288 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.

Disclosed are a genome-wide low-density SNP chip for milk goats and a use thereof. The provided SNP chip is applicable to genetic improvement of economic traits of European milk goat varieties and Chinese native milk goat varieties, can also be applied to a plurality of fields of milk goat genome-wide association study, genome-wide selection breeding, population genetics analysis, trait-related candidate genes, QTL analysis and locating, and the like, and has high value in production application and scientific research.

The invention relates to the technical field of crop genetic breeding and plant molecular design breeding, in particular to a pakchoi whole genome liquid phase chip and application. The pakchoi breeding gene chip disclosed by the invention comprises a target capture probe which is designed by taking 1000 core SNP (Single Nucleotide Polymorphism) molecular markers positioned on 40KSNP sites on a pakchoi reference genome version V4.0 as templates. The pakchoi whole genome liquid phase chip provided by the invention comprises a 40K site targeted capture probe mixed solution and a hybridization capture reagent. The pakchoi 40KSNP targeted capture probe can rapidly and effectively track genetic materials of pakchoi, and is suitable for different application scenes such as accurate identification of pakchoi germplasm resources, genetic relationship analysis between materials, variety authenticity identification, QTL gene positioning and mining, molecular marker-assisted breeding, variety improvement and whole genome selective breeding application. Therefore, the method has good application prospect and important social value.

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 silver carp 20K liquid phase chip and application thereof, the liquid phase chip comprises a probe combination of 20,909 SNP molecular markers covering a whole genome, the physical positions of the 20,909 SNP molecular markers are determined based on sequence alignment of the silver carp genome (GCA041475455.1), and the site information of the 20,909 SNP molecular markers is shown in the specification table 1. The invention provides a silver carp first type whole genome SNP liquid phase breeding chip, which effectively reduces the application cost of silver carp in genetic diversity analysis, QTL positioning, GWAS analysis and the like in scientific research, solves the problem that no applicable product exists in silver carp molecular auxiliary breeding and whole genome selective breeding, accelerates the progress of silver carp basic research and breeding, and has a wide application prospect. The method is of great significance in improving the utilization efficiency of silver carp germplasm resources, accelerating the breeding process of excellent characters and improving the economic value and environmental adaptability of bred varieties.

The invention relates to the technical field of biological breeding, in particular to a biological breeding management method and system based on big data. The method comprises the following steps: acquiring original germplasm data; multi-source heterogeneous data integration is carried out on the original germplasm data, the data integration comprises genotype sequencing integration and historical phenotype integration, and integrated germplasm data is generated and stored in a database in a distributed mode; obtaining original growth data, performing data preprocessing, generating standardized germplasm resource comprehensive data including a crop image feature set and an environment response parameter set, and synchronizing the data to the database; and performing whole genome selection prediction on the integrated germplasm data based on the standardized germplasm resource comprehensive data to generate a genotype-phenotype prediction model. By integrating germplasm resources, field management, breeding management, phenotype management, genotype management and whole genome selection, the accuracy and adjustment flexibility of biological breeding management are improved.

Provided are a dairy goat whole-genome 55K SNP chip and a use thereof. The chip has a total of 54344 SNP sites. The provided dairy goat whole-genome 55K SNP chip can be used for the identification and kinship analysis of imported dairy goat breeds and domestically bred dairy goat breeds, and can also be used in multiple fields such as dairy goat whole-genome association analysis, whole-genome selective breeding, population genetics analysis, and trait-related candidate gene and QTL site analysis and positioning, and has high value in both production applications and scientific research.

The embodiment of the invention discloses an SNP chip of channa maculata and application. The SNP chip comprises a probe combination which is fixedly provided with markers respectively aiming at SNP1-SNP50000. The chip has the advantages of uniform site distribution, high typing accuracy, strong repeatability and higher flexibility, is suitable for mainstream next-generation sequencing platforms such as Illumina and MGI, and has universality. A reliable genotyping technology can be provided for correlation researches such as population genetics analysis, genetic relationship identification, whole genome correlation analysis and genome selection of channa maculata, the breeding efficiency of channa maculata is improved, and the development of the aquatic product breeding industry is promoted.

The invention provides an SNP (Single Nucleotide Polymorphism) molecular marker combination, a molecular probe combination, a liquid phase chip and a kit for corn genotyping and application of the SNP molecular marker combination, the molecular probe combination, the liquid phase chip and the kit, and belongs to the technical field of gene chips. The SNP molecular marker combination and the liquid chip provided by the invention can be used for efficient and rapid genetic typing of corn germplasm resources, and are low in cost and suitable for corn biological breeding. The SNP marker provided by the invention uniformly covers the whole corn reference genome, provides a high-quality molecular marker for silage corn whole genome selective breeding, and can also be used for map-based cloning of important agronomic trait genes of silage corn.

The invention provides a genome selective breeding method and system based on an EN-CNN model. The method comprises the following steps: capturing important feature information from genotype data of a to-be-bred object by using an auto-encoder; predicting growth traits of the to-be-bred object according to the important feature information by using a convolutional neural network model; and according to the growth traits of the to-be-bred object, determining whether to select the to-be-bred object for breeding. According to the method, the precision and robustness of genome selective breeding are improved.

The invention discloses a method for screening molecular markers based on apparent annotation information to carry out whole genome selective breeding, which comprises the following steps: step A, carrying out phenotype determination and genome sequencing on growth traits of a litopenaeus vannamei breeding population to obtain phenotype data and SNP (Single Nucleotide Polymorphism) typing data; step B, performing GS analysis by using phenotype data and SNP typing data, predicting a genome breeding value of a breeding population through a mainstream breeding model, and screening out an optimal breeding model; and step C, classifying chromatin states through ChromHMM analysis by combining the optimal breeding model with the key histone modified region, and screening out the functional SNPs with the key histone modified region. The SNPs have relatively strong functional relevance, are used for different regional groups, and can provide more accurate molecular markers for growth character genetic analysis of bred animals by using less SNPs under the same prediction accuracy, so that the accuracy of genetic breeding value estimation and the cross-group effect are remarkably improved, and the breeding process is accelerated.

The invention provides a fine-wool sheep genome selection method, which relates to the field of animal genetic breeding, and comprises the following steps: establishing a sheep genome reference group, and carrying out main phenotypic character determination on the sheep genome reference group; designing a liquid phase chip based on re-sequencing data of a plurality of sheep varieties, and performing fine-wool sheep genome selection to obtain GWAS prior information; estimating heritability of the genetic variance and the error variance to different characters based on an RRBLUP model, and obtaining a character heritability statistical result; performing genome estimation breeding value prediction analysis based on a character heritability statistical result; constructing a breeding target character according to the breeding target, and constructing a genome comprehensive breeding value estimation model based on the breeding target character; comprehensive breeding values of the sheep individuals are calculated based on a genome comprehensive breeding value estimation model, comprehensive breeding value ranking is carried out, and sheep seed selection and matching are carried out according to the comprehensive breeding values; and carrying out important economic character genome breeding value prediction analysis based on the GWAS priori information.

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 discloses a high-efficiency wheat breeding method based on a modern biotechnology, and belongs to the technical field of high-efficiency wheat breeding, and the method comprises the following steps: S1, collecting and identifying wheat germplasm resources, and screening materials with target character expressions; s2, performing phenotype identification on the screened material under a multi-ecological environment condition to obtain integrity expression data; s3, carrying out genetic typing on the identified material by adopting an SNP chip or a sequencing technology, and constructing a wheat high-density genetic map; s4, based on the genetic map and phenotype data, carrying out QTL positioning analysis on the target character, and determining a key control site; s5, establishing a whole genome selection model based on the genetic map and phenotype data, and performing predictive selection and breeding value evaluation on the germplasm material offspring; by integrating a QTL positioning result and a high-throughput SNP typing technology, target character recognition on a gene level is realized in a germplasm resource preliminary screening stage, the precision and efficiency of early-stage material selection are remarkably improved, and the screening burden of breeding populations is reduced.

The invention relates to the technical field of molecular markers and molecular breeding, and particularly discloses a group of SNP (Single Nucleotide Polymorphism) molecular markers related to corn ear rot resistance and application of the SNP molecular markers. According to the invention, 1223 parts of corn inbred line population materials composed of SS, NSS, PA, PB and TSPT subgroup materials are utilized, GWAS analysis is carried out on 6840,000 high-quality SNP markers obtained based on re-sequencing and spike rot resistance phenotype data of 9 environments, and 50 SNPs significantly associated with the corn spike rot resistance exist in Chr147833646-48395513 bp through identification. The SNP1-SNP50 marker provided by the invention can be used for rapidly selecting a spike rot resistant corn material through a whole genome selection or molecular marker-assisted selection method, and the molecular breeding process of a new spike rot resistant corn variety is accelerated.

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 discloses a grape downy mildew resistance whole genome selective breeding method based on machine learning, which comprises the following steps: randomly dividing 132 samples into a training set and a test set according to a ratio of 4: 1, and respectively extracting first 1-100 thousand variation sites as gradient training data sets according to a whole genome association analysis result; and on the basis of 10 classic regression models and the dimensionality-reduced variation data set, machine learning training and evaluation are carried out on 105 training set samples, finally, the variation data set with the highest prediction accuracy and an optimal model are screened out, and phenotype prediction is carried out on 27 test set samples by using the optimal model. The invention relates to the technical field of plant breeding, and the grape downy mildew resistance whole-genome selective breeding method based on machine learning has remarkable advantages in resistance prediction and screening, breeding efficiency improvement and multi-character comprehensive improvement, breaks through the limitation of a traditional breeding method, and is suitable for large-scale popularization and application. An innovative solution is provided for green and sustainable development of the grape industry.

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 belongs to the technical field of molecular biology, and particularly discloses a cotton 10K functional site breeding chip and application thereof. The breeding chip is named as' Cotton Core No.1 ', and comprises a 10K functional site targeting capture probe group designed based on a reference genome of disease-resistant, high-quality and high-yield modern upland cotton No.8, the probe group comprises 11159 SNP (Single Nucleotide Polymorphism) loci, 3981 of the SNP loci are functional loci associated with 13 important agronomic characters, and 7178 of the SNP loci are background loci reflecting genetic diversity; the SNP site information is shown in the specification table 1. The invention discloses a cotton 10K functional site breeding chip and application thereof, the breeding chip contains functional sites with more index function genetic variation, has higher detection accuracy among different cotton varieties, is applied to cotton molecular marker-assisted selection breeding, whole genome selection breeding and whole genome correlation analysis, and has higher detection accuracy. The breeding efficiency can be obviously improved, and the practical application is wider.

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 discloses a western China cattle parameter-free Bayesian genome selection method. The method comprises the following steps: step 1, constructing a reference group and measuring important classification characters; step 2, collecting blood from the western China cattle, preserving, extracting DNA, and performing genetic typing to obtain the genotype of each SNP site; step 3, for the individual Chinese western cattle, using plink2 software to associate the genotype file and the phenotype file to obtain summarized statistical data; partitioning each SNP site according to the position of a chromosome to obtain an LD reference file; 4, the summarized statistical data and the LD reference file serve as input files of a parameter-free Bayesian model, and an effect value of the SNP site is obtained through calculation; and multiplying the genotype vector of the candidate individual by the locus effect value vector to obtain a genome estimation breeding value. The invention aims to establish a breeding method for classification characters of the Huaxi cattle based on a parameter-free Bayesian genome selection technology, and provides a molecular breeding method for breeding high-quality Huaxi cattle so as to promote rapid development of beef cattle breeding industry.

The invention discloses a pea whole genome 20K SNP (Single Nucleotide Polymorphism) liquid phase breeding chip and application thereof, the liquid phase breeding chip comprises 21 and 659 SNP loci on a pea whole genome, the SNP loci comprise published 235 reliable functional loci obviously related to 57 characters, and examples for pea sample genetic typing are provided. The chip can be widely applied to important character analysis, germplasm resource genetic diversity analysis, variety identification analysis, auxiliary selective breeding, population structure analysis, heredity and evolution analysis, genetic relationship identification, whole genome association analysis or genome selection of peas, and is helpful for improving the pea breeding efficiency; the innovation and improvement of pea varieties are promoted.

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 an introduced-variety pig 10K SNP liquid chip based on targeted capture sequencing and application, and belongs to the technical field of biomolecular breeding. Target SNP sites are collected, selected and filtered, an SNP site set with comprehensive performance is screened out, a probe is designed on the basis of the SNP site set, the introduced variety pig 10K SNP liquid phase chip is further prepared, the SNP sites of the chip have the characteristics of uniformity, polymorphism, compatibility, stability and functionality, pig genomes can be covered to the maximum extent, and the detection sensitivity is high. Meanwhile, the selection of pig genomes can be greatly reduced, especially the cost of early selection of variety pigs is reduced, in addition, the selection efficiency and filling accuracy of chip sites filled to more than 50K can be ensured, and the requirements of subsequent variety identification, lineage analysis, genetic relationship identification, genome selective breeding and whole genome association analysis are met.

A GAN model construction method, and a data fitting, phenotype prediction, sample augmentation and breeding method based on a GAN model. The construction of a GAN model comprises: first, entering a real multi-omics data generator G1 on the basis of input real multi-omics data, extracting features, and then entering a real phenotype discriminator D1, and training G1 and D1; and then randomly generating a group of noise, inputting same into a fitting multi-omics data generator G2, inputting real data into G1, outputs of G2 and G1 entering a fitting multi-omics data discriminator D2, and training G2 and D2. The method can be at least used for making up for an insufficient data amount and also fully exerting the advantages of a deep learning algorithm, thereby comprehensively improving the accuracy of genome selection.

The invention provides a Sichuan local chicken 11K SNP liquid phase chip and application thereof, the liquid phase chip is prepared from a Sichuan local chicken 11K SNP molecular marker combination, the Sichuan local chicken 11K SNP molecular marker combination is composed of 11747 SNP molecular markers, and chromosome positions and numbers of the 11747 SNP molecular markers on a chicken reference genome GRCg7b are shown in a specification table 1. The chip is high in detection flux, high in target site detection rate (99.91%) and accurate and reliable in typing result (the repetition consistency rate is 99.82%), and is a molecular marker chip with low density, high accuracy and low cost; the method can be used for chicken germplasm resource identification and improvement, genetic diversity evaluation, population structure analysis, genetic relationship identification, transmission map construction and QTL positioning, whole genome association analysis, molecular marker-assisted selection, whole genome selective breeding and the like.

The invention discloses a lateolabrax japonicus liquid-phase chip based on a targeted genotype detection technology and application of the lateolabrax japonicus liquid-phase chip, the lateolabrax japonicus liquid-phase chip can detect genotypes of 45 and 459 target sites, and the lateolabrax japonicus liquid-phase chip comprises 44 and 927 background SNPs sites uniformly distributed in a whole genome, 454 INDELs sites located in a coding region and capable of causing frame shift mutation and 78 functional sites related to lateolabrax japonicus growth. The chip is based on a targeted sequencing genotype detection technology (GBTS) of liquid-phase probe hybridization, and compared with an existing lateolabrax japonicus genotyping method, the liquid-phase chip provided by the scheme has great advantages in the aspects of repeatability and accuracy of target site detection, experiment standardization degree, data analysis simplicity degree, required computing resources and the like. The invention fills up the blank that the lateolabrax japonicus lacks genetic typing chips, and is suitable for genome selective breeding, whole genome association analysis, germplasm identification and genetic diversity analysis of lateolabrax japonicus.

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.