Low-density dairy cow genome-wide 30K SNP chip and its application

Abstract

The present invention provides a low-density dairy cow whole genome 30K SNP chip, which contains reagents for detecting 30326 SNP sites, and the SNP sites come from: the first category, the SNP sites significantly related to the important economic traits of dairy cows that were excavated and identified by the inventor team in the early stage of research, including 3,399 SNP sites; the second category, the main genetic defect gene sites and parentage identification gene sites of dairy cows, including 226 SNP sites; the third category, based on my country's large-scale dairy cow population, according to the detection rate, gene frequency, position uniqueness, genotype filling principle and distribution on the genome, the SNP sites selected from the existing commercial dairy cow genome chip include 26,701 SNP sites. The chip of the present invention can be used for whole genome association analysis, whole genome selection breeding, parentage identification and identification of common cattle genetic defects in Chinese Holstein cattle.

Description

Technical Field

[0001] The present invention relates to the field of molecular biology and biochips. Specifically, the present application provides a low-density dairy cow whole genome 30K SNP chip and application thereof. Background Art

[0002] SNP (single nucleotide polymorphism) analysis is currently an important analytical method for mining and identifying key genes for important complex traits and genome selection. Chip-based SNP genotyping technology can detect a large number of SNP sites at the same time, with the advantages of rapidity and high throughput, significantly improving the detection efficiency. Since 2009, Illumina has successively developed two cattle genome chips, Bovine SNP50K chip (containing 50,000 SNPs) and BovineHD (containing 777,000 SNPs); since 2014, Neogen has successively launched GeneSeek 80K, GeneSeek150K, GeneSeek 100K, and GeneSeek 9K cattle genome SNP chips. At present, all the chips used in dairy cattle breeding in my country rely on imports. These chips are widely used in dairy cow genome assessment and gene mining at home and abroad, but they have the following shortcomings: (1) The chip research and development is based on the Holstein dairy cow population in Europe and the United States (Holstein dairy cows dominate the dairy production in most countries in the world), and the SNP effect sites related to the important traits of the Chinese Holstein dairy cow population are not included in the chip (Chinese Holstein cattle account for 90% of my country's dairy cow inventory). Therefore, the efficiency of genome assessment and gene mining for the genetic background of the Chinese Holstein dairy cow population is relatively low; (2) The detection cost of medium and high density chips such as 50K, 777K, 80K, 150K and 100K is high and not suitable for large-scale cow populations; (3) Although the detection cost of 9K low and high density chips is low, the physical location of its SNP sites has not been disclosed by the American company Neogen, which limits the independent genome assessment of Chinese dairy cows; (4) The probe molecules are fixed on the support to form a regularly arranged dot matrix, and the site update and upgrade cycle is long and the cost is high. In view of this, designing and developing a low-density commercial SNP chip for Holstein cows in my country for whole genome selection can significantly reduce the detection cost, facilitate the addition of new important trait-related SNP sites, and promote the application of genomic selection in the establishment of breeding core groups, seed cow screening, and breeding selection. Taking the above factors into consideration, a low-density dairy cow whole genome 30KSNP chip based on liquid phase capture of target region genome sequences and high-depth sequencing typing technology is proposed. Summary of the invention

[0003] The present application provides a low-density dairy cow whole genome 30K SNP chip, wherein the 30K SNP chip comprises reagents for detecting SNP sites associated with dairy cow milk production, body shape and health traits.

[0004] Furthermore, the 30K SNP chip comprises reagents for detecting the SNP sites shown in Table 3 of the specification.

[0005] Furthermore, the reagent is a probe.

[0006] Furthermore, the 30K SNP chip is a liquid phase probe hybridization chip.

[0007] Furthermore, the 30K SNP chip comprises probes with sequences as shown in SEQ ID NO.1-12.

[0008] On the other hand, the present application provides the application of the above 30K SNP chip in dairy cattle breeding.

[0009] Furthermore, the breeding is molecular marker-assisted breeding.

[0010] On the other hand, the present application provides the use of the above-mentioned 30K SNP chip in dairy cow genotyping detection.

[0011] On the other hand, the present application provides the use of the above 30K SNP chip in kinship identification in dairy cows.

[0012] Furthermore, the dairy cow is a Holstein cow.

[0013] The SNP molecular markers mainly come from three types of SNP sites: the first type is the SNP sites significantly related to the important economic traits of dairy cows that were excavated and identified by the inventors' team in the early stage of research, including 3,399 SNP sites; the second type is the main genetic defect gene sites and parentage identification gene sites of dairy cows, including 226 SNP sites; the third type is based on my country's large-scale dairy cow population, according to the detection rate, gene frequency, position uniqueness, genotype filling principle and distribution on the genome, and selected from the existing commercial dairy cow genome chip, including 26,701 SNP sites. The above three categories contain a total of 30,326 SNP sites.

[0014] Due to space constraints, only some probe sequences are listed in this application. In the case of known SNP sites, those skilled in the art can routinely design corresponding detection probes according to chip types, detection methods and other requirements, and verify their accuracy.

[0015] The 30K SNP chip for dairy cows of this application has three advantages: (1) important trait-related loci for the genetic background of the Holstein dairy cow population in my country are added. The inventor team has previously explored and identified a large number of SNP effect loci significantly related to milk production, body shape and health traits through multi-omics research, making this chip more suitable for genomic selection and genetic analysis of Holstein dairy cows in my country; (2) SNP loci are highly polymorphic in the dairy cow population in my country and are evenly distributed across the genome, ensuring the accuracy of genomic selection; (3) low cost, the marker density of the chip is more suitable for large-scale genomic selection of cows. In order to speed up the breeding of excellent cows, considering the typing cost and genomic selection accuracy, this patent designs a 30KSNP (30,326SNPs) chip, which is of great significance for the application of genomic selection technology to population genetic improvement of Holstein dairy cows nationwide, and gets rid of the dependence on chip imports. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of the design and preparation of the chip of the present invention.

[0017] Figure 2 The SNP sites of the present invention are distributed at the whole genome level.

[0018] Figure 3 This is a physical picture of the SNP chip of the present invention. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below in conjunction with specific embodiments, and the examples given are only for illustrating the present invention, rather than for limiting the scope of the present invention. The embodiments provided below can be used as a guide for further improvement by those skilled in the art, and do not constitute a limitation of the present invention in any way.

[0020] The chip design process is as follows Figure 1 shown.

[0021] Example 1 Acquisition of the first type of SNP sites

[0022] Studies have shown that adding SNP sites significantly associated with target traits to the SNP chip can improve the accuracy of genomic selection. Therefore, it is necessary to add sites of the genetic background of the Chinese Holstein dairy cow population to the chip. The inventor's team previously used whole genome association analysis, resequencing, transcriptome and metabolome and other multi-omics technologies to discover and identify 3,399 SNP sites significantly associated with important traits of Chinese Holstein dairy cows (including milk production, body shape and health traits).

[0023] Due to the genetic correlation between traits, some SNPs may affect multiple traits at the same time. After merging and removing the significant SNP sites obtained based on the following studies, the milk production, body shape and health traits are 3,298, 59 and 42 SNP sites respectively.

[0024] The first type of loci are located at SNP loci 20,702-29,999, SNP loci 30,000-30,058 and SNP loci 30,059-30,100 in Table 3. The detailed process of obtaining the SNP loci related to each trait is as follows:

[0025] 1. Milk production traits

[0026] Milk production traits are the most important economic traits of dairy cows, including milk yield, milk fat content, milk protein content, milk fat rate, milk protein rate and milk fatty acids.

[0027] (1) Analysis of genetic effects of candidate genes

[0028] ① The inventor team previously identified 41 candidate functional genes for milk production traits, including APOA2, AKT3, CYP7A1, PKLR, and SEC13, through transcriptome and proteome studies of liver tissues at different lactation stages of dairy cows. A total of 947 Chinese Holstein cows from 22 farms and 45 bull families of Beijing Shounong Animal Husbandry were used as the experimental population for genetic effect analysis. A total of 135 SNP sites were identified through mixed pool sequencing of frozen sperm DNA, and individual genotyping was performed using targeted sequencing genotyping technology (Genotyping By Target Sequencing, GBTS). The SAS software MIXED process and animal model (model as follows) were used to perform single marker and haplotype association analysis on SNP sites and five milk production traits (milk yield, milk fat content, milk fat rate, milk protein content, and milk protein rate).

[0029] y=μ+hys+b×M+G+a+e

[0030] Where y is the phenotypic value of milk production traits (individual 305-day milk production, milk fat content, milk protein content, milk fat rate and milk protein rate), μ is the overall mean, hys is the production year and season utility, b is the regression coefficient of the covariate M, M is the calving age effect, G is the genotype / haplotype combination effect, a is the individual random additive genetic effect and e is the random residual effect.

[0031] According to the results of single marker and haplotype association analysis, the above 135 SNP loci were significantly associated with one or more milk production traits (P<0.05, P<0.01), allele substitution effect or additive genetic effect (P<0.05, P<0.01).

[0032] ② The inventor team previously conducted transcriptome studies on mammary epithelial tissues of lactating dairy cows with extremely high and low milk fat / milk protein rates and identified 14 candidate genes for milk production traits, including DDIT3, RPL23A, SESN2, and NR4A. Based on the Chinese Holstein cow population of Beijing Shounong Livestock, 1,093 cows with complete pedigrees and standardized DHI records were selected as the experimental population. First, the genomic DNA of 40 Holstein bulls (the fathers of the 1,093 cows) was used to perform segmented PCR amplification and sequencing of 3,000 bp of the entire coding region and upstream and downstream regulatory regions of the above four candidate genes using the genomic DNA mixed pool sequencing method. According to the mixed pool DNA sequencing results, a total of 35 SNP sites were found. Individual genotypes were further detected using time-of-flight mass spectrometry technology, and the results of single marker association analysis showed that all 35 SNP sites were significantly associated with at least one milk production trait (P≤0.0001-0.0493), allele substitution effect or additive genetic effect (P<0.05, P<0.01).

[0033] (2) Genome-wide association analysis

[0034] ① The study adopted a daughter design, and the experimental population was 2,093 cows from 14 bull families of Beijing Shounong Livestock. The estimated breeding value (EBV) of the individual was used as the phenotypic value for analysis. Using Bovine SNP50K chip typing, after strict quality control of the genotype data, two statistical analysis methods, namely single marker transmission disequilibrium test (L1-TDT) and single marker regression analysis (MMRA) methods, were used to conduct association analysis on five milk production traits, namely milk yield, milk fat content, milk protein content, milk fat rate, and milk protein rate. A total of 105 SNP sites were found to reach the genomic significance level (P<1.27E-06), of which 38 SNP sites were detected by both methods, and the other 4 and 63 SNP sites were detected by the L1-TDT method and MMRA method respectively. The L1-TDT and MMRA methods located a total of 20, 9, 21, 65 and 28 significant SNP loci affecting milk yield, milk fat content, milk protein content, milk fat rate and milk protein rate.

[0035] ② A total of 784 Chinese Holstein cows from 21 bull families in 18 cattle farms of Beijing Shounong Animal Husbandry were selected as the research group. Genotype data were obtained by BovineSNP50 chip typing. The milk fatty acid content in milk samples was detected by gas chromatography, and the phenotypes of 22 milk fatty acid content traits such as lauric acid, myristic acid, palmitic acid, and linoleic acid were obtained. First, the fixed effect analysis was performed using the SAS9.1 generalized linear model process to correct the milk fatty acid phenotype values; then, the quantitative trait additive effect model in PLINK software (v1.07) was used for genome-wide association analysis, and a total of 83 SNP loci were identified at the genome-wide level that were significantly associated with 22 milk fatty acid content traits (P<1.23E-06).

[0036] (3) Genome resequencing

[0037] The whole genome of 8 Holstein bulls (from 4 full / half sibs: high / low groups) with extremely high / low milk protein and milk fat breeding values ​​(EBV) were resequenced (10×) using the Illumina second-generation sequencing platform. By comparing with the bovine reference genome (UMD3.1), a total of 10,961,243 SNP sites were detected, of which 57,451 shared SNP sites with consistent allele directions between the 4 high and low groups (based on the uniform distribution described later, 3,047 SNP sites were included in the chip).

[0038] 2. Body shape traits

[0039] The Bovine SNP50 bovine whole-genome SNP chip was used to detect the individual genotypes of 1,314 Chinese Holstein cattle from Beijing Shounong Livestock. The LASSO model (the model is as follows) was used for genome-wide association analysis of 29 somatotype traits (including size, body height, front segment, chest width, body depth, loin strength, rump width, rump angle, bone texture, hoof angle, hind limb side view, udder depth, udder texture, central suspensory ligament, anterior chamber attachment, anterior teat position, teat length, posterior attachment height, posterior attachment width, posterior teat position and angularity, as well as 8 functional scoring traits including total score, capacity, milking characteristics, rump, limbs and hooves, front udder, hind udder and lactation system).

[0040] First, the effect size of each SNP was estimated using single trait mixed model analysis (SMMA). Then, the 500 SNPs with the lowest P values ​​were selected for LASSO analysis. The SMMA model is y = 1μ + x j β j +Zg+e, where y is the phenotypic value of each body type trait, 1 is the unit vector, μ is the population mean, and x is the j is the genotype of the jth marker, β jis the SNP effect, g is the minor polygenic effect, Z is the correlation matrix of g, and e is the random residual. g~N(0,Aσ g 2 ), e~N(0,Iσ e 2 ), where A is the pedigree-based additive genetic correlation matrix, σ g 2 is the residual variance.

[0041] Secondly, the improved LASSO was used to estimate the effect value of the SNPs detected by the SMMA model. The model was y = 1μ + Xβ + Zg + e, where X was the 500 SNP genotype covariate matrix and β was the SNP effect vector.

[0042] Genome-wide association analysis detected 59 significant SNP loci at the genome level that were significantly associated with 26 individual traits (P<0.01).

[0043] 3. Health traits

[0044] (1) Immunoglobulin

[0045] A group of 588 Chinese Holstein cattle from Beijing Shounong Animal Husbandry was selected as the research subjects. Colostrum, serum and hair samples were collected within 24 hours after calving. The concentrations of immunoglobulins and albumin in colostrum and serum were detected by ELISA kits, and genotyping was performed using GeneSeek 150K chip. Based on GCTA software, the estimated heritability of colostrum and serum IgG, IgA IgM and albumin concentrations was 0.08-0.48. Except for serum IgG1 and IgG2 concentrations, most immunoglobulin concentrations had medium-to-high heritability (0.12-0.48). A genome-wide association analysis was performed based on a mixed linear model using GCTA software. The results showed that 36 SNP loci were significantly associated with colostrum and serum IgG, IgG2 and IgM concentrations at the genome-wide level (P<3.08E-6).

[0046] (2) Susceptibility / resistance to paratuberculosis

[0047] A total of 945 dairy cows from Beijing Shounong Animal Husbandry were selected as the research population, and a case-control strategy was used to conduct a genome-wide association analysis of paratuberculosis susceptibility / resistance. Bovine 50K chip and GeneSeek 150K chip were used for individual genotyping, and the serum paratuberculosis antibody OD value was used as the phenotype (185 positive and 760 negative). The two data sets (50K and 150K chip intersection data vs. the data set after filling low density to high density) were analyzed by GRAMMAR-GC and ROADTRIPS software respectively. The two methods detected 14 and 18 genome-wide significant SNP loci, respectively, which were significantly associated with paratuberculosis susceptibility / resistance in Holstein cows (P<5×10 -5 ).

[0048] (3) Ketosis

[0049] A total of 78 cows from Beijing Shounong Animal Husbandry were used as the experimental group. The blood ketone levels before and after delivery during the peripartum period were detected. Finally, 12 adult Holstein cows were selected as the research subjects and divided into a healthy group (4 cows) and a diseased group (8 cows). A total of 24 blood samples were collected at two time points, 2 weeks before calving and 5 days after calving, for transcriptome sequencing and determination of 7 blood biochemical metabolic indicators, and the data were integrated for weighted gene co-expression network analysis (WGCNA). The results of the genome-wide association analysis of ketosis in publicly published literature were integrated for enrichment. Each SNP site within the 20kb upstream and downstream extension of each gene in the module that was significantly enriched in the genome-wide association analysis signal was sorted by P value. With FDR<0.01 as the threshold, the SNP with the smallest enrichment P value was selected as the candidate SNP site, and finally 5 SNP sites related to ketosis were screened.

[0050] Example 2 Acquisition of the second type of SNP sites

[0051] 1. Genetic defects

[0052] Genetic defects in dairy cows mainly include spinal deformity syndrome CVM, leukocyte adhesion deficiency BLAD, uridylate synthase deficiency and citrullinemia, which can lead to early abortion of cows, death of calves, and reduced survival rate, causing huge economic losses to the dairy farming industry. By adding genetic defect gene loci to the SNP chip, it is possible to easily, quickly and accurately identify and screen whether individual dairy cows carry recessive harmful genes with genetic defects, thereby reducing the frequency of harmful genes in the group through early elimination or scientific selection and matching, and improving the quality of my country's dairy cow population. Therefore, 20 common cattle genetic defect causative mutation sites, a total of 26 SNP sites, were added to this chip, and the site information came from the main cattle genetic defect sites included in the OMIA database.

[0053] Table 1 Common mutation sites causing genetic defects in cattle

[0054]

[0055]

[0056] 2. Paternity test

[0057] In dairy cattle breeding, correct pedigree records are an important basis for accurately estimating individual breeding values ​​and accelerating population genetic progress. Pedigree errors are common in dairy farms, and parentage testing and pedigree correction through genetic markers are of great significance. The International Society of Animal Genetics (ISAG) has studied and recommended 200 SNP sites for cattle paternity testing (to facilitate research and communication between laboratories in various countries), so they are added to this chip.

[0058] The second type of sites are located at SNP sites 30,100-30,326 in Table 3.

[0059] Example 3 Obtaining the third type of SNP sites

[0060] Large-scale, high-quality reference populations are an important foundation and necessary link for genomic selection. Since 2008, the inventor team has built the only reference population for dairy cow genomic selection in my country, which currently has a size of 17,000 cows. The SNP chips used for genotype detection of the reference group individuals are all from abroad, including 50K 8080, 80K 3209, and 150K 6157. Therefore, this chip needs to have a high genotype filling accuracy with the chip data of the reference group, so as to accurately evaluate the genome of the cow population.

[0061] The genotype filling method is based on the inferred haplotype (referring to the combination of alleles inherited in linkage between adjacent markers on the same chromosome) to fill in the missing genotype. The basic process is: first, use individuals with high-density markers and family information and linkage disequilibrium information between populations to construct haplotypes; then, the markers in the chip to be filled are matched with the markers in the haplotype for filling.

[0062] Factors that affect the accuracy of chip genotype filling include: minimum allele frequency, marker density, reference population size and filling method, etc. Considering that the genotype chip data of the above reference population includes three types of chips: 50K, 80K and 150K SNP, the inventors selected some SNP sites from the existing 50K, 80K and 150K commercial cattle genome chips based on the large-scale dairy cow population in my country, according to the detection rate, gene frequency, position uniqueness, genotype filling principle and distribution on the genome.

[0063] 1. Quality Control

[0064] Based on the genotype data of 17,000 Chinese Holstein cows (8080 50K, 3209 80K, and 6157 150K), effective SNP loci suitable for the Chinese Holstein dairy cow population were selected according to the detection rate, minimum allele frequency, and Hardy-Weinberg equilibrium test. PLINK software was used for quality control: (1) SNP loci with a SNP detection rate less than 0.95 were eliminated; (2) SNP loci with a minimum allele frequency less than 0.01 were eliminated; (3) SNP loci that did not conform to Hardy-Weinberg equilibrium (P-value < 1 × 10 -6 ). After quality control, 39,036, 73,409 and 126,543 SNP sites remained in the 50K, 80K and 150K chips, respectively. After deduplication of the common sites among the three, 154,363 SNP sites were obtained.

[0065] 2. SNP site distribution

[0066] To ensure that SNP sites evenly cover the entire genome of dairy cows, capture genetic variation of important traits within the entire genome, and achieve accurate genome evaluation, a 100Kb sliding window was set on the chromosome to screen the aforementioned site set. Finally, 26,701 third-category SNP sites were identified.

[0067] The third type of sites are located at SNP sites 1 to 26,701 in Table 3.

[0068] Example 4 Preparation of Chip

[0069] The above three types of SNP sites are shown in Table 1, and their distribution on chromosomes is shown in Figure 2 shown.

[0070] To ensure that the physical position of the SNP site is unique across the entire genome, the above three types of SNPs were site checked and evaluated.

[0071] Firstly, based on the two currently used cattle reference genome sequences (UMD3.1.1 and ARS-UCD1.2), the flanking sequences of 30,335 SNP sites were aligned separately using blastn software with the default parameters of -evalue 1e-5, -dust yes, identical>=98%. The SNP sites that met the requirements were retained, and finally a total of 30,326 SNP sites were included.

[0072] Then, based on the physical location and flanking sequences of the SNP sites on the cow reference genome, probe designs were successfully performed (partial examples are shown in SEQ ID NO.1-12). Figure 3 shown.

[0073] Table 2 Some probe sequences

[0074]

[0075]

[0076] Due to the limitation of the sequence table format, SEQ ID NO. 1-12 only represent the unchanged original sequences. Those skilled in the art can obtain the mutant sequences from the mutation sites and mutation modes recorded in Table 2.

[0077] Example 5 Practical Effects of the Chip of the Present Application

[0078] To verify the practical effect of this chip, 95 healthy Holstein cows were selected from Saikexing Dairy Farm in Inner Mongolia as the verification group. The 30K chip and GeneSeek 100K chip were used for individual genotype detection and comparative verification analysis.

[0079] Firstly, PLINK software was used to perform quality control on the 30K and 100K chip genotype data of 95 dairy cows: ① individuals with detection rates lower than 95% were eliminated; ② sex chromosome loci and loci with unknown physical locations were eliminated; ③ loci with the minimum allele frequency less than 0.01 were eliminated.

[0080] Then, a reference population (17,868 heads) was selected based on the genome described in Example 3, and the 30K genotype data were filled to 50K using Beagle5.2 software to calculate the filling accuracy. The results showed that the filling accuracy was 99.25%, which met the needs of genome evaluation work.

[0081] Table 3 List of SNP sites used in the chip

[0082]

[0083]

[0084]

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141]

[0142]

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159]

[0160]

[0161]

[0162]

[0163]

[0164]

[0165]

[0166]

[0167]

[0168]

[0169]

[0170]

[0171]

[0172]

[0173]

[0174]

[0175]

[0176]

[0177]

[0178]

[0179]

[0180]

[0181]

[0182]

[0183]

[0184]

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191]

[0192]

[0193]

[0194]

[0195]

[0196]

[0197]

[0198]

[0199]

[0200]

[0201]

[0202]

[0203]

[0204]

[0205]

[0206]

[0207]

[0208]

[0209]

[0210]

[0211]

[0212]

[0213]

[0214]

[0215]

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224]

[0225]

[0226]

[0227]

[0228]

[0229]

[0230]

[0231]

[0232]

[0233]

[0234]

[0235]

[0236]

[0237]

[0238]

[0239]

[0240]

[0241]

[0242]

[0243]

[0244]

[0245]

[0246]

[0247]

[0248]

[0249]

[0250]

[0251] The variation information of the SNP site is expressed in the form of chromosome number: physical position reference genotype>allele type. The numbering of the SNP sites in Table 3 described in the embodiment is arranged in sequence according to the horizontal row, that is, Chr1_100041952A>G is the first, Chr1_100094035T>A is the second, Chr1_100151489T>G is the third, and so on.

Claims

1. A low-density Holstein cow whole genome 30K SNP chip, characterized in that: The 30K SNP chip contains reagents for detecting SNP sites associated with milk production, body shape, reproduction and health traits of dairy cows, and the SNP sites are as follows: The 30K SNP chip according to claim 1 , wherein the reagent is a probe. 3 . The 30K SNP chip according to claim 2 , wherein the 30K SNP chip is a liquid phase probe hybridization chip.

4. Use of the 30K SNP chip according to any one of claims 1 to 3 in Holstein cow breeding.

5. The use according to claim 4, wherein the breeding is molecular marker-assisted breeding.

6. Use of the 30K SNP chip according to any one of claims 1 to 3 in genotyping detection of Holstein cows.

7. Use of the 30K SNP chip according to any one of claims 1 to 3 in identifying the genetic relationship of Holstein cows.

Images