CN117701722B - Cattle plateau adaptive breeding 10K liquid phase chip and application - Google Patents

Abstract

The invention relates to a 10K liquid phase chip for bovine plateau adaptive breeding and application thereof, belonging to the field of genome breeding, and comprising (1) development of a 10K SNP chip in the whole genome range of cattle: identifying bovine elevation association sites by continuous elevation bovine population genomics, screening bovine plateau adaptive 10K SNP sites by marking, designing a liquid chip and designing a probe, and further obtaining a 10K liquid chip; (2) The liquid phase chip (10K) with low cost and high flux genotyping effect is provided, the accuracy and the genotyping effect of the chip are high, the plateau adaptability problem faced by plateau cattle group breeding can be solved, a rapid and accurate molecular means can be provided for breeding plateau tolerant individuals, a reliable technical platform is provided for developing relevant genetic breeding works such as cattle stress resistance character breeding, the development of the plateau cattle industry in China is promoted, and theoretical reference and method guidance are provided for breeding other plateau animals.

Description

Cattle plateau adaptive breeding 10K liquid phase chip and application

Technical Field

The invention relates to the field of genome breeding, in particular to a 10K SNP sequencing typing liquid phase chip with adaptive plateau and application thereof.

Background

The targeted sequencing genotype detection (Genotyping by target sequencing, GBTS) technology is a novel detection technology for genotyping, can be used for genetic variation and genotype detection of animals, plants, microorganisms and the like, and is widely applied to the fields of molecular marker assisted selection, germplasm resource evaluation, gene positioning and cloning, genetic map construction and the like. GBTS includes a multiple PCR targeted sequencing genotype detection technology (GenoPlexs) and a liquid phase probe hybridization targeted genotype detection technology (GenoBaits), both of which can realize accurate capture of any position and any length section of a genome and can detect various genetic variations such as SSR, SNP, inDel at the same time. GBTS can have stronger targeting, higher site coverage and sample homogeneity, select specific targeting sites from a large number of genomic DNA for sequencing and genotype detection.

Plateau hypoxia adaptation is a series of morphological structure and physiological and biochemical change processes of species of the world plateau, which are irreversible and stable inheritance generated by adaptation to the plateau hypoxia environment. The blood physiological mechanisms of plateau hypoxia adaptation are mainly manifested by changes in the number of erythrocytes, hemoglobin concentration, oxygen binding capacity, etc., and domestic animals including Tibetan pigs (Kong et al 2019), tibetan sheep (Wei et al 2016; liu et al 2020), tibetan chickens (Nie et al 2005) and yaks (Wu et al 2015) have evolved unique physiological characteristics, such as superior blood oxygen transport system and high metabolic efficiency, to adapt to the low-oxygen living pressure.

Tibet cattle improvement began in the 80 s of the last century, and current advanced crosses of improved Tibet cattle (Holstein Niu XTibet cattle) have been made over the F3 generation. Through the progressive hybridization of more than 40 years, the coverage rate of 'yellow modified milk' reaches 80 percent, and the historical breakthrough is realized in the quantity and quality of the improvement. With the increase of the generation number of the improvement, the production performance of the improved Tibetan cattle is improved to a certain extent, such as growth speed, milk yield, lean meat percentage and the like. Along with the continuous progress of progressive hybridization, the proportion of the blood margin of Tibetan cattle is lower and lower, the adaptability of the hybridized offspring of high generation is obviously reduced, the death rate is about 20 percent, and the milk yield is only about 2300 kg. Therefore, no commercialized SNP chip is available in the breeding of the improved Tibetan cattle at present, the cross fixation and generation breeding of the improved population must be carried out, the gene and the locus of the hypoxia adaptation of the Tibetan cattle are excavated, the excellent blood system of the hypoxia adaptation of the Tibetan cattle is reserved, and the hypoxia tolerant individuals can be rapidly bred through a molecular breeding means.

Disclosure of Invention

The invention carries out whole genome measurement on continuous elevation cattle groups, identifies elevation association sites related to hypoxia adaptation of cattle, and carries out whole genome association analysis on blood physiology and blood rheological indexes and plateau adaptation SNP sites of third-generation individuals of improved Tibetan cattle. The liquid phase chip containing 10K loci is designed and developed preliminarily, so that efficient and reliable technical means are provided for developing genetic breeding work such as stress resistance traits of cattle, the method is convenient and quick, low in cost, the problem of long generation interval in the breeding process is reduced, and greater economic benefits are brought to farms.

In order to achieve the above purpose, the invention is realized by the following technical scheme:

The first aspect of the invention provides a bovine plateau adaptive breeding 10K liquid phase chip, which comprises 11637 SNP loci for probe design, wherein the SNP locus information for probe design is shown in table 1, and the version number of the whole genome sequence of a reference genome is as follows: bos taurus UMD 3.1.

The SNP locus in the bovine plateau adaptive breeding 10K liquid phase chip is obtained by the following method: first, genes and loci associated with altitude are screened by continuous altitude bovine population genomics analysis, specific methods: performing group genomics analysis on continuous elevation bovine species by three analysis methods of F _ST (3500-500 m), MEMEA and BayPass, and screening genes and loci associated with elevation; further preferably, the continuous altitude means 500m (Yingjiang, barley land), 1500m (Tengchong), 2500m (Lijiang), 3000m (Diqing) and 3500m (Goibojianda), and the bovine species is cattle; secondly, creating a liquid breeding chip based on the association sites; finally, based on the existing backcross and cross high-generation hybridization segregation population, the system determines the index of the blood physiological series related to hypoxia, uses the chip to implement the whole genome association analysis (GWAS) case of hypoxia physiology, further digs the hypoxia physiological association site, and verifies and improves the reliability of the chip. The research result can provide a molecular approach for solving the problem of low oxygen bottle neck facing the current plateau cattle breeding.

The second aspect of the invention provides a genotyping method of a 10K liquid phase chip for adaptive breeding of cattle plateau, comprising the following steps:

(1) DNA extraction: extracting blood DNA of cattle to be detected, detecting the purity and the integrity of the DNA of the extracted DNA sample, and accurately quantifying the concentration of the DNA;

(2) GenoBaits experimental procedure: randomly and physically crushing the DNA with qualified quality inspection by using an ultrasonic crusher, controlling the peak value of the crushed fragment to be 200-300bp, and connecting the crushed DNA with the tail A after the end repair; connecting the DNA fragment added with A with a sequencing joint by using ligase, purifying the library and selecting the fragment by using carboxyl modified magnetic beads, and reserving a connecting product of the inserted fragment in 200-300 bp; adding a sequencing primer with Barcode and a high-fidelity PCR reaction system into the connection product to carry out PCR amplification, wherein different Barcode are used for distinguishing different samples; the amplified product can be used for probe hybridization experiments after being purified by carboxyl magnetic beads.

(3) Library construction and on-machine sequencing: taking the sequencing library which is completely constructed, adding a probe and a hybridization reagent after freeze-drying, and placing the mixture at 65 ℃ for 2 hours after denaturation to complete hybridization reaction; washing the hybridization product, performing a round of PCR to complete the construction of a hybridization capture library, performing preliminary quantification by using Qubit2.0, and accurately quantifying the effective concentration of the library by using a qPCR method to ensure the quality of the library; and after the library is detected to be qualified, entering an on-machine sequencing stage, and finally obtaining the genotype of the target SNP.

The third aspect of the invention provides application of the liquid chip in genotype detection, whole genome association analysis and whole genome selective breeding of Tibetan cattle.

The invention has the beneficial effects that:

The invention is based on the group genomics analysis of continuous elevation cattle, identifies genes and loci associated with elevation, digs the plateau adaptation loci of Tibet cattle, and creates a low-cost high-throughput genotyping liquid chip (10K) based on the elevation-associated loci. According to the existing backcross and cross high-generation hybridization segregation population, the system determines the blood physiological index related to hypoxia, uses the 10K SNP chip to implement the whole genome association analysis (GWAS) case of hypoxia physiology, further digs the hypoxia physiological association site, and verifies and improves the reliability of the chip. The invention can solve the problem of low oxygen bottle neck faced by plateau cattle breeding, provides a quick and accurate molecular means for breeding plateau tolerant individuals, provides a reliable technical platform for developing relevant genetic breeding works such as cattle stress resistance character breeding and the like, promotes the development of the plateau cattle industry in China, and simultaneously provides theoretical reference and method guidance for breeding other plateau animals.

Drawings

FIG. 1 is a diagram of a main component cluster and population structure of cattle; in the graph, (A) a principal component cluster graph, wherein the principal graph is a first second principal component, the sub-graph is a third fourth principal component, and the contribution degree of each principal component is in brackets; (B) Group structure diagram, ancestor presumes K value from 2 to 5, each color represents an ancestor component, each vertical bar represents a cattle individual; the length of the color represents the proportion of the corresponding ancestor component.

FIG. 2 is a radicle adjacent tree between bovine individuals.

FIG. 3 shows the distribution of SNP sites on different chromosomes.

FIG. 4 is a uniform distribution diagram of SNP sites on different chromosomes.

FIG. 5 is a Gap analysis of the target site on the genome.

FIG. 6 shows the distribution of SNP sites in a gene structure.

FIG. 7 is SNP annotation statistics.

Fig. 8 is a sample principal component analysis.

Detailed Description

In order to make the objects, technical solutions and advantageous effects of the present invention more apparent, preferred embodiments of the present invention will be described in detail below to facilitate understanding by the skilled person.

Example 1 preparation of cattle plateau adaptive Breeding low-Density 10K SNP liquid phase chip

1. Continuous elevation bovine population sample sampling

The invention selects Tibetan cattle (3500 m) and Yunnan local cattle (3000-2500-1500-500) with different elevation gradient distribution, wherein each elevation is respectively provided with 20 heads, the specific sample information is 20 heads collected in the Tibetan autonomous region Gongbujiangda county (GB) with the elevation of 3500 m; 20 heads are collected in the autonomous state (DQ) of the Diqing Tibetan family of Yunnan province with the altitude of 3000 m; 10 heads are collected in the old junshan region (JS) of Wenshan in Yunnan province and the Lijiang city region (LJ) of Yunnan province with the altitude of 2500 m; 10 heads are collected in Yunnan province Tengchong City (TC) and Yunnan province and county area (WD) with the altitude of 1500 m; 10 heads are collected in the two-cypress county barley town (SB) of the Yunnan province and the Yingjiang county region (YJ) of the Yunnan province at the altitude of 500 m. Jugular vein blood sampling was performed using a vacuum blood collection tube containing EDTA anticoagulant, 5ml, and DNA was extracted for whole genome resequencing.

2. Bovine whole genome resequencing

2.1DNA extraction

The procedure was performed using the blood genomic DNA extraction kit (tiangen biochemical technology, DP 348) according to the instructions to extract the genomic DNA of cattle.

2.2 Detection of genomic DNA

DNA detection was performed using a 1% agarose gel, which was formulated with nucleic acid dye, using a Maker DL2000. Electrophoresis was performed in a1 XTAE buffer at 120V for about 30 min. And after electrophoresis is completed, a gel imaging system is used for observation and photographing, and a DNA result picture is stored.

2.3 Huang Niuquan genomic resequencing

Breaking the DNA sample which is qualified in detection into fragments of 300-500 bp, then carrying out terminal modification, adding an Illumina sequencing joint, selecting products of 400-500 bp through 2% gel electrophoresis, then carrying out LM-PCR amplification, and preparing a sequencing library. Library sequencing was performed using an Illumina HiSeq2500 platform for double-ended sequencing with a sequencing coverage of about 5X per individual genome, with a sequencing data volume of no less than 15G, and the entire sequencing flow was controlled by Illumina HiSeq Control Software software. Genome re-sequencing was done by beijing berui and kang biotechnology Co., ltd (Beijing, china).

2.4SNP calling and sequence alignment

Firstly, performing quality control on sequencing original machine-down data, removing bases with sequencing quality less than 20 (namely sequencing accuracy lower than 99%) in reads, and discarding reads with length less than 35bp after trimming. For quality controlled data, the data were aligned to the corresponding reference genome (Bos taurus UMD 3.1) using the Burrows-Wheeler-ALIGNMENT (BWA) software (Li & Durbin, 2010), resulting in aligned bam files, and the samtools software (Li et al, 2009) was used to sequence and tag the repeat sequences. Next, a standard procedure of Genome Analysis Toolkit (GATK) v3.7 (MCKENNA ET al, 2010) was performed SNP CALLING to obtain a high quality set of genetic variation information. First, VARIANTS CALLING is carried out by utilizing HaplotypeCaller in GATK, and a mutation information set g.vcf file of an individual is generated. The g.vcf files for all individuals were pooled and joint calling was performed using GenotypeGVCFs to obtain variation information for this population and the exact genotype for each individual. The variation information is then quality controlled by hard filtering (HARD FILTERING) due to the lack of a high quality set of known variations as a reference. Using SELECTVARIANTS command split SNP (single nucleotide polymorphism) and InDel (Insertion-delivery), for the initial SNP file split, using VariantFiltration command filter out SNP information that does not meet quality conditions, generating the final VCF file. For VCF files with a filter parameter of "-cluster 3-window 20;QD<2.0;QUAL<30;MQ<40.0;FS>60.0;SOR>3.0;MQRankSum<-12.5;ReadPosRankSum<-8.0;DP<10;--missing-values-evaluate-as-failing true"., further SNP quality control was performed using plinkv1.90b (Chang et al 2015), SNPs with multiallelic, deletion rate greater than 10% and minimal allele frequency of 0 were knocked out, individuals with SNP deletion rate greater than 20% were knocked out, and the quality controlled data were used for subsequent analysis.

The cattle genome gff file was then downloaded from Ensemble and SNP annotated with ANNOVAR software.

3. Population structure and genetic relationship and polymorphism level assessment

To assess cattle population structure, the obtained SNP data was subjected to linkage disequilibrium (linkage disequilibrium, LD) filtration using Plink software (Purcell et al, 2007) and low-linkage SNPs were retained (r 2< 0.3). Principal component analysis was performed on the filtered data using smartpca in the EIGENSOFT (Price et al, 2006) software package. Next, group structure analysis was performed using ADMIXTURE (Alexander et al 2009) software, where the number of groups parameter K was set from 2 to 5. To evaluate the relationships between individuals, identity By State (IBS) distance between individuals is calculated based on Plink software, and a Neighbor-joining tree (MEGA, et al, 2016) is constructed using MEGA (Kumar, et al) software, thereby exploring the relationships between individuals.

Through principal component analysis, it was found that the I.Bujiangda and Diqing populations could be completely separated from the other populations by the first and second principal components, but the Diqing populations were more dispersed, but the trends remained consistent. Other groups are mixed with each other, especially Wuding group, tengchong, barley, junshan and Lijiang, and show abnormality. However, if divided by altitude, the Wuding population is excluded, and 2500m (Lijiang, junshan) can be grouped into one class and separated from the other. Of the three remaining populations, the barley population could be singly grouped into one class, but the Tengchong Yingjiang had individual individuals present confounding, and even with the addition of the third and fourth principal components, two Yingjiang individuals were mixed with Tengchong, indicating that 1500m and below populations, possibly closely related, were not easily separable (FIG. 1A).

To further resolve the population structure, a population structure analysis was performed using ADMIXTURE software, assuming 2-5 ancestor components. When k=2, the cattle population is bounded by 3000m, with more than 3000m worker and diligent populations as a group, and less than 3000m populations as a group. When k=3, the junshan and lijiang at 2500m are independent, and the armed population at 1500m is not similar to TC population at the same altitude, but rather closer to junshan and lijiang populations. When k=4, the dirties at 3000m separate into one class. When k=5, the population at 3000m had more complex genetic background, soaring and Yingjiang could still be grouped into one class, the genetic background inside the remaining populations was not completely consistent, and the genetic background of the diqing population at 3000m was also complicated (fig. 1B). In combination with the results of PCA and ADMIXTURE, the population genetic relationship between each elevation is more similar, so that in subsequent analysis, the elevation is classified. However, since the armed population exhibits an abnormal distribution, it is excluded to reduce the interference of the later analysis. In order to further explore the relativity among individuals, an adjacent tree is constructed by utilizing the IBS distance among individuals, and the group is found to be approximately divided into three branches, one class of worker cloth, one class of Diqing and one class of group below 3000 m. Wherein the population below 3000m is mixed with each other, lijiang and Junshan are mixed together, but can be calculated as 2500m population. Yingjiang, barley, although each cluster, the populations below 1500m are still mixed up by altitude division, which may be less geographically separated from the low altitude populations, facilitating genetic communication between the populations, and thus leading to closer relatedness (fig. 2).

4. Screening method for hypoxia-tolerant sites of Tibetan cattle

4.1 Natural selection based on detection of the degree of differentiation between populations

There are many statistics in population genetics that measure the degree of differentiation between populations, the most common being the F _ST index. In population genetics, F-statics is an index for measuring whether the actual frequency of genotypes in a population deviates from the theoretical proportion under the Hash temperature balance, and F _ST index is evolved from F-statics and represents the inbreeding coefficient of a subgroup relative to the total population, namely the average inbreeding coefficient among related subgroups. in practice, it is assumed in advance that the vast majority of genotypes are marked as neutral sites, followed by identification of the overdifferentiated loci from the extreme tail of the empirical distribution of the F _ST indices. There are a number of ways of calculating the F _ST index, in this study we used VCFtools v0.1.13 to calculate the F _ST index, which was estimated according to the method proposed by Weir and Cockerham in 1984, Including a single site F _ST index and a window F _ST index (window size 20kb, step size 5 kb). the value range of the F _ST index is 0-1, and the larger the value is, the larger the differentiation degree among the populations is. When the F _ST index is 1, it indicates that the alleles are fixed in the respective populations, fully differentiated; when the F _ST index is less than 0, no specific biological explanation exists and the biological explanation can be omitted; When the F _ST index is 0-0.05, the differentiation degree among the groups is small and can be ignored; when the F _ST index is 0.05-0.25, the intermediate differentiation exists among the populations; when the F _ST index is greater than 0.25, it is shown that the degree of inter-population differentiation is great, and is a potential positive selection site. The high-low population cattle were compared and their top1% window was set as the potential candidate window.

4.2 Allele frequency and altitude association analysis

Plateau adaptation is a process of micro-evolution of animals under hypoxic conditions based on changes in allele frequency, in which animals are physiologically or ecologically directionally regulated and the adaptation of the whole species to the environment is mediated by genetic mechanisms, all of which are reflected in changes in allele frequency. The altitude is the optimal environmental variable for representing the selective pressure intensity of the low-oxygen environment, and the candidate loci responding to the environmental adaptability constraint can be detected by carrying out correlation analysis on the allele frequency and the altitude of the continuous altitude group, and meanwhile, the inherent differentiation loci caused by the group history and genetic drift are eliminated, so that the screening range of the candidate genes is effectively narrowed. In this study, we used two methods, the environmental adaptation site detection, of the environmental adaptation mixed effect model (Mixed Effect Model for Environmental Adaptation, MEMEA) (Wu Fuquan, 2018) and BayPass (Gautier, 2015) developed by the subject group.

Based on the population genetics method, likelihood estimation is used to build MEMEA method, and the model can be used for detecting genetic polymorphic sites subjected to environmental adaptability selection among populations under specific environmental variable gradients. The method adopts multielement normal distribution to identify SNP loci with allele frequencies selected by environmental factors, and allows adjacent loci to be subjected to different selection intensities by introducing random effect u among loci. Meanwhile, the method fully considers genetic loading effect, and a sliding window mode is used for detecting the site subjected to environmental selection pressure. In the present invention, the detection of the environmental adaptation site was performed by expanding 10kb in the front-back direction with each SNP as the center as a window.

BayPass is a set of group genomics analysis software that, based on bayesian theory, identifies genetic markers that are undergoing natural selection or are highly correlated with target group covariates (e.g., environmental variables, quantity, or quality phenotypic characteristics). BayPass software was based on the BayEnv model published Coop et al (2010) (Coop et al, 2010). The BayEnv model can identify both natural selection sites and further annotate the screened selection imprint by quantifying the association with specific population covariates, with the most critical parameter being the covariance matrix across population allele frequencies. BayPass are improved in three ways: (1) The estimation of the overall covariance matrix and different relevant metrics is more accurate; (2) A posterior procedure based on XtX statistic calibration is proposed to detect sites where adaptation occurs; (3) A model with binary auxiliary variables was introduced to classify each locus as either associated or unassociated.

Both methods are based on allele frequency data, so before analysis, we first reject Gao Queshi-rate SNP sites, and if the rate of deletion of a certain SNP in any altitude population is greater than 10%, then reject the SNP sites in all altitude populations to eliminate the influence of excessive deletion rate on analysis results. Both types MEMEA and BayPass of software essentially perform regression analysis to screen SNP sites highly correlated with environmental factor trends. The MEMEA model considers the carrying effect, effectively reduces the false positive rate, but is sensitive to the locus with the allele frequency of 0 in the subgroup, so that the locus score value is higher; bayPass mainly considers the elevation trend of single sites, and the screened environment adaptability sites have higher false positives.

5. Design and development of low density liquid phase chip

5.1 Optimized screening of 10K SNP markers

In the invention, two analysis methods MEMEA and BayPass are integrated, genetic polymorphic sites subjected to environmental adaptability selection among groups under continuous elevation gradient are detected, and then the analysis results of single site F _ST are combined for mutual verification and complementation, so that candidate sites of the three analysis methods are intersected. F _ST sliding window results (20 kb window, 5kb step length) are calculated through vcftools software, fst windows with top1% are combined into a region (overlapped or separated by less than 20 kb), bayPass, MEMEA and single-point F _ST intersection sites are included in the region and are converted onto a reference genome ARS-UCD1.2 as hypoxia adaptation related SNP, 11637 SNP sites related to hypoxia tolerance characters of the cattle are finally screened, and site information is shown in table 1.

TABLE 1SNP site information Table

Description of SNP sources: SNP sequence numbers 0001-8151 are 10K in origin; SNP sequence numbers 8152-11636 are 4K in origin; SNP sequence number 11637 is from 4K &10K.

5.2 Synthesis of probes

Screening and checking target site information, designing and synthesizing probes, testing and adjusting the probes, and determining final probes and capture sites.

According to the DNA complementation principle, one or more probes covering the target 10K SNP are designed at each site to be detected, the probes modified by Biotin (Biotin) can be hybridized with a target region in a denatured resequencing library to form double chains, and the streptavidin-coated magnetic beads are used for adsorbing molecules carrying the Biotin, and finally the genotype of the target SNP is obtained through elution, amplification and sequencing.

5.3 Detection of bovine plateau adaptive breeding chip

Regarding the frozen semen improvement F3 generation of Holstein cattle as cattle to be detected.

(1) DNA extraction: 10 modified Tibetan cattle blood DNA are extracted by adopting a high-throughput DNA extraction kit. The extracted DNA samples were subjected to 2 assays: the purity and integrity of the DNA was analyzed using a 1% agarose gel electrophoresis method; the DNA concentration was accurately quantified using Qubit. The purity is OD260/280 more than or equal to 1.8, and the result shows that the DNA sample is complete and the total DNA amount is more than or equal to 0.5ug as qualified quality inspection through agarose gel electrophoresis detection.

(2) Library construction and on-machine sequencing: and (3) taking DNA qualified in quantitative quality inspection, carrying out random physical crushing by using an ultrasonic crusher, controlling the peak value of the crushed fragments to be 200-300bp, and connecting the crushed DNA with the A tail after terminal repair. The DNA fragment added with A is connected with a sequencing joint by using ligase, then the library is purified and fragment selected by using carboxyl modified magnetic beads, and the connection product of the inserted fragment between 200 and 300bp is reserved. The ligation products were added to sequencing primers with Barcode and a high-fidelity PCR reaction system for PCR amplification, and different Barcode were used to distinguish between different samples. The amplified product can be used for probe hybridization experiments after being purified by carboxyl magnetic beads.

Taking 500ng of the sequencing library which is constructed, adding a probe and a hybridization reagent after freeze-drying, and placing the mixture at 65 ℃ for 2 hours after denaturation to finish hybridization reaction. After washing the hybridization product, performing a round of PCR to complete the construction of a hybridization capture library, performing preliminary quantification by using Qubit2.0, and accurately quantifying the effective concentration of the library by using a qPCR method to ensure the quality of the library. And after the library is detected to be qualified, entering an on-machine sequencing stage.

Chip performance detection analysis: the targeted sequencing genotyping (Genotyping By Target Sequencing, GBTS) technology is a technology for deep resequencing of target sites, and has stronger targeting, higher site coverage and sample uniformity. The detection rate of 10 samples was 96.69-99.79%, the average detection rate was 99.88%, and the test performed well (FIGS. 3-6).

Example 210K evaluation of SNP liquid phase chip

1. Blood sample collection and physiological index measurement

The 1551 modified Tibetan cattle blood was collected, and within 4 hours, the normal index 11 items of blood and the viscous index 13 items of blood were measured by using a veterinary full-automatic blood analyzer (BC-30 Vet) and an automatic blood rheology tester (ZL 6000), and the detailed indexes are shown in the following table 2.

TABLE 2 blood physiological index to be measured

2. Liquid phase chip evaluation

And (3) extracting 1551 modified Tibetan cattle blood DNA by using a high-throughput DNA extraction kit, and carrying out genotyping on a quality control qualified sample by using a 10K SNP liquid-phase chip.

Gwas analysis

The original sequenced sequence (raw reads) obtained from the sequencing was filtered using software fastp [2] (version 0.20.0, parameter: -N10-q 20-u 40), including removal of the linker sequence, requiring removal of the pair PAIRED READS when the N content in the sequencing read exceeds 10% of the length of the strip; when the number of low-mass (Q.ltoreq.20) bases contained in a sequencing read exceeds 40% of the length proportion of the strand, the pair PAIRED READS needs to be removed. CLEAN READS was obtained and used CLEAN READS for subsequent analysis. Comparing CLEAN READS after quality control with a reference genome (Bos taurus UMD 3.1) sequence by using software BWA, and performing mutation detection by using a UnifiedGenotoyper module of software GATK (version v3.5-0-g36282e 4) according to the comparison result of CLEAN READS in the reference genome, wherein detection parameters are as follows: "-dcov 1000000-MININDELFRAC 0.15-glm BOTH-l INFO. Filtering by using a VariantFiltration module, extracting genotype information of SNP loci by using self-compiled Perl script according to the filtering parameters of :--filterExpression"MQ0>＝4&&((MQ0/(1.0*DP))>0.1)"--filterName"HARD_TO_VALIDATE"--filterExpression"DP<5||QD<2"--filterName"LOW_READ_SUPPORT". comparison result and mutation result, and expressing NA in a table when the coverage depth of a sample at a certain SNP locus is less than 5X to indicate that the sample is insufficient in sequencing depth at the locus so as to ensure accurate genotype typing result; when a sample has mutation in the genotype of a certain SNP locus, the mutation frequency of the locus needs to be judged, if the mutation frequency is more than or equal to 0.8 or less than or equal to 0.2, the locus is homozygous, if the mutation frequency is between 0.2 and 0.8, each allele in the heterozygous genotype is supported by at least 4 reads, the SNP locus is heterozygous mutation, otherwise, the locus is treated according to deletion. Functional annotation of SNP sites was performed using ANNOVAR (fig. 7). And carrying out principal component analysis on the detection samples subjected to subsequent association analysis, and removing the outlier group. As shown in fig. 8, the samples are basically not clustered, and the actual situation of the samples is met.

GWAS analysis was performed using a linear regression model (GLM) general linear model in Tassel software, the model was as follows:

y＝Wα+xβ+ε

in the formula, y represents the phenotype to be studied, namely, blood routine and blood rheological indexes in the study; wα is the fixed effect (age, sex and feeding level), other factors affecting y, mainly population structure; x beta is the labelling effect; epsilon represents the residual error.

The liquid phase chip for the hypoxia tolerance site is prepared to carry out whole genome association analysis on the phenotype of the blood physiological index of the Tibetan modified cow, GLM (global stem cell) of Tassel software is adopted to carry out analysis, the number of marker sites which are obviously related to the data of the blood physiological index of the Tibetan modified cow is 1930, the number of candidate genes is 21, and the genes are related to membrane generation, angiogenesis, development, erythrocyte shape, tumor, central nervous system, skeletal development and the like.

Finally, it is noted that the above-mentioned preferred embodiments illustrate rather than limit the invention, and that, although the invention has been described in detail with reference to the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention as defined by the appended claims.

Claims (4)

1. Cattle plateau adaptation breeding 10K liquid phase chip, its characterized in that: the 10K liquid phase chip for bovine plateau adaptive breeding comprises probes for detecting 11637 SNP loci, SNP locus information designed by the probes is shown in a specification table 1, and the version number of the whole genome sequence of a reference genome is as follows: bos taurus UMD 3.1.

2. The bovine plateau adaptive breeding 10K liquid phase chip of claim 1, wherein: the chip is obtained by the following method:

s1: collecting continuous elevation cattle for whole genome sequencing, wherein continuous elevation distribution comprises 500m, 1500m, 2500m, 3000m and 3500m, carrying out population genomics analysis on continuous elevation cattle population by using three analysis methods of F _ST, MEMEA and BayPass, and screening 11637 loci associated with elevation;

S2: screening out the sea-tangle related sites according to the S1, designing one or more probes covering the target 10K SNP at each site to be detected according to the DNA complementation principle at the position of the binding site on the whole genome;

S3: the chip was developed using a targeted sequencing genotyping technique.

3. The use of the bovine 10K liquid chip of claim 1 in genotyping, whole genome association analysis, whole genome in hypoxia tolerance of cattle.

4. The genotyping method of the bovine plateau adaptive breeding 10K liquid phase chip according to claim 1, wherein: the method comprises the following steps:

(1) DNA extraction: extracting blood DNA of cattle to be detected, detecting the purity and the integrity of the DNA of the extracted DNA sample, and accurately quantifying the concentration of the DNA;

(2) GenoBaits experimental procedure: randomly and physically crushing DNA by using an ultrasonic crusher, controlling the peak value of a crushed fragment to be 200-300bp, and connecting the crushed DNA with the tail A after the end of the crushed DNA is repaired; connecting the DNA fragment added with A with a sequencing joint by using ligase, purifying the library and selecting the fragment by using carboxyl modified magnetic beads, and reserving a connecting product of the inserted fragment in 200-300 bp; adding a sequencing primer with Barcode and a high-fidelity PCR reaction system into the connection product to carry out PCR amplification, wherein different Barcode are used for distinguishing different samples; the amplified product after purification of carboxyl magnetic beads can be used for probe hybridization experiments;

(3) Library construction and on-machine sequencing: taking the sequencing library which is completely constructed, adding a probe and a hybridization reagent after freeze-drying, and placing the mixture at 65 ℃ for 2 hours after denaturation to complete hybridization reaction; washing the hybridization product, performing a round of PCR to complete the construction of a hybridization capture library, performing preliminary quantification by using Qubit2.0, and accurately quantifying the effective concentration of the library by using a qPCR method to ensure the quality of the library; and after the library is detected to be qualified, entering an on-machine sequencing stage, and finally obtaining the genotype of the target SNP.