Molecular breeding chip for accurately identifying cold tolerance of rice in cold region and application of molecular breeding chip

Abstract

The invention provides a molecular breeding chip for accurate identification of cold tolerance of rice in cold regions and application, the chip comprises 400-550 functional verified SNP sites, and the SNP sites are divided into a bud stage, a seedling stage and a booting stage obstacle cold injury module and cover a key cold sensitive stage in a whole growth period. On the basis of omics and phenotypic data construction of cold region core germplasm at multi-gradient low temperature, the chip disclosed by the invention calculates a whole-growth-period cold resistance index CCTI through high-throughput genotyping in combination with a weighting algorithm, so that quantitative grading of cold resistance and accurate typing of cold damage types are realized. The method can be widely applied to germplasm evaluation, parent matching, progeny early selection and variety region adaptation, the cold region rice cold-tolerant breeding efficiency and accuracy are remarkably improved, the breeding period is shortened by 2-3 years, and a core technical support is provided for guaranteeing stable yield of high-latitude / high-altitude rice regions.

Description

Technical Field

[0001] This invention relates to the field of rice molecular breeding technology, and more specifically, to a molecular breeding chip and its application for the precise identification of cold resistance in cold-region rice. Background Technology

[0002] As the staple crop for more than half of the world's population, the stability of rice production is directly related to national food security. However, rice is a typical warm-season crop and is extremely sensitive to low-temperature stress, especially in cold-region rice-growing areas at high latitudes or high altitudes, such as the Northeast Plain, the Sanjiang Plain, and the Yunnan-Guizhou Plateau in China. In spring, the rice often encounters late frosts during the sowing period, leading to chilling injury during the germination and seedling stages. If early frost or prolonged low temperatures occur before or after heading in autumn, it can easily cause chilling injury that hinders the booting stage, resulting in pollen abortion and a sharp drop in the seed setting rate. In severe years, yield reduction can reach 30%–50%.

[0003] Traditional methods for identifying cold tolerance mainly rely on field observations of natural chilling injury or simulated stress in artificial climate chambers. These methods have limitations, including long cycles, high costs, poor reproducibility, and difficulty in distinguishing different types of chilling injury. In recent years, marker-assisted selection (MAS) and genomic selection (GS) have provided new pathways for cold-tolerant breeding. Several cold-tolerant QTLs / genes have been identified, such as qLTG3-1, which controls cold tolerance during the bud stage; OsDREB1A, which regulates resistance during the seedling stage; and CTB4a, which determines cold tolerance during the booting stage. Some SNP markers have also been developed.

[0004] However, existing molecular tools generally suffer from three major shortcomings: 1. Incomplete coverage: Most markers only target a single growth stage, such as only the budding stage or only the heading stage, lacking a systematic integration of cold-sensitive stages throughout the entire growth period; 2. Weak regional adaptability: Most general-purpose breeding chips are developed based on tropical or subtropical materials, without fully considering the genetic background and low-temperature response mechanism of core germplasm in cold regions, resulting in a significant decrease in prediction accuracy in regions such as Northeast China and Yunnan-Guizhou. 3. Lack of functional differentiation capability: The inability to distinguish the tolerance mechanisms of materials to the effects of growth-delayed chilling injury on vegetative growth and reproductive-disorder chilling injury on abnormal floral organ development restricts precise parental selection and targeted improvement. Therefore, a molecular breeding chip for precise identification of cold tolerance in cold-resistant rice and its application are proposed. Summary of the Invention

[0005] The purpose of this invention is to address the problems raised in the existing background technology. To achieve the above-mentioned objective, this invention provides the following technical solution: a molecular breeding chip for precise identification of cold tolerance in cold-resistant rice, wherein the chip contains 400–550 single nucleotide polymorphism (SNP) molecular marker sites, which are obtained based on the joint analysis and screening of transcriptomic and phenotypic data of core cold-resistant rice germplasm under multi-gradient low-temperature stress conditions, and are divided into the following three functional modules: (a) Cold tolerance module for germination, containing 120–160 SNP sites, is used to evaluate the germination ability and seedling vigor of rice seeds at low temperatures of 5–10°C. (b) Seedling cold tolerance module, containing 130–180 SNP loci, is used to predict the survival rate and growth potential of rice at a sustained low temperature of 10–15°C from the three-leaf stage to the tillering stage; (c) Cold damage module during the booting stage, containing 150–210 SNP loci, is used to identify pollen fertility and seed setting potential when rice is exposed to temperatures below 17°C 15 days before heading.

[0006] As a preferred technical solution of the present invention, the SNP sites are distributed on all 12 chromosomes of rice, covering known cold-resistant related functional genes and their regulatory regions, including but not limited to OsDREB1A, OsTPP1, CTB4a, qLTG3-1, OsMYB30 and OsSAPK8.

[0007] As a preferred technical solution of the present invention, the SNP sites are all selected and confirmed by linkage disequilibrium analysis of natural populations of cold-region rice with n≥500, genome-wide association analysis (GWAS), and at least one functional verification method. The functional verification method includes gene knockout, overexpression, allelic complementation experiment, or eQTL co-localization analysis.

[0008] As a preferred technical solution of the present invention, the chip is constructed using a high-throughput genotyping platform, which includes one of Illumina Infinium XT, Affymetrix Axiom, or Thermo Fisher TaqMan OpenArray.

[0009] The application of a molecular breeding chip in the evaluation of cold tolerance of cold-resistant rice germplasm resources involves genotyping the rice materials under test, calculating the cold tolerance index throughout the entire growth period using a preset weighting algorithm, and outputting cold tolerance scores for the budding, seedling, and booting stages, thereby achieving a quantitative classification of the material's cold tolerance.

[0010] As a preferred technical solution of the present invention, the CCTI is calculated by a weighted linear regression model, and the weights of each module are dynamically adjusted according to the main chilling injury types in the target ecological zone. The basic weights of the budding stage, seedling stage, and booting stage modules are 0.3, 0.3, and 0.4, respectively.

[0011] The application of the molecular breeding chip in the selection of parental lines for cold-resistant rice involves prioritizing the selection of two parents with scores above a threshold of ≥0.8 in the corresponding functional module for hybridization, based on the main cold damage risk type in the target planting area, in order to aggregate cold-resistant alleles at different growth stages.

[0012] An application of the aforementioned molecular breeding chip in the early selection of offspring of cold-resistant rice: In the F2, BC1F1 or subsequent segregating generations, the chip is used to perform high-throughput typing of individual plants, and individuals with CCTI scores below a preset threshold or unqualified key module scores are eliminated, thereby accelerating the breeding process of cold-resistant homozygous lines.

[0013] The application of the aforementioned molecular breeding chip in the regional adaptability assessment of new cold-region rice varieties uses the chip typing results as the molecular basis for variety approval or promotion decisions, and helps to delineate the range of varieties suitable for planting in specific cold-region rice-growing areas such as the Northeast Plain, the Sanjiang Plain, and the Yunnan-Guizhou Plateau.

[0014] A cold tolerance prediction system constructed from the molecular breeding chip, comprising: a genotyping module for acquiring genotyping data of the rice sample to be tested at the 400–550 SNP loci; The data processing module is used to call the pre-trained cold tolerance prediction model to calculate the CCTI and sub-scores for each reproductive stage. The output module generates cold tolerance level reports and breeding recommendations. The system is deployed on a local server or cloud platform.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention has high prediction accuracy: The transcriptome and multi-year phenotypic data of the 400-550 SNP loci contained in the chip in the core germplasm of typical cold rice growing areas under real low temperature gradients, after functional verification and population verification, ensure the accuracy of cold tolerance prediction in the target ecological area, which is significantly better than the existing general chips.

[0016] Achieving integrated assessment of cold tolerance throughout the entire growth period: For the first time, molecular marker systems for the three cold-sensitive stages of budding, seedling, and heading stages are integrated into a single chip, breaking through the limitations of traditional single-point evaluation and providing breeders with full-process cold tolerance assurance from sowing to heading.

[0017] It has the ability to accurately classify chilling injury types: Through modular design, it can clearly distinguish the response characteristics of materials to delayed chilling injury affecting germination and seedling growth and barrier chilling injury leading to pollen abortion. It supports customized parent selection on demand, such as focusing on cold resistance during the seedling stage in Heilongjiang and focusing on cold resistance during the heading stage in Guizhou.

[0018] Significantly improves breeding efficiency and accuracy: High-throughput cold tolerance screening can be completed in F2 or earlier generations, sensitive individuals can be eliminated, field testing workload can be reduced by more than 60%, and the breeding cycle can be shortened by 2-3 years.

[0019] Effectively mitigate regional yield reduction risks: By identifying cold-sensitive genotypes in advance, losses from disasters such as spring seedling rot and autumn empty husks can be significantly reduced, providing molecular insurance for cold-region rice production and contributing to the implementation of the national strategy of "storing grain through technology".

[0020] Supports intelligent breeding decision-making: Combines preset algorithms to automatically generate the cold tolerance index (CCTI) and grading report for the entire growth period, providing objective and quantifiable molecular basis for germplasm evaluation, variety approval, and regional promotion, and promoting the transformation of cold-region rice breeding towards digitalization and precision. Attached Figure Description

[0021] Figure 1 This is a data block diagram of the molecular breeding chip module provided by the present invention; Figure 2 A standard data flowchart for the cold tolerance index throughout the entire reproductive period provided by this invention; Figure 3 A data block diagram illustrating the chip prediction accuracy provided by this invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention.

[0023] Therefore, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely illustrates some embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention. It should be noted that, in the absence of conflict, the embodiments and features and technical solutions in the embodiments of the present invention can be combined with each other. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0024] Example 1: A molecular breeding chip for precise identification of cold tolerance in cold-resistant rice. The chip contains 400–550 single nucleotide polymorphism (SNP) molecular marker sites, which were obtained by joint analysis and screening of transcriptomic and phenotypic data of core cold-resistant rice germplasm under multi-gradient low-temperature stress conditions, and are divided into the following three functional modules: (a) Cold tolerance module for germination, containing 120–160 SNP sites, is used to evaluate the germination ability and seedling vigor of rice seeds at low temperatures of 5–10°C. (b) Seedling cold tolerance module, containing 130–180 SNP loci, is used to predict the survival rate and growth potential of rice at a sustained low temperature of 10–15°C from the three-leaf stage to the tillering stage; (c) Cold damage module during the booting stage, containing 150–210 SNP loci, is used to identify pollen fertility and seed setting potential when rice is exposed to temperatures below 17°C 15 days before heading.

[0025] SNP sites are distributed across all 12 chromosomes of rice, covering known cold-resistance-related functional genes and their regulatory regions. These functional genes include, but are not limited to, OsDREB1A, OsTPP1, CTB4a, qLTG3-1, OsMYB30, and OsSAPK8.

[0026] All SNP sites were selected and confirmed through linkage disequilibrium analysis of natural populations of cold-region rice with n≥500, genome-wide association analysis (GWAS), and at least one functional verification method, including gene knockout, overexpression, allelic complementation experiments, or eQTL co-localization analysis.

[0027] The chip was constructed using a high-throughput genotyping platform, which includes one of Illumina Infinium XT, Affymetrix Axiom, or Thermo Fisher TaqMan OpenArray.

[0028] The application of a molecular breeding chip in the evaluation of cold tolerance of cold-resistant rice germplasm resources involves genotyping the rice materials under test, calculating the cold tolerance index throughout the entire growth period using a preset weighting algorithm, and outputting cold tolerance scores for the budding, seedling, and booting stages, thereby achieving a quantitative classification of the material's cold tolerance.

[0029] CCTI calculates the weights of each module using a weighted linear regression model, with the weights dynamically adjusted based on the main chilling injury types in the target ecological zone. The basic weights for the budding stage, seedling stage, and booting stage modules are 0.3, 0.3, and 0.4, respectively.

[0030] The application of a molecular breeding chip in the selection of parental lines for cold-resistant rice: based on the main cold damage risk type in the target planting area, two parents with scores above the threshold of ≥0.8 in the corresponding functional module are preferentially selected for hybridization to aggregate cold-resistant alleles at different growth stages.

[0031] An application of a molecular breeding chip in the early selection of cold-resistant rice offspring: In the F2, BC1F1 or subsequent segregating generations, the chip is used to perform high-throughput genotyping on individual plants, and individuals with CCTI scores below a preset threshold or unqualified key module scores are eliminated, thereby accelerating the breeding process of cold-resistant homozygous lines.

[0032] The application of a molecular breeding chip in the regional adaptability assessment of new cold-region rice varieties uses the chip typing results as the molecular basis for variety approval or promotion decisions, and helps to delineate the range of varieties suitable for planting in specific cold-region rice-growing areas such as the Northeast Plain, the Sanjiang Plain, and the Yunnan-Guizhou Plateau.

[0033] A cold tolerance prediction system constructed from a molecular breeding chip includes: (a) a genotyping module for acquiring genotyping data of rice samples at 400–550 SNP sites; (b) Data processing module, used to call the pre-trained cold tolerance prediction model and calculate CCTI and sub-scores for each reproductive stage; (c) Output module, used to generate cold tolerance level reports and breeding recommendations, the system is deployed on a local server or cloud platform.

[0034] The molecular breeding chip for precise identification of cold tolerance in cold-resistant rice described in this invention is based on an integrated design approach that combines genotype, phenotype, and environment. Its working principle can be summarized as follows: taking cold-resistant ecological low-temperature stress as the core selection pressure, through omics and phenotypic big data mining under multiple growth stages and multiple gradient low temperatures, functional SNP sites highly associated with cold tolerance are identified, a modular molecular marker system covering key cold-sensitive stages of the entire growth period is constructed, and high-throughput genotyping and intelligent algorithms are used to achieve accurate prediction and genotyping of the cold tolerance of rice materials.

[0035] The specific workflow is as follows: 1. Site screening and functional verification, material selection: collect more than 500 representative core germplasm resources from typical cold-region rice-growing areas in Northeast China, including local varieties, backbone parents and wild rice derivatives, covering a wide range of genetic diversity.

[0036] Stress treatment and phenotypic data collection: A low-temperature scenario in a cold region was simulated in an artificial climate chamber, with low-temperature gradients set for three key growth stages. Bud stage: 5°C treatment for 72 hours, germination rate, bud length, and root vigor were measured; Seedling stage: 12°C for 7 consecutive days, record survival rate, chlorophyll content and biomass; During the booting stage: Plants were treated at 16°C 15 days before heading to assess pollen fertility, spikelet abortion rate, and seed setting rate.

[0037] Transcriptome sequencing and association analysis: RNA and seq were performed on each treatment group. Combined with phenotypic data, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) were conducted to identify candidate genes and regulatory regions that were significantly associated with the cold-resistant phenotype (P<0.001).

[0038] Functional validation: The causal role of candidate genes in low-temperature response was confirmed through CRISPR / Cas9 gene editing, overexpression or allelic complementation experiments, and 400–550 high-confidence SNP sites were finally screened.

[0039] 2. Modular chip design: Based on the differences in the timing and physiological mechanisms of chilling injury, SNP sites are divided into three functional modules: Cold tolerance module during germination: Focuses on genes related to seed germination energy metabolism, membrane stability and ABA signaling pathway, including qLTG3, 1 and OsTPP1, reflecting the material's ability to resist seed and bud rot; Seedling cold tolerance module: Enriched with genes encoding photosynthetic protection, reactive oxygen species scavenging and cold shock proteins, including OsDREB1A and OsSAPK8, to characterize the growth resilience of seedlings under sustained low temperatures; The chilling injury module during the booting stage targets key genes involved in anther development, sugar transport, and hormone balance, including CTB4a and OsMYB30, to predict the risk of low-temperature-induced pollen abortion.

[0040] Each module site is analyzed by LD decay to ensure independence and avoid redundancy, while covering the entire genome to ensure the generalization ability of the prediction model.

[0041] 3. Genotyping and Cold Tolerance Index Calculation Sample testing: DNA was extracted from the rice samples to be tested, and the SNP sites contained in the chip were genotyped using high-throughput platforms such as Illumina Infinium XT to obtain the allele combinations at 512 sites for each sample.

[0042] Scoring Modeling: Based on a historical phenotypic and genotypic database of a large cold-region population (n≥500), a weighted linear regression or machine learning prediction model, including XGBoost and Random Forest, is established. Each SNP is assigned a weight according to its effect size, and the scores within each module are normalized and then summed using a weighted average.

[0043] Output metrics: The CCTI (Comprehensive Cold Resistance Index) reflects the overall cold resistance level of a material, ranging from 0 to 1. ≥0.8 indicates high resistance, 0.6–0.8 indicates medium resistance, and <0.6 indicates sensitivity. Sub-item rating: Cold tolerance is given separately for the budding stage, seedling stage, and booting stage, allowing breeders to select according to their needs.

[0044] 4. Breeding decision support Germplasm evaluation: Rapid screening of potential new cold-tolerant resources in the germplasm bank; Parental selection: In the main promotion area of ​​Heilongjiang, priority is given to parents with high scores in both the budding and seedling stages; in the high-altitude areas of Guizhou, the focus is on high-scoring combinations in the heading stage. Offspring selection: Individuals with low CCTI or critical module defects can be eliminated in the F2 generation, reducing field testing costs; Variety promotion: Provide molecular adaptability labels for approved varieties to achieve precise promotion with a one-region-one-policy approach.

[0045] The working process of the molecular breeding chip for precise identification of cold tolerance in cold-region rice, as described in this invention, refers to the complete operational flow from the rice material to be tested to obtaining the assessment results of its cold tolerance throughout its entire growth period and guiding breeding decisions. This process integrates high-throughput molecular detection, bioinformatics analysis, and breeding applications, and specifically includes the following steps: Step 1: Sample Preparation The rice material to be tested can be seeds, seedling leaves or dry seeds for DNA extraction, and high-quality genomic DNA should be extracted. The DNA concentration and purity must meet the requirements of the microarray platform, including A260 / A280≈1.8 and concentration≥50 ng / μL. The samples can come from germplasm resource banks, breeding segregating populations F2, BC1F1, new lines or approved varieties.

[0046] Step 2: High-throughput genotyping The extracted DNA sample is loaded into the molecular breeding chip described in this invention, including construction based on the Illumina Infinium XT platform; DNA amplification, fragmentation, hybridization, single base extension and fluorescence scanning are completed using an automated liquid handling system; genotype data such as AA, AB, BB, etc. are obtained for each sample at 400-550 preset SNP sites; The data underwent quality control filtering, including a detection rate of >95% and consistency of duplicate samples of >99%, resulting in a standardized genotype matrix.

[0047] Step 3: Cold Resistance Score Calculation Import genotype data into a pre-trained cold tolerance prediction model and deploy it on a local server or cloud platform. The model automatically calculates the following based on the effect size β coefficient of each SNP locus in a large cold-region population and the module weights: Cold tolerance score during bud stage = Σ locus genotype code × bud stage weight; Seedling cold tolerance score = Σ locus genotype code × seedling weight; Cold tolerance score during the booting stage = Σ locus genotype code × booting weight; Based on the combined scores of the three modules, the Cold Tolerance Index (CCTI) for the entire reproductive period is calculated using the following formula: in, The default weights are 0.3, 0.3, and 0.4, but can be dynamically adjusted based on the cold damage risk in the target ecological zone. For example, in Northeast China, where cold damage is frequent in spring, the weights can be increased. .

[0048] Step 4: Result Analysis and Classification The system automatically generates a structured report, including: CCTI total score range of 0–1; Fertility scores for the three reproductive stages and their corresponding cold resistance levels: high resistance, moderate resistance, and sensitive; carrier status of key cold-resistant alleles, including whether they carry the qLTG3 and 1 favorable allele variants; The following criteria are used to classify resistance based on preset thresholds: Highly Tolerant: CCTI ≥ 0.8, and no module score < 0.7; Moderately Tolerant: 0.6 ≤ CCTI < 0.8. Sensitive: CCTI < 0.6, or key modules, including the spikelet score < 0.5.

[0049] Step 5: Breeding Application Decisions Based on the evaluation results, targeted breeding operations will be carried out: Germplasm resource screening: Rapidly identify superior cold-resistant germplasm with CCTI>0.85 from thousands of materials as new parents; Parental pairing optimization: If the target area is mainly characterized by cold damage during the booting stage, including the Yunnan-Guizhou Plateau, priority should be given to crossbreeding parents with a booting stage module score of >0.85. Early selection of offspring: In the F2 generation, 500 individual plants were genotyped using microarrays, and only individuals with CCTI>0.75 and no defects in the target module were retained to enter the next round of field testing, with a rejection rate of over 60%. Variety regional adaptation recommendations: Issue cold tolerance labels to approved varieties, such as suitable for the third accumulated temperature zone of Heilongjiang, but not recommended for planting in areas above 1800m altitude in Guizhou.

[0050] Step 6: Model Iteration and Update As new phenotypic data accumulates, including multi-year, multi-location field records of cold damage, it is periodically backflowed to verify the accuracy of chip predictions. If new cold-resistant genes or changes in site effects are discovered, the chip model can be upgraded by adding probes or updating weight parameters to ensure long-term applicability.

[0051] Example 2: Selection and mating of cold-resistant parental lines for cold-region rice based on molecular breeding chips In the Sanjiang Plain rice-growing area of ​​Heilongjiang Province, spring temperatures of 5–10°C often cause seed rot during the budding stage, while the heading stage in late July is susceptible to periods of low temperatures below 17°C, affecting the seed setting rate. To cultivate new varieties with cold tolerance during both the budding and heading stages, the breeding team used the molecular breeding chip described in this invention to conduct parental selection and mating.

[0052] First, 200 candidate parental materials were selected from the Cold Region Core Germplasm Bank, and high-throughput genotyping was performed using the Illumina Infinium XT platform to obtain genotypic data for 142 budding stage, 158 seedling stage, and 186 booting stage SNPs at 486 loci. Then, a preset weighted algorithm (0.3 for budding stage, 0.3 for seedling stage, and 0.4 for booting stage) was used to calculate the Comprehensive Cold Tolerance Index (CCTI) for each material, and sub-scores for each of the three growth stages were output.

[0053] Based on the risk characteristics of the Sanjiang Plain, which are mainly characterized by chilling injury during the budding stage and chilling injury during the booting stage, a score threshold of ≥0.8 was set for both the budding stage and booting stage modules. Two parental lines that simultaneously met both criteria were selected: Parent A had a budding stage score of 0.85, a booting stage score of 0.82, and a CCTI of 0.81; Parent B had a budding stage score of 0.88, a booting stage score of 0.86, and a CCTI of 0.85. Both lines carried the OsDREB1A cold tolerance allele, marked by the budding stage module SNP rs12345, and the CTB4a functional allele, marked by the booting stage module SNP rs67890. eQTL co-location analysis confirmed that their expression was significantly associated with the cold tolerance phenotype.

[0054] Parents A and B were crossed to obtain the F1 generation, which was used to aggregate cold-resistant alleles at different growth stages, significantly improving the offspring's adaptability to multi-stage low-temperature stress.

[0055] Example 3: Accelerating the early selection of cold-resistant homozygous lines of cold-resistant rice using molecular breeding chips A cold-resistant japonica rice breeding project was carried out in Yanbian region of Jilin Province, with the goal of selecting stable lines that can withstand sustained low temperatures of 10–15°C during the seedling stage and resist cold damage during the booting stage. The F2 segregating population contains 1,200 individual plants. Traditional field phenotypic identification requires at least two growing seasons, which is time-consuming and costly.

[0056] This embodiment utilizes the chip of the present invention for early molecular-assisted selection. DNA from F2 individual plant leaves was collected, and all 486 SNP loci were genotyped using the ThermoFisher TaqMan OpenArray platform. After the data was imported into a locally deployed cold tolerance prediction system, the CCTI and three module sub-scores for each plant were automatically calculated.

[0057] Based on the characteristics of frequent low temperatures during the seedling stage in Yanbian region from mid-May to early June and occasional chilling injury during the booting stage, the screening criteria were set as follows: CCTI ≥ 0.75, and seedling stage module score ≥ 0.8 and booting stage module score ≥ 0.75. The system automatically removed 862 plants that did not meet the criteria, retaining 338 plants for the next round. Further analysis revealed that 92% of the retained lines carried the OsTPP1 cold-resistant allele seedling stage module SNP rs24680 and the qLTG3-1 bud stage functional allelic variant, although not the primary selection, they had a synergistic effect, and the OsSAPK8 regulatory region SNP rs13579 was significantly correlated with pollen fertility.

[0058] The homozygosity of the selected single plants was further verified using microarrays in the BC1F1 generation. In just one year, 12 lines with CCTI>0.85 and high homozygosity in key modules were obtained, which shortened the breeding cycle by 2–3 years compared with traditional methods and significantly improved the breeding efficiency of cold-resistant varieties.

[0059] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. A molecular breeding chip for precise identification of cold tolerance of rice in cold region, characterized in that, The chip contains 400–550 single nucleotide polymorphism (SNP) molecular marker sites, which were obtained through joint analysis and screening of transcriptomic and phenotypic data of core germplasm of cold-region rice under multi-gradient low-temperature stress conditions, and are divided into the following three functional modules: (a) Cold tolerance module for germination, containing 120–160 SNP sites, is used to evaluate the germination ability and seedling vigor of rice seeds at low temperatures of 5–10°C. (b) Seedling cold tolerance module, containing 130–180 SNP loci, is used to predict the survival rate and growth potential of rice at a sustained low temperature of 10–15°C from the three-leaf stage to the tillering stage; (c) Cold damage module during the booting stage, containing 150–210 SNP loci, is used to identify pollen fertility and seed setting potential when rice is exposed to temperatures below 17°C 15 days before heading.

2. The molecular breeding chip for precise identification of cold tolerance of rice in cold region according to claim 1, characterized in that, The SNP sites are distributed across all 12 chromosomes of rice, covering known cold-resistance-related functional genes and their regulatory regions. These functional genes include, but are not limited to, OsDREB1A, OsTPP1, CTB4a, qLTG3-1, OsMYB30, and OsSAPK8. 3.The molecular breeding chip for precise identification of cold tolerance of rice in cold region according to claim 2, characterized in that, All SNP sites were selected and confirmed through linkage disequilibrium analysis of natural populations of cold-region rice with n≥500, genome-wide association analysis (GWAS), and at least one functional verification method, including gene knockout, overexpression, allelic complementation experiments, or eQTL co-localization analysis. 4.The molecular breeding chip for precise identification of cold tolerance of rice in cold region according to claim 1, wherein, The chip is constructed using a high-throughput genotyping platform, which includes one of Illumina Infinium XT, Affymetrix Axiom, or Thermo Fisher TaqMan OpenArray.

5. The application of the molecular breeding chip in the evaluation of cold tolerance of rice germplasm resources in cold regions according to any one of claims 1-4, characterized in that, By genotyping the rice materials under test and calculating the cold tolerance index throughout the entire growth period using a preset weighting algorithm, and outputting cold tolerance scores for the budding, seedling, and booting stages respectively, the cold tolerance ability of the materials can be quantitatively graded.

6. The application of the molecular breeding chip in cold tolerance evaluation of cold region rice germplasm resources according to claim 5, characterized in that, The CCTI is calculated using a weighted linear regression model, with the weights of each module dynamically adjusted according to the main chilling injury types in the target ecological zone. The basic weights for the budding stage, seedling stage, and booting stage modules are 0.3, 0.3, and 0.4, respectively.

7. An application of the molecular breeding chip as described in any one of claims 1-4 in the selection and mating of parental lines for cold-region rice, characterized in that, Based on the main chilling injury risk type in the target planting area, priority is given to selecting areas where the score in the corresponding functional module is higher than or equal to the threshold. Two parents with a growth rate of 0.8 were crossed to aggregate cold-resistant alleles at different growth stages.

8. The application of a molecular breeding chip as described in any one of claims 1-4 in the early selection of offspring in cold-region rice, characterized in that, In F2, BC1F1, or subsequent segregating generations, high-throughput genotyping of individual plants is performed using chips to eliminate individuals with CCTI scores below a preset threshold or unqualified scores in key modules, thereby accelerating the breeding process of cold-resistant homozygous lines.

9. An application of the molecular breeding chip as described in any one of claims 1-4 in the regional adaptability assessment of new cold-region rice varieties, characterized in that, Chip typing results can be used as the molecular basis for variety approval or promotion decisions, and can help delineate the range of varieties suitable for planting in specific cold rice-growing areas such as the Northeast Plain, the Sanjiang Plain, and the Yunnan-Guizhou Plateau.

10. A cold tolerance prediction system based on the molecular breeding chip described in claim 1, characterized in that, include: The genotyping module is used to obtain genotyping data of the rice sample to be tested at the 400–550 SNP loci. The data processing module is used to call the pre-trained cold tolerance prediction model to calculate the CCTI and sub-scores for each reproductive stage. The output module generates cold tolerance level reports and breeding recommendations. The system is deployed on a local server or cloud platform.

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