Four-stage precise breed conservation method and platform for local livestock and poultry

Abstract

The invention provides a four-level precise breed conservation method and platform for local livestock and poultry, and the method comprises the following steps: collecting newly born or newly introduced samples in a breed conservation population of a target local livestock and poultry variety in each generation, constructing a whole genome genotype database, and constructing a whole genome genotype database of the samples on the premise of maintaining the genetic diversity of the population; genomic breeding values on the concerned phenotypic characters are sequenced, a predetermined proportion of individuals ranked at the last are eliminated or are not reserved for seed use any more, and a four-level seed conservation system and an integrated management platform for dynamically monitoring all data in real time are established. According to the method and the platform, a four-stage breed conservation system and an integrated management platform are constructed, so that real protection, accurate real-time dynamic monitoring, characteristic maintenance and efficient utilization of local livestock and poultry genetic resources are realized.

Description

A local four-level precision breeding method and platform for livestock and poultry Technical Field

[0001] This invention relates to the field of livestock and poultry genetic resource protection technology, specifically to a local livestock and poultry four-level precision breeding method and platform. Background Technology

[0002] With the large-scale promotion of commercial high-yield varieties, there is an urgent need to build a more scientific and efficient conservation technology system for local varieties.

[0003] The current conservation technology system has the following significant limitations: First, it relies on phenotypic and population size to determine the purity of a variety, making it difficult to accurately identify the purity and easily leading to crossbreeding. Second, it cannot quantify and assess the true level of genetic diversity within a population, making it difficult to scientifically formulate conservation plans. Third, it lacks targeted protection for key genes related to the distinctive traits of local varieties, such as tolerance to roughage, stress resistance, and high-quality meat, which can easily lead to the degradation of excellent genetic characteristics. Fourth, information is fragmented across the conservation, breeding, production, and monitoring stages, and a unified data integration and decision support platform has not been formed, which restricts the improvement of conservation effectiveness.

[0004] Chinese patent application CN 117542418A discloses a method for evaluating the conservation effect of a breeding population based on low-depth whole-genome resequencing technology, comprising the following steps: First, samples are collected from the breeding population, and genomic DNA is extracted. Then, qualified and effective SNP markers at the whole-genome level are obtained through low-depth resequencing and related bioinformatics analysis. Using the obtained whole-genome SNP marker information, parameters such as the proportion of polymorphic markers in the breeding population, average expected heterozygosity and average observed heterozygosity, linkage disequilibrium decay rate, principal component analysis between breeding populations, genetic distance and genetic phase coefficient between individuals and between breeding populations, and ROH-based inbreeding coefficients of each breeding population are analyzed. This allows for a more comprehensive evaluation of the conservation effect of the breeding population, timely identification of problems during the succession process, and the proposal of corresponding solutions.

[0005] Because the assessment is conducted only at a specific point in time, its results reflect long-term, relatively stable genetic changes, and therefore cannot reflect dynamic problems that arise during the succession of the breeding population. Genetic changes typically develop slowly over multiple generations, leading to a significant lag in assessment results. This can result in ineffective feeding, wasted conservation funds, and even irreversible damage to the genetic health of the breeding population. In reality, it fails to achieve its goal of "timely detection of problems arising during the succession of the breeding population and the proposal of corresponding solutions." Summary of the Invention

[0006] To address the problems existing in the prior art, the present invention aims to provide a four-level precision conservation method for local livestock and poultry. This method addresses the shortcomings of existing conservation methods in terms of targeted protection of distinctive genes and systematic management of the conservation process. By constructing a four-level conservation system and an integrated management platform, it achieves the true protection, precise monitoring, distinctive maintenance, and efficient utilization of local livestock and poultry genetic resources.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] This invention provides a four-level precision conservation method for local livestock and poultry, characterized by the following steps: after collecting newborn or newly introduced samples from the conservation population of the target local livestock and poultry breed in each generation and constructing its whole genome genotype database, the following steps are performed respectively: determining the number of the conservation population, identifying the purity of local livestock and poultry breeds, assessing genetic diversity based on genomic information, protecting characteristic genes, and establishing an integrated information platform for genetic resources.

[0009] The genetic diversity assessment steps mentioned therein include the calculation of genetic diversity parameters selected from one or more of the following dimensions: observed heterozygosity, expected heterozygosity, polymorphism information content, genomic inbreeding coefficient, and genomic kinship matrix;

[0010] The protection of distinctive genes involves, while maintaining the genetic diversity of the population, ranking the genomic breeding values ​​of the phenotypic traits of interest, and eliminating or no longer retaining individuals at the bottom of the rankings for breeding purposes.

[0011] The integrated information platform for genetic resources includes real-time, dynamic monitoring of all data.

[0012] Preferably, the observed heterozygosity and the expected heterozygosity are calculated using the following formulas:

[0013] ;

[0014] ;

[0015] Where H o H represents the observed heterozygosity. e N represents the expected heterozygosity. h p represents the number of heterozygous individuals in the conservation population; N represents the total number of individuals in the conservation population; i This represents the frequency of the i-th allele in the conservation population;

[0016] The polymorphic information content is calculated using the following formula:

[0017] ;

[0018] Where PIC represents polymorphic information content; p i q j These represent the frequencies of the i-th allele and the j-th allele in the conservation population, respectively.

[0019] The genomic inbreeding coefficient is calculated using the following formula:

[0020] ;

[0021] Where F ROH L represents the genomic inbreeding coefficient; k represents the individual sequence number in the conservation population; N represents the total number of individuals in the conservation population; ROH Indicates the length of the ROH fragment in the genome of each individual; L g Indicates the total length of the autosomal genome;

[0022] The genome kinship matrix is ​​calculated using the following formula:

[0023] ;

[0024] Where G represents the genomic kinship matrix; Z represents an n×m genotype design matrix containing genotype information for all individuals to be analyzed; n represents the number of individuals, and m represents the number of SNP markers; Z′ represents the transpose of matrix Z, with dimensions m×n; p i This represents the frequency of the i-th allele in the conservation population.

[0025] Preferably, the step of identifying the purity of local livestock and poultry breeds includes screening core SNP loci from the whole genome genotype database to form a breed identification standard library, genotyping the individual to be tested, comparing its genotype data with the standard library, calculating the pedigree composition ratio (determining whether it is a purebred individual of the local breed by the pedigree composition ratio); setting a pedigree content threshold Th (Th is 90%), if it is higher than the pedigree content threshold, it is determined to be a genetically pure individual, otherwise it is a hybrid or mixed individual.

[0026] Preferably, the screening criteria for the core SNP loci are as follows: calculate the genetic differentiation index Fst of each variety population relative to other populations in the genotype database, extract the top n SNP loci with the highest Fst values ​​for each population for variety identification, and screen out m core loci as a standard library for variety identification through a gradient boosting decision tree model; wherein, n for each population is not less than 1000, and the total number of SNPs m is not less than 5000.

[0027] Preferably, the quality control standards adopted in the genotype database construction step include: removing low-quality locus data with a detection rate of <95% and filtering low-frequency allele data with a frequency of <0.01.

[0028] Preferably, the special gene protection step includes forming a phenotypic database that corresponds one-to-one with the genotype data of the target local livestock and poultry breeds; using the best linear unbiased predictive statistical model of the genome, calculating and ranking the genomic breeding value of each individual on the phenotypic trait of interest, and culling or no longer retaining the bottom-ranked individuals for breeding purposes.

[0029] More preferably, the steps for establishing the integrated genetic resource information platform include: integrating and storing data on the number of conservation populations, genotype data, purity identification data, genetic diversity assessment data, and characteristic gene protection data in a unified central database for management; collaboratively managing the core conservation population and the production population, and providing the optimal mating scheme obtained from automated simulation; generating scientific breeding and mating schemes, including suggestions for elimination of the lowest-performing individuals, based on the ranking of genomic breeding values ​​and preset breeding goals and conservation requirements, providing intelligent breeding decision support; visualizing and monitoring all data in real time and dynamically, setting safety thresholds for key indicators, and automatically triggering an early warning mechanism when the threshold is reached.

[0030] This invention also provides an integrated genetic resource information platform for the aforementioned four-level precision breeding method for local livestock and poultry, characterized by comprising a central database module, a collaborative management module for the core breeding group and production group, an intelligent breeding decision-making module, and a data visualization module; wherein the central database is used to integrate, store, and manage genotype data, purity identification data, genetic diversity assessment data, and characteristic gene protection data of the target local livestock and poultry breeds; the collaborative management module for the core breeding group and production group is used to provide automated simulation of optimal mating schemes; the intelligent breeding decision-making module is used to provide scientific breeding and mating schemes; and the data visualization module is used to provide visual display and real-time, dynamic monitoring.

[0031] The following are the technical effects of the present invention:

[0032] This invention constructs a dynamic response mechanism of "sampling at birth - data uploading - automatic analysis - visual decision-making". By collecting genotype data in advance at the individual birth stage and including individuals that have changed in real time, the platform algorithm outputs four-level preservation instructions in real time, realizing dynamic monitoring and instant optimization of the preservation population. This can significantly improve the timeliness and accuracy of preservation work, and most importantly, it makes it easier for managers to keep abreast of the preservation status of the preservation farm.

[0033] This invention, during automated analysis, constructs a standard library based on genomic SNP markers and quantifies pedigree content to address the inaccuracies of traditional phenotypic identification, ensuring the genetic purity of the preserved population and achieving precise purity identification. Through multi-dimensional genomic parameter calculations, it enables precise assessment and dynamic monitoring of population genetic diversity, providing a scientific basis for optimizing preservation strategies and thus quantifying genetic diversity. Furthermore, through genomic breeding value screening, it targets and protects key genes for distinctive traits, preventing the degradation of superior genetic characteristics and achieving directed protection of these genes.

[0034] Furthermore, this invention enables integrated management throughout the entire process, breaking down information barriers between different stages and achieving digitalization and intelligentization of conservation, production, breeding, and monitoring, thereby improving conservation efficiency and sustainability. Under the multi-objective constraints of a four-level conservation system, this invention achieves the protection of distinctive genes, ensuring that the dominant trait loci (distinctive genes) of specific varieties are not lost or degraded while maintaining a high level of genetic diversity (high heterozygosity) in the population. Attached Figure Description

[0035] Figure 1 is a flowchart of the four-level precision seed preservation system in an embodiment of the present invention.

[0036] Figure 2 is a schematic diagram of the variety identification results in an embodiment of the present invention.

[0037] Figure 3 is a schematic diagram of genetic diversity assessment based on genomic information in an embodiment of the present invention.

[0038] Figure 4 is a schematic diagram of the platform for precise protection of genetic resources in an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0040] Example 1:

[0041] A four-level precision conservation method for local livestock and poultry includes protecting the quantity of local livestock and poultry breeds, identifying the purity of local livestock and poultry breeds, assessing genetic diversity based on genomic information, protecting distinctive genes, and precisely protecting genetic resources.

[0042] The protection of local livestock and poultry breeds is carried out in accordance with the "Management Measures for the Protection Zones and Gene Banks of Livestock and Poultry Genetic Resources Conservation Farms," ​​which clearly stipulates the number of breeding populations for various livestock and poultry breeds, ensuring that the number of protected populations is not lower than the prescribed minimum. The number of protected populations includes the basic population size required to determine and maintain the long-term survival and continuation of local livestock and poultry breeds. This level is the prerequisite and foundation for all subsequent precise conservation operations, and the specific implementation method is as follows:

[0043] According to the "Management Measures for Livestock and Poultry Genetic Resources Conservation Farms, Protection Zones and Gene Banks", basic conservation numbers are set for different livestock species in accordance with the aforementioned regulations to ensure that the population size exceeds the established requirements.

[0044] Pigs: More than 100 sows, more than 12 boars, and at least 6 families with no blood relation within three generations.

[0045] Cattle, horses, donkeys, and camels: more than 150 female animals (horses, camels) and more than 12 male animals (horses, camels), with no fewer than 6 families that are not related by blood within three generations.

[0046] Sheep: More than 250 ewes and more than 25 rams, with a family number of no less than 6 families that are not related by blood within three generations.

[0047] Chickens: More than 300 hens; no fewer than 30 families of roosters.

[0048] Ducks and geese: more than 200 female birds; no fewer than 30 male birds.

[0049] Rabbits: More than 300 female rabbits and more than 60 male rabbits, with a family number of no less than 6 families that are not related by blood within three generations.

[0050] Dogs: More than 30 female dogs and no fewer than 10 male dogs.

[0051] The identification of the purity of local livestock and poultry breeds includes:

[0052] Sample collection and genotyping: Collect blood or tissue samples from the core conservation population of the target local varieties, as well as varieties with similar historical origins or geographical proximity. Use high-density SNP chips or whole-genome resequencing technology to obtain whole-genome SNP genotype data and construct an initial genotype database.

[0053] Population genetic structure analysis: Based on SNP data, principal component analysis (PCA), population structure analysis and phylogenetic tree construction are used to visualize the genetic consistency within the population and remove genetically mixed individuals.

[0054] Core SNP (Single Nucleotide Polymorphism) site screening: Calculate the genetic differentiation index (Fst) of each variety relative to other populations, extract the top n SNPs with the highest Fst values ​​in each population for variety identification (n is 1000), and screen out m core sites as genetic markers using the gradient boosting decision tree (GBDT) model (m is 5000).

[0055] Establishment of a breed identification standard database: Using the screened core SNP loci as genetic markers, the genotype data of all purebred individuals are compiled to form a local livestock and poultry breed identification reference database;

[0056] Breed identification and evaluation based on pedigree content: Genotyping of the individuals to be tested is performed, and their genotype data is compared with a standard library to calculate the pedigree composition ratio (the pedigree composition ratio is used to determine whether the individual is a purebred of the local breed); a preset pedigree content threshold Th (Th is 90%) is set. If the pedigree content is higher than the pedigree content threshold, it is determined to be a genetically pure individual; otherwise, it is a hybrid or mixed individual. This enables accurate assessment and screening of the genetic purity of each individual in the breeding population (in this embodiment, Rongchang pig, Landrace pig, Large White pig, Duroc, and Basin Mountain pig are used as examples, and their breed identification results are shown in Figure 2).

[0057] Genomic-based genetic diversity assessment uses genomic data to accurately assess the genetic diversity of conservation populations, monitor inbreeding levels, and dynamically monitor genetic structure, providing a direct basis for the scientific formulation of conservation strategies (the final results are shown in Figure 3), including:

[0058] Full-coverage sample collection and dynamic database updates: Samples are collected and genotyped for individuals in the core population of target varieties in all conservation farms. A dynamic monitoring mechanism is established, and newborn, newly introduced and newly culled individuals are tracked and sampled and genotyped every generation or year to ensure that the database reflects the dynamic changes of the population in real time and provides a data foundation for continuous evaluation.

[0059] Standardized genotype data quality control and preprocessing: Strict quality control and standardized preprocessing were performed on the collected high-throughput SNP genotype data, including SNP missing rate filtering, minimum allele frequency (MAF) filtering, and genotype imputation. SNP missing rate filtering: SNP loci with excessively low detection rates (e.g., > 5%) in all individuals were removed to ensure data reliability. Minimum allele frequency filtering: Loci with excessively low rare allele frequencies (e.g., MAF < 0.01) were removed to avoid interference with population-level statistical analysis. Genotype imputation: Based on a hidden Markov model, missing genotype data in the conservation population were imputed to obtain a complete, high-quality genotype matrix for subsequent analysis.

[0060] Calculation of multidimensional genetic diversity parameters: Calculation of observed heterozygosity (H o ), expected heterozygosity (H e ), polymorphic information content (PIC), genomic inbreeding coefficient (F) ROH The genetic health status of the population is comprehensively assessed using the genome kinship matrix (G), providing a basis for the formulation of conservation plans.

[0061] Among them, observed heterozygosity (Ho) and expected heterozygosity (H e These two indicators are used to measure the proportion of heterozygotes actually observed and the proportion of heterozygotes expected in a population, respectively, and are the basic indicators for assessing the level of genetic diversity in a population.

[0062] Observed heterozygosity (H o ): ;

[0063] Expected heterozygosity (H e ): ;

[0064] Where H o H represents the observed heterozygosity. e N represents the expected heterozygosity. h p represents the number of heterozygous individuals in the conservation population; N represents the total number of individuals in the conservation population; i This represents the frequency of the i-th allele in the conservation population;

[0065] Polymorphism Information Content (PIC) is used to directly assess the polymorphism of SNP loci in a population. The higher the PIC value, the richer the information provided by the locus.

[0066] ;

[0067] Where PIC represents polymorphic information content; p i q j These represent the frequencies of the i-th allele and the j-th allele in the conservation population, respectively.

[0068] Genomic inbreeding coefficient (F) ROH The genome-level inbreeding coefficient for individuals and populations is precisely calculated using a method based on run-of-homozymes (ROHs) to directly reflect the risk of inbreeding depression.

[0069] ;;

[0070] Where F ROH L represents the genomic inbreeding coefficient; k represents the individual sequence number in the conservation population; N represents the total number of individuals in the conservation population; ROH Indicates the length of the ROH fragment in the genome of each individual; L g Indicates the total length of the autosomal genome;

[0071] The genomic kinship matrix (G) constructs a pairwise genomic kinship matrix of all individuals, accurately quantifying the genetic similarity between individuals, and providing a direct basis for developing scientific mating strategies to avoid inbreeding:

[0072] ;

[0073] Where G represents the genomic kinship matrix; Z represents an n×m genotype design matrix containing the genotype information of all individuals to be analyzed, obtained through microarray sequencing or genome resequencing. n represents the number of individuals, and m represents the number of SNP markers. Z′ represents the transpose of matrix Z, with dimensions m×n. p i This represents the frequency of the i-th allele in the conservation population.

[0074] Specialty gene protection integrates genomic and phenotypic data and applies quantitative genetics methods. It uses genomic breeding values ​​to select superior genes for distinctive traits to ensure that the distinctive traits of a variety do not degenerate or get lost in the production population. This addresses the challenge that traditional preservation methods cannot effectively protect key genes for the distinctive traits of local varieties, including:

[0075] Linked with dynamic genotype database: Linked with genetic diversity assessment methods based on genomic information, continuously genotyping all individuals in the core population of all conservation farms, and establishing a dynamic update mechanism to ensure that genotype data can reflect changes in population genetic composition in real time, providing the latest and most complete genotype data for subsequent genomic breeding value estimation;

[0076] Standardized data quality control: Adopting a standardized process consistent with the genetic diversity assessment methods based on genomic information, we conduct strict quality control on genotype data, including SNP deletion rate filtering, minimum allele frequency (MAF) filtering, and high-precision genotype imputation, to ensure the quality and consistency of data used for genetic assessment.

[0077] Precise collection of distinctive phenotypic traits: For key economic or adaptive traits unique to local breeds to be protected (e.g., total egg production of Sichuan White Goose, intramuscular fat content of Rongchang Pig), systematic and standardized phenotypic data are recorded in the conservation population; at the same time, standardized phenotypic collection procedures are established to ensure the accuracy, comparability and sustainability of the data, and to form a phenotypic database that corresponds one-to-one with the genotype data.

[0078] Genome breeding value calculation: By combining whole-genome SNP genotype data with precise phenotypic data, and using the Genome Best Linear Unbiased Prediction (GBLUP) statistical model, the genome breeding value (GEBV) of each individual on the trait of interest is calculated.

[0079] Targeted breeding: Based on the calculated genomic breeding values, optimized management is implemented for the conservation population. Specifically, a bottom-ranking elimination breeding strategy is adopted, that is, each generation (or year) individuals that have reached the optimal age are ranked according to their genomic breeding values ​​of characteristic traits, and the individuals ranked at the bottom (such as the bottom 10%) are eliminated or no longer retained for breeding. By applying a stable selection pressure of no less than 10%, it is ensured that the frequency of characteristic trait genes in the population can be maintained or steadily increased across generations, thereby actively preventing trait degradation caused by random seed retention or inbreeding, and achieving dynamic and efficient protection of the characteristic gene resources of this variety.

[0080] Precision conservation of genetic resources involves constructing an information management platform that integrates data integration, intelligent analysis, and decision support. This platform seamlessly connects the three core technology modules of purity identification, diversity assessment, and protection of distinctive genes, enabling full-process, digital, and intelligent management of local livestock and poultry genetic resources from protection to utilization. This solves the "information silo" problem caused by disconnects and poor information flow in existing conservation efforts, including:

[0081] Central Database and Data Integration Management: Establish a unified central database to integrate and store genotype data (including core SNP sets and whole genome data), pedigree data, dynamically updated phenotypic data (such as egg production, meat quality, etc.), genome breeding value (GEBV) results, genetic diversity parameters (such as inbreeding coefficient, heterozygosity), and purity identification results; the central database has standardized interfaces and dynamic update functions;

[0082] Integrated management of conservation and production populations: Based on the genome kinship matrix (G) and genetic assessment results, the optimal mating scheme is automatically recommended to avoid inbreeding and maintain the genetic diversity of the population; at the same time, the flow of excellent germplasm resources between the core population and the production population is tracked to achieve "conservation through use" and form a virtuous cycle of conservation and utilization.

[0083] Intelligent breeding and decision support: Based on the genomic breeding value (GEBV), candidate individuals are automatically sorted, and combined with breeding objectives (such as positive selection for distinctive traits) and preservation requirements (such as maintaining a certain effective population size), a breeding and selection plan (including end-elimination recommendations) is generated; this greatly improves the efficiency and accuracy of breeding work, and transforms the experience of breeding experts into standardized and executable digital instructions;

[0084] Dynamic monitoring and visual early warning: Provides a data visualization dashboard to monitor key indicators such as effective population size, inbreeding coefficient, allele frequency changes, and genomic breeding value trends of characteristic traits in real time. It presets safety thresholds and automatically issues early warnings when the thresholds are reached, thereby reminding managers to take timely intervention measures, transforming passive response into proactive management, and ensuring the long-term safety and efficiency of seed preservation work.

Claims

1. A four-level precision breeding method for local livestock and poultry, characterized in that... The process includes the following steps: After collecting newly born or introduced samples from the conservation population of the target local livestock and poultry breed in each generation and constructing its whole-genome genotype database, the following steps are performed: determining the size of the conservation population, identifying the purity of the local livestock and poultry breed, assessing genetic diversity based on genomic information, protecting distinctive genes, and establishing an integrated information platform for genetic resources. The genetic diversity assessment step includes calculating genetic diversity parameters selected from one or more of the following dimensions: observed heterozygosity, expected heterozygosity, polymorphism information content, genomic inbreeding coefficient, and genomic kinship matrix. The protection of distinctive genes involves maintaining the genetic diversity of the population, ranking the genomic breeding values ​​of the phenotypic traits of interest, and culling or no longer retaining individuals at the bottom of the rankings for breeding purposes. The integrated information platform for genetic resources includes real-time, dynamic monitoring of all data.

2. The local livestock and poultry four-level precision breeding method according to claim 1, characterized in that: The observed heterozygosity and the expected heterozygosity are calculated using the following formulas: ； ;where H o H represents the observed heterozygosity. e N represents the expected heterozygosity. h p represents the number of heterozygous individuals in the conservation population; N represents the total number of individuals in the conservation population; i The frequency of the i-th allele in the conservation population is represented by the following formula: ; where PIC represents polymorphic information content; p i q j Let represent the frequencies of the i-th and j-th alleles in the conservation population, respectively; the genomic inbreeding coefficient is calculated using the following formula: ;where F ROH L represents the genomic inbreeding coefficient; k represents the individual sequence number in the conservation population; N represents the total number of individuals in the conservation population; ROH Indicates the length of the ROH fragment in the genome of each individual; L g This represents the total length of the autosomal genome; the genome phylogenetic matrix is ​​calculated using the following formula: Where G represents the genomic kinship matrix; Z represents an n×m genotype design matrix, which contains the genotype information of all individuals to be analyzed; Where n represents the number of individuals, m represents the number of SNP markers, and Z′ represents the transpose of matrix Z, with dimensions m×n; p i This represents the frequency of the i-th allele in the conservation population.

3. The local livestock and poultry four-level precision breeding method according to claim 2, characterized in that: The local livestock and poultry breed purity identification step includes screening core SNP loci from the whole genome genotype database to form a breed identification standard library. For the individual to be tested, its genotype data is compared with the established breed identification standard library. By calculating the proportion of pedigree content of the corresponding SNP loci, it is determined whether it is a purebred individual of the local breed. When the SNP pedigree content of the individual to be tested is higher than the preset pedigree content threshold, it is determined to be a genetically pure individual; otherwise, it is determined to be a hybrid or mixed individual.

4. The local livestock and poultry four-level precision breeding method according to claim 3, characterized in that: The specific screening criteria for the core SNP loci are as follows: calculate the genetic differentiation index Fst of each variety group relative to other groups in the genotype database, extract the top n SNP loci with the highest Fst values ​​for each group for variety identification, and screen out m core loci as a standard library for variety identification through a gradient boosting decision tree model; where n is not less than 1000 and m is not less than 5000.

5. The method for four-level precision breeding of local livestock and poultry according to claim 4, characterized in that: The quality control standards adopted in the genotype database construction steps include: removing low-quality locus data with a detection rate of <95% and filtering low-frequency allele data with a frequency of <0.

01.

6. The method for four-level precision breeding of local livestock and poultry according to claim 5, characterized in that: The special gene protection steps include forming a phenotypic database that corresponds one-to-one with the genotype data of the target local livestock and poultry breeds; using the best linear unbiased predictive statistical model of the genome, calculating and ranking the genomic breeding value of each individual on the phenotypic trait of interest, and culling or no longer retaining the bottom-ranked individuals for breeding purposes.

7. A four-level precision breeding method for local livestock and poultry as described in claim 6, characterized in that: The steps for establishing the integrated information platform for genetic resources include: integrating and managing data on the number of conservation populations, genotypes, purity identification, genetic diversity assessment, and protection of distinctive genes in a unified central database; collaboratively managing the core conservation population and production populations, and providing the optimal mating scheme obtained through automated simulation; generating scientific breeding and selection schemes, including suggestions for eliminating the lowest-performing individuals, based on the ranking of genomic breeding values ​​and preset breeding goals and conservation requirements, and providing intelligent breeding decision support; visualizing and monitoring all data in real time and dynamically, setting safety thresholds for key indicators, and automatically triggering an early warning mechanism when the threshold is reached.

8. A genetic resource integrated information platform for the four-level precision breeding method for local livestock and poultry as described in any one of claims 1-7, characterized in that... It consists of a central database module, a core breeding group and production group collaborative management module, an intelligent breeding decision-making module, and a data visualization module. The central database is used to integrate, store, and manage genotype data, purity identification data, genetic diversity assessment data, and characteristic gene protection data of the target local livestock and poultry breeds. The core breeding group and production group collaborative management module is used to provide automated simulation of optimal mating schemes. The intelligent breeding decision-making module is used to provide scientific breeding and mating schemes. The data visualization module is used to provide visual display and real-time, dynamic monitoring.

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