Liquid-phase chip for detecting genetic stability of pigs and application of liquid-phase chip

Abstract

The invention discloses a pig genetic stability detection liquid chip and application, and belongs to the technical field of pig variety identification. The pig genetic stability detection liquid phase chip provided by the invention comprises a probe combination for detecting 10000 loci of five groups of genetic stability, and position information and base types of probes corresponding to the 10000 loci of the five groups in an experimental pig reference genome are shown in a table 1 in the specification. By screening common and specific SNP sites of five experimental pigs, the liquid-phase SNP detection chip for detecting the genetic stability of the experimental pigs is constructed, and an important detection method and means can be provided for establishing a rapid and automatically-operated agricultural experimental pig genetic quality detection technical system.

Description

Technical Field

[0001] This invention belongs to the field of pig breed identification technology, and relates to a liquid phase chip for detecting the genetic stability of pigs and its application. Background Technology

[0002] SNP detection is an important tool in genetics and medical research, and there are currently several main detection methods: ① Oligonucleotide Ligation Analysis (OLA). This method uses ligase to connect two adjacent oligonucleotide probes, one binding upstream of the target sequence and the other downstream. If both probes perfectly match the target sequence, the ligase will connect them to form a complete oligonucleotide chain. The genotype of the target sequence can be determined by detecting the presence or absence of the ligation product. Disadvantages include relatively complex operation, strict control of reaction conditions, and the ligase activity being easily affected by various factors. ② Allele-Specific Oligonucleotide Hybridization (ASO). This method designs two oligonucleotide probes that specifically bind to different alleles of the target sequence. The sample is hybridized with both probes. If a complementary allele is present in the sample, the probe binds to the sample. The genotype of the sample can be determined by detecting the intensity of the hybridization signal. Disadvantages include relatively low specificity, a high likelihood of false positives, and strict requirements for hybridization conditions. ③ Dynamic Allele-Specific Hybridization (DASH). The genotype of the target sequence is determined by monitoring changes in fluorescence signal during hybridization using fluorescently labeled oligonucleotide probes to hybridize with the target sequence. During hybridization, the binding and dissociation of the probe and target sequence are in dynamic equilibrium. By changing the hybridization conditions, the binding stability of the probe and target sequence can be affected, thus distinguishing different genotypes. The disadvantages are high requirements for equipment and complex optimization of hybridization conditions. ④ Mass spectrometry. Mass spectrometry is used to analyze nucleic acid molecules and determine the genotype of SNP sites by detecting differences in the mass of nucleic acid molecules. Typically, nucleic acid samples are first amplified by PCR, and then the amplification products are digested with enzymes or chemically modified to produce fragments of different masses. Finally, these fragments are detected by mass spectrometry, and the genotype of the SNP site is determined based on the differences in fragment mass. The disadvantages are expensive equipment, high operational skill requirements, and high sample purity requirements. ⑤ Single-base extension labeling. An oligonucleotide primer adjacent to the target SNP site is added to the PCR reaction system. The 3' end of this primer is adjacent to the upstream or downstream of the target SNP site. After the PCR reaction, a specific DNA polymerase and four different fluorescently labeled deoxyribonucleotide triphosphates (dNTPs) are added, causing the primers to extend to a single base at the target SNP site. Depending on the genotype of the target SNP site, the primers will extend to different bases, thus producing different fluorescent signals. By detecting the intensity and color of the fluorescent signal, the genotype of the target SNP site can be determined. The disadvantages are that primer design is crucial and the cost of fluorescently labeled dNTPs is relatively high.

[0003] While liquid-phase chip detection of SNPs has many advantages, it also has some disadvantages, mainly including the following: high instrument and equipment costs, suitable for the detection of large batches of samples; strict requirements for probe design, but high specificity; and it can only detect known SNP sites, and cannot effectively detect unknown SNP sites.

[0004] Laboratory animals are crucial experimental materials in life science research, and the uniformity of their quality plays a key role in the accuracy and reliability of experimental results. Genetic quality is one of the most important factors influencing the quality of laboratory animals. In scientific research, the use of laboratory animals with high genetic stability is essential to ensure the comparability and reliability of animal experimental results. The purpose of genetic testing is to verify the genetic characteristics that different strains of animals should possess, check for genetic mutations and contamination, and ensure that the tested subjects meet the requirements of that strain. Single nucleotide polymorphism (SNP) detection is currently an important research area for the genetic quality testing of laboratory animals and a crucial indicator for evaluating their genetic quality. Therefore, developing or establishing efficient, automated, and accurate SNP detection methods is a prerequisite for conducting genetic quality testing of laboratory animals.

[0005] Traditional genetic testing methods include morphological, immunological, and biochemical approaches, but each has its limitations and cannot effectively detect genetic differences between subspecies. Molecular biology testing methods, however, can directly examine changes in animal nucleic acid sequences, providing a direct and objective pathway for genetic testing of inbred strains. Currently, many SNP detection methods have been established, including restriction fragment length polymorphism (RFLP), direct sequencing, high-performance liquid chromatography (DHPLC), allele-specific PCR (ASPCR), matrix-assisted laser desorption / ionization time-of-flight mass spectrometry (MALDI-TOF), and single-strand conformation polymorphism (PCR-SSCP). However, these methods all have their own limitations, such as short detection fragment lengths, low detection rates, cumbersome testing processes, slow results, unsuitability for large-scale populations, and difficulty in automation, thus limiting their application. With the rapid development of modern biotechnology, high-throughput sequencing, represented by gene chips and whole-genome resequencing technologies, has become an important tool for solving biomedical problems. However, the application of liquid-phase microarray detection technology, an important method for detecting SNPs, in the genetic quality testing of laboratory animals remains unexplored. To improve the quality assessment and scientific supervision system for laboratory animals and address the problems of outdated quality assessment technologies and low testing efficiency, it is imperative to establish an automated genetic quality testing technology system for agricultural laboratory animals based on gene chips and whole-genome resequencing technologies.

[0006] Pigs are the most widely distributed and agriculturally important species in the world. Laboratory pigs are widely used as crucial experimental materials in life science research, including new drug trials, disease diagnosis, and alternative models for disease research. The uniformity of their genetic quality plays a key role in the accuracy and reliability of experimental results. Currently, with the deepening of life science research, the demand for high-quality laboratory pigs is increasing. Developed countries and regions are continuously strengthening their quality evaluation systems for these laboratory animals, paying close attention to related technological developments, and formulating many advanced international and industry standards, incorporating them into national science and technology innovation and development plans to enhance national scientific and technological competitiveness. Leading international companies also place great emphasis on this. However, when using pigs as laboratory animals, the genetic characteristics and stability of their breeds are crucial for quality evaluation and are an important prerequisite for ensuring the reliability and reproducibility of animal experimental results in disease research. Currently, the key technical system for evaluating the genetic quality of laboratory pigs is still immature. Therefore, there is an urgent need for a method to identify the genetic stability of laboratory pigs during generations of inheritance, so as to accurately use laboratory animals in subsequent research. Summary of the Invention

[0007] To overcome the shortcomings of existing technologies, this invention provides a liquid-phase chip for detecting the genetic stability of pigs and its application. By developing a liquid-phase chip for detecting SNPs in experimental pigs, it screens and verifies SNP genetic marker loci for detecting SNPs in SPF Large White, SPF Landrace, Rongchang, Tibetan, and Wuzhishan miniature pig populations, providing a reference for detecting the genetic stability of experimental pig populations. The technical solution is as follows:

[0008] First, an embodiment of the present invention provides a liquid phase chip for detecting porcine genetic stability. The porcine genetic stability detection liquid phase chip includes a probe combination for detecting genetic stability at 10,000 loci in five populations. The position information and base types of the probes corresponding to the 10,000 loci in the five populations in the experimental pig reference genome are shown in Table 1. In this table, the numbers on the left indicate the chromosome numbers where the 10,000 loci in the five populations are located, the values ​​in the middle indicate the physical location of the chromosomes where the 10,000 loci in the five populations are located, and the letters on the right indicate the two base types of the 10,000 loci in the five populations.

[0009] The positions of the probes corresponding to 10,000 loci in the five groups in the experimental pig reference genome were determined based on the genes of five experimental pig species: Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature. Among them, RC represents Rongchang pig, CB represents Landrace pig, DB represents Large White pig, T represents Tibetan pig, and WZ represents Wuzhishan Miniature.

[0010] Table 1. Location and base information of probes corresponding to 10,000 sites in the five populations in the experimental pig reference genome.

[0011]

[0012]

[0013]

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023]

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039] Of the 10,000 loci in the five groups, 5,000 are common loci, with 1,000 each from Large White, Landrace, Rongchang, Tibetan, and Wuzhishan miniature pigs. "Common" represents the location information and base type of the probes corresponding to the 5,000 common loci in the experimental pig reference genome.

[0040] Secondly, the present invention also provides the application of any of the pig genetic stability detection liquid-phase chips described in the present invention in the identification of SNP genetic marker sites in pig populations.

[0041] Furthermore, the application described in this invention includes the following steps:

[0042] S1: Sample collection from experimental pigs;

[0043] S2: Using the ear vein method, 50 blood samples were collected from the parent generations of five experimental pigs (Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature Pigs); 10 blood samples were collected from 5 healthy females and 5 healthy males of each pig species.

[0044] S3: Extract genomic DNA from whole blood samples; construct paired-end sequencing libraries (insertion size 300-400 bp) for each individual using the NovaSeq 6000 NGS platform, and perform quality control to filter low-quality reads to obtain high-quality clean reads; quality filtering includes removing 1) reads with ≥10% unidentified nucleotides; 2) reads with >50% of Phred quality scores ≤20; 3) reads aligned with barcode adapters;

[0045] S4: To identify SNPs, clean reads were mapped to the duck reference genome (https: / / www.ncbi.nlm.nih.gov / assembly / GCF_015476345.1) using the Burrows-Wheeler Aligner (version 0.7.15) software; all samples were analyzed using the Unified Genotyper (GATK) toolkit; to reduce false discovery rates, SNPs were filtered using Variant Filtration in GATK (GATK: -Window 4, -filter "QD < 2.0 || FS > 60.0 || MQ < 40.0," -G_filter "GQ < 20"); to determine the physical location of each SNP, the software tool ANNOVAR was used to align and annotate the SNPs.

[0046] S5: High-quality SNPs are obtained according to the following criteria: 1) average coverage depth ≥ 5; 2) minimum allele frequency ≥ 5%; and 3) sample missing rate < 10%.

[0047] S6: Fixed index values ​​were used to analyze whole-genome selectivity scans of different experimental pigs; these values ​​were calculated using the R package PopGenome in a 100 kb sliding window (step size = 10 kb); then the window-based FST values ​​were normalized using Z-transform (ZFST); the ZFST values ​​in the top 5% of the window were defined as selectable regions, and genes in these regions were identified as candidate genes;

[0048] S7: Sites with a depth less than 10× are set as missing, and then sites with missing or intergenic features are filtered out. Sites consistent across all samples are selected as common markers for the five experimental pigs.

[0049] S8: Sites with a depth less than 10× are set as missing, and then sites with missing depths are filtered out. Sites that are consistent within each population and not present in the other four populations are used as unique markers for the five populations.

[0050] S9: Based on the proportion of SNP loci detected on each chromosome, 20,000 SNP loci were selected as candidate loci, including 10,000 common SNP loci and 10,000 unique SNP loci (2,000 from each population). Probes were designed and evaluated on the selected loci based on the SNP chromosome distribution, locus type distribution, and SNP density. Loci with higher scores and a priority of 1 were selected. The selected loci were determined according to the proportion of SNPs detected on each chromosome, resulting in a total of 5,000 unique loci (1,000 each from Large White, Landrace, Rongchang, Tibetan, and Wuzhishan miniature pigs) and 5,000 common loci (Table 1).

[0051] S10: Through bioinformatics analysis, probes were designed and synthesized for the 10,000 selected sites, and then tested and verified.

[0052] S11: Compare the sequencing sequence with the reference genome of the locus. When the proportion of common loci detected in offspring Landrace pigs is 50-64.9% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Large White pigs is 55.0-66% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Rongchang pigs is 56.1-62.7% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Wuzhishan miniature pigs is 55.0-66.1% of all common loci in the liquid phase chip, and the proportion of common loci detected in offspring Tibetan pigs is 64.1-76.8% of all common loci in the liquid phase chip.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0054] This invention develops a liquid-phase chip for detecting specific SNP genetic markers, enabling precise identification of genetic stability in experimental pigs. This chip, designed based on five pig-specific and shared SNP loci, exhibits high specificity and accuracy. Compared to existing identification methods, it provides a faster and more accurate assessment of the genetic quality of experimental pigs. The liquid-phase chip organically combines flow cytometry with chip technology, creating a unique detection mode. Compared to traditional methods, the liquid-phase chip uses microspheres instead of cells as the reaction carrier. This innovative design makes the detection system more flexible and diverse, offering advantages such as high throughput, high sensitivity, good repeatability, ease of operation, and short processing time. It is widely used in disease detection and genetic resource conservation.

[0055] Most genetic markers currently on the market are designed for a wide range of animal species or specific economic animal breeds, while this invention is specifically designed for experimental pigs (Large White, Landrace, Rongchang, Tibetan, and Wuzhishan miniature pigs). This invention fills this gap and provides a completely new solution for detecting the genetic stability of experimental pigs.

[0056] The liquid-phase chip of this invention has advantages such as simple operation, low cost, high efficiency, and high detection throughput. This makes the method easy to promote and apply in laboratories and production practices, providing services to more research institutions and enterprises. At the same time, it can accurately detect the genetic quality of experimental pigs, providing researchers with reliable experimental animal resources, which helps improve the accuracy and reliability of research results and promotes the development of life science research.

[0057] This invention constructs a liquid-phase SNP detection chip for detecting the genetic stability of experimental pigs by screening five common and unique SNP loci in experimental pigs. It provides an important detection method and means for establishing a rapid and automated agricultural experimental pig genetic quality detection technology system. Attached Figure Description

[0058] Figure 1 It is a distribution map of 10,000 SNP loci on each chromosome. Detailed Implementation

[0059] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] The specific steps are as follows:

[0061] S1: All experimental pig samples in this study were collected by ourselves.

[0062] S2: Using the ear vein method, 50 blood samples were collected from the parent generations of five experimental pigs (Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature Pigs). Ten blood samples were collected from each type of pig, consisting of five healthy females and five healthy males.

[0063] S3: Genomic DNA was extracted from whole blood samples. Paired-end sequencing libraries (insert size 300-400 bp) were constructed for each individual using the NovaSeq 6000 NGS platform and quality-controlled to filter low-quality reads to obtain high-quality clean reads. Quality filtering included removing 1) reads with ≥10% unidentified nucleotides; 2) reads with >50% of Phred quality scores ≤20; and 3) reads aligned with the barcode adapter.

[0064] S4: To identify SNPs, clean reads were mapped to the duck reference genome (https: / / www.ncbi.nlm.nih.gov / assembly / GCF_015476345.1) using the Burrows-Wheeler Aligner (version 0.7.15) software. All samples were analyzed using the Unified Genotyper (GATK) toolkit. To reduce the false discovery rate, SNPs were filtered using Variant Filtration in GATK (GATK: -Window 4, -filter "QD < 2.0 || FS > 60.0 || MQ < 40.0," -G_filter "GQ < 20"). To determine the physical location of each SNP, the software tool ANNOVAR was used to align and annotate the SNPs.

[0065] S5: High-quality SNPs are obtained according to the following criteria: 1) average coverage depth ≥ 5; 2) minimum allele frequency ≥ 5%; and 3) sample missing rate < 10%.

[0066] S6: Fixed index values ​​were used to analyze whole-genome selectivity scans from different experimental pigs. These values ​​were calculated using the R package PopGenome within a 100 kb sliding window (step size = 10 kb). The window-based FST values ​​were then normalized using Z-transform (ZFST). The ZFST values ​​in the top 5% of the window were defined as selectable regions, and genes within these regions were identified as candidate genes.

[0067] S7: Sites with a depth less than 10× are set as missing, and then sites with missing or intergenic features are filtered out. Sites consistent across all samples are selected as common markers for the five experimental pigs.

[0068] S8: Sites with a depth less than 10× are set as missing, and then sites with missing depths are filtered out. Sites that are consistent within each population and not present in the other four populations are used as unique markers for the five populations.

[0069] S9: Based on the proportion of SNP loci detected on each chromosome, 20,000 SNP loci were selected as candidate loci, including 10,000 common SNP loci and 10,000 unique SNP loci (2,000 from each population). Probes were designed and evaluated for the selected loci based on the SNP chromosome distribution, locus type distribution, and SNP density. Loci with higher scores and a priority of 1 were selected. The screening loci were determined according to the proportion of SNPs detected on each chromosome, resulting in a total of 5,000 unique loci (1,000 each from Large White, Landrace, Rongchang, Tibetan, and Wuzhishan miniature pigs) and 5,000 common loci (Table 1).

[0070] S10: Through bioinformatics analysis, probes were designed and synthesized for the 10,000 selected sites, and then tested and verified.

[0071] S11: Compare the sequencing sequence with the reference genome of the locus. When the proportion of shared loci detected in offspring Landrace pigs accounts for 50-64.9% of all shared loci in the liquid-phase microarray, the proportion in offspring Large White pigs accounts for 55.0-66%, the proportion in offspring Rongchang pigs accounts for 56.1-62.7%, the proportion in offspring Wuzhishan miniature pigs accounts for 55.0-66.1%, and the proportion in offspring Tibetan pigs accounts for 64.1-76.8%, we can consider the individual to have stable inheritance. Therefore, this invention can accurately determine whether the genetic quality of experimental pigs of different breeds is stable by using the proportion of detected loci in the microarray.

[0072] Figure 1 The paper illustrates the liquid phase chip for detecting pig genetic stability provided by the present invention. The liquid phase chip for detecting pig genetic stability includes the distribution of 10,000 SNP loci on various chromosomes from five populations for detecting genetic stability.

[0073] This invention selected five common experimental pig species (Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature) for 10× whole-genome resequencing and analysis. Unique SNP loci and shared SNP loci were screened for each of the five pig species. Based on SNP chromosome distribution, locus type distribution, and SNP density, probes were designed and evaluated for the screened loci. Loci with higher scores and a priority of 1 were selected. Screening loci were determined according to the proportion of SNPs detected on each chromosome, resulting in a total of 5000 unique loci (1000 each for Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature) and 5000 shared loci. Microarray probes were synthesized and their performance was measured for these 10000 loci, ultimately leading to the development and application of a liquid-phase microarray for detection.

Claims

1. A liquid-phase chip for detecting porcine genetic stability, characterized in that, The liquid-phase chip for detecting pig genetic stability includes a probe combination for 10,000 loci in five populations for detecting genetic stability. The position information and base types of the probes corresponding to the 10,000 loci in the experimental pig reference genome are shown in the table below. The numbers on the left indicate the chromosome numbers of the 10,000 loci in the five populations, the values ​​in the middle indicate the physical location of the 10,000 loci in the five populations on the chromosomes, and the letters on the right indicate the two base types of the 10,000 loci in the five populations. The positions of the probes corresponding to 10,000 loci in the five groups in the experimental pig reference genome were determined based on the genes of five experimental pig species: Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature. Among them, RC represents Rongchang pig, CB represents Landrace pig, DB represents Large White pig, T represents Tibetan pig, and WZ represents Wuzhishan Miniature. Of the 10,000 loci in the five groups, 5,000 are common loci, with 1,000 each from Large White, Landrace, Rongchang, Tibetan, and Wuzhishan miniature pigs. "Common" represents the location information and base type of the probes corresponding to the 5,000 common loci in the experimental pig reference genome.

2. The application of the liquid phase chip for detecting pig genetic stability as described in claim 1 in the identification of SNP genetic marker sites in pig populations.

3. The application according to claim 2, characterized in that, Includes the following steps: S1: Sample collection from experimental pigs; S2: Using the ear vein method, 50 blood samples were collected from the parents of five types of experimental pigs: Large White, Landrace, Rongchang, Tibetan, and Wuzhishan Miniature. For each type of pig, 10 blood samples were collected from 5 healthy females and 5 healthy males. S3: Extract genomic DNA from whole blood samples; construct paired-end sequencing libraries for each individual using the NovaSeq 6000 NGS platform with an insert size of 300-400 bp, and perform quality control to filter low-quality reads to obtain high-quality clean reads; S4: To identify SNPs, use the Burrows-Wheeler Aligner version number: The software 0.7.15 mapped clean reads to the duck reference genome https: / / www.ncbi.nlm.nih.gov / assembly / GCF_015476345.1; all samples were analyzed using the Unified Genotyper from the Genome Analysis Toolkit. S5: High-quality SNPs are obtained according to the following criteria: 1) average coverage depth ≥ 5; 2) minimum allele frequency ≥ 5%; and 3) sample missing rate < 10%. S6: Fixed index values ​​are used to analyze whole-genome selective scans of different experimental pigs; These values ​​were calculated using the R package PopGenome within a 100 kb sliding window; then the window-based FST values ​​were normalized using the Z-transform; the ZFST values ​​in the top 5% of the window were defined as selective regions, and genes in these regions were identified as candidate genes. S7: Sites with a depth less than 10× are set as missing, and then sites with missing or intergenic features are filtered out. Sites consistent across all samples are selected as common markers for the five experimental pigs. S8: Sites with a depth less than 10× are set as missing, and then sites with missing depths are filtered out. Sites that are consistent within each population and not present in the other four populations are used as unique markers for the five populations. S9: Based on the proportion of SNP loci detected on each chromosome, 20,000 SNP loci were selected as candidate loci, including 10,000 common SNP loci and 10,000 unique SNP loci, with 2,000 from each population. Probes were designed and evaluated on the selected loci based on the SNP chromosome distribution, locus type distribution, and SNP density. Loci with higher scores and a priority of 1 were selected. The selection loci were determined according to the proportion of SNPs detected on each chromosome, with a total of 5,000 unique loci, 1,000 each from Large White pigs, Landrace pigs, Rongchang pigs, Tibetan pigs, and Wuzhishan miniature pigs, and 5,000 common loci. S10: Through bioinformatics analysis, probes were designed and synthesized for the 10,000 selected sites, and then tested and verified. S11: Compare the sequencing sequence with the reference genome of the locus. When the proportion of common loci detected in offspring Landrace pigs is 50-64.9% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Large White pigs is 55.0-66% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Rongchang pigs is 56.1-62.7% of all common loci in the liquid phase chip, the proportion of common loci detected in offspring Wuzhishan miniature pigs is 55.0-66.1% of all common loci in the liquid phase chip, and the proportion of common loci detected in offspring Tibetan pigs is 64.1-76.8% of all common loci in the liquid phase chip.

4. The application according to claim 3, characterized in that, In step S3, quality filtration includes removing 1) readings with ≥10% unidentified nucleotides; 2) readings with >50% Phred quality score ≤20 bases; and 3) readings aligned with the barcode adapter.

5. The application according to claim 3, characterized in that, In step S4, SNPs are filtered using VariantFiltration in GATK; the software tool ANNOVAR is used to align and annotate SNPs.

Images