A rapid matching breeding improvement parental composition, acquisition method and application

Abstract

The present invention belongs to the technical field of genetic breeding, and discloses a method for rapidly matching breeding improved parental compositions, obtaining the same, and applications thereof. The method obtains basic SNP markers; performs GWAS analysis based on the collected phenotypes, identifies the dominant genotypes of the markers associated with the phenotypes, and constructs a dominant genotype library of functional loci; analyzes by calculating the contribution degree PVE of the functional loci to the phenotypes, and simultaneously calculates the linkage region Block of each material or population to construct a material PVE score library and a Block library; performs pairwise matching combinations of materials based on the dominant genotypes, the PVE of the functional loci, and the linkage region Block of the materials / populations to obtain the best combined parents for each material. The present invention can achieve a state of aggregation of more favorable genotypes.

Description

Technical Field

[0001] The present invention belongs to the technical field of genetic breeding, and particularly relates to a method for rapidly matching breeding improved parental combinations, an acquisition method and an application thereof. Background Art

[0002] Breeding is an important means to improve crop yields. Conventional breeding methods mainly utilize trait recorded values and the genetic relationships between individuals calculated based on pedigrees, and comprehensively consider trait differences to select samples. However, there are many problems in this process. For example, the parental plants need to have phenotypic differences, and often a large number of phenotypic data of materials are required to determine phenotypic differences. This not only requires a long cultivation cycle but also consumes a lot of manpower. Genomic information largely determines the development direction of phenotypes. Therefore, the variation information of different parental candidates can be directly matched and combined through the genome to determine the best combined parents with greater potential for obtaining high-quality target trait offspring, so as to avoid a large amount of phenotypic statistics and a long growth cycle. In addition, the representativeness of known functional loci has been verified, and it is necessary to cover these loci.

[0003] Superior loci need to be considered. There is a large amount of variation information on the genome, and these variation information have different effects on different phenotypes. Therefore, a large number of markers associated with phenotypes identified through GWAS analysis often have greater potential impact on phenotypes.

[0004] The epistatic effects between loci have strong potential for improvement and breakthrough. Loci located within the same Block region are often in a strong linkage state. Therefore, a superior genotype may carry multiple inferior loci. The difference in the length of Blocks between different materials can provide the possibility of breaking the linkage for chromosomal recombination variation, enabling more superior genotypes to aggregate in the offspring.

[0005] Through the above analysis, the problems and defects of the existing technology are as follows: Conventional breeding methods involve finding individuals with obvious phenotypic differences as breeding parents, which requires waiting for all individuals to mature and is based on a large number of phenotypic records, thus consuming a long time and a large amount of labor costs; moreover, the breeding efficiency of the existing technology is low. Summary of the Invention

[0006] To overcome the problems existing in the related art, the disclosed embodiments of the present invention provide an application of a method for rapidly matching breeding improved parental combinations and an acquisition method, specifically relating to a method for finding the best improved parents through genomic variation information and superior loci of related phenotypes. The purpose of the present invention is to provide a method for finding the best improved parents through genomic variation information and superior loci of related phenotypes to rapidly match the best breeding improved parents, thereby greatly reducing breeding costs and accelerating the breeding process, providing new references and guidance for breeding scientists.

[0007] The technical solution is as follows: a method for obtaining a parent composition for rapid matching breeding improvement, which analyzes the genotype complementarity between functional loci, combines the contribution degree PVE of each functional locus to the phenotype and the Block between different groups / materials for evaluation, and provides a reference for breaking the hitchhiking effect between loci during parent combination so as to aggregate more advantageous genotypes in the offspring; specifically including the following steps:

[0008] S1. Obtain basic SNP markers;

[0009] S2. Perform GWAS analysis based on the collected phenotypes and the obtained basic SNP markers, identify the advantageous genotypes of the markers associated with the phenotypes, and construct a functional locus advantageous genotype library;

[0010] S3. Calculate the contribution degree PVE of the functional locus to the phenotype, calculate the linkage region Block of each material or population, and construct a material PVE score library and a Block library;

[0011] S4. Based on the advantageous genotypes, the contribution degree PVE of the functional locus, and the linkage region Block of the material / population, perform pairwise matching combinations between two materials to obtain the best combined parents for each material.

[0012] In step S1, obtaining basic SNP markers includes:

[0013] Perform quality control on the WGS sequencing data of all samples using the FASTP software to obtain valid data, use the BWA software for alignment to obtain a bam file, use the GATK software for variant detection to obtain SNP markers, and filter based on depth, missing rate, and minor allele frequency to obtain basic SNP markers.

[0014] In step S2, among the phenotypes, the genotypes with high single-plant yield and high grain weight are advantageous genotypes; the genotypes with low performance within the plant height range are judged as advantageous genotypes.

[0015] In step S2, based on the collected phenotypes, collect the information of known functional loci for phenotype analysis;

[0016] Constructing a functional locus advantageous genotype library includes: according to the experiment and GWAS results, score the genotype loci related to each trait of the material, score the advantageous allele genotypes as 1, and score the disadvantageous allele genotypes as -1; according to the order and score of each locus, each sample forms a genotype score matrix; finally, all sample materials jointly form a functional locus advantageous genotype library.

[0017] In step S3, analyze the contribution degree PVE of functional sites to the phenotype, including: using the software R package lme4 to analyze the contribution degree PVE of functional sites to the phenotype;

[0018] Construct a PVE score library for materials, including: after obtaining the PVE value of each functional site corresponding to each material, according to the position information, store the PVE values related to the functional sites of each sample in json format as the PVE score library.

[0019] In step S3, construct a PVE score library and a Block library for materials, including: using Plink software to calculate the linkage region Block of each material or population;

[0020] Construct the Block library, including: according to the linkage region Block calculated by Plink software, combined with the position information of functional sites, set a Block identification matrix for each sample and each functional site as the Block library; that is, if two functional sites are in the linkage position, the positions of the two sites in the corresponding Block library are 1, and if not linked, they are set to 0.

[0021] In step S4, perform pairwise matching combinations between two materials based on the dominant genotype, the contribution degree PVE of functional sites, and the linkage region Block of materials / populations, including:

[0022] According to the constructed dominant allele genotype library, PVE score library, and Block library; use the third-party library Python numpy for vectorized calculation to obtain the best combined parents after pairwise comparison between the functional site score matrix of the target sample and all samples in the built-in library;

[0023] Obtain the best combined parents of each material, including:

[0024] S401, Evaluation score system, multiply the functional site score by the PVE value at the corresponding position as the final effect value of the site on the phenotype;

[0025] S402, Site recombination logic, select the one with a larger score as the score of the offspring at the corresponding position;

[0026] S403, Evaluate the best combined parents, take the sum of the best scores of the offspring obtained from each combination as the final score of the combination. After performing pairwise combination calculations for all samples in the library, obtain the several combinations with the highest scores, and these combinations are used as the best parent combinations for breeding for subsequent experimental breeding.

[0027] In step S402, the site recombination logic selects the one with a higher score as the score of the corresponding position of the offspring, including: for the pairwise comparison samples, traversing each region. If the regions are not linked to each other, it is determined that the score of the two combinations to obtain the offspring is the score of the one with the higher score; if both samples in the region are linked and the linkage lengths are the same, it is determined that the side with the larger total score of the site scores within the linked region is used as the score of the offspring in this region; if one side is linked and the other side is not linked or the linked regions are inconsistent, then according to the cross-segment situation, the linkage is broken, and the linkage regions of the two samples are broken with the smallest cross-segment as the unit. After breaking, the total scores of the split sub-regions are calculated respectively, and the side with the higher score is selected as the score of the corresponding position of the offspring.

[0028] Another object of the present invention is to provide a fast-matching breeding improved parental combination, which is obtained by implementing the method for obtaining the fast-matching breeding improved parental combination.

[0029] Another object of the present invention is to provide an application in genomic information breeding without waiting for the mature judgment of the genomic situation and evaluating the breeding potential, and screening and obtaining the improved parental combination by applying the method for obtaining the fast-matching breeding improved parental combination

[0030] Combining all the above technical solutions, the beneficial effects of the present invention are as follows:

[0031] The present invention greatly shortens the breeding cycle and cost. Through genomic information breeding, the genomic situation can be judged and its breeding potential can be evaluated without waiting for maturity, effectively reducing the breeding cost. In addition, the phenotypes determined by the genomic variation information are often more stable in inheritance. Therefore, high-quality phenotypes with stable inheritance can be obtained more quickly through genomic breeding.

[0032] Breaking the hitchhiking effect and providing more breeding possibilities: Based on a large number of markers associated with phenotypes identified by GWAS analysis, in addition to evaluating their contribution degrees (PVE), matching is also carried out according to the Block (linked segments) of different materials or populations to find possible breakthrough linkages and achieve a state of more favorable genotype aggregation.

[0033] Fast combination mode, which can analyze the genotype information of a large number of materials and construct a data base. Based on information such as PVE, Block, and dominant genotypes, the best parental combination matching the improved individual can be quickly found, greatly improving the breeding efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings herein are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure;

[0035] Figure 1 It is a flowchart of a method for obtaining a fast-matching breeding improved parental composition provided by an embodiment of the present invention;

[0036] Figure 2 It is a schematic diagram of the principle of a method for obtaining a fast-matching breeding improved parental composition provided by an embodiment of the present invention;

[0037] Figure 3 It is a schematic diagram of the framework principle of a method for obtaining a fast-matching breeding improved parental composition provided by an embodiment of the present invention;

[0038] Figure 4 It is a PVE interface diagram of the contribution degree of superior genotype information and position to phenotype provided by an embodiment of the present invention;

[0039] Figure 5 It is a Block information interface diagram of a population or an individual provided by an embodiment of the present invention;

[0040] Figure 6 It is an application example interface diagram of a PVE score library provided by an embodiment of the present invention;

[0041] Figure 7 It is an application example interface diagram of a superior genotype library provided by an embodiment of the present invention;

[0042] Figure 8 It is an application example interface diagram of a Block library provided by an embodiment of the present invention. Detailed implementation manners

[0043] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following describes the detailed implementation manners of the present invention with reference to the accompanying drawings. Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific implementations disclosed below.

[0044] The innovative points of the rapid matching breeding improved parental composition, acquisition method and application provided by the embodiments of the present invention are as follows: Based on the fact that the additive effect is the dominant effect affecting phenotypic variation, functional loci related to phenotypes are identified by GWAS and combined with the advantageous genotypes of the functional loci identified by phenotypic identification, or the functional loci with known advantageous and disadvantageous genotypes are used to scan the advantageous and disadvantageous loci of the sequencing materials within the whole genome, and the best combined parents of the materials to be improved are matched through the complementary situation of the advantageous and disadvantageous genotypes between different materials, so as to provide reference and guidance for improving the phenotypes of the offspring. This method not only considers the complementary situation of genotypes between functional loci, but also combines the contribution degree (PVE) of each functional locus to the phenotype and the linkage region Block between different populations / materials for evaluation, and also provides a new and possible reference for breaking the hitchhiking effect between loci during parental combination so as to aggregate more advantageous genotypes in the offspring.

[0045] The present invention proposes an optimal combined parent for breeding improvement based on the advantageous genotype of functional loci, the contribution degree (PVE) of functional loci to phenotypes, and the linkage region (Block).

[0046] Example 1, as Figure 1 shown, the acquisition method of the rapid matching breeding improved parental composition provided by the embodiments of the present invention includes:

[0047] S1, obtaining basic SNP markers;

[0048] The WGS sequencing data of all samples are quality controlled using the FASTP software to obtain valid data, aligned using the BWA software to obtain bam files, and SNP markers are detected using the GATK software. Based on depth, missing rate, minimum allele frequency, etc., filtering is performed to obtain basic SNP markers;

[0049] S2, performing GWAS analysis based on the collected phenotypes and the obtained basic SNP markers, identifying the advantageous genotypes of the markers associated with phenotypes, and constructing a functional locus advantageous genotype library;

[0050] It can be understood that this marker is subjected to GWAS analysis on the basis of obtaining the basic markers, and then the markers associated with phenotypes obtained through GWAS analysis;

[0051] Different criteria are adopted according to different phenotypes. For example, the genotype with high single-plant yield and higher grain weight is the advantageous genotype; the genotype with lower plant height within a certain range is judged as the advantageous genotype; it is also possible to collect known functional locus information instead of GWAS;

[0052] Constructing a library of dominant genotypes of functional loci includes: according to experimental results and GWAS results, scoring each genotype locus related to a trait of the material, with a score of 1 for the dominant allele genotype and a score of -1 for the recessive allele. According to the order and score of each locus, each sample forms a genotype score matrix. Finally, all sample materials together form a library of dominant genotypes of functional loci;

[0053] S3. Calculate the contribution degree PVE of the functional locus to the phenotype, calculate the linkage region Block of each material or population, and construct a PVE score library and a Block library for the materials;

[0054] Use the R package lme4 of software to calculate the contribution degree (PVE) of the functional locus to the phenotype for analysis. At the same time, use Plink software to calculate the linkage region (Block) of each material or population, and construct a PVE score library and a Block library for the materials;

[0055] It can be understood that calculating PVE is the function of calculating PVE by the R package lme4 of software, and this invention utilizes this data; furthermore, use Plink software to calculate the linkage region (Block) of each material or population by a conventional method. This invention utilizes this data.

[0056] Among them, constructing a PVE score library includes:

[0057] After obtaining the PVE value of each functional locus corresponding to each material, according to the location information, store the PVE values related to the functional loci of each sample in json format as a PVE score library.

[0058] Among them, PVE is a part of the evaluation score system of functional loci, which is jointly composed of functional loci, their corresponding dominant characteristics, and PVE (the contribution degree of functional loci to the phenotype).

[0059] Constructing a Block library includes:

[0060] According to the linkage region (Block) calculated by Plink software, combined with the location information of functional loci, set a Block identification matrix for each functional locus of each sample as the Block library; that is, if two functional loci are in a linked position, the positions of the corresponding Block library of these two loci are 1, and if they are not linked, they are set to 0.

[0061] It can be understood that the sample score library is jointly composed of the PVE score library of materials and the library of dominant genotypes of functional loci, and is used to measure the influence and score of each functional locus on the phenotype; the Block library records the Block linkage information of each sample and is used to calculate the breaking of linkage.

[0062] S4. Based on the dominant genotypes, the contribution degree of functional loci PVE, and the linkage regions Block of materials / populations, pairwise matching combinations are performed between materials to obtain the best combined parents for each material.

[0063] According to the constructed dominant allele genotype library, PVE score library, and Block library. Using the third-party library Python numpy for vectorized calculation, the best combined parents obtained after pairwise comparison between the functional locus score matrix of the target sample and all samples in the built-in library are obtained. Finding the best combined parents for each material includes:

[0064] S401. Evaluation score system. The product of the functional locus score and the PVE value at the corresponding position is used as the final effect value of the locus on the phenotype.

[0065] S402. Locus recombination logic. For pairwise compared samples. Each region is traversed. If the regions are not linked to each other, then it is judged that the score of the offspring obtained from the two combinations is the larger score; if both samples in this region are linked and the linkage lengths are exactly the same, then it is judged that the sum of the locus scores in the linked region of the larger party is used as the score of the offspring in this region; if one is linked and the other is not linked or the linked regions are inconsistent, then according to the cross-segment situation, the linkage is broken, that is, the smallest segment of the cross part is used as the unit to break the linkage regions of the two samples. After breaking, the sum of the scores of each sub-region after splitting is calculated, and the larger party is selected as the score of the offspring at the corresponding position.

[0066] S403. Evaluate the best combined parents. The sum of the best scores of the offspring obtained from each combination is used as the final score of the combination. After performing pairwise combination calculations for all samples in the library, several combinations with the highest scores can be obtained. These combinations can be used as the best parent combinations for breeding and subsequent experimental breeding.

[0067] As can be seen from the above embodiments, genome-wide association analysis (GWAS) is introduced in the invention to obtain a large number of functional loci associated with phenotypes; the dominant genotypes of these functional loci are identified, and at the same time, the phenotypic contribution rate (PVE) is introduced to calculate the effect value of each function; the Block segments of each material / population are calculated, providing a potential assessment for breaking the hitchhiking effect through recombination of different Block segments during the chromosomal variation process.

[0068] Based on the dominant genotype information, the effect value of functional loci, and the Block information, the best combined parents with greater potential for breeding improvement can be quickly found, providing a new reference and perspective for breeding scientists.

[0069] Example 2. The present invention provides an improved parent composition, which is obtained by implementing the method for obtaining the fast-matching breeding improved parent composition.

[0070] Example 3, as another implementation manner of the present invention, as Figure 3 the framework principle of the method for obtaining a fast-matching breeding improved parental composition. In the above method, it includes:

[0071] (1) The contribution degree PVE of the dominant genotype information and position to the phenotype (one for one phenotype), such as Figure 4 shown;

[0072] Among them, CHROM represents the chromosome, POS represents the physical position of the modified snp on the chromosome, ref is the reference genotype corresponding to the reference genome, ALT is the mutant genotype, Adv_geno is which is the dominant genotype (ref is the reference gene Xu is the dominant genotype, alt is the mutant genotype is the genotype), and PVE represents the contribution degree of this position to the phenotype.

[0073] (2) The Block information of the population or individual, such as Figure 5 shown;

[0074] Among them, CHR represents the chromosome, BP1 represents the starting position of the Block, BP2 represents the ending position, and KB represents the length of the Block.

[0075] (3) The vcf file is a normal variant information file.

[0076] Based on the method for obtaining a fast-matching breeding improved parental composition of the present invention, an application example of the PVE score library, such as Figure 6 shown; among them, the Json file records the locus position information and the corresponding PVE value;

[0077] An application example of the dominant genotype library, such as Figure 7 shown; the dominant genotype library is a two-dimensional matrix, one row is a sample, and each column is the SNP locus information.

[0078] An application example of the Block library, such as Figure 8 shown; the Block library is a two-dimensional matrix, one row is a sample, and the column is the Block information of each locus. The order of the sample and the locus corresponds one by one to the dominant genotype library.

[0079] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] To further illustrate the relevant effects of the embodiments of the present invention, the following experiments are carried out.

[0081] The present invention not only considers the complementarity between functional site genotypes and their effect values on phenotypes, but also takes into account the linkage region Block situations among different materials / populations, so as to provide a possibility of breaking the hitchhiking effect between sites through structural variations occurring during the parental combination process. The present invention aggregates more favorable functional site genotypes in the offspring through this possibility.

[0082] Traditional breeding has a long cycle. The present invention can scan the genotype situations of functional sites of different materials based on re-sequencing data, and search for matching materials in the materials that are complementary to the materials to be improved at the functional sites, can break the hitchhiking effect and aggregate more advantageous genotypes in the offspring as improved parents, thereby accelerating the breeding cycle.

[0083] The essence of matching is the complementarity between sites and the expectation of retaining as many advantageous genotypes of functional sites as possible in the offspring. Suppose a functional site affecting yield is located at position 4526689bp on chromosome 3, the base type (ref) of the reference genome is A, and one of the variant types (alt) is G, and after identification, its advantageous genotype is GG. Based on this premise, the matching algorithm detects the genotypes of all materials (including the materials to be improved) at this position. When the material to be improved is AA or AG (disadvantageous genotype) at this site, it searches for materials that are of the advantageous (GG) genotype at this position. On this basis, the effect sizes of these sites and the linkage region Block between materials are comprehensively evaluated.

[0084] The additional datasets used in the matching method of the present invention include: a material library for parental matching of the material to be improved or internal matching within itself (snp dataset obtained based on re-sequencing data);

[0085] A dataset of the advantageous and disadvantageous genotypes of functional sites related to phenotypes (derived from experiments / literatures, or need to be obtained and identified by oneself. Obtaining and identifying by oneself requires information such as the snp dataset of population materials and the precise phenotypes of each material, and this matching algorithm does not provide relevant calculations);

[0086] The PVE values of the above functional sites (if not available, it needs to be jointly identified with the above self-identification, so the phenotypic values of each material under different phenotypes are also required);

[0087] Block information, which needs to be calculated based on the plink software by oneself;

[0088] In short, the matching algorithm of the present invention requires these datasets to be provided additionally when in use, and will calculate based on these datasets to recommend combined parents.

[0089] As described above, it is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A method for obtaining a rapid matching breeding improvement parent composition, characterized in that: The method specifically comprises the following steps: S1, obtaining basic SNP markers; S2, performing GWAS analysis based on the collected phenotypes and the obtained basic SNP markers, identifying the dominant genotypes of the markers associated with the phenotypes, and constructing a functional site dominant genotype library; S3, calculating the contribution PVE of the functional site to the phenotype, calculating the linkage region Block of each material or population, and constructing a material PVE score library and a Block library; S4, performing matching combinations between two materials based on the dominant genotype, the contribution PVE of the functional site, and the linkage region Block of the material or population, and obtaining the best combination parent of each material; In step S4, pairwise matching and combination of materials is performed based on dominant genotype, contribution degree PVE of functional loci, and linkage region Block of materials or populations, including: constructing dominant allele type library, PVE score library, and Block library; using Python numpy third-party library to perform vectorized calculation, and obtaining the best combination parent after pairwise comparison of the functional loci score matrix of target samples and all samples in the built-in library; obtaining the best combination parent of each material, including: S401, evaluation score system, multiplication of functional loci score and PVE value of corresponding position as the final effect value of loci on phenotype; S402, locus recombination logic, selecting the one with the largest score as the score of the corresponding position of the offspring; S403, evaluating the best combination parent, taking the best score of the offspring obtained by each combination as the final score of the combination, and after performing pairwise combination calculations on all samples in the library, obtaining the combination with the highest score as the best parent combination for breeding, and performing subsequent experimental breeding; In step S402, the site recombination logic selects the larger score as the score of the corresponding position of the offspring, including: for the samples compared pairwise, each region is traversed, and if the regions are not linked to each other, the score of the offspring obtained by combining the two groups is determined to be the larger score; if the two samples in the region are linked and the linkage lengths are consistent, the one with the larger sum of the site scores in the linkage region is determined as the score of the offspring in the linkage region; if one is linked and the other is not linked or the linkage regions are inconsistent, the linkage is broken according to the cross-segment situation, and the linkage region of the two samples is broken with the smallest segment of the cross-part as the unit, and after breaking, the sum of the scores of each sub-region after the split is calculated respectively, and the one with the larger score is selected as the score of the corresponding position of the offspring.

2. The method for obtaining the rapid matching breeding improved parent composition according to claim 1, characterized in that: In step S1, basic SNP markers are obtained, including: all sample WGS sequencing data are quality controlled using FASTP software to obtain valid data, BWA software is used to align bam files, GATK software is used to perform variation detection to obtain SNP markers, and filtering is performed based on depth, deletion rate and minimum allele frequency to obtain basic SNP markers.

3. The method for obtaining the rapid matching breeding improved parent composition according to claim 1, characterized in that: In step S2, among the phenotypes, the genotypes with high single plant yield and high grain weight are the dominant genotypes; the genotypes with low plant height within the range are judged as the dominant genotypes.

4. The method for obtaining the rapid matching breeding improved parent composition according to claim 1, characterized in that: In step S2, a functional site dominant genotype library is constructed, including: scoring each trait-related genotype site of the material according to the experimental and GWAS results, with the dominant allele genotype scored as 1 and the inferior allele scored as -1; forming a genotype score matrix for each sample according to the order and score of each site; and finally all sample materials together constitute the functional site dominant genotype library.

5. The method for obtaining the rapid matching breeding improved parent composition according to claim 1, characterized in that: In step S3, the contribution PVE of the functional site to the phenotype is calculated for analysis, including: using the software R package lme4 to calculate the contribution PVE of the functional site to the phenotype for analysis; constructing a material PVE score library, including: after obtaining the PVE value of each functional site corresponding to each material, according to the position information, the PVE value related to the functional site of each sample is stored in json format as a PVE score library.

6. The method for obtaining the rapid matching breeding improved parent composition according to claim 1, characterized in that: In step S3, constructing a material PVE score library and a Block library includes: using Plink software to calculate the linkage region Block of each material or population; constructing the Block library includes: according to the linkage region Block calculated by the Plink software, combining the functional site position information, setting a Block identification matrix for each functional site of each sample as a Block library; that is, if two functional sites are in a linkage position, the position of the Block library corresponding to the two sites is 1, if not linked, it is set to 0.

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