Single nucleotide polymorphism (SNP) site combination of beef cattle, screening method, gene chip and application of SNP site combination

Abstract

The invention discloses a beef cattle SNP site combination, a screening method, a gene chip and application thereof. The SNP site combination comprises SNP sites corresponding to at least part of physical position information in a table 1. The locus combination sheet optimizes and integrates specific gene loci of beef cattle in Hubei and various foreign varieties of beef cattle, is associated with main economic traits of the beef cattle, reduces the number of SNPs unassociated with the traits, reduces the cost, and improves the economic benefits of the beef cattle. The method has high application value in beef cattle character identification, prediction and molecular breeding in a covered variety range.

Description

Technical Field

[0001] The present application relates to the technical field of beef cattle breeding, and in particular to a beef cattle SNP site combination, a screening method, a gene chip and applications thereof. Background Art

[0002] Hubei Province has five well-known local beef cattle breeds, including Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, and Yiling cattle. Although Hubei's common cattle local breeds are rich in genetic resources, they generally have problems such as small individual size, slow growth rate, and low meat production. In order to improve the production performance of these local breeds, Hubei has introduced a number of foreign breeds including Simmental cattle, Angus cattle, Charolais cattle and Limousin cattle for hybridization and improvement. However, the blind introduction of foreign breeds for hybridization not only leads to the loss of local genetic diversity, but also fails to ensure the continuous improvement of the economic traits of the breeds. So far, the effect of local breed improvement and breeding is not ideal, mainly because the breeding work of local breeds has not accurately identified genetic markers related to key economic traits based on the breeds. Therefore, the production performance of local breeds still lags behind that of introduced breeds, which will also cause the introduced breeds to further impact the local breeds, resulting in a gradual reduction in the population size of the original breeds. Summary of the invention

[0003] The present application provides a combination of SNP sites for beef cattle, a screening method, a gene chip and applications thereof, which can solve the technical problems existing in the above-mentioned prior art.

[0004] In a first aspect, the present invention provides a combination of SNP loci for beef cattle, using the following technical solution:

[0005] A SNP locus combination for beef cattle, the SNP locus combination comprising SNP loci corresponding to at least part of the physical location information in Table 1.

[0006] In combination with the first aspect, in one embodiment, the SNP site combination is the SNP sites corresponding to the physical location information in Table 1.

[0007] In a second aspect, the present application embodiment provides a method for screening a combination of SNP loci for beef cattle as described above, using the following technical solution:

[0008] A method for screening a combination of SNP loci in beef cattle, characterized in that it comprises the following steps:

[0009] Obtaining the location information of the SNP sites corresponding to the genome sequence of each breed in the target coverage breed set; wherein the target coverage breed set at least includes Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle, Simmental cattle, Limousin cattle, Charolais cattle and Angus cattle;

[0010] Obtaining variety characteristic sites, genetic defect disease sites and important economic trait functional sites in the SNP sites of each variety to form a first candidate site set;

[0011] Acquire the SNP sites involved in each of the multiple target compatible chips, and determine that among the SNP sites shared by the multiple target compatible chips, the SNP sites that are not repeated in the first candidate site set constitute a second candidate site set;

[0012] According to the allele frequencies of all sites of each variety, determine that among the SNP sites whose allele frequencies are greater than a set frequency threshold, the SNP sites that are not repeated in the first candidate site set and the second candidate site set constitute a third candidate site set;

[0013] According to the preset chromosome SNP site density distribution requirement, the required target SNP site is determined from the first candidate site set, the second candidate site set, and the third candidate site set in sequence.

[0014] In conjunction with the second aspect, in one embodiment, determining the required target SNP site from the first candidate site set, the second candidate site set, and the third candidate site set in sequence according to the preset chromosome SNP site density distribution requirement comprises the following steps:

[0015] The chromosome is segmented according to a preset segmentation length to obtain windows constituting the chromosome;

[0016] According to the preset upper limit on the number of SNP sites in the window, SNP sites located within the window are selected as target sites from the first candidate site set, the second candidate site set, and the third candidate site set in descending order of priority until the target sites in each window reach the upper limit.

[0017] In combination with the second aspect, in one embodiment, according to the preset upper limit of the number of SNP sites in the window, the SNP sites whose position information is within the window are selected as target sites from the first candidate site set, the second candidate site set, and the third candidate site set in descending order of priority until the target sites in each window reach the upper limit of the number, comprising the following steps:

[0018] When the total number of SNP sites that can be selected as the target sites in the window combined with the target sites already selected in the window exceeds the upper limit, the SNP site with higher distribution uniformity is determined as the target site based on the distribution uniformity of the positions of the various SNP sites in the window.

[0019] In a third aspect, the present application provides a probe for detecting the SNP site combination of beef cattle as described above.

[0020] In a fourth aspect, the present application provides a gene chip for detecting the SNP site combination of beef cattle as described above, using the following scheme:

[0021] A gene chip for detecting the above-mentioned SNP site combination of beef cattle, wherein the gene chip contains a set of probes for detecting the above-mentioned SNP site combination of beef cattle.

[0022] In conjunction with the fourth aspect, in one embodiment, the gene chip is a liquid phase gene chip.

[0023] In a fifth aspect, the present application provides an application of the SNP locus combination of beef cattle as described above in genetic improvement breeding of beef cattle.

[0024] In combination with the fifth aspect, the SNP site combination of beef cattle as described above is used for genetic improvement breeding within specific breeds of beef cattle, including the application of genetic improvement breeding within the breeds of Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle, Simmental cattle, Limousin cattle, Charolais cattle and Angus cattle.

[0025] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0026] 1. This locus combination optimizes and integrates the specific gene loci of Hubei local beef cattle and a variety of foreign beef cattle breeds, and is associated with the main economic traits of beef cattle, reducing the number of SNPs that are not associated with these traits and reducing costs, making it have a high application value in the trait identification, prediction and molecular breeding of beef cattle within the covered breed range.

[0027] 2. The SNP sites involved in the site combination also include the common sites of many mature commercial chips. This makes this site combination have good coverage and the ability to be directly replaced when used in gene chips in the market, and has a high market value. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of the distribution of the SNP loci combination of beef cattle in this application on each chromosome;

[0029] Figure 2 Schematic diagram of a process for screening a combination of SNP loci for beef cattle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0032] In a first aspect, an embodiment of the present application provides a combination of SNP loci for beef cattle, which includes SNP loci corresponding to at least part of the physical location information in Table 1;

[0033] In Table 1, the number before the “_” of each SNP site is the chromosome where it is located, and the number after the “_” is the physical location information on the chromosome.

[0034] Table 1: Physical location information of SNP loci involved in the SNP locus combination of beef cattle

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[0157] In this embodiment, the SNP site combination of beef cattle provided is preferably the SNP site corresponding to the physical position information in Table 1. It should be noted that the key point of this application is the physical position information of these selected SNP sites, rather than the specific nucleotide information designed on these SNP sites. It is understandable that in the process of further obtaining molecular detection products using this SNP site combination, the corresponding nucleotide information designed on these SNP sites on different molecular detection products may be different. For example, those skilled in the art can design multiple sets of gene chips according to the physical position information of the SNP sites involved provided in this application, combined with their own detection needs. These gene chips will all be used to perform nucleotide detection on the DNA sample of the object to be detected according to this SNP site combination, so as to obtain the nucleotide information on the SNP sites at these physical positions, and the nucleotide information used for detection and pairing with the SNP sites at these physical positions in these gene chips can be designed independently by the technicians according to the needs and are not the same, and finally the information of each SNP site in the SNP site combination of beef cattle provided in this application can be obtained. Based on the above factors, the specific nucleotide information of these SNP sites is not disclosed by example in this application.

[0158] In a second aspect, the present application also provides a method for screening a combination of SNP loci in beef cattle as described above, which comprises the following steps:

[0159] S100, obtaining the location information of the SNP sites corresponding to the genome sequence of each breed in the target coverage breed set; wherein the target coverage breed set at least includes Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle, Simmental cattle, Limousin cattle, Charolais cattle and Angus cattle;

[0160] S200, obtaining the variety characteristic sites, genetic defect disease sites and important economic shape function sites in the SNP sites of each variety to form a first candidate site set;

[0161] S300, obtaining SNP sites involved in each of the multiple target compatible chips, and determining that among the SNP sites shared by the multiple target compatible chips, the SNP sites that are not repeated in the first candidate site set constitute a second candidate site set;

[0162] S400, according to the allele frequencies of all sites of each variety, determining that among the SNP sites whose allele frequencies are greater than a set frequency threshold, the SNP sites that are not repeated in the first candidate site set and the second candidate site set constitute a third candidate site set;

[0163] S500: According to a preset chromosome SNP site density distribution requirement, determine a desired target SNP site from the first candidate site set, the second candidate site set, and the third candidate site set in sequence.

[0164] Specifically, in the above step S100, firstly, 98 different breeds of Hubei local beef cattle (Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle) are selected in the core seed conservation farm, ranging from 14 to 28 heads of each breed, including breeding bulls and breeding cows, and the whole genome is resequenced 20× after extracting the ear tissue DNA. Then, the whole genome sequencing data of the introduced beef cattle breeds are downloaded from the public database of NCBI (Home-BioSample-NCBI (nih.gov)). Specifically, including: 67 Simmental cattle, 90 Limousin cattle, 45 Charolais cattle, 38 Angus cattle, the sequencing depth is 5.02-26.67, and the average sequencing depth is 8.50;

[0165] After obtaining the original genome sequence data of each variety in the above target coverage variety set, the obtained sequencing data will be processed in multiple steps, including: quality control of the original genome sequence data of each variety, including filtering out low-quality bases with a base quality of less than 10; removing adapter sequences in reads; when the content of unmeasured bases (N) in a single-end sequencing read is greater than 10% of the length ratio of the read, it is necessary to remove this pair of paired reads; when the number of low-quality bases contained in a single-end sequencing read exceeds 50% of the length ratio of the read, remove this pair of paired reads;

[0166] The quality-controlled genomic data of each breed in the target coverage population set will be further compared with the currently known beef cattle reference genome sequence (ARS-UCD1.2). The location of the quality-controlled genomic data on the reference genome can be located through comparison, and the location information of the SNP sites contained in the genomic data can be obtained. Among them, the sample comparison rate can reflect the similarity between the sample sequencing data and the reference genome;

[0167] After obtaining the high-quality SNP sites and physical information of the sites in each variety in the target coverage population set, these data will still be further SNP variation detection and screening optimization. Specifically, the GATK software is used to accurately mark the repeated sequences of the sequence data after alignment, identify and eliminate the repeated reads caused by PCR amplification errors, and significantly reduce the possibility of false positive variation detection. Through the HaplotypeCaller tool, potential SNP variations are identified and filtered. The filtering conditions are: eliminate variation sites with quality depth (QD) less than 2.0, overall quality (QUAL) less than 30.0, sequence repetition ratio (SOR) greater than 3.0, Fisher precision score (FS) greater than 60.0, mapping quality (MQ) less than 40.0, mapping quality rank sum (MQRankSum) less than -12.5, and read position rank sum (ReadPosRankSum) less than -8.0;

[0168] In addition, after the above process, further quality control of SNPs is required, including using vcftools to perform quality control on SNP sites, removing SNP sites with a detection rate less than 90% and a minimum allele frequency less than 0.05, and finally obtaining the SNP sites corresponding to the genome sequences of each variety in the target coverage variety set that can be screened and the position information corresponding to the SNP sites.

[0169] For step S200, in this embodiment, all the SNP sites after the above quality control are first used to screen the breed characteristic sites, and wFst, detla, and Informativeness for Assignment (In) analyses are performed according to five different populations (the five Hubei local beef cattle breeds are regarded as one population, and Simmental, Limousin, Charolais and Angus are regarded as one population respectively). The result scores of the analysis of each method are combined, and then the 4000 most representative sites are selected as the breed characteristic sites in the first candidate site set of the SNP site combination provided in this application.

[0170] Furthermore, by consulting the literature and manually analyzing the big data, the genetic defect disease sites (200) and the important economic trait-related functional sites (7993) that have been identified in the above quality-controlled data are used as the genetic defect disease sites and the important economic trait functional sites in the first candidate site set of the SNP site combination provided in this application;

[0171] Finally, it can be seen that the first candidate loci set screened out has a high value in the identification of each variety, genetic defect disease and important economic traits in the target coverage variety set.

[0172] For step S300, five commercial chips are selected in this embodiment, including: 50K chip (9913_ARS1.2_53218_SNP50V3_marker_name_180910), 60K chip (9913_ARS1.2_59825_ZOETIS1_marker_name_180910), 80K chip (9913_ARS1.2_76999_GGP90KT_marker_name_180910), 777K chip (9913_ARS1.2_777962_HD_marker_name_180910) and 150K chip (GGPSNP150K). The sites common to the five chips and the sites that do not belong to the first candidate site set are taken as the second candidate site set, and the total number of sites is 19459. Furthermore, full consideration is given to the compatibility design with the five existing commercial chips of Niu to ensure efficient connection with the self-test data during use.

[0173] For step S400, in this embodiment, the allele frequencies of all SNP sites of all individuals after quality control are calculated, and the sites with the minimum allele frequency greater than 0.2 and that do not belong to the first candidate site set and the second candidate site set are taken as the third candidate site set of the SNP site combination provided in this application, with a total of 7834583 sites.

[0174] Further, in one embodiment, the step S500, according to a preset chromosome SNP site density distribution requirement, sequentially determining the required target SNP site from the first candidate site set, the second candidate site set, and the third candidate site set, comprises the following steps:

[0175] S510, segmenting the chromosome according to a preset segmentation length to obtain windows constituting the chromosome;

[0176] S520. According to the preset upper limit on the number of SNP sites in the window, select SNP sites located in the window as target sites from the first candidate site set, the second candidate site set, and the third candidate site set in descending order of priority, until the target sites in each window reach the upper limit.

[0177] Among them, step S510 in this implementation specifically divides each chromosome of the cattle into 50K windows. Subsequently, the target sites in each window will be selected from the first candidate site set, the second candidate site set and the third candidate site set in turn according to the priority. It is ensured that the final SNP site combination can have a greater advantage in variety, economic traits, and genetic breeding, and can be compatible with various chips currently on the market.

[0178] Furthermore, in order to ensure that the SNP site combination finally selected has a good distribution on all chromosomes, the above steps require an upper limit on the number of SNP sites allowed to be selected in each window to avoid too many SNP sites being concentrated in the window of one chromosome. Based on this purpose, the present application further requires in step S520:

[0179] When the total number of SNP sites that can be selected as the target sites in the window combined with the target sites already selected in the window exceeds the upper limit, the SNP site with higher distribution uniformity is determined as the target site based on the distribution uniformity of the positions of the various SNP sites in the window.

[0180] Specifically, the above requirements can be regarded as satisfying the same rule in the process of selecting target sites in each window from the first candidate site set, the second candidate site set, and the third candidate site set. This embodiment takes the upper limit of the number of SNP sites in the preset window as 2 as an example to explain this rule. Since the upper limit is 2, the following situations may occur in each round of selection, and the corresponding selection methods to be adopted in this application are:

[0181] Case A: 0 or 1 SNP sites have been selected in the window in the previous round of selection. At this time, there are still 2 or 1 SNP sites that can be selected in the window. At this time, the specific number of SNP sites in the window (that is, the number of SNP sites that can be selected as target sites) will be determined from the candidate site set corresponding to this round to further subdivide the situation, and determine the specific selection method based on the subdivision situation:

[0182] A1: If the number is greater than the remaining quota of the window (2 or 1), it is necessary to perform density screening for each SNP site combination that may be selected in the window, see the following formula:

[0183]

[0184] In the above formula, S and E are the starting and ending positions of the window respectively; N i and N j is the position of the SNP site in the window; N i and N j The average value of the position;

[0185] Ultimately, to minimize SD 2 N i and N j will be retained as a target site;

[0186] A2: If the number is less than the remaining number of sites in the window (2 or 1), the 2 or 1 involved in the candidate site set corresponding to this round will be used as the target site of the window;

[0187] Case B: If two SNP sites have been selected in the previous round for this window (reaching the upper limit), the window ends the selection of the target site and no longer considers screening SNP sites from the next priority candidate site set.

[0188] In a third aspect, the present application provides a probe for detecting the SNP site combination of beef cattle as described above.

[0189] In a fourth aspect, the present application provides a gene chip for detecting the above-mentioned SNP site combination of beef cattle, and all the selected candidate sites are site-checked, and the parameters such as the complexity of the upstream and downstream sequences of the target site and the G content are mainly evaluated using the probe design method, and the final site is confirmed, and the relevant probes for detecting the above-mentioned SNP site combination of beef cattle and other parts of the gene chip are customized. In this embodiment, the gene chip is specifically a liquid phase gene chip.

[0190] In a fifth aspect, the present application provides an application of the above-mentioned SNP loci combination of beef cattle for genetic improvement breeding within a specific breed of beef cattle, including calculation of the association between each locus in the whole genome and the target trait, and calculation of the breeding value of the target individual with respect to the target trait, the target trait is such as growth traits (including birth weight, 6-month-old weight, etc.) and body size traits (such as body height, body oblique length, etc.), and the specific calculation steps of the above two parameters are as follows:

[0191] S600, performing gene detection on the target breed using the gene chip with the combination of SNP sites of beef cattle as described above;

[0192] S700, obtaining a phenotype of a target trait, wherein the phenotype of the target trait is obtained by detecting individuals of the target variety during their growth process;

[0193] S800, calculating the association between each site in the whole genome and the target trait;

[0194] Specifically, a mixed linear model was used for genome-wide association analysis, and the model is as follows:

[0195] y=μ+Wv+Xβ+Zg+e

[0196] Among them, y is the phenotype of the target trait; μ is the total mean; v is the single SNP marker effect; W is the SNP genotype matrix, coded as 0, 1, 2; β is the fixed effect, including the effects of field year and season, gender, etc.; X is the corresponding structure matrix; g is the normal distribution. The random polygenic effect of is the variance of the polygenic effect; G is the genomic kinship matrix, Z is the relationship matrix of the random polygenic effect, and e is the individual random residual.

[0197] S900, calculation of breeding value of target individual with respect to target trait; the calculation model is as follows:

[0198] y=μ+Xβ+Zg+e

[0199] Among them, y is the phenotype of the target trait; μ is the total mean; β is the fixed effect, including the effects of field year and season, gender, etc.; X is the fixed effect design matrix; g is the individual genome breeding value vector, that is, the breeding value of the target individual for the target trait, which obeys Where G is the genome kinship matrix, is the additive genetic variance; Z is the design matrix based on the genotype values; e is the individual random residual.

[0200] After obtaining the correlation between each site in the above-mentioned whole genome and the target trait, as well as the breeding value of the target individual for the target trait, the two can be used to select individuals for breeding and carry out improved breeding within the variety.

[0201] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0202] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0203] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0204] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0205] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0206] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A combination of SNP loci for beef cattle, characterized in that: The SNP site combination includes SNP sites corresponding to at least part of the physical location information in Table 1.

2. The SNP locus combination for beef cattle according to claim 1, characterized in that: The SNP site combination is the SNP site corresponding to the physical position information in Table 1.

3. A method for screening a combination of SNP loci in beef cattle as claimed in claim 1 or 2, characterized in that: It includes the following steps: Obtaining the location information of the SNP sites corresponding to the genome sequence of each breed in the target coverage breed set; wherein the target coverage breed set at least includes Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle, Simmental cattle, Limousin cattle, Charolais cattle and Angus cattle; Obtaining variety characteristic sites, genetic defect disease sites and important economic trait functional sites in the SNP sites of each variety to form a first candidate site set; Acquire the SNP sites involved in each of the multiple target compatible chips, and determine that among the SNP sites shared by the multiple target compatible chips, the SNP sites that are not repeated in the first candidate site set constitute a second candidate site set; According to the allele frequencies of all sites of each variety, determine that among the SNP sites whose allele frequencies are greater than a set frequency threshold, the SNP sites that are not repeated in the first candidate site set and the second candidate site set constitute a third candidate site set; According to the preset chromosome SNP site density distribution requirement, the required target SNP site is determined from the first candidate site set, the second candidate site set, and the third candidate site set in sequence.

4. The method for screening a combination of SNP loci in beef cattle according to claim 3, characterized in that: The method of determining the required target SNP site from the first candidate site set, the second candidate site set, and the third candidate site set in sequence according to the preset chromosome SNP site density distribution requirement comprises the following steps: The chromosome is segmented according to a preset segmentation length to obtain windows constituting the chromosome; According to the preset upper limit on the number of SNP sites in the window, SNP sites located within the window are selected as target sites from the first candidate site set, the second candidate site set, and the third candidate site set in descending order of priority until the target sites in each window reach the upper limit.

5. The method for screening a combination of SNP loci in beef cattle according to claim 4, characterized in that: The method comprises the following steps: selecting SNP sites whose position information is within the window from the first candidate site set, the second candidate site set, and the third candidate site set in descending order of priority according to the preset upper limit of the number of SNP sites in the window, until the target sites in each window reach the upper limit of the number, including the following steps: When the total number of SNP sites that can be selected as the target sites in the window combined with the target sites already selected in the window exceeds the upper limit, the SNP site with higher distribution uniformity is determined as the target site based on the distribution uniformity of the positions of the various SNP sites in the window.

6. A set of probes for detecting the SNP locus combination of beef cattle as claimed in claim 1 or 2.

7. A gene chip for detecting the SNP site combination of beef cattle as claimed in claim 1 or 2, characterized in that: The gene chip contains a set of probes for detecting the SNP site combination of the beef cattle as claimed in claim 1 or 2.

8. The gene chip of beef cattle SNP loci combination according to claim 4, characterized in that: The gene chip is a liquid phase gene chip.

9. Use of the beef cattle SNP locus combination as claimed in claim 1 or 2 in beef cattle genetic improvement breeding.

10. The use of the beef cattle SNP locus combination as claimed in claim 9 for genetic improvement breeding within a specific breed of beef cattle, characterized in that: It includes the application of genetic improvement breeding within the Zaobei cattle, Huangpi cattle, Yunba cattle, Enshi cattle, Yiling cattle, Simmental cattle, Limousin cattle, Charolais cattle and Angus cattle breeds.

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