-f: Correlation of grain WBR, WCR, WBA, WCA, WBD, and WCD. WBR, white belly rate; WCR, white core rate; WBA, white belly area; WCA, white core area; WBD, white belly degree; WCD, white core degree; FER, floury endosperm rate.

[0017] Figure 3 Phenotypic plasticity of rice chalkiness under five-year environments. a: Phenotypic description and variation components of 10 grain chalkiness traits under five-year environments; SD, standard deviation; CV, coefficient of variation; b, c: Dispersion quartile coefficient and PVE estimation of phenotypic mean for linear and nonlinear plasticity of 10 rice chalkiness phenotypes; d, e: Trends of GCA, GCD, and GCR in the process of rice breeding improvement identified by phenotypes under five-year environments; f: Trends of chalkiness phenotypic plasticity from 1950 to 1990.

[0018] Figure 4 QTL mapping and H-QTL screening for rice conditional GWAS. a: QTL mapping of phenotypic mean, phenotypic plasticity, environment-specific phenotype, and condition-specific phenotype of rice grain chalkiness; b: H-QTL screening.

[0019] Figure 5 Minimal marker set for molecular breeding of rice chalkiness quality. a: Minimal representative SNPs identified by LASSO regression; b: Minimal marker set identified by BLUP; average phenotype (purple), linear plasticity (yellow), and nonlinear plasticity (green) of candidate genes. Each dot in the plot represents a SNP.

[0020] Figure 6 Functional validation of phenotypic mean and plasticity of MPC5 transgenic materials. a-d: Identification of a common major gene MPC5 for phenotypic mean and plasticity of rice grain chalkiness rate; e: Trends of mean, linear plasticity, and nonlinear plasticity of grain chalkiness rate among different genotypes of MPC5; f, g: Grain chalkiness and kernel width phenotypes of two complementary lines and three OE lines of SLG; h, i: Comparison of chalkiness phenotype and its plasticity between wild type ZH11 and knock-out line CR of MPC5.

[0021] Figure 7: Expression changes and plasticity of MPC5 in rice endosperm and young panicle under high and normal temperature conditions. a: The maximum, minimum and average values of air temperature during rice grain filling stage in Wuhan in 2012-2014 and 2017; b: Comparison of chalkiness, chalkiness area and chalkiness rate of 533 rice in 2013 and 2014; c: Three grain chalkiness phenotypes under four temperature environments; d: Pearson correlation coefficient (PCC) of minimum, average and maximum air temperature with chalkiness, chalkiness area and chalkiness rate; e: Phenotypic plasticity represented by coefficient of variation (CV) of grain chalkiness under four temperature environments; f: PCC of minimum, average and maximum air temperature with CV of chalkiness, chalkiness area and chalkiness rate; g: Physical location and nucleotide sequence of three haplotypes of MPC5; h: Chalkiness phenotype and plasticity of different haplotypes of MPC5 in 533 rice under five-year environments; i: qRT-PCR detection of expression changes of MPC5 in rice endosperm and young panicle under high and normal temperature conditions; j: RNA-seq data analysis of expression changes of MPC5 in rice endosperm and young panicle under high and normal temperature conditions. DETAILED DESCRIPTION

[0022] The following examples are only used to more clearly illustrate the technical solutions of the present application, and therefore are only examples, and cannot be used to limit the protection scope of the present application. It should be noted that, unless otherwise specified, the technical terms or scientific terms used in the present application should be the common meanings understood by the skilled in the art to which the present application belongs. Unless otherwise specified, the reagents, methods and devices used in the present application are the conventional reagents, methods and devices in the art. Unless otherwise specified, the reagents and materials used in the following examples are commercially available.

[0023] EXAMPLE 1. Analysis of plasticity of rice chalkiness phenotype 1. Variance analysis and heritability analysis of rice chalkiness phenotype data To investigate the relationship between rice chalkiness and environmental changes, 533 rice germplasm resources from all over the world were tested in the field for 5 years under different natural environments, and their grain chalkiness phenotype was measured. Statistical analysis was conducted on the total chalkiness rate, area and degree of rice germplasm resources, as well as three independent chalkiness types (back white type, belly white type, and heart white type). R language (version 4.0.0) was used to statistically analyze the rice chalkiness data. First, Shapiro-Wilk test was used to detect whether the grain chalkiness phenotype data conforms to the normal distribution. The part of the phenotype data that does not conform to the normal distribution is fitted with a linear mixed model using the lme4 package. Then, the effects of different variances and their interactions (i.e., genotype and environment) on various rice chalkiness phenotypes are evaluated. The model formula is: Chalkiness ~ (1|Line) + (1|Env) + (1|Line:Env). The significance LRT statistical test of random effects is performed using the ranova() function in the lmerTest package. The formula for testing heritability is Hap3 = V g / (V g + V E + V GE / m + V e / n*m), where "m" represents the number of environments, and "n" represents the number of individuals.

[0024] Considering that chalky endosperm is an extreme phenotype of grain chalkiness, with chalkiness area and degree almost 100%, only the floury endosperm rate (FER) was used for measurement. The heatmap based on the phenotype values showed that there was a huge natural variation in grain chalkiness degree indicators among the 533 materials, and the materials with similar phenotypic trends in 5 years could be clustered together (Figure 2a-c). Correlation analysis among the 5 different environments also showed that there was a high correlation between grain chalkiness rate, area and chalkiness degree (Figure 2d-f). These results showed that the grain chalkiness trait had a huge natural variation in the micro-core group and was suitable for analyzing the genetic basis of grain chalkiness.

[0025] 2. Phenotypic plasticity analysis The SNPs data of rice core germplasm can be found at http: / / ricevarmap.ncpgr.cn / download / . The Bayesian Finlay-Wilkinson Regression (FWR) equation in the FW package was used to evaluate the phenotypic plasticity of grain chalkiness (Kusmec et al., 2017). The parameters of the genotype-specific FWR equation evaluated by the FW package are as follows: A = H = I, where ij represents the phenotypic value of the ith QTL measured in the jth environment, g irepresents the average phenotypic value of the genotype, bi and (1 + bi) represent the linear response of the genotype to the environment, and h j Indicates the main effect in environment j, ɛ ij This indicates a nonlinear response.

[0026] y ij = μ +g i + (1+b) i h j + ɛ ij To further verify the pleiotropic effect of grain width on chalkiness, the Pearson correlation coefficient was used to test the correlation between grain width and chalkiness phenotype, and the Wilcoxon rank-sum test was used to verify the effect of the major grain width gene GWC5 on grain chalkiness.

[0027] By examining the coefficients of variation (CV) of 10 chalkiness traits over a 5-year environmental period, as well as the variance components of genotype and environment G×E interactions (see appendix) Figure 3 a) The results showed that the CV values ​​of the 10 chalkiness traits ranged from 0.53 to 3.29, indicating that there was significant variation in various chalkiness traits among the 533 accessions under five different environments. Furthermore, the linear mixture model showed significant differences in variance among all genotypes, environments, and G×E interactions (P < 0.001). In addition, the broadly heritable value (HAP3) of the chalkiness trait ranged from 0.64 to 0.85, indicating that various chalkiness traits have a rich genetic basis. In conclusion, the phenotypic plasticity of chalkiness traits in rice grains is significant and genetically controlled.

[0028] To further explore the phenotypic plasticity of chalky grains in rice, we decomposed it into three subphenotypes: phenotypic mean, linear plasticity (LP), and nonlinear plasticity (NLP) analysis. The quartile dispersion coefficient (QCD) was used to assess the dispersion of phenotypic values ​​for 10 chalky grain traits in 533 accessions under 5 years of environmental conditions. The results showed significant differences in phenotypic plasticity among the 10 chalky grain traits, with most traits exhibiting the highest phenotypic mean distribution, reflecting the differences in genotype adaptability to different environments (see appendix). Figure 3 b). Further analysis using genome-wide SNPs to assess the phenotypic variance explained (PVE) of phenotypic means and plasticity revealed that the PVE for all phenotypic means and most nonlinear plasticities exceeded 50%, with PVEs for Mean, LP, and NLP ranging from 61-93%, 60-80%, and 43-79%, respectively (see appendix). Figure 3c) Furthermore, the PVE value of the phenotypic mean in the chalky grain trait was high, while the PVE value of LPs was low, indicating an inverse effect between phenotypic mean and linear plasticity, mainly controlled by genetic factors. To understand the artificial selectivity of rice breeding for the chalky grain trait, phenotypic plasticity analysis of local varieties and core bred varieties was conducted. It was found that the chalky area, chalkiness, and chalkiness rate of the core varieties were significantly lower than those of the local varieties (see Appendix). Figure 3 (d) indicates that grain chalkiness is an important target for rice improvement, and in addition to the high linear and nonlinear plasticity of the chalkiness rate, the phenotypic mean and plasticity from local varieties to cultivated varieties are also significantly reduced (see appendix). Figure 3 e). Furthermore, analyses from the 1950s to the 1990s showed a simultaneous decrease in the average chalky area and chalkiness, as well as linear and nonlinear plasticity, while the average chalkiness rate decreased, but linear and nonlinear plasticity increased, consistent with cultivation-local comparisons (see appendix). Figure 3 f). This demonstrates the potential to further improve grain quality during rice genetic improvement by simultaneously reducing the average chalkiness rate and plasticity.

[0029] 3. Genome-wide association study of chalky phenotype in rice Genome-wide association study (GWAS) analysis was performed on sequencing data from 529 materials. First, SNPs with a minor allele frequency (MAF) below 5% were filtered out, leaving 4,131,700 SNPs for subsequent analysis. GWAS analysis was performed using Factored Spectally Transformed Linear Mixed Models (FaST-LMM) (Lippert et al., 2011). The Bonferroni method was used to correct for genome-wide significance thresholds (i.e., corrected P = 0.05 / n, where n is the number of independent SNPs in the entire genome) and genome-wide significance levels of grain chalkiness. GEMMA (Zhou & Stephens, 2012) was used to assess the heritability and PVE of genome-wide SNPs in chalkiness under different environments.

[0030] The results showed that a multi-conditional GWAS was performed using 533 materials and 4,131,700 SNPs from 5 years of field phenotypes, and the identified QTLs were divided into 5 categories: (1) phenotypic mean; (2) linear and nonlinear plasticity QTLs; (3) environment-specific QTLs, representing the phenotype of an individual in a specific year; (4) condition-specific QTLs, referring to the indica / japonica subspecies; and (5) grain shape QTLs for traits such as grain length, grain width, and length-width ratio. A total of 1,702 redundant QTLs were identified, of which 1,587 were related to grain chalkiness: phenotypic mean (77 QTLs), phenotypic plasticity (107 QTLs), environment-specific phenotype (333 QTLs), and condition-specific phenotype (1,070 QTLs), as well as 115 QTLs related to rice grain shape (see appendix). Figure 4 a) Based on the overlap between QTLs, the number of QTLs with at least two overlaps was reduced to 317 hotspot QTLs. Among them, 129 H-QTLs covered more than three rice chalkiness screening types, suggesting that these 129 H-QTLs are reliable QTLs for the genetic basis of rice chalkiness. Further, the five H-QTLs with overlapping taxa were identified as having six common H-QTLs: H-QTL144, H-QTL172, H-QTL195, H-QTL149, H-QTL76, and H-QTL210. H-QTL144 covered the most QTLs (147 QTLs) (see appendix). Figure 4 b).

[0031] To screen for the minimal SNP combination controlling the chalky grain phenotype, we used genome-wide SNPs and determined the most important SNPs for a single phenotype using LASSO regression. Then, we continuously removed collinear variables and explored multiple linear models to predict the phenotype using the filtered SNPs. The results showed that SNPs explaining different trait PVEs ranged from 26.0% to 74.2% across various genes, with an average PVE of 48.8% (see appendix). Figure 5 a). Further analysis of multi-environmental phenotypes was conducted using Optimal Linear Unbiased Prediction (BLUP), and LASSO was used to identify the minimal marker set for grain chalkiness. The results showed that we identified 37, 20, and 23 representative SNPs responsible for chalkiness degree, chalkiness rate, and chalkiness area, respectively (see attached diagram). Figure 5 (b) These SNPs explained 83.7%, 69.3%, and 67.7% of the PVEs for chalkiness, chalkiness rate, and chalkiness area, respectively. These results provide a reasonable number of predictable SNPs with PVEs greater than 2 / 3, demonstrating the feasibility and rationality of grain quality breeding strategies based on phenotypic mean and plasticity. The reference genome for the SNPs involved is MSU rice pseudomolecule release 6.0 (MSU version 6.0).

[0032] To identify the key hotspot QTLs responsible for chalkiness within the core H-QTL144 coverage area, we found that H-QTL144 covers three representative QTLs (L1587 (phenotypic average), L1580 (linear plasticity), and L1596 (nonlinear plasticity)) (see appendix). Figure 6 a). Among these three QTLs, we identified 22 of the most significant shared SNPs (see appendix). Figure 6 b). Each SNP exhibits an inverse phenotypic effect between the phenotypic mean and the two plasticity phenotypes (β value of GWAS) (see appendix). Figure 6 c). Given the phenotypic effects and overall trends exhibited by all SNPs located to the left of the breakpoint at 5371020bp - 5371694bp (MSU ver.6) (see appendix) Figure 3 The similarity between b and c indicates that the pathogenic gene is located to the left of the breakpoint.

[0033] Haplotype analysis using 22 of the most significant shared SNPs identified three haplotypes (HAP1-HAP3). Further investigation of the phenotypes of these three haplotypes using the 22 SNPs revealed similar opposing trends: Hap1 had the lowest phenotypic mean, followed by Hap2, while Hap3 had the highest. Furthermore, the trends of linear and nonlinear plasticity were opposite to the phenotypic mean. (See appendix) Figure 6 d). Because only one gene, MPC5 / GSE5 / GW5 (LOC_Os05g09520), is annotated within the 22 SNP haplotype regions to the left of the breakpoint (see appendix). Figure 6 c) The role of MPC5 / GSE5 / GW5 was validated using min-core collection and transgenic materials (see appendix). Figure 6 Analysis of the mean, linear plasticity (LP), and nonlinear plasticity (NLP) of the chalkiness rates of the gw5 and GW5 genotypes in the core sample revealed that the mean trend was opposite to that of LP and NLP, consistent with the trends of the three haplotypes (see appendix). Figure 6 d,e).

[0034] The relationship between temperature fluctuation and grain chalkiness was assessed using four years of temperature data from the grain-filling stage of paddy rice in Wuhan. The highest daily temperature fluctuation was observed in 2013, while the lowest was observed in 2014. Comparing the chalkiness of rice in 2013 (higher temperature) and 2014 (lower temperature), which showed significant temperature differences, revealed that 40.0%, 67.6%, and 72.4% of the 533 plant samples showed significant increases in chalkiness rate, chalkiness area, and chalkiness degree, respectively. Comparison of the overall phenotypes of chalkiness degree, chalkiness area, and chalkiness rate over the four years showed that the chalkiness trend was consistent with temperature changes (Figures 7a-c). Pearson correlation coefficient (PCC) analysis revealed a strong positive correlation between all three grain chalkiness phenotypes and air temperature, particularly the maximum air temperature (PCC≈1, P = 0.03) (Figure 7d). Further analysis using the coefficient of variation (CV), an index of phenotypic plasticity, showed that the CV trend was opposite to the trends of grain chalkiness and air temperature changes (Figures 7a, c, e). Meanwhile, the PCC of temperature with the CV of chalkiness, chalkiness area, and chalkiness rate also showed a strong negative correlation (<-0.95) (Figure 7f). To further verify the GCR phenotypes of the three haplotypes of MPC5 under different environments, haplotype analysis of MPC5 was first performed using 22 SNPs, dividing it into three haplotypes (Hap1-Hap3), with MSU as the basis. Version 6.0 is the reference genome, with physical locations of 505359498; 505359576; 505359659; 505361254; 505361872; 505363589; 505364539; 505364742; 505365234; 505368128; 505368197; 505368290; 505369089; 505369533; 505369780; 505370. The nucleotides 584; 505370884; 505371020; 505371694; 505373702; 505373728; and 505374146, when their sequence is AGCCGGTCGGACTTGGACATAA, represent haplotype Hap1; when their sequence is GATTAGTAAGAAAAAGTGCGG, they represent haplotype Hap2; and when their sequence is AGCCGATTAAGAAAAAGTGCGC, they represent haplotype Hap3. (See appendix) Figure 7 g), and analyzed the chalkiness rate phenotypes of the three haplotypes of MPC5 in six environments and the variance in five environments using phenotypic data from 533 materials (see appendix). Figure 7The results confirmed the inverse trend between chalkiness rate and variance of the three haplotypes of MPC5. Haplotype Hap1 rice plants had higher MPC5 expression levels, resulting in lower average chalkiness and grain width, higher plasticity, and better tolerance to high temperatures. In contrast, haplotypes Hap2 and Hap3 rice plants had lower MPC5 expression levels, resulting in higher average chalkiness and grain width, lower plasticity, and poorer tolerance to high temperatures. The results also reinforced the antagonistic effect of H-QTL144 on the average chalkiness rate phenotype and plasticity.

[0035] 4. MPC5 Function Verification To confirm the role of GSE5 / GW5 in grain chalkiness plasticity, we constructed complementary and overexpression lines of GSE5 / GW5 in flour endosperm with nonfunctional GW5 alleles and in the background of the wide-grain variety SLG. The overexpression plasmid proActin:GSE5 used for MPC5 genetic transformation experiments was provided by Professor Li Yunhai's research group at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. The coding sequence of MPC5 was amplified using specific primers cGSE5-F / R and cloned into the pIpkb003 vector using In-Fusion enzyme to generate the proActin:GSE5 plasmid. A 488 bp sequence was amplified from the PCR products of crGSE5-1 and crGSE5-2 using crGSE5-1F and crGSE5-2R and cloned into the vector pMDC99-Cas9 using In-Fusion enzyme to generate the CRISPR / Cas9-gse5 plasmid. Agrobacterium-mediated transgenic methods were used to transfer knockout and overexpression vector plasmids into Agrobacterium GV3101 via electroporation. Using the Agrobacterium-mediated rice genetic transformation protocol, the vectors were introduced into callus tissue of the Zhonghua 11 rice variety. Using the Agrobacterium-mediated rice genetic transformation protocol, the overexpression vector plasmids were transferred into Agrobacterium EHA105 via electroporation. Using the Agrobacterium-mediated rice genetic transformation protocol, the vectors were introduced into callus tissue of the SLG rice variety. Wild-type seeds were induced and subcultured to obtain non-resistant callus tissue. After Agrobacterium infection, co-culture, and selection, hygromycin-resistant callus tissue was obtained. Following differentiation, rooting, and hardening-off, transgenic rice plantlets were obtained. Primer sequences are shown in Table 1.

[0036] Table 1 The results showed that, compared with the negative transgenic control, the complementary line and the OE line were more effective in Hainan in 2022 (see attached). Figure 6 f) and 2023 Wuhan (attached) Figure 6g) Both conditions significantly reduced grain chalkiness and grain width, confirming the novel function of GSE5 / GW5 in rice grain chalkiness. Furthermore, we examined the chalkiness rate and coefficient of variation (CV) of the wild-type (ZH11) and knockout (CR) GW5 lines in an 8-year field trial (see appendix). Figure 6 It is worth noting that the CR line exhibited higher grain chalkiness and lower CV than ZH11 (see appendix). Figure 6 These results confirm that GSE5 / GW5 is the main pathogenic gene causing the antagonistic effect between the mean chalkiness phenotype and plasticity in grains. Therefore, we renamed GSE5 / GW5 to MPC5 (Mean and Plasticity of grain Chalkiness on chromosome 5), with its nucleotide sequence shown in SEQ ID NO:1 and its protein sequence shown in SEQ ID NO:2.

[0037] RNA-Seq data from endosperm and young spikes under high and normal temperature conditions were used, and qRT-PCR was used to detect changes in MPC5 expression in young spikes and endosperm samples under high temperature (36°C) and normal temperature (27°C) conditions. The results showed that the expression level of MPC5 was significantly increased under high temperature conditions (Figures 7i,j), which further proved the new function of MPC5 in regulating the chalky phenotype of grains and its interaction with ambient temperature.

[0038] The above detailed embodiments describe the implementation of the present invention; however, the present invention is not limited to the specific details described in the above embodiments. Within the scope of the claims and technical concept of the present invention, various simple modifications and changes can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

Claims

1. Use of a MPC5 gene, an expression cassette containing the same, an expression vector or a recombinant microorganism in any of the following A1) to A6): A1) regulating endosperm development of rice grains; A2) preparing a product for regulating endosperm development of rice grains; A3) regulating chalkiness rate, chalkiness area and / or chalkiness degree of rice grains; A4) preparing a product for regulating chalkiness rate, chalkiness area and / or chalkiness degree of rice grains; A5) breeding a high-temperature-tolerant rice variety; A6) preparing a product for breeding a high-temperature-tolerant rice variety; The nucleotide sequence of the MPC5 gene is shown in SEQ ID NO:

1.

2. Use according to claim 1, characterized in that, Overexpression of the MPC5 gene promotes normal endosperm development of rice, reduces grain chalkiness and average grain width, and increases plasticity, and exhibits relatively low chalkiness degree under high temperature conditions; or knockout of the MPC5 gene in rice further causes abnormal endosperm development of rice, increases grain chalkiness and average grain width, and reduces plasticity.

3. A method for promoting normal development of endosperm, inhibiting chalk formation, improving grain quality and / or breeding high temperature tolerant rice varieties, characterized by, An MPC5 overexpression vector is constructed in rice or an allelic complementation vector is constructed using allelic whole gene sequences, and the nucleotide sequence of the MPC5 gene is shown in SEQ ID NO:

1.

4. The method of claim 3, wherein, The method comprises the following steps: (1) constructing an MPC5 gene overexpression vector or an allelic complementation vector using allelic whole gene sequences; (2) introducing the recombinant vector of step (1) into rice callus by Agrobacterium-mediated method, and obtaining transgenic plants after culture; (3) obtaining positive transgenic plants by hygromycin marker screening, and further obtaining MPC5 overexpression positive plants by RT-PCR method.

5. The method of claim 4, wherein, The primers used in RT-PCR are shown in SEQ ID NO: 3-4.

6. Use of a reagent for detecting MPC5 gene haplotype in any of the following: B1) identifying or assisting in identifying endosperm development of rice grains; B2) preparing a product for identifying or assisting in identifying endosperm development of rice grains; B3) identifying or assisting in identifying chalkiness rate, chalkiness area and / or chalkiness degree of rice grains; B4) preparing a product for identifying or assisting in identifying chalkiness rate, chalkiness area and / or chalkiness degree of rice grains; B5) breeding a high-temperature-tolerant and / or high-quality rice variety; B6) preparing a product for breeding a high-temperature-tolerant and / or high-quality rice variety; The MPC5 gene haplotype is divided according to the polymorphism of 22 common SNPs, and the reference genome is MSU version 6.0, and the physical positions are 505359498; 505359576; 505359659; 505361254; 505361872; 505363589; 505364539; 505364742; 505365234; 505368128; 505368197; 505368290; 505369089; 505369533; 505369780; 505370584; 505370884; 505371020; 505371694; 505373702; 505373728; 505374146, and when the nucleotides are AGCCGGTCGGACTTGGACATAA in turn, it is haplotype Hap1, when the nucleotides are GATTAAGTAAGAAAAAGTGCGG in turn, it is haplotype Hap2, and when the nucleotides are AGCCGATTAAGAAAAAGTGCGC in turn, it is haplotype Hap3.

7. Use according to claim 6, characterized in that, The rice plant of haplotype Hap2 or Hap3 has a lower MPC5 expression level, and further shows that the chalkiness and the average value of grain width are higher, the plasticity is lower, and the tolerance to high temperature is poorer; the rice plant of haplotype Hap1 has a higher MPC5 expression level, and further shows that the chalkiness and the average value of grain width are lower, the plasticity is higher, and the tolerance to high temperature is better.

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