A SNP molecular marker related to milk buffalo somatic cell score and application thereof

Abstract

This invention discloses a SNP molecular marker associated with somatic cell count (SCC) score in dairy buffalo and its application. The marker is located at position 625821 on chromosome 6 of the reference genome GCF_000471725.1, with a C / T polymorphism, and the locus is located at position 51 of SEQ ID NO.1. Dairy buffalo genotype CT results in significantly lower somatic cell count scores. This invention also provides primer pairs, a kit for detecting this marker, and its application in dairy buffalo breeding. This invention, through genome-wide association analysis, is the first to obtain a SNP molecular marker significantly associated with somatic cell count in dairy buffalo. It can be applied to early selection of dairy buffalo, screening for superior individuals with low somatic cell count scores, effectively solving the problems of inaccurate phenotypic selection due to low heritability of somatic cell count scores and the inability of common bovine markers to be applied across species. This significantly shortens the breeding cycle, reduces breeding costs, and provides an effective molecular tool for disease-resistant breeding of dairy buffalo.

Description

Technical Field

[0001] This invention belongs to the field of molecular biology technology, and in particular relates to a SNP molecular marker related to somatic cell count scoring in dairy buffalo and its application. Background Technology

[0002] Buffalo are important dairy animals, and their dairy products (such as buffalo milk and mozzarella cheese) have a significant market advantage due to their unique nutritional value and flavor. With consumption upgrading and industrial restructuring, the intensive farming scale of buffalo is continuously expanding. However, similar to high-yielding dairy cows, improved production performance is often accompanied by increased health stress. Among these, udder health problems, especially subclinical mastitis, have become a key bottleneck restricting the healthy development of the buffalo dairy industry.

[0003] Mastitis not only leads to decreased milk production and altered milk composition (such as impaired synthesis of milk fat and milk protein), but also severely affects the processing quality of dairy products. In mammary gland health monitoring systems, somatic cell count (SCC) is the internationally recognized core indicator trait. To make its statistical distribution closer to a normal distribution, it is usually converted to a somatic cell score (SCS) in breeding, calculated as SCS = log2(SCC / 100) + 3. The level of SCS directly and sensitively reflects the inflammatory state of the mammary gland: a higher SCS indicates a more severe inflammatory response and deeper damage to mammary tissue. Therefore, reducing the SCS of dairy buffalo and screening for resistant individuals with low SCS is an effective way to improve mammary gland health from a genetic perspective and reduce treatment costs.

[0004] Traditional breeding methods rely on phenotypic determination, but SCS (Social Strains) are influenced by multiple environmental factors such as season, rearing environment, and pathogen infection, and have low heritability (usually h...). 2 For complex traits such as <0.1), relying solely on phenotypic values ​​for breeding is inaccurate and time-consuming. Directly conducting challenge experiments is neither economical nor in line with animal welfare. With the development of molecular biology, genome-wide association analysis (GWAS) and candidate gene strategies have been widely applied in Holstein cattle breeding. By mining single nucleotide polymorphism (SNP) markers associated with SCS or mastitis resistance, early screening of resistant individuals has been achieved.

[0005] However, these research findings exhibit significant species specificity. Although several candidate genes and SNP markers associated with SCS, such as TLR4, CD14, SLC4A4, and LYZ, have been reported in conventional dairy cows, these markers cannot be directly applied to molecular-assisted breeding of dairy buffaloes due to significant differences in genetic background, physiological metabolism, and mammary gland immune regulation mechanisms between dairy buffaloes (chromosome number 2n=48 or 50) and conventional cattle (2n=60). Currently, there is a lack of functional SNP molecular markers specifically for dairy buffalo populations that are stably inherited and significantly associated with the SCS trait, both domestically and internationally.

[0006] Therefore, screening and developing a set of SNP molecular markers that are closely related to somatic cell count (SCS) in dairy buffalo, and establishing an efficient genotyping detection technology system, is of great theoretical significance and broad application prospects for filling the technical gap in disease-resistant breeding of dairy buffalo, accelerating the early selection of superior resistant individuals, and fundamentally improving the udder health level in large-scale farming. Summary of the Invention

[0007] To address the problems existing in the prior art, this invention provides SNP molecular markers related to somatic cell count scores in dairy buffaloes, screened based on genome-wide association analysis, and their applications; these markers can be used to quickly and easily identify dairy buffalo individuals with good udder health traits.

[0008] A SNP molecular marker associated with somatic cell count score in dairy buffalo, wherein the SNP molecular marker is located at base 625821 on chromosome 6 of the dairy buffalo reference genome GCF_000471725.1, and its polymorphism is C or T, corresponding to the 51st nucleic acid site in SEQ ID NO.1 of the nucleic acid sequence listing.

[0009] To further explain, when the genotype of the SNP molecular marker site is CT, the dairy buffalo individual has a significantly lower somatic cell count score.

[0010] The present invention also provides a primer pair for detecting the SNP molecular markers as described above, wherein the primer pair is capable of specifically amplifying nucleotide sequences containing the SNP sites.

[0011] To further explain, the primer pair has sequences as shown in SEQ ID NO.2 and SEQ ID NO.3.

[0012] The present invention also provides an SNP genotyping detection kit, comprising the primer pairs described above.

[0013] Further details include PCR reaction buffer, dNTPs, DNA polymerase, and / or instructions for use.

[0014] The present invention also provides the application of the SNP molecular markers, primer pairs, or SNP genotyping kits described above in any of the following aspects:

[0015] (1) Genetic breeding or marker-assisted breeding of dairy buffalo;

[0016] (2) To prepare products for dairy buffalo breeding or assisted breeding;

[0017] (3) Screening for dairy buffalo individuals with low somatic cell count scores.

[0018] The present invention also provides a method for screening dairy buffaloes with low somatic cell count scores, comprising: detecting the genotype of the SNP molecular markers as described above in the genome of the dairy buffalo to be tested, and selecting individuals with the genotypes as described above as breeding buffaloes with the potential for low somatic cell count scores.

[0019] To further explain, the detection includes: extracting genomic DNA from the buffalo to be tested, performing PCR amplification using the primer pairs described above or the SNP genotyping kit described above, sequencing the amplification products, and analyzing to determine the genotype of the SNP molecular marker.

[0020] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0021] First, this invention provides SNP molecular markers directly related to somatic cell count score (SCS) in dairy buffalo. Through genome-wide association analysis (GWAS), SNP loci significantly associated with SCS were precisely screened in the dairy buffalo population, filling a technological gap in the field of molecular markers for mammary gland health in this species. These markers can be directly used for marker-assisted breeding (MAS) to enable early and rapid screening of individuals with low SCS.

[0022] Secondly, this invention addresses the challenges of low heritability of SCS and its susceptibility to environmental influences, which leads to inaccurate traditional breeding methods. It utilizes stable SNP molecular markers for genotyping, significantly improving breeding selection efficiency. Compared to relying on phenotypic determination, this invention can shorten breeding cycles, reduce feeding costs, and accelerate the accumulation of superior resistance to low SCS from a genetic perspective.

[0023] Third, using the primers and detection methods provided by this invention, genotyping can be completed in the early postnatal stage of dairy buffalo through simple blood sampling and PCR sequencing, allowing for early prediction of their future mammary gland health potential. This method is accurate, rapid, and cost-effective, significantly shortening the breeding cycle and accelerating genetic progress.

[0024] Fourth, through large-sample verification, this invention has for the first time clearly demonstrated that the CT heterozygous genotype at the chr6_625821 locus is significantly associated with the lowest SCS value (i.e., optimal udder health) in dairy buffalo populations (P<0.05), providing breeders with a clear and unambiguous target for breeding / mating.

[0025] Fifth, by applying this invention to breed low-SCS dairy buffalo breeds, the incidence of subclinical mastitis can be reduced from a genetic perspective, reducing the use of veterinary antibiotics, which aligns with the national food safety strategy of "reducing antibiotics" and "alternative antibiotics," and improves the quality and added value of buffalo milk products.

[0026] In summary, this invention effectively solves the technical problems of low efficiency in traditional breeding and the inability of ordinary bovine markers to be applied across species by providing SNP molecular markers specifically for dairy buffalo populations that are significantly correlated with somatic cell count score (SCS). This invention provides a directly applicable molecular tool for disease-resistant breeding of dairy buffaloes, resulting in significant technical benefits such as improved predictive accuracy, accelerated genetic improvement, advancement of precision breeding, optimization of breeding strategies, and provision of new targets for scientific research. Attached Figure Description

[0027] Figure 1 This is a Manhattan plot of somatic cell count scoring provided in this embodiment of the invention; the horizontal axis represents chromosome number, and the vertical axis represents -log. 10 (P-value).

[0028] Figure 2 This is a quantile-quantile graph of somatic cell count scoring provided in an embodiment of the present invention. Detailed Implementation

[0029] All features disclosed in this specification, or all steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps.

[0030] Unless otherwise stated, each feature disclosed in this specification (including any appended claims and abstract) is merely one example of a series of equivalent or similar features.

[0031] Example 1: Experimental population and phenotypic data collection

[0032] This example describes the process of collecting and quality control data on dairy buffalo populations and somatic cell count score (SCS) phenotypes used in genome-wide association analysis.

[0033] 1. Group selection and collection of breast health phenotypic data

[0034] We selected 175 healthy and well-developed dairy buffaloes and collected somatic cell count (SCC) data in the milk of each buffalo at different lactation stages.

[0035] 2. Data collection, conversion, and statistical analysis of phenotypic data related to breast health traits.

[0036] First, the average somatic cell count of each dairy buffalo at different lactation stages was collected. The average somatic cell count of each dairy buffalo was converted into a somatic cell count score according to the formula: SCS = log2(SCC / 100) + 3. Then, SPSS20 software was used to perform statistical analysis on the somatic cell count score, including minimum, maximum, mean, standard deviation and coefficient of variation. The results are shown in Table 1.

[0037] Table 1. Statistical analysis of somatic cell count (SCS) scores related to mammary gland health in dairy buffalo.

[0038]

[0039] The results showed that the SCS data ranged from 0.68 to 8.11, with a mean of 3.43, a standard deviation of 1.49, and a coefficient of variation of 43.4%. This population exhibited moderate genetic variation and high phenotypic dispersion, making it suitable for GWAS analysis.

[0040] 3. Blood genomic DNA extraction and detection

[0041] 10 mL of jugular venous blood was collected from each buffalo, anticoagulated with sodium heparin, and gently shaken to mix. Genomic DNA was extracted using a blood genomic DNA extraction kit (Tiangen). DNA concentration was measured using a nucleic acid concentration analyzer, and DNA sample quality was determined by 1% agarose gel electrophoresis. Results showed that all DNA samples had clear, undegraded main bands, with OD260 / 280 ratios between 1.8 and 2.0, meeting the requirements for library construction and sequencing. The qualified DNA samples were sent to Beijing Novogene Bioinformatics Technology Co., Ltd. for genome sequencing. After passing quality control, they were used for resequencing and library construction. The sequencing strategy was Illumina PE150.

[0042] Example 2: Low-depth resequencing and SNP genotyping

[0043] This embodiment describes the process of acquiring, quality controlling, and filtering genotype data.

[0044] 1. Sequencing data quality control

[0045] 175 qualified DNA samples were resequencing at a low depth (Illumina PE150 platform) with a sequencing depth of 5X or higher. The raw data obtained from sequencing was quality controlled, and the filtering criteria included: (1) removing reads containing adapter sequences; (2) removing paired reads containing more than 10% N; and (3) removing reads with more than 50% low-quality bases (quality≤5). The obtained clean data were statistically analyzed, including sequencing data yield, Q20 content, Q30 content, and GC content, as shown in Table 2. Finally, the amount of high-quality clean data obtained was 124.11 Gb.

[0046] Table 2. Statistics of genomic DNA sequencing results of dairy buffalo.

[0047]

[0048] 2. Genomic data alignment

[0049] High-quality sequencing data was aligned to the reference genome using BWA bioinformatics software (parameters: mem -t 4 -k 32 -M). The buffalo reference genome version number is GCF_000471725.1. The reference genome can be downloaded from: https: / / ftp.ncbi.nlm.nih.gov / genomes / all / GCF / 000 / 471 / 725 / GCF_000471725.1_UMD_CASPUR_ WB_2.0 / The average alignment rate of the population sample was 99.40%, the average sequencing depth of the genome was 13.65X, and the average 1X coverage (coverage of at least one base) was 3.66%. The information is shown in Table 3.

[0050] Table 3. Statistical results of the comparison of dairy buffalo genome data

[0051]

[0052] 3. Mutation detection, quality control, and filtration

[0053] SNPs in the population were detected using SAMTOOLS software. Polymorphic sites in the population were detected using a Bayesian model. Quality control methods were used: (1) SNPs with a quality value above 20 (error rate greater than 1%) were filtered out; (2) if the distance between two detected SNPs was within 5 bp, the SNPs were removed; (3) the coverage depth of the SNPs should be between 1 / 3 and 5 times the average depth. The SNPs obtained after the initial quality control detection will be further subjected to strict quality control to ensure the accuracy of the variation information detection. The obtained SNPs were filtered to obtain high-quality SNPs. The filtering conditions were dp2, Miss0.2, Maf0.01, mapping quality <40.0, MQRankSum <-12.5, ReadPosRankSum <-8.0, SOR >3.0 and FisherStrand >60.0. Finally, 228,115 SNP sites were filtered and retained for subsequent association analysis.

[0054] This embodiment successfully performed low-depth resequencing on 175 dairy buffaloes, obtaining a high-quality SNP dataset (228,115 SNP loci), providing a reliable genotype data foundation for subsequent genome-wide association analysis.

[0055] Example 3: Genome-wide association analysis (GWAS) and identification of significant SNP sites

[0056] This embodiment describes the statistical model, parameter settings, population stratification control method of GWAS, and the significant SNP sites and their flanking sequences identified therefrom.

[0057] 1. Statistical Model of GWAS

[0058] Trait association analysis was conducted using a mixed linear model, with population genetic structure treated as a fixed effect and individual kinship as a random effect, to correct for the influence of population structure and individual kinship.

[0059] y = Xα + Zβ + Wµ + e

[0060] Where y is the phenotypic trait, X is the indicator matrix of the fixed effects, α is the estimated parameter of the fixed effects, Z is the indicator matrix of the SNP, β is the effect of the SNP, W is the indicator matrix of the random effects, µ is the predicted random individual, and e is the random residual, which follows e ~ (0, δe2).

[0061] 2. Significance threshold and population stratification control

[0062] Bonferroni correction was used, with -log 10 (P)>5 (P < 1×10) -5The significance threshold was used. The genome expansion factor (λ) was calculated using R software. The results are as follows: Figure 2 As shown in the Quantile-quantile plot, the observed P-value and the expected P-value matched well in the early stages, and the separation only occurred at the tail end, with a λ value of 0.98, indicating that there was no obvious stratification in the population and the analysis results were reliable.

[0063] 3. Identification of significant SNP sites

[0064] GWAS analysis results are as follows Figure 1 (Manhattan plot shown). The horizontal axis represents the physical location of the chromosome, and the vertical axis represents -log. 10 (P), the horizontal dashed line represents the significance threshold (-log). 10 (P) > 5). The results showed a significant association signal peak on chromosome 6 of dairy buffalo.

[0065] The significant SNP locus identified was designated chr6_625821, and detailed information is shown in Table 4. This locus is located at base 625821 on chromosome 6 of the dairy buffalo reference genome GCF_000471725.1, with a polymorphism of C / T, and the associated phenotype is somatic cell count score (SCS). The significance level was log-1. 10 The (P) value is 7.88369.

[0066] 4. Flanking sequence provided

[0067] The 101 bp base sequence before and after the SNP site is shown in SEQ ID NO.1, with a [C / T] variation at base position 51. The specific sequence is: TTGTCAGAGT CAGGCTACAT TTGTCAATCC AAATTCTACA CAGTAATTCT[C / T]ATAAAAACA ATGCATTGAT ATTGCTTACT TTGAGTCAAC TAATATTTTA A.

[0068] Table 4. Molecular markers significantly associated with SCS in dairy buffalo udder health.

[0069]

[0070] Example 4: Correlation analysis between SNP molecular markers and SCS phenotype

[0071] This embodiment provides detailed SCS mean, standard deviation, and significance of different genotypes of the SNP locus chr6_625821, demonstrating the significant advantage of the dominant genotype.

[0072] 1. Validation population and genotyping

[0073] Eighty-five dairy buffaloes unrelated to those in Example 1 were selected, and jugular vein blood was collected to extract genomic DNA. Genomic DNA was extracted from the jugular vein using a blood genomic DNA extraction kit. DNA concentration was measured using a nucleic acid concentration analyzer, and DNA sample quality was determined by 1% agarose gel electrophoresis. Specific PCR amplification primers were designed for the chr6_625821 locus. The primer sequences are as follows:

[0074]

[0075] Using the primers described above, PCR amplification was performed using genomic DNA from dairy buffalo blood as a template. A 50 μL PCR reaction mixture was used: 19 μL ddH2O, Premix Taq. TM 25 μL of DNA template, 2.0 μL of primers (both upstream and downstream primers are 10 μmol / L) and 2.0 μL of primers.

[0076] PCR reaction conditions: 95 °C pre-denaturation for 4 min; 94 °C denaturation for 10 s, annealing for 30 s (at 60 °C), extension at 72 °C for 1 min, for a total of 35 cycles; 72 °C extension for 5 min.

[0077] The PCR amplification products were purified using the Gel Extraction Kit from Shanghai Sangon Biotech Co., Ltd. Specific steps are detailed in the kit's instruction manual. The purified PCR products were then directly sent to BGI Genomics (Shenzhen) Co., Ltd. for first-generation sequencing.

[0078] 2. Genotype frequency statistics

[0079] Individual genotyping was performed based on sequencing results. The genotyping results are shown in Table 5.

[0080] Table 5. Genotype and allele frequencies of the chr6_625821 locus in dairy buffalo.

[0081]

[0082] As can be seen from Table 5, the frequency of the T allele at the mutation site chr6_625821 is significantly greater than that of the C allele.

[0083] 3. Association analysis between genotype and SCS phenotype

[0084] The SCS phenotypic values ​​of individuals with different genotypes were statistically analyzed, and the results are shown in Table 6.

[0085] Table 6. Significant association between somatic cell count (SCS) score and SNP in mammary gland health of dairy buffalo.

[0086]

[0087] Note: Somatic cell count (SCS) phenotypic values ​​of dairy buffalo udder health are expressed as "least square mean ± standard deviation". Different letters in the same column indicate significant differences (P<0.05); the same letter or no letter in the column indicates no significant differences (P>0.05); SNP locus genotypes are arranged in the order of reference type, heterozygous type, and mutant type.

[0088] The results, shown in Table 6, indicate that validation revealed significant differences in somatic cell count scores between different genotypes of candidate chr6_625821 and dairy buffalo (P<0.05). The SCS value of the heterozygous CT genotype (3.15±1.29) was significantly lower than that of the homozygous CC (3.95±1.86) and TT (3.93±1.92) genotypes (P<0.05), while there was no significant difference between the CC and TT genotypes (P>0.05). Therefore, selecting the heterozygous CT genotype resulted in the lowest somatic cell count score, indicating a healthier udder and better milk quality. The validation results are consistent with the genome-wide association analysis (GWAS) results, demonstrating that the SNP molecular markers screened by GWAS are accurate and reliable and can be directly used as molecular markers to assist breeding in identifying udder health traits in dairy buffalo and applied to production.

[0089] Example 5: Breeding Application Case

[0090] This embodiment describes how to apply the above-mentioned SNP molecular markers to screen dairy buffalo with low somatic cell count scores in actual breeding.

[0091] A method for early selection of dairy buffalo based on SNP molecular markers of the present invention includes the following steps:

[0092] (1) Sample collection and DNA preparation: In the early stage of the selected dairy calves (e.g., 6 months of age), about 5-10 mL of jugular vein blood was collected and placed in heparin sodium anticoagulant tubes. Whole genome DNA was extracted using a commercially available blood genomic DNA extraction kit.

[0093] (2) Genotype detection: Using the extracted genomic DNA as a template, PCR amplification was performed using the specific primers (SEQ ID NO. 2-3) for the SNP locus (chr6_625821) of this invention. The reaction system and conditions were the same as in Example 4. The amplification products were subjected to Sanger sequencing to determine the genotype (CC, CT, or TT).

[0094] (3) Determination of dominant genotype and selection decision: According to the results in Table 6 of Example 4, individuals with the CT genotype have significantly lower SCS values ​​(P<0.05), which means they have better udder health traits and milk quality. Therefore, individuals with the CT genotype should be given priority as replacement breeding cattle; for individuals with the CC or TT genotypes, a comprehensive evaluation based on pedigree information or gradual elimination can be carried out.

[0095] Example 6: Preparation of SNP Genotyping Detection Kit

[0096] This embodiment provides a detection kit based on the SNP molecular marker combination of the present invention and its usage method.

[0097] Based on the flanking sequence of SEQ ID NO.1, two pairs of specific PCR primers (primer sequences SEQ ID NO.2 and SEQ ID NO.3) were designed to amplify DNA fragments containing each SNP locus. The kit was assembled and contained the following components: (1) 10×PCR reaction buffer; (2) dNTPs mixture (2.5 mM each); (3) Taq DNA polymerase (5 U / μL); (4) 10 pairs of specific primers (10 μM each for upstream and downstream, aliquoted or mixed); (5) positive control DNA (genomic DNA of dairy buffalo with the known chr6_625821 locus genotype CT); (6) negative control (ddH2O); (7) instruction manual.

[0098] Detection steps: (1) Extract genomic DNA from the blood or tissue of the dairy buffalo to be tested; (2) Perform PCR amplification using the above kit (under the same conditions as in Example 4); (3) Perform Sanger sequencing on the amplified product and determine the genotype at the chr6_625821 locus; (4) Compare the determination result with the dominant genotype (CT) to determine whether the individual to be tested carries the dominant genotype.

[0099] In summary, this invention successfully constructed a mixed linear model through genome-wide association analysis (GWAS) on 175 dairy buffaloes, verifying that the population structure had no significant impact (λ=0.98), and for the first time identified the SNP marker chr6_625821 (C / T) significantly associated with somatic cell count score (SCS), with a significance level as high as 7.88. Functional validation in 85 independent dairy buffalo populations confirmed the stability and effectiveness of this marker, and determined that the CT heterozygous genotype was the dominant genotype indicating lower SCS and superior udder health (P<0.05). Based on this marker, this invention also developed standardized detection methods, early selection procedures, and detection kits containing specific primers, enabling accurate assessment of udder health potential in early calves, significantly shortening the breeding cycle and reducing costs. This invention fills the technological gap for molecular markers specifically targeting the SCS trait in dairy buffalo populations, effectively solving the technical problems of low efficiency in traditional phenotypic selection and the inability of ordinary bovine markers to be applied across species, possessing significant industrial application value and broad market prospects.

[0100] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A SNP molecular marker associated with milk buffalo somatic cell score, characterized in that, The SNP molecular marker is located at base 625821 on chromosome 6 of the dairy buffalo reference genome GCF_000471725.1, and its polymorphism is C or T, corresponding to the 51st nucleic acid site in SEQ ID NO.1 of the nucleic acid sequence listing.

2. The SNP molecular marker according to claim 1, characterized in that, When the genotype of the SNP molecular marker site is CT, the dairy buffalo individual has a significantly lower somatic cell count score.

3. A primer pair for detecting the SNP molecular marker of claim 1 or 2, characterized in that, The primer pair can specifically amplify nucleotide sequences containing the SNP sites.

4. The primer pair according to claim 3, characterized in that, The primer pair has sequences as shown in SEQ ID NO.2 and SEQ ID NO.

3.

5. An SNP genotyping detection kit, characterized in that, It contains the primer pair as described in claim 3 or 4.

6. The SNP genotyping detection kit according to claim 5, characterized in that, It also includes PCR reaction buffer, dNTPs, DNA polymerase and / or instructions for use.

7. The application of the SNP molecular marker of claim 1 or 2, the primer pair of claim 3 or 4, or the SNP genotyping detection kit of claim 5 or 6 in any of the following aspects: (1) Genetic breeding or marker-assisted breeding of dairy buffalo; (2) To prepare products for dairy buffalo breeding or assisted breeding; (3) Screening for dairy buffalo individuals with low somatic cell count scores.

8. A method for screening dairy buffaloes with low somatic cell count scores, characterized in that, include: The genotype of the SNP molecular marker of claim 1 in the genome of the dairy buffalo to be tested is detected, and individuals with the genotype of claim 2 are selected as breeding buffalo with low somatic cell count potential.

9. The method according to claim 8, characterized in that, The detection includes: extracting genomic DNA from the dairy buffalo to be tested, performing PCR amplification using the primer pair described in claim 3 or 4 or the SNP genotyping detection kit described in claim 5 or 6, sequencing the amplification products, and analyzing to determine the genotype of the SNP molecular marker.

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