80 results about "Linkage disequilibrium" patented technology

The present application discloses a method, device, equipment and storage medium for constructing a population pedigree, which obtains a chromosome map file of a population sample, wherein the population sample includes multiple individual samples, and the chromosome map file includes SNP site information of the individual samples; the segment ratios of multiple target chromosome segments between individual samples are calculated based on the chromosome map file using the principle of linkage disequilibrium, and the number and type of common ancestor segments contained in each target chromosome segment are different; the genome kinship correlation coefficients between individual samples are calculated based on the chromosome map file using the similarity between SNP sites; the kinship between individual samples is determined based on the segment ratio and the genome kinship correlation coefficient; and the population pedigree of the population sample is constructed based on the genome kinship correlation coefficient and the kinship. The reconstruction of a multi-generation and multi-variety population pedigree is achieved, filling the gap in the current method for reconstructing a real large-scale population pedigree.

The embodiment of the invention discloses a data processing method and device, relates to the technical field of data processing, and can screen out core SNPs with high hereditary characteristics from biological SNPs. The method includes obtaining a first SNP set. And determining a second SNP set from the first SNP set according to the first information of the SNPs. And determining a third SNP set from the second SNP set according to a target feature extraction method and a nonlinear feature extraction method. Wherein the first SNP set comprises N SNPs, the N is a positive integer, the first information comprises at least one of linkage imbalance information or variance, the second SNP set comprises M SNPs, the M is a positive integer, the M is smaller than the N, the N is a positive integer, the first information comprises at least one of linkage imbalance information and variance, and the second information comprises at least one of linkage imbalance information and variance. The target feature extraction method comprises at least one of a filtering type feature extraction method, a wrapping type feature extraction method or an embedded type feature extraction method, the third SNP set comprises H SNPs, and H is a positive integer and is smaller than M.

This invention relates to the field of genetic molecular breeding, specifically to a pig 50K liquid-phase chip based on multiple single nucleotide-polymorphism and its application. The probe design of the chip in this invention takes into account the distribution of captured SNP loci across the genome, the polymorphism of the loci, the quality of mSNP markers, and other issues, effectively avoiding problems such as uneven marker density and poor polymorphism. It also considers the quality of mSNP markers and the issue of linkage disequilibrium among mSNP markers. While adhering to the basic principles of liquid-phase chip design, genomic regions with moderate linkage disequilibrium between markers were selected, generating more SNP markers with high genotyping quality and moderate linkage disequilibrium within the probe region with the target loci. The mSNP liquid-phase chip of this invention expands the detectable number of SNPs to 1.5-2 times that of the target loci, addressing the issue of the relatively small number of high-quality mSNP markers in traditional liquid-phase chips without increasing costs.

The invention belongs to the technical field of bioengineering, and particularly relates to a haplotype related to pig growth, meat production and feed conversion rate and breeding application. The genetic marker clones 22 loci from an lncMGPF gene promoter region of a pig No.8 chromosome. SNPs loci are typed through a direct sequencing technology, a linkage imbalance analysis result shows that 22 loci are all in a strong linkage imbalance state, haplotype analysis is further carried out, and a result shows that two main haplotypes are generated. Association analysis shows that compared with other combined haplotype individuals, the combined haplotype H1-H1 individuals have the characteristics that the day age time is short when the combined haplotype H1-H1 individuals reach 100 kg, the eye muscle thickness is large, and the average feed conversion ratio is small when the combined haplotype H1-H1 individuals are 30-100 kg. The invention provides a new marker for molecular breeding of pig meat traits.

The invention belongs to the field of animal and plant breeding prediction, and discloses a rapid and accurate genome prediction method based on a heritability model, which comprises the following steps: calculating the frequency and linkage imbalance score of a marked secondary allele; refining the SNP heritability model to obtain an optimal SNP heritability model; selecting an optimal layering number; acquiring layer genotype data formed by genotype data of all individuals of the to-be-predicted data set in corresponding layers, calculating a diagonal weight matrix of each layer of SNP estimated heritability assignment to the corresponding layer based on the optimal SNP heritability model, and calculating a genetic relationship matrix between individuals of the layer genotype data corresponding to each layer; and fitting the multi-random hybrid model to obtain the genome estimation breeding value of each phenotype of all individuals in the data set to be tested. The method is based on a linear model framework, the calculation complexity is low, the key steps can be subjected to parallel processing, and the calculation speed is high; according to the method, the character specific SNP heritability model is constructed, and the model representation of a complex character genetic structure is optimized, so that the prediction performance is improved.

The invention discloses a marker screening and model building method for precise evaluation of parent genome breeding values, and belongs to the technical field of molecular breeding and genomics. The method comprises the following steps: acquiring genetic typing data and target character phenotype data of a reference group, and performing digital coding; calculating a secondary allele frequency (MAF) and a linkage imbalance score (LD score) of each marker site; based on the joint screening rule of the MAF and the LD score, screening to obtain a core marker subset with relatively high genetic stability and linkage structure representativeness; and constructing a differentially weighted genome prediction model based on the core marker subset to estimate the genome breeding value of the parent individual. According to the method, allele frequency information and linkage imbalance structure information are jointly utilized, interference of low-frequency or weak linkage sites on the prediction model is reduced, the prediction accuracy of parent breeding values in cross-generation predictor representative types is improved, and the method is suitable for genome prediction and molecular breeding of complex characters.

The present invention provides a multi-variety genome joint genetic evaluation method, device and storage medium, which relates to the field of genome prediction technology. The method includes: constructing a multi-variety joint evaluation model according to prior distribution parameters, the prior distribution parameters include the prior effect variance of genotype markers; obtaining multi-variety reference group information; obtaining posterior distribution parameters according to the multi-variety reference group information and the prior distribution parameters, the posterior distribution parameters include the posterior effect variance of genotype markers; configuring the multi-variety joint evaluation model according to the posterior distribution parameters; the multi-variety joint evaluation model is used to obtain predicted phenotypic information according to the input genotype information. The multi-variety joint evaluation model is constructed by associating the effect variance based on genotype information with the genome block position divided based on linkage disequilibrium information, fully considering the differences in gene effects between different varieties, enabling information sharing between different varieties, and facilitating the improvement of the accuracy of genome prediction.

The invention discloses a tomato breeding prediction and design method based on a bidirectional generation model. The method comprises the following steps: firstly, constructing a tomato genotype and phenotype comprehensive data set, and carrying out feature correlation analysis by utilizing an attention mechanism; and then constructing a bidirectional deep learning model containing a forward prediction and reverse design path. The forward network accurately predicts phenotypes from genotypes by adopting a self-attention mechanism, the reverse network reversely deduces virtual genotypes from target phenotypes through transposition convolution, and cyclic consistency and linkage imbalance constraints are introduced for joint training. According to the method, the problem of nonlinear mapping between genotypes and phenotypes is effectively solved, two-way intercommunication between character prediction and parent design is realized, and the precision breeding efficiency of tomatoes is remarkably improved.

The application discloses a kind of molecular markers of wheat stripe rust SNP homozygous site based on whole genome sequence and application thereof.The application is analyzed to 28 strains of global wheat stripe rust genome sequence, compared with reference genome, and more than a million SNP sites are mined out.Sequence depth screening, linkage disequilibrium analysis and heterozygosity detection, identify 1076 SNP homozygous sites.Further based on the frequency of secondary allele, screening of deletion rate and adjacent simple repeat sequence, finally determine 37 core SNP markers.Through primer design to these SNP sites, and add fluorescent linker, develop KASP-SNP molecular marker, which can be used for accurate genotyping identification of wheat stripe rust population.The molecular marker developed based on global wheat stripe rust whole genome is suitable for wheat stripe rust population research in all regions of the world.Based on the development of molecular marker of homozygous site, polymorphism difference caused by heterozygous site can be effectively excluded, to ensure the accuracy of detection site.The set of KASP-SNP molecular marker has high polymorphism, good repeatability and high detection efficiency, and can be widely applied to genetic research of wheat stripe rust population.

The application discloses a high-throughput genotype intelligent analysis method, which comprises data acquisition and preprocessing, molecular marker identification and prediction of genetic relationship and hybridization advantage; high-throughput genotype data are subjected to standardization treatment, three quality evaluation standards of coverage, transversion / transversion ratio and error rate are established, and batch effect is corrected through a position effect index; then genetic similarity matrix between samples is calculated based on the pretreated data, a label SNP with high centrality is identified as a molecular marker through linkage disequilibrium network analysis; the population genetic relationship is estimated by using the marker, and a phylogenetic tree is constructed, and the hybridization advantage is predicted based on the relationship index of heterozygosity and genetic distance. The application significantly improves the quality of genotype data, optimizes the screening of molecular markers, accurately estimates the population genetic relationship and accurately predicts the hybridization advantage, and provides an efficient bioinformatics solution for modern breeding.

The present invention discloses a method for predicting and simulating the genotypes of advanced generations of hybrid combinations of self-pollinated crops, comprising the following steps: constructing a parental genotype data set and screening effective marker loci; calculating the linkage disequilibrium coefficient between marker loci, constructing a genomic linkage map, and determining the recombination rate between loci; using a random simulation algorithm to construct a gamete formation model and generate the genotypes of F1 generation individuals; based on the genotypes of the F1 generation, randomly simulating the selfing process to generate genotype data from F2 to Fn generations; establishing a mapping relationship between genotypes and phenotypes using a machine learning model to predict the phenotypic traits of advanced-generation selfing lines; the method of the present invention takes into account chromosomal exchange and linkage disequilibrium, can accurately simulate the gene recombination and segregation phenomena of the hybrid offspring of self-pollinated crops, and combines the gradient boosting decision tree model to achieve high-precision phenotypic prediction, providing an efficient auxiliary tool for the breeding of self-pollinated crops, which can significantly shorten the breeding cycle and improve the breeding efficiency.

The invention provides a genome method and an SNP (Single Nucleotide Polymorphism) marker combination for a pig to adapt to related traits in a high-temperature and high-humidity environment, and belongs to the technical field of genome prediction, the method comprises the following steps: taking a local pig SNP marker combination as a prior fixing effect; standard miscalculation of a p value, a beta value and a beta value based on whole genome association analysis; performing interval dimension reduction based on linkage imbalance; searching an optimal parameter by using a genetic algorithm, and adaptively grouping the SNPs; performing weighted summation on the G matrix; the SNP marker combination is used as a fixed effect, the weighted G matrix is used as a random effect, a genetic evaluation model is configured, and genome prediction is carried out on target characters. According to the method, the large-effect SNP and the minor-effect multi-gene effect which are causally associated with the target prediction character can be accurately captured, redundant information is removed through dimension reduction in the interval, the optimal parameter combination is found through the genetic algorithm, and the calculation speed is greatly increased while the accuracy of genome prediction is improved.

The invention relates to the field of molecular biology, and discloses a haplotype marker for dairy cow milk production butter-fat percentage character breeding and application of the haplotype marker, the haplotype marker is composed of three SNP sites in a strong linkage imbalance state, and the three SNP sites are located in a Block1 haplotype block region of a 10 # chromosome NC037337.1 of a dairy cow ARS-UCD1.2 genome; the three SNP sites are as follows: SNP1: g.59680573 A > C, SNP2: g.59743173 G > C, and SNP3: g.59743414 C > T; the dominant haplotype of the haplotype marker is H2, and the allele combination of the haplotype marker is SNP1-A, SNP2-G and SNP3-C; the homozygous H2H2 of the dominant haplotype H2 is significantly related to the high milk fat percentage character of milk production of dairy cows. The bottleneck of the traditional technology is solved, and the breeding accuracy is remarkably improved; the screening detection technical scheme is stable and reliable and has a wide application range; the milk production quality of groups is improved, and the industrial economic value is enhanced.

The invention discloses a DNA molecular marker related to rice seedling stage cold-tolerant gene haplotype and application of the DNA molecular marker, and belongs to the technical field of functional molecular markers. The rice seedling stage cold-resistant gene OsCTS11 has three main linkage imbalance blocks. Through correlation analysis of low-temperature stress phenotypes and haplotypes, it is determined that Hap4 (GCACA) of LD BLOCK1, Hap3 (GAA) of BLOCK2 and Hap4 (GTTG) of BLOCK3 are dominant haplotypes. The KASP molecular marker developed on the basis of different haplotype SNP sites can be used for analyzing OsCTS11 genotypes in different rice materials, and breeding materials with seedling-stage cold resistance can be screened out through the molecular marker.

The invention provides an SNP (Single Nucleotide Polymorphism) individual map construction method based on linkage imbalance, which introduces a weighted edge weight calculation method of a linkage imbalance value and a physical position difference, and innovatively brings a relationship between genetic association strength and a physical distance between SNPs into edge weight calculation; through logarithmic transformation of the physical position difference, the genetic relevance of the SNP pair which is close to the gene map is highlighted, it is ensured that the weight of the edge in the gene map can accurately reflect the biological significance, and the interpretability of the gene map and the biological relevance of data are improved.

To provide simple and efficient means for predicting the risk of side effects in chemotherapy for pancreatic cancer.SOLUTION: The single nucleotide polymorphism of any of (a) to (c): (a) a single nucleotide polymorphism identified by rs1980576 in APCDD1 L gene or a single nucleotide polymorphism in linkage disequilibrium or genetic linkage with the single nucleotide polymorphism; (b) a single nucleotide polymorphism identified by rs2272761 in R3HCC1 gene or a single nucleotide polymorphism in linkage disequilibrium or genetic linkage with the single nucleotide polymorphism; and (c) a single nucleotide polymorphism identified by rs9425343 in EDEM3 gene or a single nucleotide polymorphism in linkage disequilibrium or genetic linkage with the single nucleotide polymorphism, which are present on the genomic DNA in a biological sample taken from a subject, is analyzed, the genotype for the single nucleotide polymorphism is determined, and based on the determined genotype, the prediction of the risk of side effects when chemotherapy for pancreatic cancer is performed is assisted.SELECTED DRAWING: None

The invention belongs to the field of molecular breeding of aquatic animals, and particularly relates to a fish genome selective breeding method based on machine learning, which comprises the following steps: acquiring genome sequencing data and target character phenotype data of a target fish individual; carrying out whole genome association analysis to screen out candidate variation sites significantly related to characters; dimensionality reduction is performed on the candidate sites through linkage imbalance analysis, and representative sites are selected to form a feature set; screening the model by using the feature set as an input feature; training the model through the test set to obtain a genome prediction model; and finally, carrying out genome breeding value prediction on individuals with unknown phenotypes by utilizing the trained genome prediction model, and carrying out breeding selection according to a prediction result. According to the method, the prediction accuracy and breeding selection efficiency of complex characters such as fish disease resistance are remarkably improved, and the method has important application value.

This invention relates to the field of genetic molecular breeding, specifically to a pig 10K liquid-phase chip based on multiple single nucleotide-polymorphism and its application. The present invention, while adhering to the basic principles of liquid phase chip design, adds new markers to existing chips and optimizes probes using multiple single nucleotide-polymorphism technology. This results in the generation of more SNP markers with high genotyping quality and moderate linkage disequilibrium with target SNP loci within the probe region, thereby increasing the effective marker count of the chip. The mSNP liquid phase chip of the present invention increases the number of detectable SNPs to 1.5-2 times the number of target SNP markers, addressing the issue of existing chips that only contain target SNPs and cannot provide mSNP markers, without increasing the cost. By using genotype imputation technology, genotype data from the chip of the present invention is imputed into mainstream 50K chips for genomic selection, achieving molecular breeding accuracy comparable to or similar to that of the 50K chips, thereby reducing the cost of pig molecular breeding.

The present invention discloses a method for analyzing the selective breeding effects of corn by integrating population genetics and deep learning. The method collects corn germplasm resource data, including phenotypic data, genotypic data and environmental data; standardizes the phenotypic data and fills in missing values, and calculates population genetic parameters, including allele frequency, linkage disequilibrium and population structure stability; uses a deep learning model to perform association analysis between the population genetic parameters and the phenotypic data, uses the trained model to predict the phenotypic values ​​of candidate parents, calculates the breeding index in combination with the population genetic parameters, and provides guidance for corn breeding decisions based on the prediction results. The present invention achieves accurate prediction and evaluation of the selective breeding effects of corn by organically combining deep learning technology with the principles of population genetics, thereby improving breeding efficiency and providing a new technical path for corn variety improvement.

The invention discloses application of a diplotype of a high-association SNP (Single Nucleotide Polymorphism) site of a rudon septentrionalis body in breeding, and belongs to the technical field of aquatic breeding. The method comprises the following steps: analyzing early-stage sequencing data of a W group and an M group of navodon septentrionalis to identify two linkage imbalance SNP sites at 269 and 469 positions of an MYF6 gene with relatively high genetic diversity, totally detecting three haplotypes in the W group and the M group, and randomly forming five diplotypes by the three haplotypes, compared with other four diplotypes, the homozygous diplotype V (G269G269C469C46969) has remarkable advantages in the aspects of average body height and MYF6 gene expression, can be used as a molecular marker related to the body height, and is applied to molecule-assisted breeding of a new fast-growing strain of the navodon septentrionalis so as to improve the yield of a fast-growing improved variety of the navodon septentrionalis.

The invention discloses a high-throughput genotype intelligent analysis method. The method comprises the steps of data acquisition and preprocessing, molecular marker recognition and genetic relationship and hybridization advantage prediction. Performing standardization processing on the high-throughput genotype data, establishing triple quality evaluation standards of coverage rate, conversion / transversing rate and error rate, and correcting batch effect through a position effect index; then calculating a genetic similarity matrix among the samples based on the preprocessed data, and analyzing and identifying a tag SNP with high centrality as a molecular marker through a linkage imbalance network; the markers are used for estimating the genetic relationship of the population and constructing a phylogenetic tree, and meanwhile, the hybridization advantage is predicted based on the relationship index of the heterozygosity and the genetic distance. According to the method, the genotype data quality is remarkably improved, molecular marker screening is optimized, the population genetic relationship is accurately estimated, the hybridization advantage is accurately predicted, and an efficient bioinformatics solution is provided for modern breeding.

The application belongs to the technical field of aquatic animal genomics and molecular breeding, and particularly relates to a fine positioning method and application of a major QTL of growth traits of redfin pufferfish. Fin samples of a redfin pufferfish family population and growth phenotypes in a continuous breeding stage are used as materials, low-density skeleton SNPs are obtained by targeted sequencing of a breeding chip, and high-density genotypes are filled by means of whole genome resequencing reference panels; then, mixed linear model whole genome association analysis, GCTA-COJO conditional-association analysis, linkage disequilibrium analysis, Bayesian statistical fine positioning and allele frequency verification of extreme individuals are sequentially performed, so that a complex pericentromeric QTL cluster is analyzed into multiple independent association signals, and a candidate causative gene and a molecular marker are locked. The application has high positioning accuracy, can distinguish multiple independent signals in close linkage, and provides reliable markers for molecular marker-assisted breeding and genome selection of growth traits of redfin pufferfish.

The invention belongs to a bioengineering technology, and particularly relates to a haplotype breeding marker related to the utilization rate of pig feed and meat traits and application of the haplotype breeding marker. The genetic marker clones 19 sites of an SYISL gene promoter from a pig No.8 chromosome. Three pairs of primers are designed according to a pig genome sequence (NC010450.4) published by an NCBI (National Center of Biotechnology Information) database. 19 base substitutions exist in amplification sequences of the three pairs of primers. SNPs loci are typed through a direct sequencing technology, a linkage imbalance analysis result shows that 19 loci are all in a complete linkage imbalance state, and two haplotypes are generated through analysis. Association analysis shows that compared with other haplotype individuals, the combined haplotype H2-H2 individuals have the characteristics that the backfat thickness is small, the eye muscle thickness is large, the average feed intake of 30-100 kg of individuals is small, and the feed conversion ratio is small. The invention provides a new marker for molecular breeding of pig meat traits.

The invention discloses a method for constructing a gene regulatory network by utilizing eQTL and application, and the method specifically comprises the following steps: utilizing eQTL data, calculating linkage unbalance degree between eSNP in each eQTL and all other SNPs in a 1 million base pair range of a chromosome where the eSNP is located through an eQTL2GRN program, classifying according to the linkage unbalance degree, and utilizing physical coordinate positions of the eSNP and eGene to construct a gene regulatory network. Judging that the regulation and control type is cis or trans; and finally, constructing a gene regulation and control network, and carrying out visualization. By means of the method, the regulation and control relation between the genes can be recognized and analyzed, and then how genetic variation affects gene expression and phenotypic characteristics can be deeply understood.

The application relates to a method for screening functional sites based on sequencing data, and the specific steps are as follows: 1. obtaining SNP sites of all samples through genome sequencing, randomly selecting a plurality of samples as a discovery population, and extracting biological prior information; 2. demarcating important regions of the genome according to the biological prior information obtained in step 1; 3. performing frame linkage disequilibrium filtering on the whole genome, reducing the threshold of LD filtering in the important regions or not performing filtering, and improving the marker density of the important regions, and finally screening a trait-specific marker set. Before performing breeding value estimation, the selective linkage disequilibrium site screening can increase the signal-to-noise ratio of the site, improve the prediction accuracy, and further reduce the consumption of computing resources and time, and improve the breeding efficiency.

The application belongs to the field of animal and plant breeding prediction, and discloses a fast and accurate genomic prediction method based on a genetic force model, which calculates the minor allele frequency and linkage disequilibrium score of a marker; obtains an optimal SNP genetic force model through a SNP genetic force model; selects an optimal number of layers; obtains layer genotype data formed by the genotype data of all individuals in a corresponding layer of a to-be-predicted data set; calculates the estimated genetic force of each layer of SNPs based on the optimal SNP genetic force model, and assigns the estimated genetic force to a corresponding diagonal weight matrix of the layer; calculates the kinship matrix between individuals in the corresponding layer genotype data of each layer; fits a multi-random mixed model to obtain the genomic estimated breeding value of each phenotype of all individuals in the to-be-tested data set. The application is based on a linear model framework, has low calculation complexity, and the key steps can be processed in parallel, so the calculation speed is fast; the application constructs a trait-specific SNP genetic force model, optimizes the model representation of the genetic structure of a complex trait, and thus improves the prediction performance.

The application discloses a method for fine positioning of anti-sporozoan genes of Carassius auratus based on linkage disequilibrium analysis, relates to the technical field of fine positioning of fish genes, and comprises the following steps: collecting whole blood samples of a Carassius auratus population, extracting genomic nucleic acid sequences, constructing a whole genome marker site set with a preset marker density gradient, dividing haplotype blocks to generate an initial haplotype data set, obtaining a population linkage disequilibrium distribution map through sliding window comparison, selecting a region with a decay rate lower than a standard value as a candidate correlation section and extracting a genotype coding sequence, matching and calculating correlation strength values with sporozoan infection survival phenotype data, reconstructing haplotype phase information of the candidate section and iteratively calculating until the threshold is met if the preset threshold is not reached. The method is suitable for genetic structure differences of genomes, optimizes correlation determination processes, and improves the accuracy of anti-sporozoan gene positioning and the reliability of section screening.

The application relates to the field of homologous tetraploid organisms, in particular to a combined determination method of homologous tetraploid double-reduction parameters and HWD coefficients. The method comprises the following steps: constructing a homologous tetraploid natural population double-reduction and linkage disequilibrium combined model; constructing a combined calculation model; inputting actual values of double-marker offspring zygote frequencies into the combined calculation model to determine estimated values of double-marker direct parent gamete frequencies; calculating estimated values of single-marker direct parent gamete frequencies according to the estimated values of the double-marker direct parent gamete frequencies; inputting the estimated values of the single-marker direct parent gamete frequencies into a single-marker direct parent gamete frequency calculation model to obtain a nonlinear equation; and determining the measured values of the double-reduction parameters and the Hardy-Weinberg disequilibrium coefficients according to the nonlinear equation. The application simultaneously completes the determination of double-reduction frequency estimation, Hardy-Weinberg disequilibrium and linkage disequilibrium between markers by constructing a combined model, and improves the precision of parameter estimation.

The invention relates to the technical field of molecular identification of pig varieties, and discloses an SNP molecular marker combination for identification of Huoshou black pigs, the combination is composed of the following 27 SNP sites, and the physical position and allele information of each SNP site are determined based on a pig reference genome Sscrofa11.1: rs3473390918 located at 229783932bp of a chromosome 1, the allele of which is C / T; the rs690957272 is located at the 230954563bp position of the chromosome 1, and the allele of the rs690957272 is T / C; and the rs337901794 is located at the 231278598bp position of the chromosome 1, and the allele of the rs337901794 is T / A. According to the invention, through whole genome re-sequencing and population genetics analysis (FST screening), in combination with partial least squares regression importance evaluation, PLS-DA modeling, cross validation and linkage imbalance redundancy elimination, 27 Houshou black pig specific SNP loci are finally optimized.

This invention discloses a negative regulatory gene for cold tolerance in rice seedlings. OsDMY01 Haplotypes and KASP molecular markers and their applications. Genes OsDMY01 The nucleotide sequence is shown in SEQ ID NO.1. Knocking out this gene using gene editing technology significantly improved the survival rate of rice seedlings under low-temperature stress, while overexpression of this gene reduced cold tolerance, indicating that... OsDMY01 It is a negative regulator of cold tolerance in rice seedlings. OsDMY01 Two linkage disequilibrium blocks (LD BLOCK1 and LD BLOCK2) were identified in the regulatory and exon regions of the gene, each containing the favorable haplotype Hap2, which was significantly associated with cold tolerance at the seedling stage. Corresponding KASP molecular markers were developed for the favorable haplotypes, which can be used for efficient and precise screening and creation of cold-tolerant rice germplasm, providing important genetic resources and molecular tools for molecular breeding of cold-tolerant rice.