Genome mating optimization method and system for boars and sows based on GK-SDAF fusion algorithm

Abstract

The application provides a boar and sow genome mating optimization method and system based on a GK-SDAF fusion algorithm, and belongs to the technical field of biological nucleic acid detection and livestock and poultry molecular breeding crossing. The method first carries out whole genome SNP typing detection to obtain individual genotype data; then calculates the genomic kinship GK and allele frequency square difference SDAF of each mating combination; for each sow to be mated, a candidate boar that meets the conditions of genomic kinship GK being lower than a first predetermined threshold and allele frequency square difference SDAF being higher than a second predetermined threshold is screened; and then combined with the upper limit constraint of the number of times of boar mating, a suitable boar is screened for each sow. The method determines the boar and sow mating combination by considering the degree of kinship and the degree of allele frequency difference based on genomic SNP typing data, does not need to rely on phenotype information, relieves inbreeding depression, and blocks inbreeding mating from the source.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of biological nucleic acid detection and livestock molecular breeding technology. More specifically, it relates to a method and system for optimizing the mating of boar and sow genomes based on the GK-SDAF fusion algorithm. Background Technology

[0002] With the decreasing cost of high-throughput genotyping and sequencing, genotyping data, represented by single nucleotide polymorphisms (SNPs), has become the core detection target for livestock and poultry genetic assessment and breeding. Nucleic acid polymorphism differential detection technology itself is a mature and standardized genetic testing service, but the use of its test results in breeding decisions still has significant limitations.

[0003] Current pig breeding commonly employs a genomic selection approach. For example, patent CN118266438B assigns scores to parameters such as genomic kinship between boars and sows (GK), boar and sow genomic performance, and the number of litters bred in the core boar herd to determine mating combinations. However, this approach still relies heavily on phenotypic performance or predicted breeding values. Numerous other studies use predicted genetic values, inbreeding penalty weights, or genetic algorithms to perform linear / integer optimization of mating combinations, which similarly depend on phenotypic breeding values ​​or pre-trained genetic effect models. Meanwhile, the average inbreeding coefficient of the world's three major commercial pig breeds (Duroc / Landrace / Large White) has exceeded 0.10, far higher than the level of no more than 0.0625 typically seen in non-three-generation inbreeding offspring. Inbreeding depression leads to decreased sow fertility, increased piglet mortality, and reduced disease resistance in the herd. Therefore, the challenge lies in how to further reduce the inbreeding level of offspring during mating using only genotype data obtained from whole-genome SNP genotyping, without introducing any phenotypic breeding values ​​or pre-trained genetic effect models. Currently, existing methods that rely solely on genomic kinship (GK) to avoid inbreeding or solely on phenotypic / genetic values ​​to optimize mating cannot simultaneously achieve a further reduction in the inbreeding level of offspring. Summary of the Invention

[0004] The purpose of this invention is to address the problem that existing genome selection methods rely on phenotypic breeding values ​​or pre-trained genetic effect models, and are difficult to further reduce inbreeding levels in offspring during mating. This invention provides a method and system for optimizing boar and sow genome mating based on the GK-SDAF fusion algorithm. It selects boar and sow mating combinations based on the closeness of pure genomic kinship and allele frequency differences, reducing inbreeding levels in offspring without relying on any phenotypic or training model.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm includes the following: S1. Obtain nucleic acid samples from candidate boars and sows to be bred, and perform whole-genome SNP genotyping on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. S2, for each candidate breeding combination consisting of a candidate boar and a sow to be bred, calculate the genomic kinship GK and the squared difference of allele frequencies SDAF corresponding to the candidate breeding combination based on the genotype data; wherein, the genomic kinship GK is used to characterize the degree of genomic kinship between the boar and sow in the combination, and the squared difference of allele frequencies SDAF is used to quantify the overall difference in gene frequencies of the two parents of the candidate breeding combination at each SNP locus; S3, for each sow to be bred, from the multiple candidate mating combinations formed by the sow and each candidate boar, select the candidate boars that simultaneously meet the following two conditions to determine them as a mating combination: the genomic kinship GK of the candidate mating combination is lower than a first predetermined threshold, and the squared difference of allele frequencies SDAF of the candidate mating combination is higher than a second predetermined threshold; and under the constraint that the number of matings assigned to the candidate boar does not exceed its maximum number of matings, assign one boar from the mating candidates to each sow to be bred. S4, generate and output the optimized list of boar-sow mating combinations; The selection of mating combinations in S2 to S3 is based on the genomic kinship GK and the squared difference of allele frequencies SDAF, without taking the phenotypic breeding values ​​of candidate boars or sows to be mated or the genetic effects of pre-training as selection criteria.

[0006] The first predetermined threshold is 0.125, and the second predetermined threshold is 0.12; in S4, candidate boars with genomic kinship GK<0.125 and allele frequency squared difference SDAF>0.12 are identified as breeding candidates for the corresponding sows.

[0007] In step S1, the whole-genome SNP genotyping detection of the nucleic acid sample includes: After amplification and fragmentation of the nucleic acid samples, genotyping chips are used to hybridize the nucleic acid fragments at each SNP locus with the site probes. The hybridization products are then subjected to single-base extension, staining, and scanning to obtain the raw signal values ​​for each SNP locus. A quality control process is then performed on these raw signal values ​​to obtain the genotype data for each candidate individual at each SNP locus. This standard SNP genotyping workflow—hybridization-single-base extension-staining scanning—provides highly reliable genotype data for subsequent calculations of genomic kinship (GK) / squared difference of allele frequencies (SDAF).

[0008] After obtaining the genotype data of each candidate individual at each SNP locus and before executing S2, a second round of quality control is performed on the genotype data, including: removing SNP loci located on sex chromosomes and removing SNP loci with a detection rate lower than 0.90 in the entire sample. By removing sex chromosome SNPs and low-detection-rate loci, sex bias and low-quality noise are eliminated, improving the estimation accuracy of genomic kinship GK / squared difference of allele frequencies (SDAF).

[0009] The genomic kinship (GK) is used to quantify the degree of blood sharing among candidate mating combinations, providing a calculable and normalizable kinship index to avoid inbreeding.

[0010] The squared difference of allele frequencies (SDAF) is used to quantify the overall difference in gene frequencies at each SNP locus between the two candidate individuals of the candidate mating combination. The larger the value, the higher the expected genetic heterozygosity of the offspring obtained from the mating combination.

[0011] In S3, the upper limit of the number of mating attempts for a candidate boar is determined as follows: the upper limit of the number of mating attempts for each candidate boar is determined based on the number of sows to be mated in the current batch and the amount of available semen of each candidate boar; wherein, when the amount of available semen of a candidate boar is insufficient to cover all sows to be mated, the upper limit of the number of mating attempts for that candidate boar is allocated according to the proportion of the amount of available semen to the total demand.

[0012] In step S4, for any sow to be bred, if there are multiple candidate boars that meet the two conditions, the boar with the largest allele frequency squared difference (SDAF) is preferentially selected for mating to maximize the genetic heterozygosity of the offspring. If multiple candidate boars have the same allele frequency squared difference (SDAF), one is randomly assigned. Prioritizing the boar with the largest allele frequency squared difference (SDAF) among multiple qualified boars maximizes the genetic heterozygosity of the offspring and further reduces inbreeding.

[0013] The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm further includes: follow-up tracking based on the genotype data: S5, after mating and farrowing according to the optimized mating combination list, offspring are sampled by litter and whole-genome SNP genotyping is performed again. The inbreeding coefficient is calculated based on the continuous homozygous segments ROH on the offspring's genome. The inbreeding coefficient is equal to the ratio of the total length of the continuous homozygous segments on the individual's genome to the total length of the autosomes in the pig genome. The changes in the inbreeding coefficients of the offspring population and the parent population are compared to evaluate the effectiveness of the method in reducing the inbreeding level of offspring.

[0014] Based on the same concept, this application also provides a genome mating system for optimizing inbreeding based on the GK-SDAF fusion algorithm. This system is used to implement the above-described method for optimizing boar and sow genome mating based on the GK-SDAF fusion algorithm, comprising: The SNP genotyping module is used to acquire nucleic acid samples from each candidate boar in the boar population and each candidate sow in the sow population, and to perform whole-genome SNP genotyping on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. The relationship calculation module is used to calculate the genomic kinship GK and the squared difference of allele frequencies SDAF for each candidate boar and each sow to be bred, based on the genotype data. The mating number determination module is used to determine the upper limit of the number of matings each candidate boar can be mated in the current batch based on the actual mating conditions of the current batch. The mating combination generation module is used to determine, for each sow to be bred, a candidate boar that simultaneously meets the conditions of genomic kinship GK being lower than a first predetermined threshold and allele frequency squared difference SDAF being higher than a second predetermined threshold as a brooding candidate, and under the constraint that the number of times the candidate boar has been assigned to bred has not exceeded its maximum number of times it can be bred, assign a boar from the brooding candidates to bred the sow. The output module is used to generate and output an optimized list of boar-sow mating combinations; The mating combination generation module selects mating combinations based on the genomic kinship (GK) and the squared difference of allele frequencies (SDAF), without using the phenotypic breeding values ​​of candidate boars or sows to be mated, or the genetic effects of pre-training, as selection criteria.

[0015] The beneficial effects of the embodiments in this application compared with the prior art are: This application relies solely on pure genomic genotype data obtained through SNP typing to screen breeding combinations using two pure genetic indicators: genomic kinship (GK) and squared difference of allele frequencies (SDAF). The entire process requires no collection or input of any boar or sow phenotypic data, nor does it necessitate the prior construction and training of genetic effect assessment models. Testing institutions can directly output breeding plans based solely on gene chip typing results, making it suitable for small and medium-sized pig farms without complete performance records and third-party genetic testing service platforms, thus broadening its application scenarios. The GK threshold strictly limits overly close pairings, preventing inbreeding at its source. The newly added SDAF indicator quantifies the overall difference in allele frequencies between parents, prioritizing pairings with greater genomic differences to maximize offspring heterozygosity. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a method for optimizing the mating of boar and sow genomes based on the GK-SDAF fusion algorithm, provided as an embodiment of the present invention.

[0018] Figure 2 This invention provides a comparison of inbreeding levels of offspring from different SDAF standards, based on a GK value less than 0.125, as an embodiment of the invention.

[0019] Figure 3 This invention provides a comparison of inbreeding levels between parent and offspring generations based on GK less than 0.125 and SDAF greater than 0.12, as an embodiment of the invention.

[0020] Figure 4 This invention provides a comparison of newborn piglet mortality rates under different SDAF standards, based on a GK value of less than 0.125, as an embodiment of the invention. Detailed Implementation

[0021] It should be understood that, when used in this application specification and the appended claims, the term includes indicating the presence of the described feature, integral, step, operation, element and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0022] It should also be understood that the terms used in this application specification and the appended claims refer to any combination of one or more of the associated listed items and all possible combinations, and include such combinations.

[0023] Example 1: like Figure 1 As shown, this application provides a method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm, including the following: S1. Obtain nucleic acid samples from candidate boars and sows to be bred, and perform whole-genome SNP genotyping on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. Preferably, EDTA anticoagulant vacuum blood collection tubes are used to collect blood from the anterior vena cava of the boars and sows to be mated, with a blood volume of 8-10 mL per individual. After blood collection, the blood collection tube is gently inverted 5-8 times to thoroughly mix the anticoagulant with the blood to prevent blood cell coagulation. The blood samples are processed using the Monarch HMW high molecular weight DNA extraction kit: red blood cell lysis, white blood cell precipitation, protein digestion, specific binding of nucleic acid to silica gel column, low-salt impurity washing, and high-salt DNA elution are performed sequentially; the elution buffer is the enzyme-free TE buffer provided with the kit, with an elution volume of 60 μL.

[0024] In step S1, the whole-genome SNP genotyping detection of the nucleic acid sample includes: after amplification and fragmentation of the nucleic acid sample, hybridization of nucleic acid fragments at each SNP locus with site probes using a genotyping chip; single-base extension, staining, and scanning of the hybridization products to obtain the raw signal values ​​of each SNP locus; and a round of quality control of the raw signal values ​​to obtain the genotype data of each candidate individual at each SNP locus. This standardized chip genotyping process can stably output high-fidelity site genotyping results, avoid human detection errors, and provide reliable genotype data for subsequent quantitative calculations of genomic kinship (GK) and allele frequency squared difference (SDAF).

[0025] In one embodiment, the nucleic acid samples that have passed quality inspection are subjected to amplification and fragmentation: the DNA template is placed in a 37°C constant temperature water bath for amplification for 20–24 hours. After amplification, it is digested and fragmented, precipitated, and reconstituted. The reconstituted nucleic acid system is added to a porcine-specific Illumina Porcine SNP50K genotyping microbead chip, the chip is sealed, and incubated in a 48°C hybridization oven for 16–24 hours to allow the nucleic acid fragments to fully hybridize with the specific probes of each SNP site on the chip. After hybridization, the non-specifically bound free nucleic acid fragments on the chip surface are washed away, and then the specific probes on the chip are further processed. Single base extension reaction and fluorescence staining were performed sequentially on the heterozygous binding sites. The stained chip was then placed in an iScan chip scanner for full-area scanning, and the original fluorescence signal intensity values ​​corresponding to each target SNP site were collected. All original signal values ​​were imported using GenomeStudio genotyping software to conduct the first round of quality control. The software automatically identified and removed abnormal sites with a signal-to-noise ratio lower than the set threshold or complete hybridization failure. The base genotyping information of the effective sites was converted into 0, 1, and 2 numerical encoding formats to obtain the genotype data of each candidate individual at each SNP site.

[0026] Wherein, code 0: the individual is homozygous for the wild type at the corresponding SNP locus, and both homologous chromosomes carry the wild-type allele; code 1: the individual is heterozygous for the corresponding SNP locus, with one homologous chromosome carrying the wild-type allele and the other carrying the variant allele; code 2: the individual is homozygous for the variant type at the corresponding SNP locus, and both homologous chromosomes carry the variant allele. For any individual i and any k-th SNP locus, the genotype code is denoted as... The complete set of all loci codes constitutes the complete genotype data of this individual.

[0027] After obtaining the genotype data of each candidate individual at each SNP locus and before executing S2, a second round of quality control is performed on the genotype data. This includes using PLINK 1.9 population genetic analysis software to perform a second round of refined quality control filtering, removing SNP loci located on sex chromosomes and removing SNP loci with a detection rate lower than 0.90 in the entire sample. By removing sex chromosome SNPs and low-detection-rate loci, sex bias and low-quality noise are eliminated, improving the estimation accuracy of genomic kinship GK / squared difference of allele frequencies (SDAF).

[0028] S2, for each candidate breeding combination consisting of a candidate boar and a sow to be bred, calculate the genomic kinship GK and the squared difference of allele frequencies SDAF corresponding to the candidate breeding combination based on the genotype data; wherein, the genomic kinship GK is used to characterize the degree of genomic kinship between the boar and sow in the combination, and the squared difference of allele frequencies SDAF is used to quantify the overall difference in gene frequencies of the two parents of the candidate breeding combination at each SNP locus; The genomic kinship (GK) calculation is based on adjusting the genotype codes of all SNP loci of both parents and their corresponding gene frequencies in the population to obtain the similarity of the genotype codes of the parents at each SNP locus. This similarity is then aggregated and normalized across all SNP loci, resulting in candidate mating combinations with higher genomic kinship values. This numerical genomic kinship quantifies the degree of kinship among candidate mating combinations, providing a calculable and normalizable kinship index. Therefore, a GK value below a threshold is used to avoid inbreeding. The complete formula for calculating genomic kinship is as follows: ; in, To determine the genomic relationship between paired boars and sows, boar exist Genotype coding at the locus (0, 1, 2). For sows exist Genotype coding at the locus (0, 1, 2). The first in the entire group Allele frequencies at each SNP locus This represents the total number of sites.

[0029] The squared difference of allele frequencies (SDAF) is calculated by traversing all SNP loci, obtaining the square of the difference in allele frequencies at each locus of the parents, summing the values ​​over all loci, and then dividing by the total number of loci. This quantifies the overall difference in gene frequencies at each SNP locus between the two candidate individuals of the candidate mating combination. A higher SDAF value indicates a higher expected genetic heterozygosity in the offspring. Furthermore, the calculation only requires genotype, not phenotype; therefore, an SDAF value higher than a threshold is used to increase the genetic heterozygosity of the offspring. The complete formula for calculating the squared difference of allele frequencies is as follows: ; in, The squared difference of allele frequencies between paired boars and sows boar exist Allele frequencies at loci For sows exist Allele frequencies at loci This represents the total number of sites.

[0030] S3. For each sow to be bred, from the multiple candidate mating combinations formed by the sow and each candidate boar, select the candidate boars that simultaneously meet the following two conditions and determine them as mating candidates: the genomic kinship GK of the candidate mating combination is lower than a first predetermined threshold, and the squared difference of allele frequencies SDAF of the candidate mating combination is higher than a second predetermined threshold; and under the constraint that the number of matings assigned to the candidate boar does not exceed its maximum number of matings, assign one boar from the mating candidates to each sow to be bred.

[0031] In this embodiment, the two thresholds correspond to two independent criteria: avoiding inbreeding (genomic kinship GK) and increasing heterozygosity (squared allele frequency difference SDAF), both of which must be met simultaneously. The genomic kinship GK threshold of 0.125 is slightly relaxed compared to the usual level of ≤0.0625 for non-three-generation inbreeding offspring, aiming to ensure a sufficient number of candidate boars and avoid an overly narrow selection range. The squared allele frequency difference SDAF threshold of 0.12 is an empirical cutoff used to distinguish between high-complementarity and low-complementarity breeding combinations. This value is derived from 857 Yorkshire boar and sow breeding comparison trials: under the premise of genomic kinship GK < 0.125, combinations with squared allele frequency difference SDAF > 0.12 had an average inbreeding coefficient that was 0.0206 lower than combinations with squared allele frequency difference SDAF ≤ 0.12, proving that 0.12 is an effective cutoff.

[0032] S4, generate and output the optimized list of boar-sow mating combinations; The selection of mating combinations in S2 to S3 is based on the degree of genomic kinship and the degree of overall difference in allele frequencies, as represented by the genomic kinship GK and the squared difference of allele frequencies SDAF. The phenotypic breeding values ​​of candidate boars or sows to be mated or the genetic effects of pre-training are not used as selection criteria.

[0033] The first predetermined threshold is 0.125, and the second predetermined threshold is 0.12; in S4, candidate boars with genomic kinship GK < 0.125 and allele frequency squared difference SDAF > 0.12 are identified as breeding candidates for the corresponding sows.

[0034] In S3, the upper limit of the number of mating attempts for a candidate boar is specifically determined as follows: the upper limit of the number of mating attempts for each candidate boar is determined based on the number of sows to be bred in the current batch and the amount of available semen in each candidate boar; wherein, when the amount of available semen in a candidate boar is insufficient to cover all sows to be bred, the upper limit of its mating attempts is allocated according to the proportion of available semen to the total demand. Preferably, the number of mating attempts for each boar in the current batch is determined based on the actual situation. For example, if the current number of sows to be bred is 10 and the number of available boars is 2 (including boars A and B), but boar A has insufficient semen, then boar A is determined to have 3 mating attempts and boar B is determined to have 7 mating attempts.

[0035] In step S4, for any sow to be bred, if multiple candidate boars satisfy the two conditions, the boar with the largest allele frequency squared difference (SDAF) is preferentially selected for mating to maximize the genetic heterozygosity of the offspring. When multiple candidate boars have the same allele frequency squared difference (SDAF), one is randomly assigned. Prioritizing the boar with the largest allele frequency squared difference (SDAF) among multiple qualified boars maximizes the genetic heterozygosity of the offspring and further reduces inbreeding. Figure 2 In the double hard threshold screening shown, there may be more than one candidate boar falling into the acceptable zone; at this time, the best boar is further selected in order of the size of the squared difference of allele frequency (SDAF). The boar with the largest squared difference of allele frequency (SDAF) corresponds to the highest expected heterozygosity of offspring and the lowest inbreeding.

[0036] The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm further includes: follow-up tracking based on the genotype data: S5, after mating and farrowing according to the optimized mating combination list, offspring are sampled by litter and whole-genome SNP polymorphism is determined again. The inbreeding coefficient is calculated based on the continuous homozygous segments ROH on the offspring genome. The inbreeding coefficient is equal to the ratio of the total length of the continuous homozygous segments on the individual genome to the total length of the autosomes in the pig genome. The changes in the inbreeding coefficient between the offspring population and the parent population are compared to evaluate the effect of the method on reducing the inbreeding level of offspring.

[0037] Among them, the inbreeding coefficient based on ROH: ; in, This refers to the total length of continuous homozygous segments on the individual's genome. This is the total length of the autosomes in the pig genome (usually 2466 Mb by default).

[0038] This embodiment uses Yorkshire pigs as a control in a field mating experiment. All candidate boars and sows undergoing the same procedures as described in S1: sample collection, SNP genotyping, and two rounds of genotyping quality control. In S2, the genomic kinship (GK) and allele frequency squared difference (SDAF) of all matings are calculated in batches. A uniform kinship constraint is set for the experiment: only candidate mating combinations with a genomic kinship (GK < 0.125) are selected for breeding trials to exclude interference from highly inbred pairings. Based on this, qualified pairings are divided into two groups: a control group (SDAF ≤ 0.12) and an optimized group (SDAF > 0.12), and mating and breeding are carried out separately. The inbreeding coefficient of offspring and the newborn piglet mortality rate are calculated after farrowing.

[0039] like Figure 2The figure shows a box plot comparing the inbreeding coefficients of the offspring of the control group (SDAF ≤ 0.12) and the optimized group (SDAF > 0.12) under the condition of genomic kinship GK < 0.125. (See attached figure.) Figure 1 It is evident that, under the premise of controlled genomic affinity (GK < 0.125), the median inbreeding coefficient of offspring in the optimized group (SDAF > 0.12) was significantly lower than that in the control group (SDAF ≤ 0.12). The overall distribution range of inbreeding coefficients in the optimized group shifted downwards, and the proportion of highly inbred individuals in the population decreased significantly. Experimental data showed that the average inbreeding coefficient of offspring in the control group was 0.3212, while the average inbreeding coefficient of offspring in the optimized group decreased to 0.3006, a decrease of 0.0206. The results indicate that relying solely on genomic affinity (GK) to avoid inbreeding has limitations; combining SDAF threshold screening with preferential selection of boars and sows with greater genomic allelic differences can further reduce the level of genomic inbreeding in offspring and inhibit the accumulation of inbreeding in the population. (See attached...) Figure 2 It is evident that the median inbreeding coefficients of both parent boar and sow populations are at a relatively high level. After using the dual-index screening scheme of this invention for breeding, the median inbreeding coefficient of the offspring population is significantly lower than that of the paternal and maternal populations, and the overall inbreeding level of the offspring is effectively reduced compared to the parent generation. This demonstrates that the breeding strategy of this invention, which utilizes genomic kinship (GK) and the squared difference of allele frequencies (SDAF) for synergistic screening, can break the trend of continuously increasing inbreeding in closed breeding populations.

[0040] like Figure 3 As shown, under the condition of uniformly controlling the kinship of boars and sows (genomic kinship GK < 0.125) and using the dual-index screening scheme of this invention (simultaneously satisfying GK < 0.125 and SDAF > 0.12) for breeding, the median inbreeding coefficient of the parent boar population is approximately 0.318, and the median inbreeding coefficient of the sow population is approximately 0.322, both at a relatively high level; while the median inbreeding coefficient of the offspring population is approximately 0.300, significantly lower than that of the paternal and maternal populations, indicating that the overall inbreeding level of the offspring is effectively reduced compared to the parent generation. This further demonstrates that the breeding strategy of this invention, which utilizes the synergistic screening of genomic kinship GK and the squared difference of allele frequencies (SDAF), can gradually reduce the overall genetic inbreeding degree of the population from the breeding source.

[0041] like Figure 4The bar chart shows the comparison of newborn piglet mortality rates between the two breeding combinations under the condition of genomic kinship GK < 0.125. In the control group (allele frequency squared difference SDAF ≤ 0.12), the newborn piglet mortality rate was 9.251%; in the optimized group (allele frequency squared difference SDAF > 0.12), the newborn piglet mortality rate decreased to 8.125%, an absolute decrease of 1.126 percentage points and a relative decrease of approximately 12.17%. This result is consistent with the changing pattern of inbreeding levels in offspring: pairing with higher allele frequency squared difference SDAF results in less inbreeding in offspring, effectively mitigating the risk of piglet mortality caused by inbreeding depression and improving piglet survival efficiency.

[0042] As can be seen, this invention, based on the unified control of boar and sow kinship (genomic kinship GK < 0.125), introduces the allele frequency squared difference (SDAF) index to screen for mating combinations with stronger genomic allele frequency differences. This reduces the inbreeding coefficient of offspring by 0.0206 and the newborn piglet mortality rate by 1.126 percentage points (a relative reduction of 12.17%). This verifies the effectiveness of the dual-index mating selection scheme of this invention, which uses genomic kinship GK inbreeding constraint and allele frequency squared difference (SDAF) genomic complementarity screening. This scheme relies solely on SNP genomic typing data for screening, without requiring individual phenotypic records, making it suitable for large-scale genomic mating applications in pig farms.

[0043] Example 2: This application also provides a boar and sow genome mating optimization system based on the GK-SDAF fusion algorithm. The system is used to implement the boar and sow genome mating optimization method based on the GK-SDAF fusion algorithm described above, including: The polymorphism typing module is used to acquire nucleic acid samples from each candidate boar in the boar population and each candidate sow in the sow population, and to perform whole-genome SNP typing on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. The relationship calculation module is used to calculate the genomic kinship GK and the squared difference of allele frequencies SDAF for each candidate boar and each sow to be bred, based on the genotype data. The mating number determination module is used to determine the upper limit of the number of matings each candidate boar can be mated in the current batch based on the actual mating conditions of the current batch. The mating combination generation module is used to determine, for each sow to be bred, a candidate boar that simultaneously meets the conditions of genomic kinship GK being lower than a first predetermined threshold and allele frequency squared difference SDAF being higher than a second predetermined threshold as a brooding candidate, and under the constraint that the number of times the candidate boar has been assigned to bred has not exceeded its maximum number of times it can be bred, assign a boar from the brooding candidates to bred the sow. The output module is used to generate and output an optimized list of boar-sow mating combinations; The mating combination generation module selects mating combinations based on the genomic kinship (GK) and the squared difference of allele frequencies (SDAF), without using the phenotypic breeding values ​​of candidate boars or sows to be mated, or the genetic effects of pre-training, as selection criteria.

[0044] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm, characterized in that, Including the following: S1. Obtain nucleic acid samples from candidate boars and sows to be bred, and perform whole-genome SNP genotyping on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. S2, for each candidate breeding combination consisting of a candidate boar and a sow to be bred, calculate the genomic kinship GK and the squared difference of allele frequencies SDAF corresponding to the candidate breeding combination based on the genotype data; wherein, the genomic kinship GK is used to characterize the degree of genomic kinship between the boar and sow in the combination, and the squared difference of allele frequencies SDAF is used to quantify the overall difference in gene frequencies of the two parents of the candidate breeding combination at each SNP locus; S3. For each sow to be bred, from the multiple candidate mating combinations formed by the sow and each candidate boar, select the candidate boars that simultaneously meet the following two conditions and determine them as their mating partners: the genomic kinship GK of the candidate mating combination is lower than a first predetermined threshold, and the squared difference of allele frequencies SDAF of the candidate mating combination is higher than a second predetermined threshold; and under the constraint that the number of matings assigned to the candidate boar does not exceed its maximum number of matings, assign one boar from the mating candidates to each sow to be bred. S4, generate and output the optimized list of boar-sow mating combinations; The selection of mating combinations in S2 to S3 is based on the genomic kinship GK and the squared difference of allele frequencies SDAF, without taking the phenotypic breeding values ​​of candidate boars or sows to be mated or the genetic effects of pre-training as selection criteria.

2. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, The first predetermined threshold is 0.125, and the second predetermined threshold is 0.12; in S4, candidate boars with genomic kinship GK<0.125 and allele frequency squared difference SDAF>0.12 are identified as breeding candidates for the corresponding sows.

3. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, In step S1, the whole-genome SNP genotyping detection of the nucleic acid sample includes: After amplification and fragmentation of the nucleic acid samples, the nucleic acid fragments of each SNP site are hybridized with site probes using a genotyping chip. The hybridization products are then subjected to single-base extension, staining, and scanning to obtain the original signal values ​​of each SNP site. The original signal values ​​are then subjected to a round of quality control to obtain the genotype data of each candidate individual at each SNP site.

4. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 3, characterized in that, After obtaining the genotype data of each candidate individual at each SNP locus and before executing S2, the process includes performing a second round of quality control on the genotype data, including: removing SNP loci located on sex chromosomes and removing SNP loci with a detection rate of less than 0.90 in the entire sample.

5. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, The genomic kinship GK is calculated according to the genomic kinship algorithm formula. Based on the genotype coding of each candidate individual at each SNP locus and the gene frequency of the corresponding locus in the population, the similarity of the genotype coding of two candidate individuals is taken for each SNP locus. The results are summarized and normalized for all SNP loci, so that the candidate mating combination with closer genomic kinship has a larger genomic kinship GK value.

6. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, The squared difference of allele frequencies (SDAF) is the sum of squares of the differences in gene frequencies at each SNP locus between two candidate individuals. It is used to quantify the overall difference in gene frequencies at each SNP locus between the two candidate individuals in the candidate mating combination. The larger the value, the higher the expected genetic heterozygosity of the offspring obtained from the mating combination.

7. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, In S3, the upper limit of the number of mating attempts for a candidate boar is determined as follows: the upper limit of the number of mating attempts for each candidate boar is determined based on the number of sows to be mated in the current batch and the amount of available semen of each candidate boar; wherein, when the amount of available semen of a candidate boar is insufficient to cover all sows to be mated, the upper limit of the number of mating attempts for that candidate boar is allocated according to the proportion of the amount of available semen to the total demand.

8. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, In S4, for any sow to be bred, if there are multiple candidate boars that meet the two conditions, the boar with the largest squared allele frequency difference (SDAF) is selected for breeding in order to maximize the genetic heterozygosity of the offspring born to the sow; when multiple candidate boars have the same squared allele frequency difference (SDAF), one is randomly assigned from among them.

9. The method for optimizing boar and sow genomic mating based on the GK-SDAF fusion algorithm according to claim 1, characterized in that, Also includes: Follow-up tracking based on the genotype data: S5. After mating and farrowing according to the optimized mating combination list, offspring are sampled by litter and whole-genome SNP genotyping is performed again. The inbreeding coefficient is calculated based on the continuous homozygous segments (ROH) on the offspring genome. The inbreeding coefficient is equal to the ratio of the total length of the continuous homozygous segments on the individual's genome to the total length of the autosomes in the pig genome. The changes in the inbreeding coefficients of the offspring population and the parent population are compared to evaluate the effectiveness of the method in reducing the inbreeding level of offspring.

10. A boar and sow genome mating optimization system based on the GK-SDAF fusion algorithm, the system being used to implement the boar and sow genome mating optimization method based on the GK-SDAF fusion algorithm as described in any one of claims 1-9, characterized in that, include: The SNP genotyping module is used to obtain nucleic acid samples from each candidate boar in the candidate boar population and each sow in the sow population, and to perform whole-genome SNP genotyping on the nucleic acid samples to obtain genotype data of each candidate individual at multiple SNP loci. The relationship calculation module is used to calculate the genomic kinship GK and the squared difference of allele frequencies SDAF for each candidate boar and each sow to be bred, based on the genotype data. The mating number determination module is used to determine the upper limit of the number of matings each candidate boar can be mated in the current batch based on the actual mating conditions of the current batch. The mating combination generation module is used to determine, for each sow to be bred, a candidate boar that simultaneously meets the conditions of genomic kinship GK being lower than a first predetermined threshold and allele frequency squared difference SDAF being higher than a second predetermined threshold as its brooding target, and under the constraint that the number of times the candidate boar has been assigned to bred has not exceeded its maximum number of times it can be bred, assign a boar from the brooding targets for brooding. The output module is used to generate and output an optimized list of boar-sow mating combinations; The mating combination generation module selects mating combinations based on the genomic kinship (GK) and the squared difference of allele frequencies (SDAF), without using the phenotypic breeding values ​​of candidate boars or sows to be mated, or the genetic effects of pre-training, as selection criteria.

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