A low-density liquid-phase SNP chip for Laoshan dairy goats and its application

Abstract

The invention discloses a Laoshan dairy goat low-density liquid-phase SNP chip and application thereof, belonging to the technical field of molecular detection; the SNP chip comprises 1792 SNP sites, and the Laoshan dairy goat low-density liquid-phase SNP chip of the invention can be used to identify the kinship of a Laoshan dairy goat group, avoid inbreeding, guide the breeding work of Laoshan dairy goats, and improve the economic value of Laoshan dairy goats.

Description

Technical Field

[0001] The invention relates to the technical field of molecular detection, and more particularly to a Laoshan dairy goat low-density liquid-phase SNP chip and application thereof. Background Art

[0002] Due to the small size of breeding stock groups and incomplete pedigree records, inbreeding often occurs in my country's local livestock breeds. Inbreeding can lead to a decline in livestock production performance, and in severe cases it can lead to inbreeding depression, resulting in higher economic losses.

[0003] The Laoshan dairy goat originated in the Jiaodong Peninsula of Shandong Province and is mainly distributed in Laoshan and surrounding cities. It is a local fine breed with high milk production performance that has been cultivated by the people in the Laoshan area for many years. It is one of the fine varieties of Chinese dairy goats. The Laoshan dairy goat has the characteristics of strong adaptability, high milk production performance, strong disease resistance, and low breeding costs. By identifying the blood relationship between different populations of Laoshan dairy goats, we can better study and breed Laoshan dairy goats.

[0004] Currently, the methods that can be used to identify the blood relationship between different populations of Laoshan dairy goats include RFLP, RAPD, minisatellites, microsatellites, SNP chips, etc. RFLP is the earliest developed DNA marker. It has only two alleles at the same locus, the polymorphism is not high enough, and the determination method is relatively complicated. It has rarely been used in recent years. RAPD cannot distinguish between homozygotes and heterozygotes, and the marker primers are very short, which can easily produce artificial amplification products, so the stability and repeatability are poor. Microsatellites and minisatellites have the problem of high mutation rates and invalid allele detection rates. When the heterozygosity is low or there are fewer sites, the reliability and accuracy of their pedigree reconstruction needs to be improved. SNP markers have been proven to be more agile and accurate, making SNP chips a method with a wide coverage and more accurate kinship identification.

[0005] At present, all goat SNP chips on the market are medium-to-high density solid-phase chips with a density of more than 10K, which can theoretically meet the requirements of Laoshan dairy goat kinship identification. However, since these chips scan a wide range of genomes with high density, the cost of use is high, and the workload of data analysis is large, their application in dairy goat breeding practice is limited to a certain extent. In addition, there are obvious differences in the number and sites of SNP molecular markers of different goat breeds; therefore, it is extremely necessary to develop a low-density SNP chip specifically for Laoshan dairy goats to improve the breeding efficiency of this breed. Summary of the invention

[0006] In view of this, the present invention provides a Laoshan dairy goat low-density liquid-phase SNP chip and application thereof.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A low-density liquid phase SNP chip for Laoshan dairy goats, characterized in that it includes 1792 SNP sites; the information of the 1792 SNP sites is shown in Table 1:

[0009] Table 1

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[0031] The application of the above-mentioned Laoshan dairy goat low-density liquid phase SNP chip in the breeding of Laoshan dairy goats.

[0032] Application of the above-mentioned Laoshan dairy goat low-density liquid phase SNP chip in the analysis of kinship of Laoshan dairy goats.

[0033] From the above technical solution, it can be known that the present invention discloses a Laoshan dairy goat low-density liquid-phase SNP chip, which is specific to Laoshan dairy goats and can be used to efficiently, quickly and low-costly identify the kinship of the Laoshan dairy goat population, avoid inbreeding, guide the breeding of Laoshan dairy goats, and improve the economic value of Laoshan dairy goats. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0035] Figure 1 The accompanying drawing is a statistical diagram of effective enzyme cutting length;

[0036] Figure 2 The attached figure is a statistical chart of the number of tags;

[0037] Figure 3 The attached figure is a statistical diagram of the comparison between sequencing data and reference genome;

[0038] Figure 4 The accompanying drawing shows the working principle of hybridization detection;

[0039] Figure 5 The attached figure is a sample cluster diagram drawn based on the PCA results;

[0040] Figure 6 The attached figure is a sample 3D cluster diagram drawn based on the PCA results;

[0041] Figure 7 The attached figure is a cross-validation error rate line graph;

[0042] Figure 8 The attached figure is a bar graph of the genetic composition of the samples;

[0043] Fig. 9 The attached figure is a phylogenetic tree diagram drawn by adding genetic distance parameters;

[0044] Fig.10 The attached figure is a kinship heat map;

[0045] Fig.11 The attached figure is the evolutionary tree of the Laoshan dairy goat population. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1 Simplified genome sequencing

[0048] 1. Sample DNA extraction and quality inspection

[0049] 300 Laoshan dairy goats of different populations were selected and blood genomic DNA was extracted using the GenoPrep Plant DNA Extraction Kit (Cat. No.: PD001-100) from Shijiazhuang Boredy Biotechnology Co., Ltd.:

[0050] Place an appropriate amount of blood in a 96-well plate, add 600μL lysis buffer, shake and mix, place in a 65℃ water bath for 30min, and shake 3-5 times during the period. Centrifuge at 4000rpm for 10min, take 300μL supernatant to a new deep-well plate; add 500μL PBD, shake and mix, and let stand at room temperature for 5min; add 200μL PP, shake and mix, and let stand at room temperature for 2min. Centrifuge at 4000rpm for 10min, take 800μL supernatant to the recovery column, start the vacuum pump, filter out the waste liquid; then add 600μL WBI and let stand for 2min; start the vacuum pump and filter out the waste liquid; add 600μL WBII and let stand for 2min; start the vacuum pump and filter out the waste liquid and repeat once. Centrifuge at 4000rpm for 5min, let stand at room temperature for 30min, and dry the residual ethanol. Finally, 80 μL of TE buffer (preheated at 65° C.) was added to the membrane of the recovery column, placed at room temperature for 10 min, centrifuged at 4000 rpm for 5 min, and recovered to a new PCR plate to complete DNA extraction.

[0051] The DNA concentration was determined by Qubit Fluorometric Quantitation (Thermo Fisher), and the integrity of the DNA was detected by 1% agarose gel electrophoresis. The qualified samples were stored in a 4°C refrigerator for future use.

[0052] 2. RAD Experiment

[0053] RADseq (Restriction-site associated DNA sequencing) is a simplified genome sequencing technology based on whole genome restriction sites developed on the basis of second-generation sequencing. It is a general term for simplified genome sequencing technologies. RADseq is not only simple to operate and cost-effective, but more importantly, it does not rely on the information of the reference genome. Tens of thousands of polymorphic genetic markers can be obtained in one sequencing. It is suitable for population evolution, polymorphism maps, genetic map construction (QTL positioning), trait association and auxiliary scaffold assembly to chromosomes and other analyses. It is widely used in the fields of systematic evolution, molecular breeding, and germplasm resource identification.

[0054] The present invention takes 25 Laoshan dairy goats of different populations as samples, and uses the selected endonuclease to perform enzyme digestion on the genome according to the selected enzyme digestion scheme. The enzyme-cut fragments are connected to the P1 and P2 connectors, and the DNA fragments with a size of 200-400bp are recovered. The library is enriched by PCR amplification and the index sequence is introduced. After the library passes the quality inspection, it is sequenced on the machine; information analysis is carried out according to the sequencing results. The main contents of the information analysis process are: after the sequencing data quality control, high-depth individual RADtag clustering is performed, compared with the reference genome, and variation detection and screening are performed; the details are as follows:

[0055] 1) Electronic enzyme digestion evaluation

[0056] The double enzyme digestion combination used was EcoRI (GAATTC)-MseI (TTAA), and the restriction site was (5'—G|AATTC—T|TAA—3'). A total of 16,839,694 restriction fragments were detected on the genome, and the number of effective restriction fragments (i.e., fragments of 200 to 400 bp) was 317,989. The statistical results are as follows Figure 1 .

[0057] 2) Sequencing data quality control

[0058] The original sequenced reads or raw reads obtained by sequencing contain low-quality reads with adapters. For the second-generation sequencing technology, the sequencing error rate distribution has the following two main reasons: 1) Due to the consumption of chemical reagents during the sequencing process, the sequencing error rate will increase with the increase of the length of the sequenced reads. 2) Incomplete binding of random primers and DNA templates during PCR may lead to a high sequencing error rate for the first few bases. In order to ensure the quality of information analysis, raw reads must be filtered to obtain clean reads, and clean reads are used for subsequent analysis.

[0059] Specifically, the raw reads were filtered using the software fastp (version 0.20.0, parameters: -n 10-q 20-u 40), and the steps of data processing were as follows:

[0060] A. Remove the adapter sequence;

[0061] B. When the N content in the sequencing read exceeds 10% of the read length ratio, the paired reads need to be removed;

[0062] C. When the number of low-quality (Q≤20) bases in a sequencing read exceeds 40% of the length of the read, the paired reads need to be removed.

[0063] 3) Enzyme digestion output data statistics

[0064] The reads captured by the double restriction enzyme combination EcoRI (GAATTC)-MseI (TTAA) and restriction enzyme cutting site (5'—G|AATTC—T|TAA—3') in the Clean reads were counted.

[0065] 4) Tag clustering

[0066] The stacks module of the Stack software was used to assemble (cluster) the read1 of each sample and cluster tags according to sequence similarity. The number of tags for each sample is counted as follows: Figure 2 shown.

[0067] 5) Reference sequence comparison analysis

[0068] Use the software BWA (mem alignment method) to align the clean reads after quality control with the reference genome sequence. The alignment can locate the position of the clean reads on the reference genome. The sample alignment rate can reflect the similarity between the sample sequencing data and the reference genome. The results are as follows: Figure 3 As shown in the figure, the higher the align_rate is, the higher the similarity between the sample sequencing data and the reference genome is.

[0069] 6) SNP test results

[0070] SNP stands for Single Nucleotide Polymorphisms, which refers to a genetic marker formed by the variation of a single nucleotide in the genome. It is numerous and rich in polymorphism, and is one of the most polymorphic genetic variations in the genome.

[0071] According to the alignment results of Clean Reads in the reference genome, the UnifiedGenotyper module of the GATK (version v3.5-0-g36282e4) software was used to detect variations (SNPs, InDels) with the following detection parameters: "-dcov1000000-minIndelFrac 0.15-glm BOTH-l INFO". The VariantFiltration module was used for filtering with the following filtering parameters: --filterExpression"MQ0>=4&&((MQ0 / (1.0*DP))>0.1)" --filterName"HARD_TO_VALIDATE" --filterExpression"DP<3||QD<2" --filterName"LOW_READ_SUPPORT".

[0072] A total of 117,940 SNP markers were detected. The above comparison results and variation results were used to extract the genotyping information of the SNP sites using a self-written Perl script. When the coverage depth of a sample at a certain SNP site is <5X, it means that the sequencing depth of the sample at this site is insufficient. To ensure the accuracy of the genotyping results, the site is treated as missing and represented by NA. When the sample has a genotype mutation at a certain SNP site, it is necessary to judge based on the mutation frequency of the site. If the mutation frequency is ≥0.8 or ≤0.2, the site is a pure and mutation. If the mutation frequency is between 0.2-0.8, each allele in the heterozygous genotype must be supported by at least 4 reads, then the SNP site is a heterozygous mutation, otherwise the site is treated as missing. Finally, the genotype results of the sample at all SNP sites are summarized.

[0073] Example 2 Development of low-density liquid phase SNP chip and its application in Laoshan dairy goats

[0074] 1. Selection of SNP sites and probe design and synthesis

[0075] As described in Example 1, simplified genome sequencing was performed on 25 Laoshan dairy goat genomic DNA samples, and the sequencing data volume of each sample was 3G; the sample data was analyzed, and finally 1792 representative SNP polymorphic sites were selected, which were evenly distributed in each chromosome of the genome, as shown in Table 1.

[0076] GenoBaits Probe Designer software was used to design liquid phase capture probes for the sequences obtained from simplified genome sequencing. The probe length was set to 110 nt, the GC content was >30%, and each SNP site was designed to be covered by at least 3 liquid phase capture probes.

[0077] Liquid capture probes with GC content between 30% and 80%, homology regions (regions with high sequence alignment similarity) of less than 10, and no SSR or N regions (regions not detected or not accurately detected) are selected. Polynucleotide probes modified with biotin are synthesized using chip in situ synthesis technology, which are subsequently used to hybridize with the target region of the genome to form a double strand, and then the molecules carrying biotin are adsorbed by streptavidin-coated magnetic beads. After elution, amplification, and sequencing, the SNP genotype is identified. The working principle is as follows Figure 4 shown.

[0078] 2. Sample DNA Library Construction

[0079] The genomic DNA of 275 Laoshan dairy goats was used for DNA library construction. The library construction used the GenoBaits library construction kit (Cat. No.: PHR0076_Ch1K) of Shijiazhuang Boredy Biotechnology Co., Ltd.:

[0080] Take 12μL of DNA that has passed the quality inspection and place it in a 0.2μL PCR tube. Place the tube in an ultrasonic crusher to randomly physically break the DNA into fragments of 200-400bp. Then add 4μL GenoBaits End Repair Buffer and 2.7μL GenoBaits End Repair Enzyme to the tube, add water to 20μL, and place it in an ABI 9700 PCR instrument and incubate at 37℃ for 20 minutes to complete the end repair and A addition process of the broken fragments.

[0081] Remove the small tube from the PCR instrument, add 2μL GenoBaits Ultra DNA ligase, 8μL GenoBaitsUltra DNA Ligase Buffer and 2μL GenoBaits Adapter, add water to 40μL, and then place it on the ABI9700 PCR instrument at 22℃ for 30 minutes to complete the connection of the sequencing adapter.

[0082] Add 48μL of Beackman AMPure XP Beads to the ligation product to purify it. After purification, perform fragment screening according to 065+02x magnetic beads, and retain the ligation product with an insert fragment of 200-300bp. Add 5μL of sequencing adapter with Barcode sequence, 1μL of P5 adapter, 10μL of GenoBaits PCR MasterMix to the PCR tube in the previous step, and fill it up to 20μL with pure water; use ABI 9700PCR instrument for amplification, and the amplification program is: 95℃ pre-denaturation for 5min; 95℃ denaturation for 30s, 60℃ annealing for 30s, 72℃ extension for 30s, a total of 8 cycles; 72℃ extension for 5min. Different Barcodes are used to distinguish different samples.

[0083] Add 24 μL Beckmen AMPure XP Beads to the second round PCR product, pipette up and down to mix evenly, place 0.2 μL of the PCR tube on a magnetic stand until the solution is clear, discard the supernatant and wash the beads once with 75% ethanol, and elute the library DNA with Tris-HCl at pH 8.0.

[0084] 3. Sample DNA Hybridization Capture

[0085] The sample DNA hybridization capture uses the GenoBaits library construction kit (Cat. No.: PHR0076_Ch1K) from Shijiazhuang Boredy Biotechnology Co., Ltd.:

[0086] Take 500ng library DNA, add 5μL GenoBaits Block I and 2μL GenoBaits Block II, place on Eppendorf Concentrator plus vacuum concentrator, evaporate to dry powder at ≤70℃. Add 8.5μL GenoBaits 2x Hyb Buffer, 2.7μL GenoBaits Hyb Buffer Enhancer, 2.8μL Nuclease-Free Water to the dry powder tube, mix with a pipette, place on ABI 9700 PCR instrument at 95℃ for 10 minutes, then take out the PCR tube, add 3μL of synthesized probe, vortex and mix, place on ABI 9700 PCR instrument at 65℃ for 2 hours to complete the probe hybridization reaction.

[0087] Add 100μL GenoBaits DNA Probe Beads to the reaction system after hybridization in the previous step, pipette up and down 10 times, and incubate at 65℃ for 45 minutes in the ABI 9700PCR instrument to allow the magnetic beads to bind to the probe. Use 100μL GenoBaits Wash Buffer I and 150μL GenoBaits Wash Buffer II to wash the magnetic beads after binding to the probe at 65℃, and then use 100μL GenoBaits Wash Buffer I, 150μL GenoBaits Wash Buffer II and 150μL GenoBaits Wash Buffer III to wash the magnetic beads at room temperature. Resuspend the washed magnetic beads with 20μL Nuclease-Free Water.

[0088] Take 13 μL of resuspended DNA (with magnetic beads) and add it to a new 0.2 mL PCR tube, then add 15 μL GenoBaits PCR Master Mix and 2 μL GenoBaits Primer Mix to configure the post PCR system, and use ABI9700 PCR instrument to amplify the library. The amplification program is: pre-denaturation at 95°C for 5 min; denaturation at 95°C for 30 s, annealing at 60°C for 30 s, and extension at 72°C for 30 s, for a total of 15 cycles; extension at 72°C for 5 min.

[0089] Add 45 μL Beckmen AMPure XP Beads to the post-PCR product and pipette up and down to mix evenly, then place the 0.2 mL PCR tube on a magnetic stand until the solution is clear, discard the supernatant and wash the magnetic beads twice with 75% ethanol, and elute the library DNA with Tris-HCl at pH 8.0. Complete the hybridization capture of the test sample.

[0090] 4. Quality inspection and sequencing of sample DNA hybridization capture library

[0091] The DNA concentration of the hybrid capture library was measured by Qubit Fluorometric Quantitation (Thermo Fisher), and then agarose gel electrophoresis was used to detect whether the fragment size of the library DNA was between 300-400 bp. The constructed DNA library was sequenced using an MGI2000 sequencer.

[0092] 5. Test data analysis

[0093] In order to ensure the quality of information analysis, the original sequencing data raw reads were filtered to obtain clean reads, which were used for subsequent analysis.

[0094] Specifically, the software fastp (version 0.20.0, parameters: -n 10-q 20-u 40) was used to filter the raw reads. The steps of data processing are as follows:

[0095] 1) Remove the adapter sequence;

[0096] 2) When the N content in the sequencing read exceeds 10% of the length of the read, the paired reads need to be removed;

[0097] 3) When the number of low-quality (Q≤20) bases contained in the sequencing read exceeds 40% of the length of the read, the paired reads need to be removed.

[0098] Use the software BWA (mem alignment method) to align the clean reads after quality control with the reference genome sequence. The position of the clean reads on the reference genome can be located through alignment.

[0099] According to the alignment results of Clean Reads in the reference genome, the UnifiedGenotyper module of the GATK (version v3.5-0-g36282e4) software was used for variation detection, and the analysis parameters were: "-dcov 1000000-minIndelFrac 0.15-glm BOTH-l INFO". The VariantFiltration module was used for filtering, and the filtering parameters were: --filterExpression"MQ0>=4&&((MQ0 / (1.0*DP))>0.1)"--filterName"HARD_TO_VALIDATE"--filterExpression"DP<3||QD<2"--filterName"LOW_READ_SUPPORT".

[0100] 6. Bloodline analysis

[0101] The following analysis was performed using the genotype results of the 25 sample SNP sites in Example 1 and the genotype results of the 275 sample SNP sites in this example:

[0102] (1) Principal component analysis

[0103] PCA analysis was performed using gcta software to obtain the variance explanation rate of each PC and the score matrix of the sample in each PC. The key information extracted from the SNP information was divided into PC1, PC2, PC3... according to the effect from large to small. The results are as follows Figure 5 , 6 shown.

[0104] (2) Group structure analysis

[0105] Admixture software (v1.3) was used to infer the population structure. The number of clusters (K value) of the samples was assumed to be 1-15, and then clustering was performed. The optimal number of clusters was determined based on the cross-validation error rate (CV error). The K value with the smallest cross-validation error rate corresponds to the optimal number of clusters. The cross-validation error rate line graph is shown in Figure 2. Figure 7 shown.

[0106] The optimal number of clusters determined by analysis is K=13.

[0107] In order to simulate the classification of the population and the pedigree composition of each sample under different subgroup numbers (subgroup number k = 2-15), the genetic composition of each sample in each subgroup was plotted into a bar graph using pophelper software (v2.2.7), as shown in Figure 8 As shown, within each K value, each color represents a Cluster.

[0108] (3) Phylogenetic tree construction

[0109] The evolutionary tree was constructed using the neighbor-joining method.

[0110] The NJ tree was constructed using MEGA-X software (model: p-distance; bootstrap: 1000 times). The results are shown in the attached figure. Fig. 9 shown.

[0111] (4) Kinship analysis

[0112] Kinship is defined as the relative value of the genetic similarity between two specific materials and the genetic similarity between any materials. Kinship analysis was performed using gcta software (v1.92.2) to obtain the kinship matrix between two samples. The heat map drawn using the kinship matrix is ​​shown in Fig.10 shown. Fig.11 This is the evolutionary tree of the Laoshan dairy goat population. This diagram can intuitively show the closeness of the blood relationship between individuals in the group.

[0113] Comparing the above analysis results with the pedigree data of 300 dairy goats, it was found that the two were highly consistent, and the SNP chip data helped to clarify the bloodline origins of some goats with incomplete pedigree records, which is of great reference value for the next step of joint breeding of Laoshan dairy goats.

[0114] The general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A low-density liquid phase SNP chip for Laoshan dairy goats, It is characterized in that The liquid phase SNP chip includes a liquid phase capture probe for identifying SNP genotypes, and the probe corresponds to 1792 SNP sites; the information of the 1792 SNP sites is as follows: 。 2. Application of the Laoshan dairy goat low-density liquid phase SNP chip according to claim 1 in kinship analysis of Laoshan dairy goats.

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