CN110195116B - Boar sperm motility related molecular genetic marker and application and acquisition method thereof - Google Patents
Boar sperm motility related molecular genetic marker and application and acquisition method thereof Download PDFInfo
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Abstract
The invention relates to the technical field of molecular markers, in particular to a molecular genetic marker related to boar sperm motility and an application and acquisition method thereof, wherein the molecular genetic marker related to boar sperm motility is positioned at the position of 8482542bp of No. 17 chromosome of a pig and is a C > T mutation; the molecular markers of the present application were obtained by one-step genome-wide association analysis (wssGWAS); the method is simple, efficient and rapid.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of molecular markers, in particular to a molecular genetic marker related to boar sperm motility and an application and acquisition method thereof.
[ background of the invention ]
With the development of the modern pig raising industry, the pig raising scale is larger and larger, and the intensification and standardization degree is also continuously improved. The domestic pig breeding reaches the first world, the slaughtered fat pigs account for 50.6 percent of the world, and the sows are stored for 4423 thousands of pigs. Pork is also the food with the largest consumption amount of meat in China, so the quality and the yield of the pork are directly related to the living standard of the nation, and the economic benefit of farmers is influenced. Two key factors for improving the productivity benefit are semen quality and the fertility of the sow.
The breeding efficiency has many influencing factors, and the semen quality of boars is one of the important factors. The sperm density, the sperm motility rate, the sperm motility and the sperm aberration rate of the boar semen determine whether the sperm can be smoothly combined with the ovum to form a fertilized egg, and the fertilized egg is the key of the farrowing performance of the sow, so the semen quality of the boar is also important to the reproductive performance of the sow, and the research proves that the sperm motility is a key factor influencing the reproductive performance of the sow.
The sperm motility refers to the percentage of the number of linearly-advanced sperm in the total number of sperm at 37 ℃, and the sperm motility detection method is an estimation method, so the method has strong subjectivity, and the detection result is not high in accuracy and precision. The motility is a unique characteristic of the sperms, and not only can visually reflect the sperm quality, but also can indirectly reflect the fertilization capability of the sperms. China has a large difference with the average litter size of sows in developed countries, which is in great relation with quality detection and screening work before fertilization. More accurate detection means are found, and the effect of artificial insemination in pig production is further improved, so that the improvement of production performance and efficiency is a consistent pursuit of pig workers.
Based on high-density SNP data covering the whole genome and the character phenotype record of a large population, candidate genes for controlling characters can be accurately positioned through a whole genome association analysis technology (GWAS). Although the technology still has some defects, the technology is widely applied to the mining of candidate genes of human complex diseases and the positioning of key genes of important economic traits of livestock and poultry, classical GWAS generally carries out single-marker regression analysis on all markers one by one on the basis of software such as Plink and the like, and then a significant threshold is set to screen significant sites. Such methods often face problems of high computational intensity, overestimation marking effect, unreasonable significance threshold setting, and the like. In order to further improve the efficiency of GWAS, it is necessary to improve the GWAS method to improve the accuracy and efficiency of screening molecular markers.
[ summary of the invention ]
In view of the above, there is a need to provide a molecular genetic marker related to boar sperm motility, which is located on the pig chromosome 17 8482542bp position; c > T mutation, and a primer for amplifying the molecular marker and a probe for identifying the molecular marker can be designed according to the mutation; the method is further applied to screening boars with high sperm activity, so that the boars are applied to artificial insemination of the boars; the application utilizes a one-step whole genome correlation analysis method for analysis, and can effectively improve the accuracy and efficiency of screening molecular markers.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a molecular genetic marker related to boar sperm motility is located at 8482542 nucleic acid site of chromosome 17 (international pig genome version 10.2 reference sequence) of a pig, wherein the base of the site is C or T and corresponds to the 101 st nucleic acid site of a nucleic acid sequence table SEQ ID NO. 1. Applicants have named this genetic marker locus: WU _10.2 \ u 17_9356778.
The invention also provides a primer for amplifying the molecular genetic marker or a probe for identifying the molecular genetic marker.
The invention also provides a kit containing the primer or the probe.
The invention also provides application of the molecular genetic marker in detecting the sperm motility of boars, assisting artificial insemination of the boars, assisting breeding and/or breeding boars with high sperm motility.
The invention also provides a method for breeding or assisting in breeding the boar with high sperm motility, which comprises the following steps: extracting the total DNA of the boar, detecting the 8482542 deoxyribonucleotide of the 17 th chromosome of the boar, detecting the 8482542 nucleotide sequence as C or T or C and T, determining the genotype of the to-be-detected boar as CC type, TT type or CT type, and selecting the boar with CC type gene for further seed selection and/or breeding.
Further, the CC genotype is a homozygote of the 8482542-site deoxyribonucleotide of the 17 th chromosome of the pig which is C; the TT genotype is the homozygote of the 8482542-th deoxyribonucleotide of the 17 th chromosome which is T; the CT genotype is a heterozygote of the 8482542 deoxyribonucleotide of the pig chromosome 17 and a C and a T.
The invention also provides a method for obtaining the molecular genetic marker related to the sperm motility of boars, which comprises the following steps: collecting ear tissue samples and/or blood of boars as samples, extracting total DNA, and carrying out quality detection on the DNA to obtain SNP marker genotypes of the whole genome; carrying out quality control on the SNP markers on all autosomes to screen out the SNPs, and then carrying out whole genome association analysis on the screened SNPs to obtain molecular genetic markers, wherein the physical positions of the obtained SNP markers are not used for association analysis for the SNPs with unknown genome positions by adopting a gene comparison method, and the quality control standard is as follows: the individual detection rate is more than or equal to 90 percent; the SNP detection rate is more than or equal to 90 percent; the minimum allele frequency is more than or equal to 0.01; hadi temperatureP value of Berger's balance is greater than or equal to 10 6 。
Further, the whole genome association analysis method comprises the following steps:
in order to fully utilize all phenotype data and genotype data, the invention adopts a weighted single step genome-wide association analysis (wssGWAS) method to carry out genome-wide association analysis. The method comprises the steps of firstly estimating individual breeding values based on a mixed model equation set, and then converting the breeding values into the marker effect based on the equivalence relation between a breeding value model and a marker effect model. The whole genome association analysis model adopted by the invention is as follows:
y＝Xb+Za+Wp+Age+Intv+e
in the formula, y is a sperm motility observation value vector;
x, Z and W are design matrixes;
b is the fixed effect vector (global mean and year-Ji Xiaoying);
p is the individual permanent environmental effect, p-N (0,
) (ii) a I is a unit matrix of the image data,
is the permanent environmental effect variance;
age is a month Age covariate when the boars collect the semen;
intv is a covariate of boar semen collection interval;
e is the residual, e to N (0,
) (ii) a I is a unit matrix of the image data,
is the residual variance;
a is a breeding vector, a to N (0,
) (ii) a Wherein H is an integration pedigree and SNP markerThe matrix of the relationship,
is additive genetic variance; the inverse H matrix calculation formula is as follows:
in the formula, A is a genetic relationship matrix based on pedigrees;
A 22 is a block matrix corresponding to the individual with the genotype in A;
G ω ＝0.9G+0.1A 22 ，
a genetic relationship matrix based on genome-wide SNP markers, wherein Z is a genotype matrix corrected by small allele frequency (MAF); wherein 0-2p,1-2p and 2-2p respectively represent three genotypes of AA, AA and AA, and p is small allele frequency; d is a diagonal matrix which represents the weight of the SNP; p i The minor allele frequency of the ith marker; m is the number of marks.
Corresponding to the mixed model, estimating variance components by using an AI-REML (estimated transformed maximum likelihood) method, and obtaining a breeding value by solving a mixed model equation set. The label weight is obtained in an iterative manner, and the main steps are as follows:
step 1: initialization (t = 1), D (t) ＝I，G (t) ＝λZD (t) Z'，
Step 2: calculating an individual breeding value by ssGBLUP;
and 3, step 3: by the formula
Converting the individual breeding value into an SNP effect, wherein
A breeding value for a genotyped individual;
and 4, step 4: using a formula
Calculating the SNP weight for the next iteration;
and 5, step 5: using formulas
Standardizing the SNP weight to ensure that the variances are consistent;
and 6, step 6: using formula G (t+1) ＝λZD (t+1) Z' calculating a genetic relationship matrix for the next iteration;
and 7, step 7: let t = t +1 and start the next iteration from step 2.
The steps are iterated for three times, and finally the SNP marker effect is obtained. And taking the marking effect output by the third iteration as a final result. The calculation process is mainly realized by programming and calling BLUPF90 software on an R statistical analysis platform, wherein an AIREMLF90 program is used for estimating variance components, a BLUPF90 program is used for calculating breeding values, and postGSf90 is used for calculating marking effects.
And (4) taking the absolute values of the effect values of all the markers to draw a Manhattan graph, and displaying and screening the SNP markers with large effects. And analyzing the difference of sperm motility of boars in different genotype groups by using variance analysis and multiple comparison (R statistical analysis platform) and WU _10.2 \/17 _/9356778 marker (8482542 nucleic acid site of No. 17 chromosome of the pig).
The invention has the following beneficial effects:
(1) The invention discloses a molecular marker WU _10.2_17_9356778 (8482542 nucleic acid locus of chromosome 17 of a pig) which influences sperm motility of boars, wherein sperm motility of boars with different genotypes is marked with extremely obvious difference; the identification result proves that the difference of the sperm motility of the WU _10.2_17 _9356778 (the 8482542 nucleic acid site of the No. 17 chromosome of a pig) marker genotype CC and TT boar individuals is 1.20 percent, so that the C allele is known to remarkably improve the sperm motility; through detecting WU _10.2_17 _9356778 (the 8482542 nucleic acid locus of the No. 17 chromosome of a pig) marker genotype assisted breeding boars, CC homozygous boars can be selected and left to enter boar stations, sperm motility is improved, and artificial insemination efficiency of the boars is effectively improved. Based on GBLUPf90 software, wssGWAS can be easily realized; the correlation between the SNP and the boar semen vitality characteristic reaches an extremely obvious level, and a new genetic resource is provided for the research of the boar semen vitality characteristic.
[ description of the drawings ]
FIG. 1 is a genome location and sperm motility genome-wide SNP effect profile for WU _10.2_17_9356778 marker.
[ detailed description ] embodiments
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
Example 1:
1. phenotypic-pedigree data acquisition
The basic research group of the application is Duroc boars, all from boar stations of Guangxi Xiupo Bingquan, and the complete pedigree comprises 12 generations of 5284 boars, wherein the sperm motility character phenotype data of 2693 boars are recorded between 2015 and 2018; sperm motility was obtained by analysis of fresh semen using the UltiMateTM CASA (Hamilton Thorne inc., beverly, MA, USA) system. A total of 143114 observations of the semen trait (53 data per boar on average) were obtained for phenotype-genotype correlation analysis.
2. Genotyping and quality control
Ear tissue samples or blood samples of 1733 boars were collected, total DNA was extracted, and genotyping was performed using GGP 50k SNP (GeneSeek, US) chips to obtain 50705 SNP markers covering the whole genome. The physical location of all SNP markers was updated using the NCBI genome alignment program according to the latest version of the pig reference genome (sscrofa 11.1). SNPs with unknown genomic positions were not used for association analysis. Quality control was performed using Plink software for SNP markers on all autosomes, with the criteria: the individual detection rate is more than or equal to 90 percent; the SNP detection rate is more than or equal to 90 percent; the minimum allele frequency is more than or equal to 0.01; the p value of Hardy Winberg balance is more than or equal to 10 6 Filling by adopting Beagle software (version 4.1); based on the above quality control criteria, 1623 boars and 28289 SNP markers remained for association analysis, with 1231 boars having both sperm motility phenotype data and genotype data.
(3) Statistical model
In order to fully utilize all phenotype data and genotype data, the invention adopts a weighted one-step genome-wide association analysis method to carry out genome-wide association analysis. The method comprises the steps of firstly estimating an individual breeding value based on a mixed model equation set, and then converting the breeding value into a marker effect based on the equivalence relation between a breeding value model and a marker effect model. The whole genome association analysis model adopted by the invention is as follows:
y＝Xb+Za+Wp+Age+Intv+e
in the formula, y is a sperm motility observation value vector;
x, Z and W are design matrixes;
b is the fixed effect vector (global mean and year-Ji Xiaoying);
p is the individual permanent environmental effect, p-N (0,
) (ii) a I is a unit matrix of the image data,
is the permanent environmental effect variance;
age is a month Age covariate when the boars collect the semen;
intv is a boar semen collection interval covariate;
e is the residual, e to N (0,
) (ii) a I is a unit matrix of the image data,
is the residual variance;
a is a breeding vector, a to N (0,
) (ii) a Wherein H is an incidence relation matrix of the integration pedigree and the SNP marker,
is additive genetic variance; the inverse H matrix calculation formula is as follows:
in the formula, A is a genetic relationship matrix based on a pedigree;
A 22 is a block matrix corresponding to the individual with the genotype in A;
G ω ＝0.9G+0.1A 22 ，
a genetic relationship matrix based on genome-wide SNP markers, wherein Z is a genotype matrix corrected by small allele frequency (MAF); wherein 0-2p,1-2p and 2-2p respectively represent three genotypes of AA, AA and AA, and p is small allele frequency; d is a diagonal matrix which represents the weight of the SNP; p i The minor allele frequency of the ith marker; m is the number of marks.
And (3) corresponding to the mixed model, estimating a variance component by adopting an AI-REML (acquired information reconstructed maximum likelihood) method, and solving a mixed model equation set to obtain a breeding value. The marking weight is obtained in an iterative mode, and the main steps are as follows:
step 1: initialization (t = 1), D (t) ＝I，G (t) ＝λZD (t) Z'，
Step 2: calculating an individual breeding value by ssGBLUP;
and 3, step 3: by the formula
Converting the individual breeding value into an SNP effect, wherein
A breeding value for a genotyped individual;
and 4, step 4: using formulas
Calculating the SNP weight for the next iteration;
and 5, step 5: using formulas
Standardizing SNP weight to ensure consistent variance;
and 6, step 6: using formula G (t+1) ＝λZD (t+1) Z' calculating a genetic relationship matrix for the next iteration;
and 7, step 7: let t = t +1 and start the next iteration from step 2.
The steps are iterated for three times, and finally the SNP marker effect is obtained. And taking the marking effect output by the third iteration as a final result. The calculation process is mainly realized by programming and calling BLUPF90 software on an R statistical analysis platform, wherein an AIREMLF90 program is used for estimating variance components, a BLUPF90 program is used for calculating breeding values, and postGSf90 is used for calculating marking effects.
(4) Marker screening
For all the marked effect values, taking the absolute values of the effect values to draw a Manhattan graph, wherein the graph is shown in FIG. 1; and displaying and screening SNP markers with large effects. And analyzing the difference of sperm motility of boars with different genotype groups marked by WU _10.2_17_9356778 (8482542 nucleic acid site of chromosome 17 of pig) by using variance analysis and multiple comparison (R statistical analysis platform), which are shown in Table 1:
TABLE 1
As can be seen from the above table, the sperm motility of the boar with CC homozygous genotype is higher than that of the boar with CT heterozygous genotype; is higher than the sperm motility of TT homozygous genotype boars.
Example 2:
according to the gene results obtained by the screening, the molecular genetic marker related to the sperm motility of the boar is shown, and is positioned at the 8482542 nucleic acid site of the 17 th chromosome of the pig, and the position is a C > T mutation (Sscofa 10.2) and corresponds to the 101 th nucleic acid site of the nucleic acid sequence table SEQ ID NO. 1.
Example 3:
the skilled person can easily design primers for amplifying the molecular markers or probes for identifying the molecular markers according to the present invention, and then use the primers or probes for detecting the molecular markers, for example, the molecular markers are obtained by PCR amplification, and the corresponding sequences are obtained by clone sequencing, or Bsm-RFLP polymorphism is used for detection. Thus, the invention also includes primers for amplifying the molecular genetic marker or probes for identifying the molecular genetic marker, and kits containing the primers or probes.
Example 4:
the molecular genetic marker can be applied to assist in detecting boar sperm activity genotype pigs, and the specific method comprises the following steps: extracting the genome DNA of the boar, designing a primer to amplify a gene fragment shown as a sequence table SEQ ID NO.1, and detecting that the 101 th site gene is C or T; judging whether the pig to be detected is CC type, CT type or TT type according to the locus genotype; then, based on the known verification results, it follows: the sperm motility of the boar with the CC homozygous genotype is higher than that of the boar with the CT heterozygous genotype; is higher than the sperm motility of TT homozygous genotype boars.
Example 5:
the molecular genetic marker can be applied to assist artificial insemination work of boars, and the specific method comprises the following steps: extracting the genome DNA of the boar, designing a primer to amplify a gene fragment shown as a sequence table SEQ ID NO.1, and detecting that the 101 th site gene is C or T; judging whether the pig to be detected is CC type, CT type or TT type according to the locus genotype; and selecting a CC type boar to enter a boar station for artificial insemination.
Example 6:
the molecular genetic marker can be applied to assist breeding or assisted breeding work of boars, and the specific method comprises the following steps: extracting the genome DNA of the boar, designing a primer to amplify a gene segment shown as a sequence table SEQ ID NO.1, and detecting that the 101 th site gene is C or T; judging whether the pig to be detected is CC type, CT type or TT type according to the locus genotype; selecting a CC type, CT type or TT type boar to carry out seed reservation or hybridization according to breeding requirements; wherein, the sperm motility of the boar with CC homozygous genotype is higher than that of the boar with CT heterozygous genotype; is higher than the sperm motility of TT homozygous genotype boars.
In conclusion, the method can simply, efficiently and accurately obtain the molecular genetic marker related to the sperm motility of the boars, and can design a primer for amplifying the molecular marker and a probe for identifying the molecular marker according to the mutation; the boars with high sperm motility are quickly screened out, so that the boars with high sperm motility are applied to the detection of the boars with sperm motility, artificial insemination, breeding of the boars with sperm motility or auxiliary breeding work of the boars; the method has the advantages that the boars with high-sperm activity are quickly screened out, and the one-step whole-genome association analysis method is utilized for analysis, so that the accuracy and efficiency of screening the molecular markers can be effectively improved.
The above examples are merely illustrative of several embodiments of the present invention, and the description thereof is more specific and detailed, but not to be construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.
Sequence listing
<110> Guangxi Yangxi agriculture and animal husbandry Limited liability company
<120> molecular genetic marker related to boar sperm motility and application and acquisition method thereof
<160> 1
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<211> 201
<212> DNA
<213> genus swine (Sus scrofa)
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cgcaaaccat caatgaaagg ttagttcaca ttaaggcaat attactctgt gtgactgtcc 60
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tatactttat ttaatgcaac atatatttca gcatgtaatc aacatcaaaa gtgttaatga 180
gaactcttac gtttattcac a 201
Claims (1)
1. A method for breeding or assisting in breeding a boar with high sperm motility is characterized in that the method comprises the following steps: extracting total DNA of the boar, detecting 8482542 deoxyribonucleotide of 17 th chromosome of the boar, detecting that the sequence of 8482542 ribonucleotide is C or T, determining that the genotype of the boar to be detected is CC genotype, TT genotype or CT genotype, and selecting the boar with the CC genotype to carry out next step of seed selection and/or breeding;
the CC genotype is a homozygote of the 8482542 deoxyribonucleotide of the pig chromosome 17 as C; the TT genotype is the homozygote of the 8482542 deoxyribonucleotide of the 17 th chromosome which is T; the CT genotype is a heterozygote of the 8482542 deoxyribonucleotide of the pig chromosome 17 and the C and the T;
the boar is a Duroc boar;
the pig reference genome is Sscrofa11.1;
the methods are useful for the diagnosis and treatment of non-diseases.
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