194 results about "Genomic selection" patented technology

The invention discloses a sugarcane germplasm resource evaluation and breeding method for smart agriculture. The sugarcane germplasm resource evaluation and breeding method comprises the following steps: step 1, collecting materials with wide genetic diversity; establishing an intelligent incubator and a greenhouse, and monitoring environmental parameters by using an Internet of Things sensor; 2, performing data acquisition on the related germplasm resources by using an unmanned aerial vehicle, a robot and a near infrared spectrum technology, and constructing a phenotype database for data management; meanwhile, genotype identification is carried out by combining molecular marker-assisted selection and genome selection technologies, molecular markers of key genes are mined, and the genetic value of related germplasm is evaluated; step 3, constructing a hybrid combination prediction model by using an AI algorithm, optimizing parent matching of the related germplasm and the cultivated sugarcane, monitoring and collecting the filial generation at the same time, and analyzing and screening in combination with smart agriculture; 4, demonstration planting is conducted on the bred excellent sugarcane strain, and application of the excellent strain is improved through government-enterprise-scientific research institution collaborative popularization and in combination with farmer technical training.

The invention relates to the technical field of bioinformatics, and provides a crop whole genome phenotype prediction method and system fused with an environmental indicator gene, and the method comprises the following steps: collecting re-sequencing data, and carrying out genome comparison to obtain variation site data; performing whole genome association analysis by using the variation site data to obtain phenotype association site information; carrying out gene expression quantity measurement on samples of the crop population material in different environments to obtain gene expression quantity data; performing differential expression analysis on the gene expression quantity data to screen environmental indicator genes to obtain an environmental indicator gene set; constructing a phenotype prediction model of double-branch fusion; and predicting a to-be-predicted material through the phenotype prediction model to obtain phenotype prediction results for different environments. According to the method, environmental factors are incorporated into the whole genome selection model, so that the phenotype prediction precision in different environments is improved.

The invention discloses a peanut quality character selective breeding method based on whole genome SNP and application, and relates to the technical field of crop breeding, the method comprises the specific steps of data acquisition, SNP optimization and marker screening, model construction and new strain breeding; by integrating whole genome re-sequencing, SNP optimization marker screening and mixed deep learning model construction, peanut quality character prediction and breeding value evaluation are achieved, through whole genome re-sequencing and quality control processes, an SNP variation map is obtained, ten key quality characters including protein, oil content, oleic acid and the like are covered, and the breeding value of peanuts is evaluated. According to the method, comprehensive genetic information is provided for subsequent analysis, a feature marker set is formed by screening out sites in the SNP optimization and marker screening link, interference of low-quality sites is avoided, a whole genome selection model is obtained by adjusting and training a mixed deep learning model and optimizing hyper-parameters through ten-fold cross validation, the breeding period is shortened, and the breeding efficiency is improved. And the prediction error rate is reduced.

The invention belongs to the technical field of gene detection and gene molecular breeding, and particularly relates to a meat duck whole genome molecular probe combination based on molecular phenotype screening, a 50K gene chip and application thereof. The molecular probe combination and the gene chip of the marker site combination for meat duck whole genome breeding simultaneously cover 7 representative meat duck varieties and 71 economic characters, have richer polymorphism and higher pertinence in meat duck groups, and are lower in cost and higher in speed compared with high-throughput sequencing detection; the breeding chip is designed according to the growth, feed efficiency, slaughtering, breeding, egg quality and various molecular phenotypes of the meat ducks, and compared with a high-throughput sequencing technology, the breeding chip is higher in seed selection accuracy, has higher breeding value, can be widely applied to breeding genotype detection of the meat ducks, and can be used for detecting the breeding genotypes of the meat ducks. And the method has creative significance in the aspect of meat duck genome selective breeding.

The invention relates to the technical field of molecular breeding, in particular to a duck whole genome chip and a manufacturing method and application thereof. The duck whole genome chip is totally provided with 40876 probe targets, 25465 probe targets are derived from duck reference genomes, and the rest 15411 probe targets are derived from duck variety specificity and character-associated SNPs (Single Nucleotide Polymorphism). The average detection rate of the 40K whole genome liquid phase chip is 99% or above, the total number of effective markers is larger than 40,000, and the 40K whole genome liquid phase chip has high stability and is suitable for genetic improvement and resource evaluation of duck varieties. Besides, the SNP sites contained in the chip are obtained by mining important characters of injection ducks, and genome selection can be stably and efficiently performed on the important characters of the injection ducks by utilizing the sites, so that the duck breeding progress can be accelerated.

The invention relates to the field of bioinformatics, in particular to a genome selection method, device and equipment, a medium and a computer program product. Integrating a plurality of machine learning models, including 13 algorithms such as a support vector machine (SVM), linear regression, Ridge regression, Lasso regression and the like; by combining automatic hyper-parameter optimization, parallel computing and efficient data preprocessing technologies, the breeding prediction precision and the computing efficiency are remarkably improved. The device comprises an IASML software module and an IASML cloud platform module, wherein software supports command line operation and is suitable for large-scale data calculation; the cloud platform provides a graphical interface and supports online data uploading, model selection, real-time monitoring and result downloading. According to the method, the problems of singleness, limited data scale, poor interactivity and the like of an existing tool model are solved, and an efficient, flexible and reproducible intelligent solution is provided for animal and plant breeding and genetic research.

The invention discloses a chip for genome breeding and variety identification of tilapia mossambica. The invention provides a group of SNP (Single Nucleotide Polymorphism) marker combination for tilapia mossambica, which comprises 50000 SNP markers which are respectively SNP1-SNP50000 markers. According to the invention, the SNP marker combination related to economic characters of tilapia mossambica is integrated, representative sites with uniform coverage are selected, a biological probe for site typing is developed, and the site coverage, typing accuracy and GS accuracy of the SNP marker combination are basically consistent with those of re-sequencing; the method can be applied to the aspects of tilapia germplasm resource identification, genetic relationship identification, SNP typing, variety identification, molecular breeding, DNA fingerprint database construction, variety purity detection, germplasm resource genetic analysis, whole genome selective breeding, functional gene positioning, genetic map construction, genetic evolution analysis, whole genome association analysis and the like.

The invention provides a target character prediction method suitable for low-depth sequencing and a whole genome selection model suitable for low-depth sequencing, and relates to the technical field of biology. According to the target character prediction method suitable for low-depth sequencing and the whole-genome selection model provided by the invention, the target character of the to-be-detected sample can be accurately predicted under a limited data volume by combining low-depth whole-genome re-sequencing data with a machine learning technology, and the genome selection efficiency can be improved by matching the two; the time and economic cost of breeding or medical research are reduced, and the method is particularly suitable for large-scale genetic analysis scenes needing rapid iteration.

The invention discloses a Chinese rose vase life whole genome SNP molecular marker combination and application thereof, the SNP locus combination comprises 1679 SNP markers significantly associated with Chinese rose vase life, and the SNP markers are uniformly distributed on 14 chromosomes of Chinese rose. The SNP loci are obtained through genome-wide association analysis and screening, a genome-wide selection model constructed by the SNP loci can accurately predict the vase life of the Chinese rose, and the prediction accuracy can reach 0.710 or above. The invention also relates to specific probes designed aiming at the SNP loci and a liquid phase breeding chip containing the probes, which can be used for rapidly and efficiently screening individuals with excellent vase life characters in a Chinese rose seed or seedling stage, so that the breeding period is remarkably shortened, the breeding efficiency is improved, and the breeding cost is reduced. Powerful technical support is provided for molecular breeding and variety improvement of the Chinese roses.

The invention discloses a China rose inflorescence whole genome SNP molecular marker combination and application thereof. A traditional breeding method for improving China rose inflorescence characters is time-consuming and labor-consuming, and ideal plants are difficult to obtain quickly. The SNP molecular marker technology is utilized, 358 Chinese rose materials and inflorescence phenotype data are analyzed through whole genome association, 1574 SNP loci remarkably related to inflorescence are screened out, a whole genome selection model with the prediction accuracy larger than 0.743 is constructed, and inflorescence characters can be effectively predicted. Meanwhile, a corresponding probe is synthesized to be used for capturing and sequencing, the capturing efficiency is high, the coverage depth is good, the SNP sites related to the rosa chinensis inflorescence can be accurately detected, an efficient technical means is provided for rosa chinensis genetic improvement and new variety cultivation, and the development of the rosa chinensis industry is assisted.

The invention discloses a Chinese rose petal outer edge wave whole genome SNP (Single Nucleotide Polymorphism) molecular marker combination and application thereof, and aims to solve the problems that the traditional Chinese rose breeding period is long, the Chinese rose breeding is easily interfered by the environment, and the petal wave character cannot be predicted in a seedling or seed stage. According to the method, 358 Chinese rose whole genome re-sequencing data and petal outer edge wave phenotype association analysis are integrated, a multi-model combined screening strategy is adopted, 1453 SNP markers obviously associated with petal outer edge waves are determined, and a whole genome selection model with high prediction precision is constructed. By combining a specific probe and chip technology, high-throughput and rapid detection is realized, the detection period can be shortened, the petal wave traits can be directly predicted by utilizing genotype data in a seedling stage, the breeding process is accelerated, and core data support is provided for Chinese rose petal outer edge wave genetic law analysis and molecular marker-assisted breeding; the method has outstanding theoretical value and application potential.

The invention relates to the technical field of biological information, and provides a whole genome selection method, device and equipment of a graph neural network and a storage medium, and the whole genome selection method of the graph neural network comprises the following steps: mapping single nucleotide polymorphism (SNP) to a gene level, and converting the SNP into a gene embedding vector; constructing a gene interaction network based on preset multi-source biological priori knowledge; inputting the target character into a graph neural network model to obtain a predicted value of the target character output by the graph neural network model; wherein the graph neural network model is determined based on a gene embedding vector and a gene interaction network. According to the method, the SNP is mapped to the gene level, and the gene interaction network is combined, so that the prediction result has clear biological significance; and the gene interaction network is constructed based on the preset multi-source biological priori knowledge, so that interaction information between genes can be fully utilized, and the accuracy of target character prediction is improved.

The invention relates to the technical field of genomics, molecular biology, bioinformatics and whole-genome selective breeding, in particular to a whole-genome liquid chip for apostichopus japonicus and application of the whole-genome liquid chip. The liquid phase chip contains sequences of background SNP loci and functional SNP loci which are used for gene analysis and are positioned on an apostichopus japonicus reference genome; wherein the functional SNP sites are associated with important economic characters of the apostichopus japonicus. The invention also discloses application of the liquid chip in apostichopus japonicus genome selective breeding, important economic character gene positioning, genetic diversity analysis, germplasm resource improvement and protection.

The invention discloses a lutjanus erythropterus breeding auxiliary method and system based on multi-character collaborative selection, and the method comprises the steps: carrying out phenotype data collection and gene detection, and constructing a standardized phenotype matrix and a genotype matrix; performing genetic parameter estimation and breeding value prediction based on the standardized phenotype matrix and the genotype matrix to obtain breeding value prediction information; the method comprises the following steps: analyzing an association relationship between characters of lutjanus rubripes to be bred, constructing a character association network, and carrying out multi-character dynamic weight configuration to obtain a dynamic weight set; performing genome selection index calculation and parent priority analysis according to the breeding value prediction information and the dynamic weight set to generate a parent selection priority list; and generating a candidate parent pool through the parent selection priority list, performing hybridization combination analysis, performing genetic gain prediction on the generated hybridization combination, and generating a hybridization auxiliary scheme. The genetic gain accuracy and balance of breeding of the lutjanus erythropterus are improved, the limitation of traditional experience selection and matching is broken through, and the breeding efficiency is improved.

The application relates to the technical field of gene chips, in particular to a SNP molecular marker combination of Pinus massoniana and application thereof. The SNP molecular marker combination is composed of 113,709 SNP molecular markers, wherein the physical position of the SNP molecular markers is determined by sequence alignment based on a reference genome Pinus.tabuliformis V1.0 of Pinus tabulaeformis. The application provides a whole genome chip of Pinus massoniana containing 113,709 SNP sites for the first time, and the chip has the advantages of high efficiency, low cost, good genetic stability and the like, and can be widely applied to different application scenarios such as identification of Pinus massoniana germplasm resources, genetic background analysis of breeding materials, gene positioning, whole genome association analysis, whole genome selection breeding and intelligent design breeding.

The invention discloses a China rose fragrance whole genome SNP molecular marker combination and application thereof, 2068 SNP markers significantly related to fragrance are screened out by analyzing 358 parts of China rose re-sequencing materials and flower fragrance phenotype data, and a whole genome selection model is constructed. The method can accurately predict the fragrance character of the China rose, improve the breeding efficiency and accuracy, shorten the breeding period and reduce the cost. Meanwhile, a new direction is provided for China rose fragrance improvement and breeding, the method has reference value for character improvement of other horticultural crops, has efficient and stable capture efficiency, and can be used for subsequent sample detection and evaluation.

The invention belongs to the technical field of aquatic genetic breeding, and particularly relates to a grass carp disease-resistant character genome breeding method and related application thereof. According to the method, filial generation juvenile fish families produced by non-family grass carp parents from different geographical sources are used for constructing an anti-hemorrhagic disease reference group, the disease-resistant SNP site provided by the invention is used for calculating a genome estimation breeding value of a candidate group, and individuals with high breeding value are relatively high in disease resistance and can be used for breeding disease-resistant improved varieties of grass carp.

The invention belongs to the technical field of molecular biology, bioinformatics, sorghum genetics and whole-genome gene chips, and particularly relates to a sorghum whole-genome SNP molecular marker combination developed based on a targeted sequencing technology, a 10K liquid chip and application of the sorghum whole-genome SNP molecular marker combination and the 10K liquid chip. The SNP molecular marker combination comprises 10,000 SNP loci, and the specific information of the 10,000 SNP loci is as shown in a table 1; the physical positions of the 10000 SNP loci are determined by performing sequence alignment based on a reference genome of the wine red tassel sorghum variety HYZ-T2T with the version number of v1.0. A liquid chip developed based on the SNP molecular marker combination provided by the invention can be effectively applied to genetic diversity analysis, whole genome association analysis, genetic typing, molecular marker-assisted selective breeding, whole genome selective breeding and other applications of sorghum germplasm resources.

The invention discloses a Chinese rose petal outer edge notch whole genome SNP molecular marker combination and application thereof, and aims to overcome the defects in the prior art, 879 SNP markers significantly related to petal outer edge notch are identified by fusing 358 Chinese rose whole genome re-sequencing data and petal outer edge notch phenotype correlation analysis and applying a multi-model combined screening technology, and the SNP markers are used for identifying the petal outer edge notch. And a whole genome selection model with high prediction accuracy is established. The markers are distributed on 14 chromosomes, high-throughput and rapid detection can be achieved, the detection period is shortened, the petal wave character is directly predicted through seedling genotype data, and the breeding process is accelerated. The method has the advantages of low cost, high throughput and industrialization potential, provides key data support for Chinese rose petal outer edge notch genetic law analysis and molecular marker assisted breeding, and significantly improves the breeding efficiency and precision.

This invention relates to the fields of genomics, molecular biology, bioinformatics, and genome-wide selection breeding, specifically a 20k liquid-phase breeding chip for the whole genome of *S. esculenta* and its applications. The liquid-phase chip contains background SNPs and functional SNPs located on the *S. esculenta* reference genome; wherein the background SNPs are uniformly distributed within the genome; and the functional SNPs are associated with important economic traits of *S. esculenta*; these important economic traits include one or more of the following: saponin content, polysaccharide content, and heat tolerance. The chip can be applied to the assessment of genetic diversity in *S. esculenta*, identification of germplasm resources and phylogenetic relationships, genome-wide association analysis of important economic traits, and genome-wide selection breeding. This chip has advantages such as high throughput, high region coverage, high locus detection rate, and high flexibility, providing powerful tool support for molecular breeding of *S. esculenta*.

The invention relates to methods of identifying and characterizing a Cannabis spp. plant comprising a quantitative trait locus (QTL) or a causal polymorphism associated with a flower density trait, and to Cannabis spp. plants having a flower density trait of interest comprising defined allelic states of polymorphisms defining the QTL or defined allelic states of causal polymorphisms provided herein. Also provided are Cannabis spp. plants with a flower density trait of interest comprising defined allelic states of polymorphisms and plants identified, characterized or produced by the methods described. Further provided are methods of marker assisted selection, genomic selection, marker assisted breeding, and genetic modification, for obtaining plants having a flower density trait of interest.

The invention discloses a construction method of an MD-100K liquid phase chip for genome selection of dairy cattle and dairy-meat cattle. The construction method comprises the following steps: step 1, obtaining multiple varieties of candidate SNP (Single Nucleotide Polymorphism) sites; step 2, performing multiple quality screening on the SNP sites; and step 3, designing and optimizing the probe. The method has the beneficial effects that the method is specially designed for the main dairy cattle variety and the dairy and meat dual-purpose cattle variety in China for the first time, and the problem that imported chips are not suitable for water and soil in local varieties in China is effectively solved.

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.

The invention discloses a sample data expansion method and device for whole genome selection, equipment and a medium, and the sample data expansion method for whole genome selection comprises the steps: obtaining real genotype data of a target crop in a historical crop breeding process and phenotype data corresponding to the real genotype data, generating an initial sample set according to the real genotype data and the phenotype data; based on linkage feature information of the real genotype data, performing segment segmentation on initial gene sample data in the initial sample set, and performing segment replacement on segmented gene segments based on auxiliary gene sample data to generate a mixed gene sample; and training a pre-constructed crop prediction model based on the mixed gene sample and the initial sample set. According to the technical scheme, the prediction efficiency of crop character prediction and the reliability of the prediction result are improved.

This invention discloses a method for calculating genome-estimated breeding values ​​based on Manhattan distance marker screening, belonging to the field of crop genetics and breeding technology. The method includes acquiring genotype and phenotypic data, determining whether to execute a Manhattan distance-based marker screening process, calculating the number of target markers to be retained on each chromosome and the number of redundant markers to be removed in each iteration, and calculating the Manhattan distance between the current reference marker and the remaining candidate markers in the current candidate marker set to determine the new reference marker and the new candidate marker set. When the number of markers in the retained marker set reaches the target number, the retained marker sets of all chromosomes are obtained to form an optimized marker subset. The genome selection model is trained based on phenotypic data and the optimized marker subset, and the genome-estimated breeding value is output. This invention solves the problems of limited prediction accuracy and heavy computational load and low efficiency of existing genome selection methods in the context of massive data environments.

The invention discloses a corn genome breeding 45K chip and application thereof, the chip covers 44, 637 SNP loci and 27 InDel loci, and the SNP loci are uniformly distributed on 10 chromosomes and part of scaffold of a corn genome and have rich polymorphism. Compared with an existing corn chip, the SNP marker of the 45K chip is derived from re-sequencing results of 507 corn varieties, has better variety representativeness, and contains 925 key functional gene loci for close planting and high yield and 96 corn variety authenticity identification loci; the method can be more effectively used for functional gene identification, genetic diversity analysis, heterosis group division, whole genome selection analysis and variety authenticity identification.

The invention relates to the technical field of bioinformatics and crop breeding, and particularly discloses a method, a device and equipment for predicting the close planting yield of brassica napus by using hypocotyl length based on a whole genome selection technology. The method is characterized by comprising the following steps: acquiring whole genome sequencing data of brassica napus germplasm; inputting the whole genome sequencing data into a target model; outputting hypocotyl length data of the brassica napus under a close planting condition through the target model; and according to the hypocotyl length data of the brassica napus under the close planting condition, obtaining a brassica napus germplasm yield potential sorting result. According to the method, whole genome selection and key morphological characters (hypocotyl length) under specific stress (close planting conditions) are combined for the first time, high-yield varieties suitable for close planting cultivation can be efficiently and accurately screened out without on-site close planting tests in the early stage of rape breeding, and the breeding efficiency is remarkably improved.

The invention belongs to the technical field of aquatic genome selective breeding, and particularly relates to an edwardsiella tarda-resistant genome selective breeding liquid-phase chip for oplegnathus punctatus and application of the liquid-phase chip. According to the method, 500 core SNP loci highly associated with the Edwardsiella tarda resistance character are screened out from 2415773 high-quality SNPs by obtaining the whole genome SNP marker of the oplegnathus punctatus and combining the three methods of MME-rank, GWAS and PVE, and the low-density liquid phase chip prepared by taking the 500 core SNP loci as the core shows extremely high prediction accuracy in a reference group and an independent verification group and can be used for detecting the Edwardsiella tarda resistance character of the Edwardsiella tarda resistance character of the Edwardsiella tarda resistance character of the Edwardsiella tarda resistance character of the Edwardsiella tarda resistance character. The method is obviously superior to a whole genome set and a uniformly distributed marker set; family verification shows that the family GEBV calculated based on the chip is significantly related to the actual survival rate of the offspring. According to the method, high-precision disease resistance performance prediction is realized at extremely low cost, and a key technical tool and a solution are provided for rapid breeding of disease-resistant improved varieties of oplegnathus punctatus.

The invention discloses a breeding method for improving grouper feed protein utilization efficiency and hypoxia-resistant selection efficiency based on a whole genome, which comprises the following steps: (1) determining phenotypic values of grouper breeding population individuals, and screening individuals with excellent characters as primary selection objects; and (2) constructing an additive genetic correlation matrix based on liquid phase chip genotype data and a molecular correlation coefficient method, calculating breeding values of feed protein utilization efficiency and hypoxia-resistant selection efficiency of individuals by utilizing a linear mixed model, and screening parent breeding values according to the breeding values to obtain candidate individuals. According to the invention, a whole genome selection technology flow of grouper feed protein utilization and hypoxia resistance is established, the prediction effect of the whole genome selection technology on the feed protein utilization and hypoxia resistance of groupers, especially epinephelus fuscoguttatus, is researched, and the selection number of reference parent groups is reduced, so that the production cost is reduced, and the economic benefit is increased. Therefore, an economical and effective whole genome selection technology is established.

The invention relates to the field of plant molecular biology, in particular to an SNP (Single Nucleotide Polymorphism) molecular marker combination for identifying length and width of upland cotton seeds and application of the SNP molecular marker combination. The SNP molecular marker combination provided by the invention comprises 12 molecular markers, and the 12 SNP molecular markers are all located on an A07 chromosome of a reference genome Gossypium hirsutum (AD1) 'TM1' gene CRIv1 of upland cotton. The SNP molecular marker combination provided by the invention exists in the form of DNA, can be detected in each tissue and development stage of cotton, is not limited by environment and seasons, is suitable for rapid large-scale screening, can realize early prediction of cottonseed utilization value, provides key technical support for cottonseed genetic research, molecular marker-assisted breeding and whole genome selection, and has a wide application prospect. The cotton molecular breeding efficiency and accuracy are improved.