CN109182505A - Mastadenitis of cow key SNPs site rs75762330 and 2b-RAD Genotyping and analysis method - Google Patents

Mastadenitis of cow key SNPs site rs75762330 and 2b-RAD Genotyping and analysis method Download PDF

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CN109182505A
CN109182505A CN201811146220.XA CN201811146220A CN109182505A CN 109182505 A CN109182505 A CN 109182505A CN 201811146220 A CN201811146220 A CN 201811146220A CN 109182505 A CN109182505 A CN 109182505A
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CN109182505B (en
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蔡亚非
杨帆
李君�
陈芳慧
江孝俊
袁露
马腾月
吕成龙
李莲
李惠侠
王根林
韩兆玉
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Nanjing Agricultural University
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    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/156Polymorphic or mutational markers

Abstract

The present invention relates to mastadenitis of cow key SNPs site rs75762330 and 2b-RAD Genotyping and analysis method, include the following steps: to build library sequencing;Bioinformatic analysis: data filtering, cleavage sequence extraction, comparing, SNP parting, whole-genome association.Whole-genome association (GWAS) is carried out to milk cow clinical mastitis phenotypic character using BayesA model and Logistic regression model.Compared with the existing technology, the invention has the benefit that relative to RADseq, 2b-RAD sequencing technologies have the advantages that the following: 1, endonuclease bamhi length is uniform, does not need subsequent screening;2, endonuclease bamhi does not need addition Y-shaped connector;3, step is simple;4, each sample sequencing cost is low;5, sequencing is time-consuming short.The present invention also constructs two kinds of whole-genome association models (BayesA and Logistics);3, it screens the only one China holstein cow mazoitis site key SNPs and corresponds to gene (PTK2B).

Description

Mastadenitis of cow key SNPs site rs75762330 and 2b-RAD Genotyping and point Analysis method
Technical field
The present invention relates to a kind of site mastadenitis of cow key SNPs rs75762330 and 2b-RAD Genotyping and analyses Method.
Background technique
Restriction enzyme site association DNA sequencing (RADseq) technology is to carry out enzyme to genome using restriction enzyme It cuts, generates a certain size DNA fragmentation, then the RAD label generated after digestion is carried out by building sequencing library high-throughput Sequencing.In past ten years, RADseq is considered as one of most important scientific breakthrough, in full-length genome by it is single, Simple and cost-effective method can once detect the single nucleotide polymorphism in thousands of a genomes (single nucleotide polymorphism, SNP), to push the research of genomics.With other sequencing technologies phases Compare, which has that flux is high, accuracy is good, experimental period is short, cost performance is high and not by whether there is or not reference genome sequences The advantages that limitation.It has been successfully applied to population population genetic variations and phylogenetic analysis, animals and plants Important Economic at present The researchs necks such as the quantitative trait locus (QTL) of shape positions and auxiliary genetic breeding, the building of genetic map and SNP marker detect Domain.
RADseq techniqueflow includes: the digestion (a kind of restriction endonuclease enzyme) of genomic DNA, building library (aptamers connection, The screening of clip size, the modification of segment end, Y type adapter, PCR amplification are added in end), upper machine sequencing is (mainly Illumina GAII or HiSeq microarray dataset), bioinformatic analysis (common analysis software: Stacks, pyRAD and UNEAK Deng).Its specific flow chart such as Fig. 1.
The shortcomings that prior art: 1, the length of endonuclease bamhi is not of uniform size, needs to screen;2, endonuclease bamhi end needs two The different connector of secondary addition;3, endonuclease bamhi needs to add the special tail portion A- and Y-shaped connector;4, step is comparatively laborious, skill Art requires high and time-consuming;5, each sample sequencing is costly.
Summary of the invention
In order to overcome drawbacks described above, it is uniform that the present invention provides a kind of endonuclease DNA fragmentation length, exempts subsequent sieve It selects, need repeatedly to add connector, step and simply shorten the sequencing time;Reduce the 2b-RAD gene of the sequencing cost of each sample Parting and analysis method.
The present invention also provides a site mastadenitis of cow key SNPs, described crucial the site SNPs rs75762330 Sub-district, SNPs C > T are included in gene PTK2B.It is related to chromosome AC_000165.1.
The 2b-RAD Genotyping and analysis method in the site mastadenitis of cow key SNPs above-mentioned are filtered out, including as follows Step:
1) build library sequencing: digestion: >=200ng genomic DNA carries out digestion using IIB type restriction enzyme;Adjunction head: Digestion products are separately added into 5 groups of different connectors, the connection of T4 deoxynucleotide ligase;
Amplification;Series connection;Mixed library;Sequencing: machine is sequenced in the DNA library of quality inspection qualification;
2) bioinformatic analysis:
(1) Quality Control data filtering: is carried out to Clean Reads;
(2) cleavage sequence extracts: extracting the sequence containing digestion recognition site, is used for subsequent analysis;
(3) comparing: cleavage sequence is compared onto the reference sequences built using SOAP software;
(4) SNP parting: according to comparison result, parting is carried out using maximum likelihood method (ML);
(5) it analyzes: building chadogram, principal component analysis, population genetic variations analysis or whole-genome association.
SNP marker point is carried out using maximum likelihood method (ML) after comparing cleavage sequence to reference sequences using SOAP software Type, using following 1 after the completion of parting work) -5) step further filters genotyping result:
1) rejecting can be with the site of parting lower than 80% individual in all samples;
2) site that MAF is lower than 0.01 is rejected;
3) site mononucleotide polymorphic (SNP) containing a kind or 4 kinds base type is rejected;
4) site of more than one SNP in label is rejected;
5) site for being lower than 2 genotype in label is rejected.
Full-length genome is carried out to milk cow clinical mastitis phenotypic character using BayesA model and Logistic regression model Association analysis (GWAS);
Before carrying out whole-genome association (GWAS), building is based on the linear of mastadenitis of cow phenotypic character first Regression model equation,Wherein, yiIndicate the phenotypic characteristic vector of i-th of body;M is total SNPs number; μ is the feature vector of total phenotypic character average value;αkIt is the additivity correlation effect vector of k-th of SNP;XikFor i-th body The genotype of k-th of SNP;E is the vector of residual error effect;K refers to the number of SNP site.
BayesA model assumption SNPs effect meets priori normal distribution, and " zero-mean " and " SNPs variance " is with σk 2It indicates (" zero-mean " and " SNPs variance " is equivalent, and only verbal description is different), wherein k=1,2 ..., M, k refer to the number of SNP site; SNPs effect variance is independent from each other, each variance to be independently distributed IID identical as inverse card side's priori normal distribution:Wherein v is the parameter of freedom degree, S2It is scale parameter, P indicates being independently distributed for each variance (IID) with inverse card side's priori normal distribution, χ-2For " inverse card side ";The prior distribution of the Critical Degree of each SNP effect meets t- Distribution: Wherein N refers to that " when probability is п, SNPs is zero effect It answers, or meeting normal distribution and probability distribution is (1- п),", P (αk│v,S2) it is expressed as the critical of each SNP effect The prior distribution of degree, αkIndicate the additivity correlation effect vector of k-th of SNP, αkPriori depend on each SNP variance, and The variance of each SNP has an inverse card side;When probability is п, SNPs is null effect, or meets normal distribution and probability point Cloth is (1- п),αk│п, Wherein,It represents all The common variance of non-zero SNPs effect, it has been divided in portion the prior distribution for meeting Chi-square Test:In model not The п value known is by its prior distribution (being between zero and one considered uniform) or п-consistent (0,1) prediction.
vaIt is designated as 4,It is calculated by additive variance:WithWherein, Pk It is expressed as the gene frequency of k-th of SNPs;For the difference of given label;By SNPs to additive genetic varianceIt carries out It explains or illustrates;For the prior distribution of Chi-square Test;PkIndicate the gene frequency of k-th of SNPs;K is total SNPs number.
Logistic regression analysis model: assuming that single nucleotide polymorphism has shadow to the clinical phenotypes character of mastadenitis of cow It rings, establishes logic (Logistic) regression model to predict a possibility that milk cow clinical mastitis occurs, building first is fitted Logistic regression equation,Wherein, wherein PjIt is in condition XjLower mazoitis The probability of clinical phenotypes, (1-Pj) it is in condition XjThe probability that lower clinical mastitis phenotype does not occur, j indicate j-th SNP Point, Xij=(X1j,X2j,X3j……Xmj) it is that (0,1 and 2), β j is the shadow of j-th of SNP to genotype of i-th of individual in the site j It rings, M is sample size, and μ is the feature vector of total phenotypic character average value;In logistic regression analysis model, Y=(μ+Σ βiXi) it is equations turned at another form:Wherein Y is expressed as the mazoitis phenotype of i-th of individual, and P is represented Clinical mastitis phenotype probability;XiFor the genotype of i-th of individual;β i is odds ratio OR;The equation expressed between P and variable Pass through equation transform: 95% confidence interval (CI)=exp (βi±1.96SE(βi)), what p1 was indicated is the probability that some SNP site of case group occurs, and what p0 was indicated is control The probability that group corresponding site occurs;SE(βi) indicate are as follows: βiStandard error.
The present invention obtains 1 site mastadenitis of cow key SNPs by two kinds of analysis models, such as table 1 and 2:
1 BayesA analysis model result of table
2 logistic regression analysis model result of table
Compared with the existing technology, the invention has the benefit that relative to RADseq, 2b-RAD sequencing technologies have following Some advantages: 1, endonuclease bamhi length is uniform, does not need subsequent screening;2, endonuclease bamhi does not need addition Y-shaped connector;3, it walks It is rapid simple;4, each sample sequencing cost is low;5, sequencing is time-consuming short.The present invention also constructs two kinds of whole-genome association models (BayesA and Logistics);3, the only one China holstein cow mazoitis site key SNPs and corresponding gene are screened (PTK2B)。
Detailed description of the invention
Fig. 1 is the RADseq sequencing technologies flow chart of the prior art;
Fig. 2 is that flow chart is sequenced in 2b-RAD of the invention;
Fig. 3 .PCR amplified fragments direct Sequencing sequence and NCBI reference sequences comparison chart, (A) and (B) are pcr amplified fragment Direct Sequencing Chromas figure;(C) 1 is NCBI reference sequences, and a and b are direct Sequencing sequence;Grey square frame is that mononucleotide is more State marker site.
Specific embodiment
The invention will be further described with attached drawing combined with specific embodiments below.
2b-RAD is a kind of based on IIB type restriction enzyme, the RAD methods of genotyping simplified, to study population Genome science of heredity provides a kind of strong technology and methods.We are research pair with china holstein cows in this research As constructing china holstein cows clinical mastitis and normal health control group cows, extracting the full genome of building cows milk cow Group carries out digestion to all milk cow sample complete genome DNAs using Bael endonuclease, obtains the endonuclease bamhi of standard, so After carry out machine sequencing and analyze, specifically building library sequencing process is (Fig. 2):
(1) digestion: >=200ng genomic DNA carries out digestion using IIB type restriction enzyme;
(2) adjunction head: digestion products are separately added into 5 groups of different connectors, T4 deoxynucleotide ligase (T4 DNA Ligase it) connects;
(3) expand: polymerase chain reaction (PCR) expands connection product;
(4) it connects: according to 5 groups of joint informations, five labels being connected in order;
(5) mix library (Pooling): connection product adds bar code (barcode) sequence, mixes library;
(6) be sequenced: machine is sequenced on the high quality library of quality inspection qualification.
Above-mentioned builds library sequencing process referring to Serial sequencing of isolength RAD tags Forcost-efficient genome-wide profiling of geneticand epigenetic variations, Author is Shi Wang et al., and on October 6th, 2016 is open online.
Bioinformatic analysis:
Is the present invention with Bos (https: //www.ncbi.nlm.nih.gov/genome/? term=Bos+Taurus) base Because a group conduct refers to genome, sequencing data is compared to reference sequences, using most using SOAP software (version 2.21) The parting in maximum-likelihood method (ML) progress site.Analysis process is as follows:
(1) Quality Control data filtering: is carried out to Clean Reads;
(2) cleavage sequence (Enzyme Reads) extracts: the sequence (Reads) containing digestion recognition site is extracted, we Referred to as Enzyme Reads is used for subsequent analysis;
(3) comparing: Enzyme Reads is compared onto the reference sequences built using SOAP software;
(4) SNP parting: according to comparison result, parting is carried out using maximum likelihood method (ML);
(5) content is analyzed: building chadogram, principal component analysis, population genetic variations analysis, whole-genome association Deng.
SNP mark is carried out using maximum likelihood method (ML) after comparing Enzyme Reads to reference sequences using SOAP software It scores type.RAD parting software package (RADtyping) used in process covers pre- from data comprising more than 10 software components Handle the overall process exported to final genotyping result.For guarantee subsequent analysis accuracy, parting work after the completion of can by with Lower index further filters genotyping result:
1) rejecting can be with the site of parting lower than 80% individual in all samples;
2) site that MAF is lower than 0.01 is rejected;
3) site mononucleotide polymorphic (SNP) containing a kind or 4 kinds base type is rejected;
4) site of more than one SNP in label is rejected;
5) site for being lower than 2 genotype in label is rejected;
All samples are obtained SNP marker 10058.
Statistical analysis model
This research carries out milk cow clinical mastitis phenotypic character using BayesA model and Logistic regression model complete Genome association analyzes (GWAS).
We construct the linear regression model (LRM) equation based on mastadenitis of cow phenotypic character first, Wherein, yiIndicate the phenotypic characteristic vector of i-th of body;M is total SNPs number;μ is the feature vector of total phenotypic character average value;αk It is the additivity correlation effect vector of k-th of SNP;XikFor the genotype (0,1 and 2) of k-th of SNP of i-th of body;E is residual error The vector of effect.
BayesA model assumption SNPs effect meets priori normal distribution, and " zero-mean " and " SNPs variance " is with σk 2It indicates, Wherein, k=1,2 ..., M;SNPs effect variance is independent from each other, and each variance is independently distributed (IID) and inverse elder generation of card side Test that normal distribution is identical, wherein v is the parameter of freedom degree;S2It is scale parameter:Each SNP effect The prior distribution for the Critical Degree answered meets t- distribution:αkPriori Depending on the variance of each SNP, and each variance has an inverse card side,.When probability is п, SNPs is null effect, or is met Normal distribution and probability distribution are (1- п),αk│п, Wherein,The common variance of all non-zero SNPs effects is represented, it has been divided in portion the prior distribution for meeting Chi-square Test:From in prior distribution prediction model unknown п value (being between zero and one considered uniform) or п-it is consistent (0, 1) it predicts.
vaIt is designated as 4,It is calculated by additive variance:WithWherein, Pk It is expressed as the gene frequency of k-th of SNPs;For the difference of given label;By SNPs to additive genetic varianceIt carries out It explains or illustrates.
Logistic regression analysis model, it is assumed that single nucleotide polymorphism has an impact to the clinical phenotypes character of mastadenitis of cow, We establish logic (Logistic) regression model to predict a possibility that milk cow clinical mastitis occurs, and establish one The Logistic regression equation of fitting,Wherein, wherein PjIt is in condition XjUnder The probability of mazoitis clinical phenotypes, (1-Pj) it is the probability that clinical mastitis phenotype does not occur;Xij=(X1j,X2j,X3j…… Xmj) be i-th of individual the site j genotype (0,1 and 2), be expressed as 2, AT for example, AA is expressed as 0, TT and be expressed as 1;It can also To be in this way: CC is expressed as 0, GG and is expressed as 2, CG being expressed as 1;It can also be expressed as 0, CC with AA and be expressed as 2, AC being expressed as 1 ...; β j is the influence of j-th of SNP;M is sample size, and μ is the feature vector of total phenotypic character average value.In logistic regression analysis mould In type, Y=(μ+Σ βiXi) equation can be converted to another form: Wherein Y is expressed as i-th of individual Mazoitis phenotype, P represents clinical mastitis phenotype probability;XiFor the genotype of i-th of individual;β i is odds ratio (OR);P and The equation expressed between variable can pass through equation transform:
95% confidence interval (CI) =exp (βi±1.96SE(βi))。
This research obtains 1 site mastadenitis of cow key SNPs by two kinds of analysis models, such as table 1 and 2:
1 BayesA analysis model result of table
2 logistic regression analysis model result of table
Note: * indicates the p- value calculated by card side (< 0.05);* is t- statistics p value (< 0.05) of Logic Regression Models; CHISQ is the chi-square value under Chi-square Test.STAT is the t- statistics coefficient under Logistic regression model.OR: odds ratio.L95: The lower limit of the likelihood ratio 95% of 95% confidence interval.The upper limit of U95:95% probability confidence interval 95%.
For the correlation for verifying SNP marker and mastadenitis of cow, using the method for case-control study, to case group and right Analysis is compared according to the crucial SNP site exposure of group.Through statistical test, if there are significant sex differernce between two groups, It may be considered and mastitis for milk cows character associated SNP positions.The interference for excluding extraneous matching factor in the comparison, only accounts for The incidence relation of SNPs and mazoitis.We using matched design and case control unequal (case/Control=1/h) come Determine the quantity of verifying sample.
OR=ad/bc
N is required clinical mastitis quantity in verifying group, and N is verifying group milk cow total quantity.P0 is normal control group Body SNP site mutation exposure, P1 be clinical mastitis group in SNP site mutation exposure, OR be odds ratio (it is expected that The strength of association of the SNP site), α is the probability (the inspection significance that expectation reaches) of hypothesis testing I class mistake, and β is The probability of hypothesis testing class ii mistake, (1- β) are the inspection power of a test that expectation reaches, and OR 95%CI is 95% confidence interval, χ2For crucial SNP site Chi-square Test.A is SNP site mutated individual quantity in clinical mastitis group, and b is normal control group SNP site mutated individual quantity in body, c are the not mutated individual amount of SNP site in clinical mastitis group, and d is normal control The not mutated individual amount of SNP site, is shown in Table 3 in group.
rs75762330
SNP site base Clinical mastitis Normal control It is total
T 36(a) 89(b) 162
C 37(c) 221(d) 221
It is total 73 310 383
The relevance verification of table 3SNP label and mastadenitis of cow
Freedom degree Df=1, OR=ad/bc=2.416OR value > 1 illustrates the danger of china holstein cows clinical mastitis It spends between due to the C > T of the site rs75762330, is i.e. " just " is associated between T and mazoitis;Card side χ2=10.279 >=7.879, P < 0.005, conclusion are refusal null hypothesis, i.e. SNP site rs75762330 difference has significance,statistical.
Example of the present invention is the description of the invention and cannot limit the present invention, with the comparable meaning of the present invention Any change and adjustment in range, are all considered as within the scope of the invention.

Claims (8)

1. a site mastadenitis of cow key SNPs, which is characterized in that the crucial site the SNPs rs75762330 is located at Gene PTK2B includes sub-district, SNPs C > T.
2. the 2b-RAD Genotyping and analysis method in the site mastadenitis of cow key SNPs described in claim 1 are filtered out, It is characterized by comprising the following steps:
1) library sequencing is built;
2) bioinformatic analysis:
(1) Quality Control data filtering: is carried out to Clean Reads;
(2) cleavage sequence extracts: extracting the sequence containing digestion recognition site, is used for subsequent analysis;
(3) comparing: cleavage sequence is compared onto the reference sequences built using SOAP software;
(4) SNP parting: according to comparison result, parting is carried out using maximum likelihood method (ML);
(5) it analyzes: building chadogram, principal component analysis, population genetic variations analysis or whole-genome association.
3. 2b-RAD Genotyping according to claim 2 and analysis method, which is characterized in that utilize SOAP software by enzyme It cuts and carries out SNP marker parting using maximum likelihood method (ML) after sequence alignment to reference sequences, under being used after the completion of parting work 1 stated) -5) step further filters genotyping result:
1) rejecting can be with the site of parting lower than 80% individual in all samples;
2) site that MAF is lower than 0.01 is rejected;
3) site mononucleotide polymorphic (SNP) containing a kind or 4 kinds base type is rejected;
4) site of more than one SNP in label is rejected;
5) site for being lower than 2 genotype in label is rejected.
4. 2b-RAD Genotyping according to claim 2 and analysis method, which is characterized in that using BayesA model and Logistic regression model carries out whole-genome association (GWAS) to milk cow clinical mastitis phenotypic character;
Before carrying out whole-genome association (GWAS), linear regression of the building based on mastadenitis of cow phenotypic character first Model equation,Wherein, yiIndicate the phenotypic characteristic vector of i-th of body;M is total SNPs number;μ is The feature vector of total phenotypic character average value;αkIt is the additivity correlation effect vector of k-th of SNP;XikFor the kth of i-th of body The genotype of a SNP;E is the vector of residual error effect;K refers to the number of SNP site.
5. 2b-RAD Genotyping according to claim 4 and analysis method, which is characterized in that
BayesA model assumption SNPs effect meets priori normal distribution, and " zero-mean " and " SNPs variance " is with σk 2It indicates, wherein k =1,2 ..., M, k refer to the number of SNP site;SNPs effect variance is independent from each other, and each variance is independently distributed IID and inverse The priori normal distribution of card side is identical:Wherein v is the parameter of freedom degree, S2It is scale parameter, P is indicated Each variance is independently distributed IID and inverse card side's priori normal distribution, χ-2For " inverse card side ";The elder generation of the Critical Degree of each SNP effect It tests distribution and meets t- distribution: P (αk│v,S2)=Wherein P (αk│v,S2) be expressed as The prior distribution of the Critical Degree of each SNP effect, αkIndicate the additivity correlation effect vector of k-th of SNP, αkPriori depend on The variance of each SNP, and the variance of each SNP has an inverse card side;When probability is п, SNPs is null effect, or is met just State distribution and probability distribution are (1- п),αk│п,Its In,The common variance of all non-zero SNPs effects is represented, it has been divided in portion the prior distribution for meeting Chi-square Test:vaIt is designated as 4,It is calculated by additive variance:WithWherein, PkIt is expressed as the gene frequency of k-th of SNPs;For the difference of given label;By SNPs to additive genetic varianceInto Row is explained or is illustrated;For the prior distribution of Chi-square Test;PkIndicate the gene frequency of k-th of SNPs;K is total SNPs Number.
6. 2b-RAD Genotyping according to claim 4 and analysis method, which is characterized in that
Logistic regression analysis model: assuming that single nucleotide polymorphism has an impact to the clinical phenotypes character of mastadenitis of cow, Logic (Logistic) regression model is established to predict a possibility that milk cow clinical mastitis occurs, building first is fitted Logistic regression equation,Wherein, wherein PjIt is in condition XjLower mazoitis The probability of clinical phenotypes, (1-Pj) it is in condition XjThe probability that lower clinical mastitis phenotype does not occur, j indicate j-th SNP Point, Xij=(X1j,X2j,X3j……Xmj) it is i-th of individual in the genotype in the site j, β j is the influence of j-th of SNP, and M is sample This quantity, μ are the feature vector of total phenotypic character average value;In logistic regression analysis model, Y=(μ+Σ βiXi) equation turn It is melted into another form:Wherein Y is expressed as the mazoitis phenotype of i-th of individual, and P represents clinical mastitis Phenotype probability;XiFor the genotype of i-th of individual;β i is odds ratio OR;The equation expressed between P and variable is become by equation It changes:95% confidence interval (CI)= exp(βi±1.96SE(βi)), what p1 was indicated is the probability that some SNP site of case group occurs, and what p0 was indicated is that control group is corresponding The probability that site occurs;CI refers to 95% confidence interval;SE(βi) indicate are as follows: βiStandard error.
7. 2b-RAD Genotyping according to claim 5 and analysis method, which is characterized in that BayesA analysis model knot Fruit is
8. 2b-RAD Genotyping according to claim 6 and analysis method, which is characterized in that
Logistic regression analysis model result is
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