Liquid phase chip for nervous necrosis virus resistant genome selective breeding of red nine-pink bass and application of liquid phase chip

Abstract

The invention belongs to the technical field of aquatic genetic breeding, and particularly relates to a nervous necrosis virus resistant genome selective breeding liquid chip for red nine-pink bass and application of the nervous necrosis virus resistant genome selective breeding liquid chip. The nervous necrosis virus resistant genome selective breeding liquid phase chip for the red nine-pink bass contains 500 SNP loci, a technical foundation is laid for establishing a rapid and low-cost nervous necrosis virus resistant genome selective breeding process through efficient capture of core loci, and the industrialization process of improved variety breeding of the red nine-pink bass is powerfully promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of aquaculture genetics and breeding, and specifically relates to a liquid-phase chip for genomic selection breeding of red grouper (Cephalopholis sonnerati) resistant to nervous necrosis virus and its application. Background Art

[0002] The red grouper ( Cephalopholis sonnerati ) is an important economically cultured marine fish. Due to its delicious meat and rich nutrition, a large-scale farming pattern has been formed. The development of its industry not only optimizes the fishery economic structure, significantly improves the income level of fishermen, but also plays an irreplaceable role in meeting the needs of the high-end consumer market.

[0003] Nervous necrosis virus ( Viral Nervous Necrosis , VNN), as one of the main pathogens in the red grouper aquaculture industry, poses a huge threat to the industry. The virus can spread rapidly through vertical transmission (carried by broodstock) and horizontal transmission (water body, bait). The infected fish show typical symptoms such as abnormal behavior and nerve tissue necrosis. The mortality rate of juvenile fish is over 80%, which is a devastating blow to aquaculture production. Currently, the prevention and control measures mainly rely on traditional methods such as water body disinfection and antibiotic use, but there are limitations such as high cost, complex operation, and difficulty in large-scale promotion. Therefore, breeding disease-resistant improved varieties has become the core requirement for the green and sustainable development of the red grouper industry.

[0004] Traditional population selection, family selection, and cross-breeding techniques have limited effectiveness in improving the VNN-resistant traits of red grouper. The reasons are, on the one hand, due to the biological characteristics of red grouper that do not allow the construction of stable families, and on the other hand, because disease-resistant traits are complex traits regulated by multiple genes, and traditional methods are difficult to accurately analyze their genetic mechanisms. In recent years, genomic selection breeding (GS) based on whole-genome sequencing technology has provided a new technical path for improving economic traits of fish. This technology can quickly evaluate the genomic estimated breeding value (GEBV) of candidate individuals through the correlation analysis of single nucleotide polymorphisms (SNPs) across the whole genome with target traits, thereby significantly shortening the breeding cycle and improving the breeding efficiency. In the breeding of aquatic animals such as Atlantic salmon, Japanese flounder, and large yellow croaker, genomic selection technology has shown advantages that traditional methods cannot match, providing an important reference for the disease-resistant breeding of red grouper.

[0005] The core of genomic selection lies in precise genotyping technology. As a key means to analyze the association between genetic variation and traits, whole-genome SNP genotyping can achieve high-depth resequencing of target sites through targeted capture sequencing (such as cGBS liquid chip technology), ensuring the accuracy of genotype detection. However, for farmed fish with relatively low individual economic value, genotyping cost remains the main obstacle restricting the large-scale application of genomic selection technology. It is worth noting that there is currently no report on a dedicated gene chip for the anti-VNN trait of red grouper (Cephalopholis sonnerati) at home and abroad. Therefore, developing a low-cost, high-throughput, and highly flexible whole-genome SNP chip and supporting disease-resistant genomic selection technology has become an urgent task to break through the technical bottleneck of disease-resistant breeding of red grouper. Summary of the Invention

[0006] To solve the above technical problems, the present invention provides a liquid chip for genomic selection breeding of red grouper resistant to nervous necrosis virus and its application.

[0007] The technical solution of the present invention is as follows: The present invention provides a liquid chip for genomic selection breeding of red grouper resistant to nervous necrosis virus. The genotyping targets of the chip include 500 SNP loci on the red grouper reference genome (GenBank: GCA_043388425.1), and the positions and mutation types of these loci on the red grouper reference genome are shown as NO.001 - NO.500.

[0008] Table 1 Positions and Mutation Types of 500 SNP Loci on the Red Grouper Reference Genome

[0009] The application of the liquid chip of the present invention in genomic selection breeding of red grouper resistant to nervous necrosis virus.

[0010] According to the positions of the 500 SNP loci in Table 1, 35bp are extended before and after on the reference genome, and the reverse complementary sequence of a total of 71bp of bases including the target locus is used as the probe sequence of this locus.

[0011] Compared with the prior art, the present invention has the following beneficial effects: In view of the technical bottlenecks of low efficiency and high cost in the traditional methods for breeding red grouper (Cephalopholis sonnerati) resistant to nervous necrosis virus, the present invention innovatively develops a liquid-phase chip "Hongxin 1" for genomic selection breeding technology. By integrating genome-wide association study (GWAS) and MLE-rank model, 500 core SNP loci with high genetic effects are accurately screened out from a 50k liquid-phase chip. This optimization strategy effectively reduces the actual application cost and computational cost while ensuring the accuracy of genomic selection, and significantly improves the technical usability and industrial adaptability of the chip. Through the efficient capture of core loci, the present invention lays a technical foundation for establishing a rapid and low-cost genomic selection breeding process for resisting nervous necrosis virus, strongly promotes the industrialization process of fine variety breeding of red grouper, and provides an important technical innovation paradigm for disease-resistant breeding of marine fish. Description of the Drawings

[0012] Figure 1 Comparison of ROC curves of GEBV prediction performance based on core SNP loci and 40,345 evenly distributed SNPs in 200 validation populations; Figure 2 Comparison of the population means of GEBV estimated by core SNP loci and 40,345 evenly distributed SNPs in 200 validation populations; Figure 3 Analysis of the population means of GEBV of core SNP loci in 80 candidate populations. Detailed Implementation Modes

[0013] In order to enable ordinary technicians in the field to better understand the technical content of the present invention, the present invention will be further described below in conjunction with specific embodiments. For those not specified in the embodiments regarding specific technologies or conditions, they shall be carried out according to the technologies or conditions described in the literature in the field or according to the product specifications. Unless otherwise specified, the equipment and reagents used in each embodiment are commercially available as normal.

[0014] Example 1 Obtaining of Chip Core SNP Loci and Chip Preparation 1. Construction of a reference population of red grouper resistant to nervous necrosis virus and establishment of a phenotypic data set In this example, a reference population of red snapper (Cephalopholis sonnerati) resistant to nervous necrosis virus was constructed. This population consisted of 1,378 diseased fish infected with nervous necrosis virus collected from Hainan, China and Qingdao, Shandong between 2023 and 2024, and an additional 200 fish were added as a validation population, for a total of 1,578 individuals. Fin samples were collected from all tested individuals for genomic analysis, and the individual death / survival status and biological data were systematically recorded, providing important phenotypic basis for subsequent breeding of disease-resistant improved varieties. The genomic data of the reference population were obtained by whole-genome resequencing on the BGI T7 sequencing platform, laying the foundation for subsequent molecular marker development.

[0015] 2. Development and quality control process of high-quality SNP markers Genomic DNA was extracted from 1,578 individuals. After passing strict quality tests, paired-end DNA libraries for second-generation sequencing were constructed, and high-throughput sequencing was completed based on the BGI T7 sequencing platform. After the sequencing data passed quality control to obtain clean reads, the BWA software was used to align them with the red snapper reference genome (GenBank: GCA_043388425.1). After removing duplicate sequences, basic data information statistics and mapping analysis were performed. Based on the alignment results of the sequencing sequences and the reference genome, the GATK software was used for SNP calling to generate the original vcf file. Further, multi-level quality filtering was implemented using the VCFtools software: first, sites with a sequencing depth lower than 15× were removed, followed by filtering out sites with a missing rate exceeding 5%, a minor allele frequency (MAF) lower than 0.05, and those not in Hardy-Weinberg equilibrium (with the P-value threshold set to 1×10⁻ 5 ) sites. Finally, 11,898,532 high-quality SNP markers were obtained, and genotype imputation was performed using the Beagle v5.1 software, significantly improving data integrity and providing reliable genetic marker resources for subsequent genome-wide association studies (GWAS) and marker-assisted breeding.

[0016] 3. Extract SNP site information Based on the quality-controlled SNP dataset, the Plink v2.0 software was used to extract information from the red snapper reference population ( Cep.s.Ref)All strictly quality-controlled SNP sites were screened out. Subsequently, using the –bp-space command of Plink v1.9 software, equal-spacing sampling was performed according to the physical positions of SNPs, and finally 40,345 SNP markers evenly distributed across the genome were obtained and stored as "geno1.bin" (Geno1); meanwhile, all 11,898,532 high-quality SNP markers in the genome were saved as geno2.bin (Geno2). On this basis, 31 genetic loci significantly associated with resistance to nervous necrosis virus were identified through a genome-wide association study (GWAS) model, and the value (effect value vector) of each SNP was calculated using the MLE-rank model and sorted from largest to smallest by absolute value. Finally, the 31 high-genetic-effect loci screened by GWAS were integrated with the 469 core loci screened by the present invention based on the MLE-rank model to construct a high-genetic-effect marker set containing 500 loci (NO.001 - NO.500), denoted as geno3.bin. Among them, the GWAS model was implemented using Plink v2.0, with the first three principal components as covariates. The GWAS model is as follows:

[0017] Among them, is the phenotype vector, is the genotype matrix of the current variant site, is the fixed covariate matrix, is the error term.

[0018] The MLE-rank model is as follows:

[0019] Among them, represents the phenotype value of the nth sample, is the genotype of the jth SNP on the nth sample (0 / 1 / 2 represents AA / Aa / aa). is the overall sample obtained. is the proportion of surviving individuals in the sample. The obtained by the MLE-rank model represents the influence of the th SNP locus on the phenotype.

[0020] Example 2 Evaluation of the narrow-sense heritability of the trait of resistance to nervous necrosis virus in Cephalopholis sonnerati In this example, the narrow-sense heritability of the trait of resistance to nervous necrosis virus in Cephalopholis sonnerati was evaluated based on 500 core SNP markers. Three marker datasets constructed in Example 1 were used: 40,345 evenly distributed SNPs (Geno1, geno1.bin), 11,898,532 high-quality SNPs across the genome (Geno2, geno2.bin), and 500 SNPs at the core loci of the present invention (Geno3, geno3.bin). Based on the phenotypic data of the reference population, the GBLUP method (implemented through the asreml4-R software) was used for heritability estimation. The specific animal model is defined as follows:

[0021] Φ(·) is the cumulative standard normal distribution function, is the genomic relationship matrix used by VanRaden in 2008 , where M defines the genotype matrix, and AA / Aa / aa are 2 / 1 / 0, is the allele frequency matrix, is a diagonal matrix, is the normalization constant. is the effect value. The calculation method of genomic heritability is as follows:

[0022] is the additive variance, is the residual, which is fixed at 1 in this model.

[0023] The results in Table 2 show that there are significant differences in the heritability estimates of different marker sets: the heritability estimate based on Geno1 is 0.241 ± 0.033, the heritability estimate based on Geno2 is 0.243 ± 0.033, while the heritability estimate based on the core marker set Geno3 is the highest, reaching 0.407 ± 0.034. This indicates that the Geno3 marker set at the patent core loci can capture the genetic variation of the trait of resistance to nervous necrosis virus more efficiently, providing a better marker combination for subsequent molecular marker-assisted breeding.

[0024] Table 2 Evaluation of genetic parameters of resistance to nervous necrosis in Cephalopholis sonnerati by three groups of SNP markers

[0025] The results show that the core SNP marker set developed in this example exhibits significant advantages in the genetic parameter evaluation of the anti-necrotic virus trait of red grouper, and can capture more additive genetic variance. The reason is that the core markers screened by integrating GWAS and MLE-rank models in the present invention have a high genetic effect correlation, while the non-related or low-effect genetic markers included in Geno1.bin and Geno2.bin introduce noise, resulting in an estimation bias of the genetic parameters by the animal model. Therefore, the core SNP marker set screened by the present invention can effectively improve the accuracy of genetic parameter estimation, provide a more reliable theoretical basis for the genomic selection breeding of red grouper against neuro-necrosis virus, and ensure the efficient progress of the breeding work.

[0026] Example 3 Verification of the detection rate of core SNP loci for red grouper against neuro-necrosis virus To evaluate the detection efficiency of the 500 core SNP loci described in the present invention, a liquid-phase chip constructed with the core loci was used to genotype 19 individuals in the reference population that had completed whole-genome resequencing. The experimental results are shown in Table 3. It can be seen that the core loci designed by the present invention exhibit extremely high detection performance: the average genotype detection rate of 19 samples is as high as 99.2%, and the consistency of the genotypes of all loci with the whole-genome resequencing data reaches 99.5%. This result fully verifies the high accuracy and stability of the core SNP loci in genotyping. The results show that the high detection rate and accurate genotype determination ability of the core loci screened by the present invention provide a solid technical support for the genomic selection breeding of red grouper against neuro-necrosis virus, and provide a reliable genomic tool for the breeding of disease-resistant improved varieties.

[0027] Table 3 Detection rates of core SNP loci for red grouper against neuro-necrosis virus in different populations

[0028] Example 4 Evaluation of the prediction accuracy of core loci for genomic estimated breeding value (GEBV) of the validation population To evaluate the prediction accuracy of the core loci of the present invention for an unknown population, 200 red groupers were selected as the validation population. Among them, 100 individuals that died after being infected with neuro-necrosis virus were defined as the susceptible population, and the individuals that survived after infection were defined as the disease-resistant population. The 200 validation population samples were genotyped using the core SNP locus set Geno3 and locus set Geno1 of the present invention, respectively.

[0029] Based on the genotyping results, the genomic estimated breeding values (GEBVs) of these 200 non-reference group red snappers were estimated and subjected to 0-1 standardization. Subsequently, the standardized GEBVs were subjected to receiver operating characteristic curve (ROC) correlation analysis with the phenotypes of the infection experiment.

[0030] The analysis results showed that when using the core SNP locus set Geno3, the average GEBV of the disease-resistant group was 0.542, and that of the susceptible group was 0.385 ( Figure 2 ), and the area under the curve (AUC) value of the GEBV and the disease-resistant phenotype reached 0.799 ( Figure 1 ). When using the locus set Geno1, the GEBV of the disease-resistant group was 0.659, and that of the susceptible group was 0.589 ( Figure 2 ), and the AUC value of the GEBV and the disease-resistant phenotype was 0.63 ( Figure 1 ).

[0031] In summary, the 500 core loci provided by the present invention can more accurately predict the disease resistance of unknown populations in the genomic selection breeding of red snappers against nervous necrosis virus, and can meet the requirements of genomic selection breeding for the trait of red snappers against nervous necrosis virus.

[0032] Example 5 Further verification of the prediction accuracy of core loci for the GEBV of red snappers against nervous necrosis virus To further verify the effectiveness of the core SNP loci (Geno3) of the present invention in genomic selection against nervous necrosis virus disease, 80 red snapper individuals infected with nervous necrosis virus were selected as an independent verification group. Among them, 37 individuals that died after infection were defined as the susceptible group, and 43 surviving individuals were defined as the disease-resistant group. All individuals were genotyped using the core locus Geno3 of the present invention, and the GEBVs of the candidate population were estimated based on the genotyping data. Subsequently, the GEBVs were subjected to 0-1 standardization.

[0033] The experimental results showed that the average GEBV value of the disease-resistant group was 0.562, which was significantly higher than that of the susceptible group, 0.469 ( Figure 3 ). Further analyzing the top 10 individuals ranked by GEBV, 8 of them were surviving individuals and 2 were dead individuals; chi-square test (chisq.test function in R language) showed that this result was statistically significant (P = 0.025). Expanding the analysis scope to the top 15 individuals ranked by GEBV, 12 were surviving individuals and only 3 were dead individuals, and the P value of the chi-square test was 0.0034, indicating that the core loci described in the invention can effectively distinguish disease-resistant and susceptible individuals.

[0034] In summary, the core SNP loci of the present invention can effectively distinguish the disease resistance of individual red grouper, and the disease-resistant individuals can be significantly enriched through the GEBV ranking, providing a reliable technical tool for genomic selection breeding of red grouper against nervous necrosis virus disease.

[0035] Term Explanation: SNP: Single Nucleotide Polymorphism, which is an abbreviation for Single Nucleotide Polymorphism, representing DNA sequence polymorphism caused by single nucleotide variation at the genomic level.

[0036] Reference population: In genomic selection, a population with phenotypes and genotypes. The phenotypes are obtained through manual measurement, and the genotypes are obtained through genomic sequencing. This population is used to train the model.

[0037] Candidate population: In genomic selection, a population with only genotypes but no phenotypes, usually the alternative individuals in the breeding process. After measuring the genotypes, the breeding values of these individuals can be estimated in combination with the reference population, and the individuals can be preferentially selected and bred based on the high or low breeding values.

[0038] GBLUP: Genomic Best Linear Unbiased Prediction, which is an abbreviation for Genomic Best Linear Unbiased Prediction. It is a method for estimating individual breeding values by constructing a genomic relationship matrix G matrix using high-density molecular markers covering the genome.

[0039] GEBV: Genomic Estimated Breeding Value, which is an abbreviation for Genomic Estimated Breeding Value. It is the breeding value estimated at the genomic level through genomic selection methods.

[0040] GWAS: Genome-wide association study, which is an abbreviation for genome-wide association study. GWAS is a hypothesis-free method for identifying associations between genetic regions (loci) and traits (including diseases).

[0041] MLE-rank: A ranking method based on maximum likelihood estimation, which may be used to rank the importance of SNP markers or individuals, assisting in screening core loci or optimizing breeding value estimation.

[0042] BayesA: A type of Bayesian method that assumes that marker effects follow a normal distribution and is applicable to complex traits controlled by multiple genes. In genomic selection, it may be used to estimate marker effects.

[0043] ROC: Receiver Operating Characteristic Curve, which is a visualization tool used to evaluate the predictive ability of classification models. The horizontal axis is the False Positive Rate (FPR), representing the proportion of non-target categories mispredicted as target categories; the vertical axis is the True Positive Rate (TPR), representing the proportion of correctly identified target categories.

[0044] AUC: Area Under the Curve. AUC is the area under the ROC curve, with a value range from 0 to 1. The closer the AUC value is to 1, the higher the predictive accuracy of the model; if AUC is 0.5, it means the model's prediction effect is no different from random guessing.

Claims

1. A liquid-phase chip for genomic selection breeding of Cephalopholis sonnerati against nervous necrosis virus, characterized in that, The genotyping targets of the chip include 500 SNP loci on the red snapper reference genome, and the positions of these loci on the red snapper reference genome and the mutation types are shown as NO.001 - NO.500: 。 2. Use of the liquid chip according to claim 1 in genomic selection breeding of red snapper resistant to nervous necrosis virus.

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