Device and method for evaluating sow lactation ability

Abstract

The present invention discloses an apparatus and method for evaluating the lactation ability of sows. The apparatus for evaluating the lactation ability of sows disclosed in the present invention comprises: A1, a data acquisition module: used to obtain relevant trait data of the sow to be tested and each sow in its group, including the litter weight at weaning on day 21 and the number of piglets; A2, a data correction module: used to correct the litter weight at weaning on day 21 of the sow, and correct the litter weight at weaning on day 21 of each sow in the group based on the number of piglets as a covariate; A3, a sow lactation ability evaluation module: used to calculate the phenotypic value of the lactation ability trait of the sow. The apparatus and method for evaluating the lactation ability of sows disclosed in the present invention are based on the litter weight at birth and the number of piglets. Compared with the existing litter weight method and extrapolation method at day 21, the method of the present invention obtains more accurate phenotypic estimation values, and the estimated heritability is higher than that of the litter weight method and extrapolation method at day 21, and has good application prospects.

Description

Technical Field

[0001] The present invention relates to a device and method for evaluating sow lactation ability in the field of bioinformatics. Background Art

[0002] Colostrum and milk are important sources of antibodies and nutrients for newborn piglets, crucial for their survival and growth during the lactation period. Over the past decade, the goal of pig genetic improvement has been to increase the total litter size. A larger litter size requires sows to produce more milk to provide the energy needed for the growth and development of lactating piglets. Conversely, low sow lactation efficiency is closely linked to poor piglet growth, high mortality, and low average weaning weight. Furthermore, sow lactation efficiency directly impacts the production efficiency and economic benefits of pig farming. Therefore, improving pig lactation performance is economically significant, and genetic improvement of sow lactation performance is crucial.

[0003] Unlike dairy cows, sow lactation cannot be directly measured. Early methods for measuring sow lactation primarily used isotope dilution and the weigh-lactate-weigh (WSW) method. However, these methods are cumbersome and costly, making them difficult to implement in production. Subsequently, researchers proposed using the litter size at 20 or 21 days of age to measure sow lactation. This method is simple and rapid, but not entirely accurate. Yang Gongshe et al. proposed an extrapolation method, assuming that every 1 kg of piglet weight gain requires 3 kg of milk to estimate lactation during lactation. DM. Thekkoot et al. used litter weight gain (LWG) as an indicator of lactation in Yorkshire and Landrace sows. Although these methods have been proposed for assessing sow lactation, lactation is influenced by multiple factors, such as litter weight at birth and piglet number, which currently reported methods do not account for. Therefore, accurately phenotyping lactation has become a bottleneck in breeding programs.

[0004] In recent years, with the rapid development of high-throughput genotyping technology, genome-wide association studies (GWAS) have become an effective tool for studying the genetic structure of complex traits. Many studies have identified quantitative trait loci (QTLs) and candidate genes associated with important economic traits in pigs, such as meat quality traits and growth traits. Some candidate genes associated with pig lactation traits were also identified in two previous GWAS studies. However, these two studies mainly used litter weight gain to evaluate the lactation capacity of sows, ignoring the effects of covariates such as piglet number. Inaccurate phenotypes may lead to inaccurate genetic parameter estimates and lower statistical power, which is not conducive to the analysis of the genetic mechanism of pig lactation traits and may slow down the genetic and phenotypic progress of the population. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to address the inaccuracy of the current estimation of sow lactation phenotype, and to propose a more scientific and reliable sow lactation assessment device and method, based on which SNP markers and candidate genes related to sow lactation can be screened.

[0006] In order to solve the above technical problems, the present invention first provides a device for evaluating sow lactation ability, which includes the following modules:

[0007] A1. Data acquisition module: used to obtain relevant trait data of the sow to be tested and each sow in its group, including the weaned litter weight and piglet number at 21 days of age;

[0008] A2. Data correction module: used to correct the 21-day weaning litter weight of sows; based on the number of piglets as a covariate, the 21-day weaning litter weight of each sow in the group is corrected. The correction formula is the following formula IV and formula V, and the 21-day weaning litter weight of each sow after covariate correction is obtained. The 21-day weaning litter weight of the i-th sow after covariate correction is recorded as y i ′ :

[0009]

[0010]

[0011] Among them, y i ′ is the litter weight of sow i at 21 days of age after covariate correction, is the litter weight of the i-th sow at 21 days of age, b is the fixed effect vector of piglet number; X is the correlation matrix of the fixed effect vector; u is the additive genetic effect vector; Z is the correlation matrix of the random effect vector; e is the random residual;

[0012] A3. Sow lactation ability evaluation module: used to calculate the phenotypic value of sow lactation ability; according to formula VI, the phenotypic value y of the lactation ability of the i-th sow to be tested is obtained. i ;

[0013]

[0014] Among them, y i is the phenotypic value of the lactation trait of the i-th sow, is the minimum litter weight at 21 days of age in the group, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, L y′ is the minimum value of the 21-day-old weaned litter weight in the population after correction for covariates, is the difference between the maximum and minimum litter weights at 21 days of age in the group, R y′ It is the difference between the maximum and minimum litter weight at 21 days of age after correction for covariates in the population.

[0015] Each sow and her piglets are kept in a separate pen.

[0016] The piglet number refers to the number of piglets raised by a sow during the lactation period.

[0017] The group includes any number of sows greater than or equal to 3.

[0018] In the above device, correction of the 21-day-old weaning litter weight of each sow in the group based on the piglet number as a covariate can be performed using a mixed linear model.

[0019] The present invention also provides a method for evaluating the lactation capacity of sows, which comprises: detecting the litter weight and number of piglets weaned at 21 days of age of the sow to be tested and each sow in its group, and obtaining the lactation capacity of the sow to be tested based on the litter weight and number of piglets weaned at 21 days of age of each sow.

[0020] The above method can be used to calculate the lactation phenotypic value y of the i-th sow to be tested according to formula VI: i ;

[0021]

[0022] Among them, y i is the phenotypic value of the lactation trait of the i-th sow, is the minimum litter weight at 21 days of age in the group, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, L y ' is the minimum value of the 21-day-old weaning litter weight in the population after covariate correction, is the difference between the maximum and minimum litter weights at 21 days of age in the group, R y ′ is the difference between the maximum and minimum values ​​of the 21-day-old weaned litter weight in the population after correction for covariates;

[0023] Among them, y i ′ The 21-day-old weaning litter weight of each sow in the group was corrected based on the number of piglets as a covariate. The correction formulas are as follows: Formula IV and Formula V. The 21-day-old weaning litter weight of each sow after covariate correction is obtained. The 21-day-old weaning litter weight of the i-th sow after covariate correction is recorded as y i ′ :

[0024]

[0025]

[0026] in, is the litter weight of the i-th sow at 21 days of age, b is the fixed effect vector of piglet size, X is the correlation matrix of the fixed effect vector, u is the additive genetic effect vector, Z is the correlation matrix of the random effect vector, and e is the random residual.

[0027] In the above method, correction of the 21-day-old weaning litter weight of each sow in the group based on the piglet number as a covariate can be performed using a mixed linear model.

[0028] The present invention also provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of the method for evaluating the lactation capacity of sows when the computer program / instruction is executed by a processor.

[0029] The present invention also provides a computer program product, comprising a computer program / instruction, which implements the steps of the method for evaluating the lactation ability of sows when executed by a processor.

[0030] The computer program product may be a software product that primarily implements its solution through a computer program.

[0031] The computer-readable storage medium refers to a carrier for storing data, which may be a tape, disk, floppy disk, optical disk, magneto-optical disk, ROM, PROM, VCD, DVD, hard disk, flash memory, USB flash drive, CF card, SD card, MMC card, SM card, memory stick (Memory Stick) or xD card, etc.

[0032] The use of the device, or the method for evaluating sow lactation ability, or the computer-readable storage medium, or the computer program product in screening genes or mutation sites related to sow lactation ability also falls within the scope of protection of the present invention.

[0033] The use of the device, the computer-readable storage medium, or the computer program product in preparing products for screening sow lactation-related genes or mutation sites also falls within the scope of protection of the present invention.

[0034] The mutation site may be a SNP site, or any other form of mutation site, including insertion / deletion, etc.

[0035] The device and method for evaluating the lactation ability of sows of the present invention are based on the newborn litter weight and the number of piglets. Compared with the existing 21-day-old litter weight method and the extrapolation method, the method of the present invention obtains more accurate phenotypic estimates, and the estimated heritability is higher than the 21-day-old weaning litter weight method and the extrapolation method. By integrating GWAS analysis, biological function analysis and pig mammary transcriptome data, the present invention successfully identified 4 SNPs and 30 candidate genes significantly associated with lactation traits, including 8 differentially expressed genes. The device and method for evaluating the lactation ability of sows of the present invention contribute to the analysis of the genetic mechanism of sow lactation traits, and can provide relevant molecular markers and candidate genes for the selection and breeding of sow lactation traits.

[0036] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Flowchart for assessing lactation performance in sows.

[0038] Figure 2 The Manhattan plot and QQ-plot of the GWAS results for the three sow lactation assessment methods in Example 1. A shows the results of the 21-day weaning litter weight method, B shows the results of the extrapolation method proposed by Yang Gongshe et al., and C shows the results of the covariate correction method for assessing sow lactation. DETAILED DESCRIPTION

[0039] Unless otherwise noted, the experimental methods in the following examples are conventional methods and were performed according to the techniques and conditions described in literature in the field or according to product specifications. The materials, reagents, and instruments used in the following examples were all commercially available unless otherwise noted. The quantitative experiments in the following examples were performed in at least three replicates.

[0040] Example 1

[0041] Identified individuals: 1,336 sows from a pig farm.

[0042] 1. For each sow, record its ear number, sample number, litter weight at birth, number of piglets, and litter weight at 21 days of weaning.

[0043] 2. DNA was extracted from the individuals to be identified and genotyped. PLINK software was used to perform quality control on the raw genotype data for all individuals. Sites with missing values ​​>10% and a minimum allele frequency <0.01 were removed, resulting in genotype data for 47,257 polymorphic sites.

[0044] The steps to obtain genotype data are as follows:

[0045] Ear tissue samples were collected from all sows and stored in a 75% ethanol aqueous solution. DNA from the individual to be tested was extracted using the TIANamp Genomic DNA Kit produced by Beijing Tiangen Biochemical Technology Co., Ltd. The extracted DNA was quality tested using a NanoDrop2000 Nucleic Acid and Protein Analyzer (Thermo Fisher Scientific, USA). DNA samples were considered qualified if their A260 / A280 ratios were between 1.7 and 2.1, and if their A260 / A230 ratios were between 1.8 and 2.2. The qualified DNA samples were then diluted to a uniform concentration of 200 ng / μl and stored in a -20°C refrigerator. Unqualified DNA samples required re-extraction.

[0046] Genomic DNA samples extracted from 1,336 pig ears were hybridized to the Illumina PorcineSNP50BeadChip whole-genome array, which contains 50,697 SNP sites.

[0047] 3. Use a general linear model to evaluate the effects of litter weight at birth and number of piglets on litter weight at weaning at 21 days of age. The evaluation method is as follows:

[0048] y=Xb+e (Formula I)

[0049] y is the litter weight of sows in this group at 21 days of age at weaning, X is the correlation matrix of the fixed effect vectors of litter weight or piglet number at birth, and b is the effect value of litter weight or piglet number at birth.

[0050] The results showed that the number of piglets carried had a significant effect on the litter weight at weaning at 21 days of age, while the litter weight at birth had no significant effect on the litter weight at weaning at 21 days of age (Table 1). The inventors subsequently added the number of piglets carried as a fixed effect to the lactation capacity calculation formula.

[0051] Table 1. Significance test of factors affecting litter weight at 21 days of weaning

[0052]

[0053] 4. Establishment of three lactation assessment formulas

[0054] 4.1 The lactation capacity of sows is assessed using the 21-day weaning litter weight method. The calculation formula is:

[0055] y=W 21 (Formula II)

[0056] Among them, y is the phenotypic value of lactation ability, W 21 This is the litter weight at weaning at 21 days of age.

[0057] 4.2 The sow's lactation capacity was evaluated using the method proposed by Yang Gongshe et al. The calculation formula is:

[0058] y=(W 21 -W0)×3(Formula III)

[0059] Among them, y is the phenotypic value of lactation ability, W 21 W0 is the litter weight at weaning age of 21 days, and W0 is the litter weight at birth.

[0060] 4.3 Evaluate sow lactation capacity based on the covariate correction method. The steps are as follows:

[0061] 1) A mixed linear model was used to correct the 21-day weaning litter weight of each sow in the group based on the covariate (i.e., the number of piglets). The correction formulas are as follows: Formula IV and Formula V. According to Formula IV, b, u, and e were obtained. According to Formula V, the covariate-corrected 21-day weaning litter weight y′ of the sow to be tested (i.e., the i-th sow below) was obtained. The covariate-corrected 21-day weaning litter weight of the i-th sow was recorded as y i ′ :

[0062]

[0063]

[0064] Among them, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, is the litter weight of the i-th sow at 21 days of age, b is the fixed effect vector of piglet size, X is the correlation matrix of the fixed effect vector, u is the additive genetic effect vector, Z is the correlation matrix of the random effect vector, and e is the random residual.

[0065] 2) Evaluate the lactation ability of sows based on the covariate correction method. The phenotypic value is represented by y. The phenotypic value of the lactation ability trait of the i-th sow is y i , calculate the phenotypic value of the lactation ability trait of the i-th sow according to formula VI:

[0066]

[0067] Among them, y i is the phenotypic value of the lactation trait of the i-th sow, is the minimum litter weight at 21 days of age in the group, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, L y′ is the minimum litter weight at 21 days of weaning after correction for covariates in the population, R is the difference between the maximum and minimum litter weights at 21 days of age in the group, y′ It is the difference between the maximum and minimum litter weights at 21 days of age after correction for covariates in the group.

[0068] Genetic parameter estimates for three milk production methods. GCTA software was used to estimate the heritability, genetic variance, and residual variance for the 21-day-old weaning litter weight method, the imputed method, and the covariate-adjusted sow milk production method. The heritability estimates for the three methods were 0.09, 0.08, and 0.14, respectively. The covariate-adjusted method achieved higher heritability than the 21-day-old weaning litter weight method and the imputed method (Table 2).

[0069] Table 2. Genetic parameter estimates for three lactation methods

[0070]

[0071]

[0072] Note: Heritability refers to the narrow sense heritability, that is, the ratio of additive genetic variance to phenotypic variance. Data are expressed as “mean ± SE”.

[0073] 5. GWAS analysis of three lactation methods. The inventors used a mixed linear model in GCTA software to perform GWAS analysis to identify SNPs associated with sow lactation traits, expressed as:

[0074] y=1μ+Xb+g - +e (Formula VII)

[0075] Where y is the phenotypic value vector of the lactation trait; μ is the population mean; b is the fixed effect of the SNP to be tested; X is the genotype vector of the SNP to be tested; g - is the cumulative effect of all SNPs on the remaining chromosomes except the chromosome where the target SNP is located, and e is the random residual.

[0076] 6. Bonferroni correction was applied to the P-values ​​of the differences in the pig GWAS analysis results, and the CMplot package in R was used to draw Manhattan and QQ plots. SNPs above the threshold line (p-value = 0.1 / 47,257) on the Manhattan plot were SNPs significantly associated with sow lactation. Manhattan and QQ-plots of the significant SNPs identified by the 21-day weaning litter weight method, the imputed method, and the covariate-corrected sow lactation assessment method are shown in Figure 2. Figure 2Neither the 21-day weaning litter weight method nor the inference method proposed by Yang et al. detected any SNPs significantly associated with lactation. The covariate-adjusted sow lactation assessment method detected four significantly associated SNPs, two of which are listed in Table 3.

[0077] 7. Using the porcine genome sequence Sscrofa11.1 from the Ensembl website, we screened for genes within 1 MB of the SNPs significantly associated with sow lactation. We then performed GO and KEGG enrichment analysis using KOBAS 3.0 and performed functional annotation of these genes using the PubMed database to identify candidate genes associated with sow lactation. Using the covariate-adjusted sow lactation assessment method, we identified 30 candidate genes associated with sow lactation traits. Some of these genes are listed in Table 3.

[0078] Table 3. SNPs and candidate genes associated with sow lactation traits

[0079]

[0080] Combining published porcine mammary gland transcriptome data with candidate genes identified by GWAS, we further validated key candidate genes associated with the lactation phenotype. Joint analysis with reported porcine mammary gland transcriptome data: 19 of the 30 candidate genes identified by the GWAS analysis of the present invention were present in the transcriptome data, including: ASL, KCTD7, RABGEF1, SBDS, TMEM248, and TPCN2. Among them, the ASL, KCTD7, and TMEM248 genes showed differential expression in pairwise comparisons between the 14th day before parturition and the first day after lactation. The KCTD7 gene was downregulated on the first day after lactation, while ASL and TMEM248 were upregulated on the first day after lactation. These three genes are priority candidate genes affecting mammary gland development.

[0081] Among them, the porcine mammary gland transcriptome data (GSE101983) was downloaded from the GEO database of NCBI, and the differentially expressed genes in the data were compared between pairs on days 14, 10, 6, and 2 before farrowing and on day 1 after farrowing, which were downloaded from the reference PMC5934875.

[0082] The present invention has been described in detail above. For those skilled in the art, without departing from the purpose and scope of the present invention, and without the need to carry out unnecessary experimental conditions, the present invention can be implemented in a wide range under equivalent parameters, concentrations and conditions. Although the present invention provides specific embodiments, it should be understood that further improvements can be made to the present invention. In short, according to the principles of the present invention, this application is intended to include any changes, uses or improvements to the present invention, including changes that depart from the disclosed scope in this application and are made using conventional techniques known in the art.

Claims

1. A device for evaluating sow lactation capacity, comprising the following modules: A1. Data acquisition module: used to obtain relevant trait data of the sow to be tested and each sow in its group, including litter weight and piglet number at 21 days of age; A2. Data correction module: used to correct the 21-day weaning litter weight of sows; based on the number of piglets as a covariate, the 21-day weaning litter weight of each sow in the group is corrected. The correction formula is the following formula IV and formula V, and the 21-day weaning litter weight of each sow after covariate correction is obtained. The 21-day weaning litter weight of the i-th sow after covariate correction is recorded as y i ′: in, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, is the litter weight of the i-th sow at 21 days of age, b is the fixed effect vector of piglet number; X is the correlation matrix of the fixed effect vector; u is the additive genetic effect vector; Z is the correlation matrix of the random effect vector; e is the random residual; A3. Sow lactation ability evaluation module: used to calculate the phenotypic value of sow lactation ability; According to formula VI, the phenotypic value y of the lactation ability trait of the i-th sow to be tested is calculated. i ; Among them, y i is the phenotypic value of the lactation trait of the i-th sow, is the minimum litter weight at 21 days of age in the group, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, L y′ is the minimum value of the 21-day-old weaned litter weight in the population after correction for covariates, is the difference between the maximum and minimum litter weights at 21 days of age in the group, R y′ It is the difference between the maximum and minimum litter weight at 21 days of age after correction for covariates in the population.

2. The device according to claim 1, characterized in that: Correction of litter weight at 21 days of age for each sow in the group based on piglet size as a covariate was performed using a mixed linear model.

3. Methods for assessing sow lactation capacity, including: Detect the litter weight and piglet number of the sow to be tested and each sow in its group at 21 days of age, and obtain the lactation capacity of the sow to be tested based on the litter weight and piglet number of each sow at 21 days of age; The method calculates the lactation trait phenotype value y of the i-th sow to be tested according to formula VI. i ; Among them, y i is the phenotypic value of the lactation trait of the i-th sow, is the minimum litter weight at 21 days of age in the group, y i ′ is the litter weight of the i-th sow at 21 days of age after covariate correction, L y′ is the minimum value of the 21-day-old weaned litter weight in the population after correction for covariates, is the difference between the maximum and minimum litter weights at 21 days of age in the group, R y′ The difference between the maximum and minimum litter weights at 21 days of age after correction for covariates in the population; Among them, y i The 21-day-old weaning litter weight of each sow in the group was corrected based on the number of piglets as a covariate. The correction formulas are as follows: Formula IV and Formula V. The 21-day-old weaning litter weight of each sow after covariate correction is obtained. The 21-day-old weaning litter weight of the i-th sow after covariate correction is recorded as y i ′: in, is the litter weight of the i-th sow at 21 days of age, b is the fixed effect vector of piglet size, X is the correlation matrix of the fixed effect vector, u is the additive genetic effect vector, Z is the correlation matrix of the random effect vector, and e is the random residual.

4. The method according to claim 3, wherein: Correction of litter weight at 21 days of age for each sow in the group based on piglet size as a covariate was performed using a mixed linear model.

5. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to claim 3 or 4 are implemented.

6. A computer program product comprising a computer program / instructions, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to claim 3 or 4 are implemented.

7. Use of the device according to claim 1 or 2, or the method according to claim 3 or 4, or the computer-readable storage medium according to claim 5, or the computer program product according to claim 6 in screening genes or mutation sites related to sow lactation ability.

8. Use of the device according to claim 1 or 2, or the computer-readable storage medium according to claim 5, or the computer program product according to claim 6 in preparing a product for screening genes or mutation sites related to sow lactation ability.

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