166 results about "Population genetics" patented technology

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 discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to calving interval traits of dairy cows and application of the SNP molecular marker. The number of the SNP molecular markers is four, and the nucleotide sequences of the four markers are as shown in SEQ ID NO.1-4. Researches find that the four SNP molecular markers are significantly related to the Chinese Holstein cattle calving interval traits, and can be used for molecular marker-assisted breeding of the Chinese Holstein cattle calving interval traits to accelerate breeding of Chinese Holstein cattle with strong fecundity. The SNP molecular marker is used for identifying the calving interval character of the Chinese Holstein cattle, the four SNP loci are detected in actual breeding, seed selection and matching are guided, the breeding efficiency is improved, the non-pregnant period is shortened, the production performance of the dairy cattle can be comprehensively improved, the breeding strategy can be optimized, and the population genetic progress can be accelerated.

The invention relates to the technical field of bioinformatics, in particular to a goat selective breeding method and system based on a genetic algorithm, and the method comprises the following steps: based on goat population genetic initialization data, extracting a character characteristic index and a genetic relationship parameter of each pairing combination in a population, analyzing genetic diversity, character matching degree and genetic relationship, and calculating the genetic diversity, character matching degree and genetic relationship; and screening matched individuals and pairing hereditary characteristics, and rearranging and recombining to obtain primary pairing data of goat breeding. According to the method, genetic diversity and character matching degree are analyzed, genetic diversity and excellent character inheritance are balanced, genetic resource utilization efficiency is improved, local optimal combinations are accurately screened, genetic drift risks are reduced, character stability is enhanced, a two-point crossing rule and global character dynamic analysis are combined, and global breeding layout is optimized; according to the method, short-term improvement and long-term stability are both considered, the genetic structure is optimized through Pareto rule screening and global state updating, and the sustainability and accuracy of a breeding scheme 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 a flood season anchoring ground-wharf channel ship scheduling optimization method based on a multi-population genetic algorithm, and belongs to the field of ship scheduling, and the method comprises the steps: building a flood season anchoring ground-wharf channel ship scheduling model with the purpose of minimizing the waiting time of a ship at an anchoring ground and the departure delay time of the ship at a transfer wharf, and optimizing the ship scheduling model; establishing constraint conditions satisfied by ship scheduling of the anchorage ground-wharf channel in the flood season; respectively solving a flood season anchoring ground-wharf channel ship dispatching anchoring ground departure time decision problem, a water flow limiting channel distribution problem and a transfer wharf berth distribution problem based on the satisfied constraint conditions to obtain a flood season anchoring ground-wharf channel ship dispatching initial scheme; and based on a multi-population genetic algorithm with a hybrid coding strategy, an elitism strategy and a self-adaptive mechanism, carrying out iterative solution on a ship scheduling problem to obtain an optimized ship scheduling scheme. The ship transportation efficiency of a water-land combined transportation mode is improved, and the navigation pressure of the hydro-junction ship lock is relieved.

The invention discloses a production line configuration optimization method and device based on digital twinborn and dual-population genetic algorithm collaboration. The method comprises the following steps: constructing a PCB production line twinborn model; constructing a single-row layout model of the PCB production line, and constructing and forming a multi-target planning model by taking the maximum production efficiency, the maximum equipment utilization rate and the minimum logistics cost as targets; the method comprises the following steps: acquiring twinborn data in real time, acquiring a priority sequence of each process unit of a PCB production line according to the twinborn data, and encoding the priority sequence of each process unit and spacing distances among the process units by using a double-population genetic algorithm, carrying out iterative solution by using a fitness function constructed based on a multi-objective planning model to obtain an optimal configuration scheme; and mapping an optimal configuration scheme obtained by iterative solution to the twin model, and evaluating an optimization effect. According to the invention, an accurate and reliable PCB production line resource configuration optimization scheme can be efficiently generated, and the production line efficiency and the equipment utilization rate are improved.

The invention relates to the technical field of information, and provides a cross-platform global weed gene database unified building method which comprises the following steps: screening out a weed population having gene exchange characteristics with a target crop, identifying gene segments of gene exchange between the crop and weeds by adopting a gene comparison method, and determining a transmission path of resistance genes in interspecific hybridization; according to a gene comparison result, extracting transmission path data of the resistance gene, and analyzing the influence of resistance gene transmission on the genetic structure of the weed population in combination with the genetic structure characteristics of the weed population; calculating the frequency distribution of the resistance genes in different weed populations, judging the diffusion trend of the resistance genes in the weed populations according to the frequency distribution, generating a resistance gene diffusion map, and predicting the variation trend of the future weed population genetic structure based on a weed population genetic structure variation trend chart and the resistance gene diffusion map. And a global weed gene database is established, so that an effective weed management strategy can be formulated.

The invention discloses a pig breeding screening method and system based on a body type database, and particularly relates to the technical field of pig breeding screening. The system comprises a multi-modal sign data acquisition and integration module for collecting and standardizing heterogeneous data sources such as phenotypic signs, genomics and environmental parameters of breeding pigs in real time, and a multi-dimensional biological characteristic modeling and analysis module for analyzing a nonlinear action mechanism among genetic markers, phenotypic characteristics and environmental factors, the genetic potential intelligent judgment module is used for quantitatively evaluating spatial expression potential and intergenerational transmission probability of genetic advantages of the breeding pigs through a deep learning algorithm; and the intelligent screening and dynamic monitoring module is used for establishing a multi-dimensional threshold dynamic regulation and control mechanism to realize accurate elimination decision and continuous optimization of a germplasm resource library. According to the method, the screening accuracy is remarkably improved by designing multi-source data fusion and online optimization capability, meanwhile, mistaken elimination is reduced through a redundant superior species temporary storage management module, and collaborative improvement of population genetic diversity and environmental adaptability is ensured.

The invention relates to the technical field of biology, in particular to a detection method for tilapia streptococcus agalactiae resistance, a KASP primer group and application. According to the invention, the key SNP site of the ABCB4 gene, which is obviously associated with the streptococcus agalactiae disease resistance, of the tilapia is identified by a population genetics method, a typing method of the SNP site is developed by a KASP technology, efficient evaluation on disease resistance characters is realized, experimental data shows that the survival time of an AA genotype individual in a challenge test is prolonged compared with that of a GA / GG genotype individual, and the survival time of the AA genotype individual in the challenge test is obviously prolonged compared with that of a GA / GG genotype individual. The proportion of resistant fishes is remarkably increased, and genotype frequency distribution is strongly related to group disease resistance. According to the breeding strategy based on the SNP marker, the disease resistance of bred groups can be integrally improved, the morbidity and death rate are reduced, an efficient genetic improvement tool is provided for breeding of tilapia mossambica for resisting streptococcus agalactiae diseases, the loss of breeding diseases is reduced, and antibiotic dependence is reduced.

The invention discloses a multi-gene risk scoring model construction method and system based on multi-population multi-phenotype data integration, and the method comprises the steps: S1, carrying out the construction of a to-be-detected phenotype according to a to-be-detected phenotype list composed of a to-be-detected phenotype and other phenotypes having genetic correlation with the to-be-detected phenotype; collecting phenotype GWAS data and reference genome data required for analysis in the descendant crowd to which the sample to be detected belongs and other descendant crowds, and collecting genotype data of the sample to be detected; s2, respectively calculating an LD score between every two sites and a comprehensive LD score of each site; s3, estimating parameters of the polygene risk scoring model, including the genetic rate of each phenotype, the genetic covariance and the environmental covariance between every two phenotypes, and the cross-population genetic covariance of each phenotype of the descendant population to which the sample to be tested belongs and other descendant population, and estimating a site weight value of a polygene risk score PRS; and S4, calculating a polygene risk score PRS value of the to-be-detected sample. The prediction precision of the complex phenotype or disease risk is improved.

The invention discloses a polar region environment-oriented two-stage micro-siting optimization method for a wind generating set, and relates to the technical field of polar region renewable energy planning and wind power generation, the optimization method comprises the following steps: polar region environment parameter initialization and scene modeling; the first stage is grid primary selection based on mixed integer linear programming; the second stage is coordinate refinement based on a multi-population genetic algorithm; and scheme output and efficiency evaluation. According to the method, a sector reweighting mechanism of extremely cold correction parameters is realized through reweighting of biochemical parameters and scenes in an environment special for a polar region, the extremely cold correction parameters are directly embedded into a wind regime scene set and a power model, and the problem that a conventional land model can obviously underestimate or overestimate single-machine power and wake flow propagation distance under extremely low temperature and low roughness conditions, so that the reliability of the model is improved is solved. Therefore, the power prediction and wake flow loss evaluation are more practical under the polar region conditions such as the south pole, so that the engineering reliability of site selection decision and the accuracy of generating capacity prediction are improved.

The invention discloses a corn selective breeding effect analysis method integrating population inheritance and deep learning, and the method comprises the steps: collecting corn germplasm resource data, including phenotype data, genotype data and environmental data; performing standardization processing and missing value filling on the phenotypic data, and calculating population genetic parameters including allele frequency, linkage imbalance and population structure stability; performing correlation analysis on the population genetic parameters and phenotypic data by using a deep learning model, predicting phenotypic values of candidate parents by using the trained model, calculating breeding indexes in combination with the population genetic parameters, and providing guidance for corn breeding decisions based on prediction results; through organic combination of a deep learning technology and a population genetics principle, accurate prediction and evaluation of the corn selective breeding effect are realized, the breeding efficiency is improved, and a new technical path is provided for corn variety improvement.

The invention discloses a subgrade structure parameter intelligent optimization method and device fusing population inheritance and reverse learning, equipment and a storage medium, and relates to the technical field of land traffic engineering subgrade structure design, and the method comprises the steps: obtaining a subgrade engineering to-be-optimized parameter set, a subgrade engineering parameter optimization model and a self-adaptive hyper-heuristic algorithm; based on the roadbed engineering parameter set to be optimized, the roadbed engineering parameter optimization model and the adaptive hyper-heuristic algorithm, population inheritance and reverse learning are carried out to generate a population, and target population individual information is determined; based on the roadbed engineering parameter set to be optimized, the roadbed engineering parameter optimization model, the adaptive hyper-heuristic algorithm and the target population individual information, correlation analysis is carried out to adjust the search direction and the search step length, and target optimization population information is determined; and completing intelligent optimization of roadbed structure parameters based on the target optimization population information. The subgrade parameters are optimized by fusing population heredity and reverse learning, and the optimization efficiency is improved.

The invention discloses an optimization method and system based on a multi-population genetic algorithm. The method comprises the following steps: initializing a plurality of populations; respectively carrying out selection, crossover and mutation operations in each population; a migration strategy is introduced among the populations; the population scale is dynamically adjusted according to the convergence trend and diversity conditions of the population in the evolution process; setting multiple termination conditions to judge whether the multi-population genetic algorithm achieves an effect or not; and after all evolution iterations are completed, outputting the currently found global optimal solution. According to the method, a fitness sharing mechanism, a migration strategy and a dynamic population scale adjustment technology are introduced among a plurality of independent populations, so that some limitations, such as local optimal search and premature convergence problems, possibly encountered by a traditional genetic algorithm are overcome.

The invention relates to a Yangtze river globefish polymorphic SNP molecular marker as well as a development method and application thereof, and belongs to the technical field of DNA molecular markers, nucleotide sequences of sites of the Yangtze river globefish polymorphic SNP molecular marker are as shown in SEQ ID NO: 1-NO.19, primers for amplifying the sites of the SNP molecular marker are as shown in Snpp 01-57, and the primers for amplifying the sites of the SNP molecular marker are as shown in SEQ ID NO: 1-SEQ ID NO: 2-SEQ ID NO: 3-SEQ ID NO: 4. The SNP molecular markers provided by the invention are all derived from high-quality chromosome-level genomes of the Yangtze-River cowfish, screening is carried out in combination with re-sequencing data of three geographical populations, polymorphic SNP loci in the genomes of the Yangtze-River cowfish can be more comprehensively detected, and by utilizing a KASP genotyping technology, the SNP molecular markers can be used for detecting the genomes of the Yangtze-River cowfish. Genetic typing can be efficiently and accurately performed on the polymorphic SNP sites of the Yangtze river globefish, the detection cost is remarkably reduced, and an effective genetic molecular marker is provided for population genetics research such as genetic diversity evaluation, genetic differentiation analysis and genetic relationship identification of the Yangtze river globefish and the sibling species of the Yangtze river globefish.

The invention discloses a satellite planning and scheduling method, medium and equipment based on enhanced multi-population inheritance, and relates to the field of multi-satellite imaging task scheduling, and the method comprises the steps: constructing a constraint model and a target function of multi-satellite task scheduling; calculating the conflict degree of the visible time window of each satellite resource, and allocating the visible time window with the conflict degree of 0 to a task to complete scheduling preprocessing; generating satellite resources and visible time window initial solution individuals of satellite task scheduling by adopting a bisection method; a double-population genetic algorithm is adopted, one population is used for exploring a new allocation scheme, the other population is used for optimizing a task planning result under a specific allocation scheme, and population communication is carried out based on reinforcement learning; and performing task insertion based on time relaxation according to a multi-satellite task scheduling solution obtained by the double-population genetic algorithm, and if task insertion cannot be performed, performing task replacement to obtain a final scheduling scheme. According to the method, the problem of complex multi-satellite imaging scheduling can be solved.

The invention belongs to the field of biotechnology application, and particularly relates to a goose whole genome liquid phase chip and application thereof. The SNP sites on the liquid phase chip are located in a goose reference genome GCA013030995.1, and the number of the SNP sites is 30000. The chip can specifically identify the genetic relationship between commercial geese and local geese, and can also be applied to whole genome association analysis, whole genome selective breeding, target trait QTL positioning analysis, population genetics analysis and the like. According to the invention, by capturing the reference gene and loci in the real sequence thereof, the coverage of sequencing data is improved, and the application value of the chip is enhanced.

The invention relates to the technical field of plant breeding, in particular to a construction method and application of a genetic map of a fruit tree F1 population. The construction method comprises the following steps: mining and screening whole genome sequencing data of a fruit tree F1 group and parents thereof to obtain SNP loci; the sites in accordance with the lmxll or nnxnp separation type in the SNP sites are taken to construct an MNP molecular marker; dividing bins for each chromosome according to a predetermined length, and endowing each bin with a corresponding separation type according to the separation type of the MNP molecular marker in the bins; and constructing a genetic map according to the separation type data of each bin. The construction method provided by the invention can correct errors and deletion of SNP, has high marker detection and positioning precision, consistent linkage relationship and recombination rate, can significantly improve the breeding efficiency when applied to plant breeding, and has significantly high practical application value.

The invention discloses a Dazu black goat gene polymorphism and lambing trait association analysis method, and relates to the field of genes. Comprising the following steps: sample collection and data collection: collecting Dazu black goats as well as blood samples and ovary samples of the Dazu black goats, respectively collecting the lambing number and birth weight of the black goats, and then calculating the average birth weight of the first birth and the average lambing number of the first three births; extracting blood DNA, namely extracting the blood DNA by adopting a traditional phenol-chloroform method; designing a PCR primer and an amplification system; and analyzing a population genetic structure, and carrying out genetic analysis and screening on SNP sites of the goat AMH gene. The molecular marker-assisted technology is utilized to screen out the marker of the targeted gene polymorphic site which is strongly related to the breeding traits of the Dazu black goats, the breeding period can be shortened in molecular breeding, the breeding and breeding efficiency can be effectively improved, and the economic value of the Dazu black goats is further improved.

The invention discloses a compression and decompression method based on generic genome expression, and relates to the technical field of compression and decompression of DNA next-generation sequencing data, in particular to the compression and decompression method based on generic genome expression. The method aims at solving the problems that in the prior art, the capacity of processing population genetic diversity is insufficient, original sequencing quality information cannot be effectively restored during decompression, and memory occupation is too high during large-scale data processing. Obtaining a to-be-compressed sequencing sequence data file, a reference genome sequence and a thousand-person genome variation sample; obtaining a haplotype list, a variation list and a haplotype offset list corresponding to each window block; storing the window number, the haplotype number, the haplotype offset, the head and tail unmatched sequences, the current sequence name and the quality score character string into a single compression block; carrying out binding storage; completing the compression processing of the mass fraction; and obtaining each to-be-compressed sequencing sequence based on the result of the compressed part.

The invention belongs to the field of plant molecular genetics, and relates to a spirodela polymorphic microsatellite molecular marker primer and application thereof. The kit comprises 10 pairs of microsatellite primers which form 5 groups of duplex PCR systems, and the kit can be applied to population genetic diversity analysis of spirodela polyrhiza. The population genetic diversity analysis comprises the following steps: collecting a sample of spirodela polyrhiza to be identified; extracting spirodela polyrhiza genome DNA from the spirodela polyrhiza sample; taking the extracted DNA as a template, and carrying out PCR (Polymerase Chain Reaction) amplification on the DNA template by using the screened 10 pairs of microsatellite primers; carrying out electrophoresis detection on a PCR product, and then carrying out silver staining; the silver staining result is digitally analyzed, the UPGMA clustering analysis chart is drawn by genetic analysis software, the clustering analysis chart of the spirodela polyrhiza is identified according to the clustering analysis result, and the method has huge popularization and utilization value.

The invention provides an AISPN marker combination and a multi-dimensional ancestral and geographic inference model, and relates to the technical field of forensic medicine. According to the method, firstly, seven groups of ancestral inference SNP (Single Nucleotide Polymorphism) sites (AISNPs, AISNPs) of East Asia and Southeast Asia crowds are screened, the screened sites are respectively subjected to efficiency evaluation based on principal component analysis, ADMIXTURE and t-SNE methods, and a set of multi-dimensional ancestral and geographic source inference model is constructed in combination with six different machine learning methods. The AISPN marker combination provided by the invention comprises at least 50 AISPN sites, has relatively high differentiation in East Asia and Southeast Asia crowds, can distinguish nine crowds based on relatively few sites, provides site information for preparation of kits, and provides valuable information for research of forensic medicine, anthropology and population genetics.

According to the multi-distribution-center collaborative medicine distribution model and the double-population genetic simulated annealing algorithm provided by the invention, aiming at the timeliness, multi-center collaboration and customer satisfaction requirements of medicine distribution, a mathematical model taking the total cost minimization as a target is constructed. The model comprehensively considers the vehicle fixed cost, the transportation cost, the customer satisfaction cost and the goods damage cost, introduces a soft time window function based on cosine distribution to quantify the influence of delivery delay on the cost, optimizes resource allocation through a multi-center order splitting strategy, and solves the problems of low delivery efficiency and high cost of a traditional single-center mode. According to the characteristics of the model, a double-population genetic simulated annealing algorithm (DPGSA) is designed. According to the algorithm, the global search capability is enhanced through a double-population coevolution mechanism, the local optimization efficiency is improved in combination with the Metropolis criterion of the simulated annealing algorithm, the defect of premature convergence of a traditional genetic algorithm is effectively avoided, the drug transportation and distribution path is optimized, and the distribution cost is minimized.

The invention discloses 36 pairs of polymorphic primers and 84 pairs of SNP molecular markers used for amplifying the swallow aculeatus, and an application of the polymorphic primers in genetic diversity analysis of the swallow aculeatus, and particularly discloses an application of the polymorphic primers in the genetic diversity analysis of the swallow aculeatus and application of the polymorphic primers in the genetic diversity analysis of the swallow aculeatus, the number of the polymorphic primers is 36, and the number of the swallow aculeatus SNP molecular markers used for amplifying the 36 pairs of the primers is 84. According to the invention, the SNP molecular markers with abundant polymorphism are established on the swallow-wing fish in batches for the first time, 36 pairs of polymorphic primers are screened out, and an efficient analysis technical tool is provided for research on genetic diversity, family identification, population genetic structure, genetic breeding, enhancement and release and the like of the swallow-wing fish; the method for developing the SNP marker is simple, convenient, rapid and efficient, and manpower and cost are saved.

This invention discloses a goose double-enzyme digestion simplified genome sequencing library construction kit, library construction method, and application. The kit includes Kit A, Kit B, and Kit C, and magnetic beads. The invention uses two conventional endonucleases to control the location and number of target fragments, and uses improved enrichment primers to significantly increase the number of library pools for GBS sequencing. This leverages the large amount of NGS data and makes goose population genetics research more feasible. In theory, this library construction strategy can exponentially increase the number of individuals to be tested simply by modifying the corresponding adapter and index sequences.

The present invention provides a sensor layout method and system for large-sized deployable antennas, including the following steps: establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix; establishing a mathematical model for the optimal configuration of sensors as the objective function; initializing the configured sensors, and simultaneously configuring the sensors through population one and population two to generate two initial populations; establishing a fitness function by mapping the objective function in the above step according to the objective function, evaluating the advantages and disadvantages of individuals through the fitness function, and performing selection and optimization using a multi-population genetic algorithm; evaluating the configuration result to determine whether the optimization criterion is satisfied. The present invention can achieve the optimal sensor layout for on-orbit structural state measurement of large-sized deployable antennas, and meet the goal of maximizing the acquisition of structural state information with limited measurement points.

This invention discloses an artificial intelligence-based method and system for predicting and intelligently replenishing SPD consumable demand, belonging to the field of medical consumable supply chain management technology. It obtains key influencing factors of SPD consumables by clustering analysis of historical SPD consumable demand correlation data and identifying influencing factors. Furthermore, through the acquisition and training of an initial SPD consumable demand prediction model, an accurate SPD consumable demand prediction model is obtained. This model is then used to predict real-time SPD consumable demand correlation data, outputting SPD consumable demand prediction results that better match actual needs and applications. In addition, the replenishment objective function is iteratively optimized using a multi-population genetic algorithm to obtain optimal SPD control parameters, thereby automating the generation of intelligent replenishment strategies.

The invention discloses a pig whole genome low-density 6K SNP (Single Nucleotide Polymorphism) chip, and the chip contains 5,866 SNP loci. The SNP chip provided by the invention is suitable for a plurality of fields of pig whole genome association analysis, whole genome selective breeding, population genetics analysis, character-related candidate gene and QTL site analysis and positioning and the like, and has relatively high value in production application and scientific research.

The invention discloses an SSR (Simple Sequence Repeat) primer composition for evaluating genetic diversity of channel catfish breeding population and an application method of the SSR primer composition, and belongs to the technical field of fish genetic breeding. The method comprises the following steps: modifying 5'ends of forward primers of the primers by using FAM fluorophores respectively, amplifying genome DNA of each breeding group by using the 10 pairs of microsatellite site primers respectively, analyzing amplification products, reading genotypes, analyzing parameters, and determining the genotype of the breeding group. The analysis result is used for evaluating the population polymorphism, the variation condition of the population genetic structure and the genetic differentiation degree among the populations. By applying the evaluation method disclosed by the invention, the population genetic diversity and genetic structure of continuous breeding generations of channel catfish can be systematically evaluated. The SSR primer and the genetic diversity evaluation method can be used for genetic improvement and new variety breeding of channel catfish.