10 results about "Linkage disequilibrium" patented technology

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 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.

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.

This application discloses a method for identifying SNP molecular markers significantly associated with potato starch content, belonging to the field of SNP molecular marker technology. Based on high-quality SNP sets and starch content phenotypic data, this application employs a mixed linear model for genome-wide association analysis, effectively controlling population structure and phylogenetic relationships, and significantly reducing the false positive rate. By constructing haplotype blocks and introducing an effect accumulation assessment algorithm, it overcomes the limitations of traditional single SNP analysis, detecting the synergistic effect of allele combinations, and the selected haplotype blocks have higher phenotypic explanatory power. Representative SNPs are screened using linkage disequilibrium analysis, and the introduction of independent validation populations ensures the stability and cross-population applicability of the molecular markers. Finally, SNP molecular markers significantly associated with potato starch content are obtained, which can be directly used for early screening of high-starch germplasm and marker-assisted breeding, significantly shortening the breeding cycle and improving selection efficiency.

This application provides a method, system, and application for identifying potential drug targets, relating to the field of bioinformatics. The method includes: S1, constructing genetic instrumental variables related to a predetermined disease based on a multidimensional dataset, wherein the multidimensional dataset includes: a disease genome dataset, a dataset of druggable genes, and a dataset of plasma protein quantitative trait loci; S2, analyzing the genetic instrumental variables using Mendelian randomization to determine the potential causal relationship between genes and the predetermined disease; S3, validating the potential causal relationship between genes and the predetermined disease using a drug-gene dataset to identify potential drug targets for the predetermined disease. The aforementioned method, by comprehensively integrating disease genome, druggable gene, and protein quantitative trait locus data, effectively eliminates the interference of horizontal pleiotropic effects on the identification of potential drug targets and eliminates the confusion that may be caused by linkage disequilibrium, thereby improving the accuracy and reliability of potential drug target screening.

This application relates to the fields of molecular genetics and biotechnology, particularly to SNP marker sets and their applications for upland cotton variety identification. Through analysis of 10K SNP microarray data from 1205 upland cotton varieties (1194 species), this application identified a core marker set containing 1553 SNP loci. These markers exhibit high polymorphism, low linkage disequilibrium, and uniform chromosome distribution among upland cotton varieties, enabling efficient and accurate identification. This application is the first to determine a genetic distance threshold of 0.3 for identifying the authenticity of upland cotton varieties using this 1553 SNP marker set. This marker set demonstrates strong identification capabilities and high cost-effectiveness, and can be widely applied in areas such as intellectual property protection, breeding, and variety management of upland cotton varieties.

The application relates to an endometriosis causal gene screening method and device based on cross-brain region genetic regulation integration analysis, equipment and a medium, and relates to the technical field of biomedical testing. The method constructs a cross-system genetic analysis platform, realizes a reproducible cross-tissue genetic integration analysis framework by integrating brain region eQTL data and large sample GWAS statistical results, and comprises the following steps: identifying a potential pathogenic path and a candidate causal gene of central expression factors by using eQTL data and GWAS data, covering data acquisition, tool variable construction, causal inference modeling, linkage disequilibrium control and functional annotation analysis, realizing cross-system analysis of a genetic regulation mechanism of an endometriosis pathogenic risk, and focusing on exploring a remote action path of brain region homeostatic expression on disease susceptibility.

This invention discloses a method and system for predicting breeding values ​​based on multi-scale gene feature tensors. The method obtains a preprocessed genotype matrix by performing quality control, missing genotype imputation, and standardization on whole-genome SNP marker data of the target population; it then uses a linear mixture model to correct for fixed effects on phenotypic observations; based on gene function annotation information and linkage disequilibrium structure information, SNP sites are divided into multiple functional regions, and a multi-scale genome feature tensor is constructed after dimensionality reduction using principal component analysis; a fused deep neural network model is constructed and trained, and the breeding value prediction results and prediction uncertainty quantification indicators are output through Monte Carlo Dropout inference. This invention can effectively capture local linkage disequilibrium patterns and long-range epistatic interactions, is applicable to endangered small population scenarios, and provides individual-by-individual prediction reliability assessments, providing a scientific basis for decision-making in the conservation and breeding of endangered local livestock and poultry genetic resources.