9 results about "Heritability" patented technology

The invention relates to the technical field of animal genetic breeding, and provides a double-character genome selection platform based on local genetic correlation (LGC). The platform is composed of a phenotype data processing module, a genotype data processing module and a genome selection module (comprising a model selection sub-module and a parameter selection sub-module). The platform performs quality control, data normality test and correction on phenotypic data; performing quality control, sequence alignment, variation detection and genotype filling on the genotype data; and identifying whole genome local genetic correlation, checking the significance of LGC, selecting a model based on a whole genome LGC estimation result of a character pair and a corresponding P value, setting a corresponding model parameter threshold, and realizing section weighted double-character genome selection analysis. According to the method, the genetic evaluation accuracy of complex characters, especially low heritability characters, can be effectively improved, and an efficient and stable genome selection tool is provided for livestock and poultry breeding.

This invention discloses a selection method for meat geese that comprehensively considers feed conversion efficiency and subcutaneous fat properties, relating to the field of poultry genetics and breeding. The method includes the following steps: S1 determining feed conversion efficiency of meat geese; S2 determining subcutaneous fat properties of meat geese; S3 calculating the family mean values ​​for each trait; S4 analyzing the correlation and heritability of each trait; S5 constructing a comprehensive selection index for feed conversion efficiency and subcutaneous fat properties of meat geese; and S6 selecting breeding geese with high comprehensive selection indices. This invention utilizes individual measurements and single-cage determination of feed conversion efficiency in meat geese, establishes a three-point method for accurately measuring subcutaneous fat thickness, and constructs a comprehensive selection index for residual feed intake, subcutaneous fat percentage, and subcutaneous fat thickness. It provides a selection method that comprehensively considers feed conversion efficiency and subcutaneous fat properties in geese, simultaneously improving feed efficiency and reducing subcutaneous fat properties, achieving simultaneous selection and synergistic improvement of multiple traits, and significantly enhancing breeding efficiency.

The invention relates to the technical field of biological information, and particularly discloses a multi-omics genome combined genetic assessment method and device. According to the method, multi-source data such as a genome, a transcriptome, a proteome, a metabolome, a microbiome and a high-throughput phenotype are integrated by constructing a multi-omics fusion similar matrix, an adaptive dichotomy is adopted to optimize omics weights, a grid search and cross validation system is introduced, and global optimal estimation of parameters is achieved. Verification of the method on livestock and poultry breeding and plant breeding data shows that the prediction accuracy of complex characters can be remarkably improved, and particularly, the prediction precision in low heritability characters is remarkably improved. The invention further provides a corresponding device which comprises a data acquisition module, a matrix construction module, a parameter optimization module and a breeding value calculation module, comprehensive utilization of multi-omics information can be efficiently achieved, and the accuracy and calculation efficiency of breeding value estimation are improved.

The invention discloses an efficient SNP marker automatic screening system for dairy cow breeding, relates to the technical field of dairy cow breeding screening, and aims to solve the problems that the scientificity and stability of a screening result are reduced, and the error between genetic improvement efficiency and marker utilization rate is increased. The method comprises the following steps: extracting dairy cow breeding character information and gene site data from a genotype-phenotype database, calculating heritability of each character, screening target characters with high genetic contribution degree, calculating character action characteristics and effect directions of gene sites on the basis of an association relationship between the target characters and SNP sites, quantitatively describing regulation intensity of the gene sites, and screening out the target characters with high genetic contribution degree. Generating a character guiding coefficient according to the character guiding coefficient, screening significant candidate sites in combination with a threshold value, performing cross-character frequency statistics on the candidate sites, calculating a breeding efficiency index in combination with a character correlation weight, and performing hierarchical marking according to the index, so as to realize multi-character comprehensive genetic effect evaluation and automatic screening. The breeding data processing efficiency and the gene selection scientificity are improved.

The application belongs to the technical field of animal genetics and breeding, and provides a genomic selection analysis method considering trait local genetic correlation significance, comprising a phenotype data processing module, a genotype data processing module and a genomic selection module; the application performs quality control on the phenotype data; performs quality control, sequence alignment and variation detection on the genotype data; performs whole genome correlation analysis to generate summary statistical data; identifies whole genome local genetic correlation, tests the significance of LGC, and realizes double-trait genomic selection analysis with segment weighting; and the application can effectively improve the genetic evaluation accuracy of complex traits, especially low heritability traits, and provides an efficient and robust genomic selection tool for livestock breeding.

The invention discloses an efficient corn drought-resistant breeding method integrating molecular marker development and a whole genome prediction model. The efficient corn drought-resistant breeding method comprises the steps of hybridization matching and DH line induction, multi-environment phenotype and genotype analysis, three-level marker set screening, optimal prediction system construction, excellent selfing line screening and the like. The method has the remarkable effects that a whole genome selection technology is applied to identification and screening of the saline-alkali-tolerant and drought-tolerant corn materials, a whole genome breeding process for selecting the saline-alkali-tolerant and drought-tolerant materials is established, and generation intervals are shortened through early selection, so that the breeding value estimation accuracy is improved, the genetic progress is accelerated, and the breeding efficiency is improved. And the method has a good prediction effect on low-heritability and difficult-to-measure complex characters, and truly realizes the breeding practice guided by a genome technology.

The invention discloses a molecular marker for analyzing reproductive performance of a large white pig and application, the molecular marker is located at five positions on chromosomes 2, 17 and 18, and the polymorphism of the molecular marker is G > A, C > T, T > A, T > C and T > C. The method has the advantages that the breeding efficiency and the selection accuracy can be improved, and meanwhile, the breeding process of high-yield and high-reproductive-performance maternal line pig breeds can be accelerated with the efficiency of selecting genomes with low heritability complexity characters such as the reproductive performance of pigs, especially the litter size, the live litter size and the healthy litter size. Based on the genetic marker provided by the invention, a more accurate and more efficient molecular marker assisted selection (MAS) or genome selection (GS) tool can be developed. By conducting genotype screening in the early stage, the breeding cycle can be remarkably shortened, the genetic improvement process of excellent boars is accelerated, and huge economic benefits are brought to the pig industry.

The application relates to the technical field of genome selection, and provides a multi-omics genome selection method and application thereof in livestock and poultry breeding, which comprises the following steps: obtaining reference population data and target population data and carrying out pretreatment; training an optimal linear unbiased prediction model and an elastic network model by using the reference population data; inputting cis-single nucleotide polymorphism site genotype data of the target population into the trained gene expression prediction model to obtain predicted gene expression of each individual in the target population; estimating the cis-heritability of each gene based on the reference population data, and screening gene prediction expression data greater than a cis-heritability threshold; integrating the screened gene prediction expression data and genome data to construct a multi-omics genome selection model, and obtaining a genome breeding value of each individual based on the multi-omics genome selection model. The application can adapt to genetic regulation structure differences of different genes and obtain high-quality prediction results.

The application provides a fine wool sheep genome selection method, relates to the field of animal genetic breeding, and comprises the following steps: assembling a sheep genome reference population, determining main phenotypic traits of the sheep genome reference population; designing a liquid phase chip based on resequencing data of a plurality of sheep breeds and performing fine wool sheep genome selection to obtain GWAS prior information; estimating genetic variance and error variance of different traits based on a RRBLUP model to obtain statistical results of trait heritability; performing genome estimated breeding value prediction analysis based on the statistical results of trait heritability; constructing breeding target traits according to breeding targets, constructing a genome comprehensive breeding value estimation model based on the breeding target traits; calculating comprehensive breeding values of sheep individuals based on the genome comprehensive breeding value estimation model, performing comprehensive breeding value ranking, and selecting and mating sheep according to the comprehensive breeding values; and performing important economic trait genome breeding value prediction analysis based on the GWAS prior information.