SNP (Single Nucleotide Polymorphism) marker combination for identifying tilapia streptococcus agalactiae disease resistance and application thereof

Abstract

The invention relates to the technical field of biology, in particular to an SNP (Single Nucleotide Polymorphism) marker combination for identifying tilapia streptococcus agalactiae disease resistance and application thereof. The invention discloses 11 SNP loci significantly related to streptococcus agalactiae resistance in a tilapia UTRN gene, and constructs 18 SNP marker combinations for streptococcus agalactiae resistance phenotype identification, so that the resistance phenotype identification accuracy and hereditary stability can be effectively improved. Besides, according to the SNP typing primer and method based on the # imgabs0 # MALDI-TOF mass spectrum platform, high-throughput and high-precision genetic typing can be achieved, and the SNP typing primer and method have important application value in resistance phenotype identification and assistant selective breeding.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, in particular to a SNP marker combination for identifying tilapia resistance to Streptococcus agalactiae disease and an application thereof. Background Art

[0002] Tilapia (Oreochromis spp.) is a staple freshwater fish species cultivated in my country, accounting for 6.76% of total freshwater fish production in 2023. However, since 2009, a large-scale outbreak of Streptococcus agalactiae has occurred in my country, with an incidence rate of 20%-30% and a mortality rate of 25%-80%, with an increasing trend year by year. Typical symptoms include proptosis, skin hemorrhages, visceral congestion, and encephalitis. Infected fish exhibit abnormal behaviors such as spiraling movements, which are particularly harmful to adult fish. Current industry prevention and control efforts primarily rely on antibiotics, but long-term use has led to the emergence of multidrug-resistant strains. Vaccine immunization strategies are also limited by the narrow window of susceptible juvenile fish and the risk of environmental residues. Therefore, enhancing the disease resistance of core populations through selective breeding is a key path to achieving sustainable development goals for the industry.

[0003] In the field of genetic breeding, although traditional phenotypic selection can reduce the mortality rate of Streptococcus agalactiae in farmed populations by 30%-50%, the efficiency of selection is limited by technical bottlenecks such as long phenotyping cycles and multiple environmental interference factors. As the application of genomic selection breeding in livestock, poultry, and aquatic animals becomes increasingly mature, breeding time has been greatly shortened and the accuracy of individual phenotypic prediction has been greatly improved. However, efficient genomic selection breeding requires accurate phenotyping and high-density single nucleotide polymorphism (SNP) mapping through genome-wide association analysis (GWAS) and quantitative trait locus (QTLs) to obtain phenotype-related molecular markers for molecular marker-assisted selection (MAS) or genome-wide selection breeding (GS).

[0004] Genomic selection breeding is one of the best approaches for disease resistance breeding, as it can avoid the impact of toxicological challenge experiments on parental seed retention and health. Tilapia resistance to Streptococcus agalactiae is a quantitative trait controlled by multiple genes. For such traits, genomic selection often relies on effector single nucleotide polymorphisms (SNPs) to improve prediction accuracy and reliability. Although genome-wide association studies have been reported for tilapia resistance to Streptococcus agalactiae, candidate SNPs have been characterized by a small number, scattered distribution, and low explanatory power of genetic effects. Recently, Chinese researchers constructed a high-density genetic linkage map for disease resistance in tilapia and located a QTL associated with Streptococcus agalactiae resistance on linkage group (LG) 9. The confidence interval was 0.67–6.67 cM, encompassing five immune-related genes. However, the authors believe that further mapping refinement is needed to narrow the scope of QTL identification for Streptococcus agalactiae resistance in tilapia. Therefore, it is urgent to develop more phenotype-related effect SNP sites for tilapia resistance to Streptococcus agalactiae disease to achieve efficient and accurate resistance identification and genome-assisted selection breeding. Summary of the Invention

[0005] In view of this, the present invention proposes a SNP marker combination for identifying tilapia resistance to Streptococcus agalactiae disease and its application.

[0006] The technical solution of the present invention is achieved as follows:

[0007] In a first aspect, the present invention provides a SNP marker combination for identifying resistance to Streptococcus agalactiae in tilapia, wherein the SNP marker combination consists of a first SNP molecular marker and a second SNP molecular marker, and the SNP marker combination includes at least one of the following (Table 1) A1-A18:

[0008] Table 1 SNP marker combinations used to identify resistance to Streptococcus agalactiae in tilapia

[0009]

[0010]

[0011] The dominant genotypes of tilapia resistant to Streptococcus agalactiae in A1-A18 are as follows:

[0012]

[0013] The dominant genotype of the SNP marker combination A11 for resistance to Streptococcus agalactiae is: the genotype of the first SNP molecular marker is AA, and the genotype of the second SNP molecular marker is GG; or the genotype of the first SNP molecular marker is GA, and the genotype of the second SNP molecular marker is AA;

[0014] The SNP sites are shown in Table 2:

[0015] Table 2 Information of 11 SNP loci in tilapia

[0016]

[0017]

[0018] Reference Nile tilapia genome O_niloticus_UMD_NMBU.

[0019] In a second aspect, the present invention provides use of the SNP marker combination in identifying resistance to Streptococcus agalactiae disease in tilapia.

[0020] In a third aspect, the present invention provides an application of the SNP marker combination in breeding tilapia resistant to Streptococcus agalactiae disease.

[0021] In a fourth aspect, the present invention provides the use of a product for detecting the SNP marker combination in identifying tilapia resistance to Streptococcus agalactiae disease or breeding tilapia resistant to Streptococcus agalactiae disease.

[0022] In a fifth aspect, the present invention provides a method for identifying resistance to Streptococcus agalactiae disease in tilapia, the method comprising: determining the genotype of a sample to be tested, wherein the genotype is the genotype of the SNP marker combination.

[0023] In a sixth aspect, the present invention provides a method for breeding tilapia resistant to Streptococcus agalactiae disease, the method comprising: determining the genotype of the SNP marker combination according to claim 1 in the individual to be tested, screening individuals with a dominant genotype as parents for breeding, and obtaining offspring with improved resistance to Streptococcus agalactiae disease.

[0024] Further, in some specific embodiments, based on time-of-flight mass spectrometry, using Genotyping was performed using MALDI-TOF. The PCR primer sequences used were selected from SEQ ID NOs: 1-33. Specifically, the required primers were selected based on the SNP sites being detected, with the corresponding relationships being as follows:

[0025] SEQ ID NO: 1-3 was used to detect the genotype of SNP31, and SEQ ID NO: 4-6 was used to detect the genotype of SNP28.

[0026] SEQ ID NOs: 7-9 were used to detect the genotype of SNP34, and SEQ ID NOs: 10-12 were used to detect the genotype of SNP49.

[0027] SEQ ID NOs: 13-15 were used to detect the genotype of SNP27, and SEQ ID NOs: 16-18 were used to detect the genotype of SNP30.

[0028] SEQ ID NOs: 19-21 were used to detect the genotype of SNP32, and SEQ ID NOs: 22-24 were used to detect the genotype of SNP50.

[0029] SEQ ID NOs: 25-27 were used to detect the SNP52 genotype, SEQ ID NOs: 28-30 were used to detect the SNP33 genotype, and

[0030] The SNP35 genotype was detected using SEQ ID NOs: 31-33.

[0031] The beneficial effects of the present invention include at least the following:

[0032] The present invention successfully constructed 18 SNP marker combinations (A1-A18) related to resistance to Streptococcus agalactiae in the functional region of the UTRN gene of tilapia. Specifically, the combination of dominant resistance genotypes composed of specific SNP sites achieved accurate identification of the resistance phenotype of Streptococcus agalactiae. The present invention's research showed that individuals carrying the dominant genotype combination of molecular markers had significantly prolonged survival time after challenge with Streptococcus agalactiae, and the phenotypic variation coefficient was also significantly reduced, indicating that the molecular marker can effectively improve the accuracy of resistance phenotype identification and genetic stability.

[0033] The present invention simultaneously develops a The SNP typing primers and methods developed using the MALDI-TOF mass spectrometry platform meet the technical requirements for high-throughput, high-precision genotyping in modern aquaculture breeding. In breeding applications, targeted selection of individuals carrying advantageous resistance genotype combinations as core breeding parents can effectively shorten the breeding cycle and has important industrial application value. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0035] Figure 1 This is the distribution of survival time of 494 Nile tilapia after challenge with Streptococcus agalactiae.

[0036] Figure 2 This is the SNP density distribution of resequencing of 494 Nile tilapia (challenged with Streptococcus agalactiae);

[0037] Figure 3A genome-wide association analysis of the survival time of tilapia after infection with Streptococcus agalactiae was performed, showing SNP sites that were significantly associated with the survival time after infection with Streptococcus agalactiae. Figure 3 Middle: a is the Manhattan plot; b is the QQ plot (Quantile-Quantile plot);

[0038] Figure 4 Functional enrichment analysis of candidate genes for resistance to Streptococcus agalactiae in tilapia; Figure 4 Middle: a is GO biological process (BP) enrichment analysis; b is KEGG pathway enrichment analysis; (Note: bubble size is proportional to the number of enriched genes, red intensity is proportional to the negative logarithm of significance, and dark red bubbles represent strong associations);

[0039] Figure 5 Based on MALDI-TOF typing validation and phenotypic association analysis of candidate SNPs for resistance to Streptococcus agalactiae in tilapia; ak (subgraphs) represent the typing results of the individual to be tested at the corresponding SNP loci. In each subgraph: the upper part represents a scatter plot of the typing results, with each color representing a genotype; the lower part is an interval plot of the association analysis between genotype and survival time. If there is no significant correlation, it is not marked as significant.

[0040] Figure 6 This is the correlation analysis between the genotype combination of SNP52 and the other 10 SNPs and the corresponding tilapia survival time. The horizontal axis represents the genotype combination in 012 format (see Table 11) (e.g. Figure 6 In subgraph a, the horizontal axis is represented by "00", the number "0" on the left represents the genotype GG of SNP52, and the number "0" on the right represents the genotype AA of SNP27. The vertical axis represents the survival time. The column interval represents the survival time interval corresponding to the genotype (greater than 95% confidence level). Significant statistics are represented by lowercase letters. If the lowercase letters are different, it means that there is statistical significance between the two groups (p < 0.05).

[0041] Figure 7 Figure 5. Correlation between genotype combinations formed by pairing the remaining 10 SNPs, excluding SNP52, and survival time. Among the 15 SNP pairs shown in this figure, there are significant differences in the survival time of individuals with different genotypes. Conversely, the SNP pairs not shown in this figure indicate that there is no significant difference in the survival time of individuals with different genotypes formed by the SNP pairs. The horizontal axis represents the genotype combination in 012 format, and the vertical axis represents the survival time. The column interval represents the survival time interval corresponding to the genotype (greater than 95% confidence level). Significant statistics are represented by lowercase letters. If the lowercase letters are different, it means that there is statistical significance between the two groups (p<0.05). The black arrow represents the genotype combination that is significantly associated with resistance to agalactiae disease after screening. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Obviously, the embodiments described are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of the present invention. If specific conditions are not specified in the embodiments, they are carried out according to conventional conditions or the conditions recommended by the manufacturer. If the manufacturer is not specified for the reagents or instruments used, they are all conventional products that can be purchased commercially.

[0043] Example 1

[0044] 1. Materials and Methods

[0045] 1. Experimental animals and sample collection

[0046] The GIFT strain of Nile tilapia used in the present invention was purchased from the Guangdong Tilapia Breeding Farm. 1,710 healthy and well-proportioned tilapia were evenly raised in 4 cement culture ponds (length: width: height = 3:3:1.5m). During the feeding period, the water temperature was maintained at 28±2°C, the dissolved oxygen was controlled at 6.0-7.5mg / L, the pH value was stabilized at 7.5-8.5, and the total ammonia nitrogen was maintained at <0.1mg / L. The fish were fed once a day at 7:00 am and 19:00 pm with commercial compound feed. One month before the experiment, all fish were marked with a passive integrated transponder (PIT), and about 2cm of the tail fin was collected and immersed in anhydrous ethanol and stored at -20°C for use.

[0047] 2. Preparation of Streptococcus agalactiae liquid

[0048] The Streptococcus agalactiae WC1535 in the embodiment can be found in the reference (Zhang Meiyan, Zhu Weijuan, Liu Zhigang, et al. Differential expression analysis of plasma proteomics before and after tilapia infection with Streptococcus agalactiae [J]. Journal of Dalian Ocean University, 2024, 39(04): 559-567. DOI: 10.16535 / j.cnki.dlhyxb.2023-288.), which is available to the public from the Pearl River Fisheries Research Institute of the Chinese Academy of Fishery Sciences. The applicant promises to release the biological material to the public within 20 years from the date of application.

[0049] The storage temperature of Streptococcus agalactiae WC1535 is -80°C. The activated strain was streaked onto Brain-Heart Infusion Broth (BHI) solid medium and cultured overnight at 37°C. A single colony was picked and placed into 10 mL of liquid BHI medium and cultured at 37°C with shaking for 24 hours (hours, h) until the colony reached the logarithmic phase (OD at 460 nm). 600 =~1.5, about 10 8 The bacterial solution was washed three times and resuspended in sterile 1× PBS. The bacterial solution concentration was measured using a BioMerieux turbidimeter. The final concentration of the bacterial solution was then adjusted to 3.8×10 6 CFU / mL. The final concentration of bacterial solution was obtained from the preliminary experiment. Briefly, 4 groups of WC1535 challenge experiments were set up, with 10 biological replicates in each group. The challenge doses were 10 9 , 10 8 , 10 7 , 10 6 CFU / mL. After the challenge with Streptococcus agalactiae, the number of dead individuals in each group was recorded within 7 days, and then the online software LD 50 The median lethal dose (LD50) was calculated using the default parameters using a calculator (https: / / www.aatbio.com / tools / ld50-calculator). 50 ). The LD of this experiment 50 3.8×10 6 CFU / mL.

[0050] 3. Virus challenge experiment and phenotypic recording

[0051] 494 fish were randomly selected from the above population and evenly distributed across five 500L aquaria to serve as the challenge group. Another 100 fish were housed in a single 500L aquarium to serve as the control group. Water quality and feeding conditions were the same for each group, except that the temperature was elevated to 31±1°C. After two weeks of training, the fish were challenged with Streptococcus agalactiae. In the challenge group, 100 μL of bacterial solution was injected intraperitoneally. In the control group, 100 μL of sterile 1× PBS was injected intraperitoneally. Survival time for each group was measured in hours per hour (hpi). Survival time was determined to be caused by S. agalactiae based on the presence of typical symptoms of S. agalactiae, such as exophthalmos, skin ulceration, and spiral swimming, compared to the control group. Survival time was recorded immediately after the last fish was injected with the bacterial solution. For example, if a fish died 1 hour after infection, the survival time was recorded as 1 hpi. During this period, survival time was recorded every 0.5 hours. Starting from the 5th day after infection, the survival time was recorded every 12 hours. In this experiment, until 14 days after the infection, the infection group still had dead individuals with typical symptoms of Streptococcus agalactiae disease, but no dead individuals appeared in the next 5 days. During this period, the fish in the control group did not show symptoms of Streptococcus agalactiae disease and there were no dead fish. Therefore, the phenotypes of the dead fish in the infection group were collected until 14 days after the infection, and the fish that survived after 14 days were uniformly recorded as 336hpi. The above 494 individuals were resequenced. At the same time, the remaining 1116 fish in the cement pond were subjected to MassARRAY typing verification. See Example 3 for specific experimental grouping and phenotype collection methods.

[0052] 4. DNA extraction, library construction and resequencing

[0053] Genomic DNA was extracted from the caudal fin according to the instructions of the HiPure Tissue DNA Micro Kit (Magen, Guangzhou, China). DNA integrity and concentration were assessed using 1.5% agarose gel electrophoresis and Nanodrop 2000 spectrophotometry. Paired-end libraries were constructed using the NEBNext Ultra II DNA Library Preparation Kit (NEB, Beijing, China). High-throughput sequencing was performed by Biomike Biotechnology Co., Ltd. (Beijing, China) on the BGISEQ-500 platform (BGI, Shenzhen, China) with a read length of 150 bp.

[0054] 5. SNP scanning, typing and heritability analysis

[0055] The raw data were quality-controlled using fastQC (v 0.12.1) with default parameters. The quality-controlled data were then mapped to the Nile tilapia reference genome, O_niloticus_UMD_NMBU (https: / / www.ncbi.nlm.nih.gov / datasets / genome / GCF_001858045.2 / ), using bwa (v0.7.17) with default parameters. The mapped files were then sorted and indexed using Samtools (v 1.21). After generating the bam file for indexing, SNPs were called using GATK HaplotypeCaller (v4.0) to generate gVCF files for each individual. High-quality SNPs were screened from the gVCF of each individual using the following parameters: QD < 2.0, MQ < 40.0, FS > 60.0, QUAL < 30.0, MQrankSum < -12.5, ReadPosRankSum < -8.0, -clusterSize 2, -clusterWindowSize 5. Finally, all gVCF files were merged using GATKGenomicsDBImport (v4.0), and the merged gVCF data were genotyped using GATK GenotypeGVCF (v4.0) to generate a single VCF file containing the called variants of all samples.

[0056] SNP position annotation was performed using snpEff software (v3.6c) based on the reference genome O_niloticus_UMD_NMBU. SNP locations were categorized as intergenic regions, upstream or downstream regions, and exons or introns. In addition, SNPs in coding exons were further categorized as synonymous or nonsynonymous mutations.

[0057] Heritability analysis was performed using GCTA (v1.94.4). First, a GRM matrix was generated using the --make-grm parameter. This matrix was then used to calculate heritability using the --grm qc parameter. Principal component analysis (PCA) of the SNPs was performed using the smartPCA program in EIGENSOFT (v.7.2.1) with default parameters.

[0058] 2. Results

[0059] 1. Descriptive statistics of binary disease resistance phenotypes and resequencing data

[0060] Using the survival time after infection as the phenotype, 494 Nile tilapia were challenged with Streptococcus agalactiae. The results showed that there were 257 survivors and 237 deaths ( Figure 1After resequencing the above individuals, approximately 5,794 Gb of high-quality data were obtained. The GC content was 40.24% and the Q30 was >97.00%. A total of 4,058,381 SNPs were obtained, which were unevenly distributed among all 22 LGs. The SNP marker density was highest in LG3 and lowest in LG19 ( Figure 2 ).

[0061] 2. Heritability estimation of survival time of tilapia infected with Streptococcus agalactiae

[0062] After infection with Streptococcus agalactiae, SNP-based genetic parameter estimation revealed a low heritability of survival time of 0.0805 (Table 3). This result suggests that this population has not been subjected to artificial selection. Through selective breeding, it is possible to improve the heritability of survival time and, in turn, enhance the resistance of progeny to Streptococcus agalactiae. Therefore, it is necessary to identify effector SNPs associated with survival time to improve the efficiency of selection in this population.

[0063] Table 3 Genetic parameter estimation of the disease resistance binary phenotype based on SNPs

[0064] Genetic parameters Coefficient of variation Standard error Additive variance components 1203.289 1072.114 Residual variance components 13743.58 1362.215 Phenotypic variance components 14946.86 952.3558 Heritability 0.080504 0.071407

[0065] Example 2 GWAS analysis and functional gene annotation of candidate SNP sites

[0066] 1. Methods

[0067] Low-quality variants were filtered using PLINK 1.9 with the following parameters: --maf 0.05, --max-missing 0.8. The filtered VCF files were converted to PLINK format using VCFtools (v0.1.16) for GWAS analysis. The GWAS used a LM model. The present invention used GEMMA (v.0.96) to run the LM model. The effects of population stratification were corrected by adjusting the first three PCs.

[0068] y=Wα+xβ+μ+e (1)

[0069] In this formula, the covariate W is the first three PCs, X is the genotype, and Y is the phenotype. The genomic kinship μ was obtained using the -gk1 program in the GEMMA software.

[0070] The present invention annotated the functional genes of candidate SNP sites. According to the attenuation distance between SNPs, the functional genes were queried within 100 kb upstream and downstream of the SNP. The annnovar (v4.7) software was used with O_niloticus_UMD_NMBU as the reference genome. The coding gene annotation of the SNPs found in the association analysis was performed based on the SNP region (-regionanno) through the annotate_variation.pl function.

[0071] The annotated gene sets were simultaneously subjected to GO and KEGG enrichment analysis. The background annotation set consisted of all coding genes in the tilapia (O_niloticus_UMD_NMBU). Protein sequences of all genes were extracted using TBtools (v1.6) and annotated using EGGNOG (http: / / eggnog-mapper.embl.de / ). GO and KEGG enrichment analysis was then performed on the OmicShare platform (https: / / www.omicsmart.com / # / ), using the candidate genes as input and all annotated genes as the background gene set.

[0072] 2. Results

[0073] After GWAS analysis, SNPs significantly associated with survival time were located on 13 different chromosomes ( Figure 3 However, clustered SNPs are mainly located in LG15, LG19 and LG20 (clustered SNPs ≥ 8) ( Figure 3 Among them, LG15 is rich in 15 SNPs that are significantly associated with disease resistance phenotypes and forms a 0.15M SNP cluster ( Figure 3 The nine phenotype-significantly associated SNPs on LG19 formed a 3.17M SNP cluster ( Figure 3 (a, Table 4). 14 phenotype-significantly associated SNPs on LG20 formed a 1.93M SNP cluster ( Figure 3 However, compared with the SNP cluster on LG15, the SNP density within the clusters on LG19 and LG20 was lower and the distances between SNPs were greater (Table 4).

[0074] Table 4 SNPs significantly associated with tilapia survival time after S. agalactiae infection

[0075]

[0076]

[0077]

[0078] As shown in Table 4, a total of 201 coding genes were annotated to the candidate SNPs. GO enrichment analysis showed that the annotated genes were significantly associated with the interleukin-27-mediated signaling pathway ( Figure 4 KEGG analysis showed that the above genes were significantly enriched in intestinal immune network for IgA production, SNARE interactions in vesicular transport and Notch signaling pathway ( Figure 4 Interleukin-27 and intestinal IgA analysis of immune networks are both important immune regulatory pathways in the body, indicating that the above candidate SNP-annotated genes are related to the immune regulation of tilapia agalactiae disease.

[0079] Since the number of trait-related SNPs distributed on LG15 is the largest and they are densely distributed in clusters. Therefore, the present invention further performed gene annotation analysis on the 0.15M SNP cluster formed by LG15. The results showed that the SNP cluster is located on dystrophin (Utrophin, UTRN) (Table 4). UTRN contains 79 exons, which are expressed in various tissues of mammals and are highly expressed in the lungs, intramuscular fat and skeletal muscle. Knockout of this gene will lead to skeletal muscle inflammation and fibrosis in mice. This is similar to the pathological symptoms of skin and muscle tissue ulceration in tilapia with Streptococcus agalactiae disease, indicating that this gene may play an important regulatory function in streptococcal disease.

[0080] Example 3 MassARRAY pool typing of mutation sites

[0081] 1. Methods

[0082] 1. Preparation of Streptococcus agalactiae culture, challenge experiment and survival time phenotype collection

[0083] The preparation of Streptococcus agalactiae liquid is the same as in Example 1. The methods of attacking and collecting phenotypes are as follows. 1116 fish in a cement pond were divided into two groups, of which the experimental group (attack group) contained 1016 tilapia and the control group contained 100 tilapia. The tilapia in the experimental group were trained and raised in 3 cement ponds of the specifications shown in Example 1, and the control group was raised in a 500L glass fish tank. The breeding conditions were the same as in Example 1. After two weeks of training, the water temperature was raised to 31±1°C, and then the experimental group and the control group were injected with bacterial liquid or PBS according to the method shown in Example 1. Individuals who died due to infection with Streptococcus agalactiae were screened based on typical symptoms of Streptococcus agalactiae disease such as exophthalmos, skin ulcers, and spiral swimming.

[0084] Survival profiles were collected as described in Example 1. In this experiment, the last individual to develop typical symptoms of streptococcal disease was 10 days after challenge. During this period, no fish in the control group developed any symptoms or died. Therefore, the survival profiles of the fish that died in the challenge group were recorded as 10 days after challenge (≤240 hpi), and the survival profiles of the fish that survived the challenge group were uniformly recorded as 250 hpi.

[0085] 2. Correlation analysis between SNPs in the UTRN gene and survival time after S. agalactiae infection

[0086] First, based on the evaluation of 15 candidate SNPs in the UTRN gene and their upstream and downstream 100bp sequence information, the present invention found that a pooled typing method for 11 of these SNPs could be constructed based on MassARRAY (Table 5). Each SNP was typed into three genotypes, corresponding to the genotypes shown in Table 3. PCR reactions and single-base extension primers (Table 6) were designed using Agena Bioscience's primer design software, Assaydesign 3.1, and synthesized by Shanghai Bioengineering.

[0087] Table 5 15 candidate SNPs located in the UTRN gene

[0088]

[0089] Table 6 Primer sequences used for MassARRAY typing (5'-3')

[0090]

[0091]

[0092] Note: 2nd-PCRP and 1st-PCRP are the upstream and downstream primers for PCR amplification of each SNP, respectively; UEP_SEQ is a single-base extension primer.

[0093] The DNA of each sample was then placed in a 384-well PCR plate for PCR reaction, shrimp alkaline phosphatase (SAP) digestion, single-base extension reaction, resin purification, and mass spectrometry detection. The PCR reaction system is shown in Table 7, and the reaction program is 94°C for 2 minutes (minutes, min); 94°C for 20 seconds (seconds), 56°C for 30 seconds, 72°C for 60 seconds, 45 cycles; 72°C for 3 minutes. The PCR reaction used a hot start enzyme. Max DNA Polymerase was used for amplification (R047A, TAKARA, Dalian). The reaction system of SAP (783901000UN, ThermoFisher scientific, Shanghai) is shown in Table 8. The reaction procedure was 37°C for 40 min and 85°C for 5 min. The single base extension reaction was performed according to Pro sample identification kit operating instructions (13116F, Agena Bioscience, Shanghai). The reaction system is shown in Table 9, and the reaction procedure is shown in Table 10. During resin purification, first centrifuge the 384 plate at 2000rpm for 2 minutes. Then, add 16ul of sterile double-distilled water to each well and centrifuge at 2000rpm for 2 minutes. Subsequently, the resin was evenly applied to the 6MG 384 plate and inverted on top of the 384-well PCR plate. Tap the 6MG plate to allow the resin to fall into the 384-well plate containing the single-base extension product. Turn the sealed PCR plate upside down to allow the resin to fully fuse with the PCR product. Finally, centrifuge at 2000rpm for 5 minutes and set aside. During mass spectrometry detection, first perform sample arrangement for the 384 detection wells according to the Typer (v4.0) software. Subsequently, the resin-purified samples were added in sequence according to the arranged sample order, with 10μL of sample added to each well. Finally, according to the Typer Chip Linker (v2.0) software operating instructions, the 11 SNPs to be detected in each sample were typed and visualized using a MassArray SNP typing mass spectrometer (SEQUENOM, San Diego, USA).

[0094] Table 7 PCR reaction system

[0095] Reagents concentration Volume (μL) Double distilled water - 927.5 <![CDATA[PCRBuffer(15mMMgCl2)]]> 10× 331.25 <![CDATA[MgCl2]]> 25mM 172.25 dNTPMix 25mM 53 PrimerMix 0.5uM 530 HotstarTaq 5U / μL 106 DNA template 10 ng / μL 1 / well Total - 5 / well

[0096] Table 8 Reaction system of SAP digestion

[0097]

[0098]

[0099] Table 9 Single base extension reaction system

[0100] Reagents concentration Volume (μL) Double distilled water - 400.2 iPLEX Bufferplus 10× 106 iPLEXterminator NA 106 PrimerMix 0.6-1.3μM 426.1 iPLEXenzyme NA 21.7 Total - 2 / well

[0101] Table 10 Single base extension reaction cycle parameters

[0102]

[0103] 3. Data Statistics

[0104] After MassARRAY typing, Minitab software (v21.0) was used to analyze the statistical significance of survival time between different genotypes. The Fisher's exact test was used. P < 0.05 was considered statistically significant.

[0105] 2. Results

[0106] The present invention conducted a challenge experiment on 1016 Nile tilapia and obtained 918 survivors and 98 deaths. After the challenge, the survival time of these fish was recorded. At the same time, MassARRAY genotyping of 11 SNPs was performed using the fin DNA of the above 1016 fish. The results showed that the average typing success rate of SNPs reached 95.81% ( Figure 5 , Table 11). However, statistical analysis found that the above-mentioned single SNPs had no significant correlation with survival time (p>0.05).

[0107] Table 11 MassARRAY typing efficiency statistics

[0108]

[0109] The results of the correlation analysis between the genotype combination composed of SNPs in the UTRN gene of tilapia and resistance to Streptococcus agalactiae disease in the present invention show that:

[0110] like Figure 6 As shown in the figure, this result uses an interval plot to show the interval of survival time for each genotype with a confidence level of more than 95%. Figure 6 As shown in Figure a, the SNP marker 00 composed of SNP52 and SNP27 has a confidence level greater than 95% in the interval of ~240-~250 hpi. The results show that although SNP52 alone is not significantly associated with survival time, among the nine genotype combinations formed by SNP52 and SNP50, the survival time corresponding to genotypes 10, 20, and 21 (012 format) is significantly higher than that of other genotypes. More noteworthy is that the genotype combination formed by the recessive homozygous genotype GG of SNP52 and the recessive homozygous genotypes of the other nine SNPs (excluding SNP50) significantly increased the survival time of tilapia after challenge. This is reflected in the following: (1) The survival time of genotype 00 fish is significantly higher than that of other genotypes; (2) the survival time interval of genotype 00 fish with a confidence level of more than 95% is around 240-250 hpi, which is the interval where the surviving fish are located. The survival times of fish of other genotypes with a confidence level of more than 95% all included intervals below 240 hpi, which were the intervals where the fish died. Therefore, the 00 genotype combination was identified as the genotype resistant to Streptococcus agalactiae disease in tilapia, corresponding to the SNP marker combinations A1-A9 and their dominant resistance genotypes in Table 12.

[0111] Table 12 SNP marker combinations and dominant resistance genotypes used to identify tilapia resistance to Streptococcus agalactiae

[0112]

[0113] like Figure 7 As shown in the figure, 10 SNPs on UTRN (except SNP52) were paired in pairs, and there were 15 groups of SNP pairs with significant differences in the survival time of individuals with different genotypes. Unlike the SNP combination formed by the above-mentioned SNP52, the number of individuals with a survival time interval of a certain genotype combination near 240-250hpi is small, which may be related to the low linkage effect between SNPs. Therefore, in addition to the two criteria of confidence interval and significance, the present invention uses the number of individuals corresponding to the genotype>20 as the third criterion for judging SNP combinations related to resistance to streptococcal disease. According to the above three criteria, the present results identified 9 SNP marker combinations A10-A18 and their dominant resistance genotypes for resistance to agalactiae from the above-mentioned 15 groups of SNP pairs as shown in Table 12 ( Figure 7 ).

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A SNP marker combination for identifying resistance to Streptococcus agalactiae in tilapia, characterized in that: The SNP marker combination consists of a first SNP molecular marker and a second SNP molecular marker, and the SNP marker combination includes at least one of the following A1-A18: The dominant genotypes of tilapia resistant to Streptococcus agalactiae in A1-A18 are as follows: The dominant genotype of the SNP marker combination A11 for resistance to Streptococcus agalactiae is: the genotype of the first SNP molecular marker is AA, and the genotype of the second SNP molecular marker is GG; or the genotype of the first SNP molecular marker is GA, and the genotype of the second SNP molecular marker is AA; The SNP sites are as follows: Reference Nile tilapia genome O_niloticus_UMD_NMBU.

2. Use of the SNP marker combination according to claim 1 in identifying resistance to Streptococcus agalactiae disease in tilapia.

3. Use of the SNP marker combination according to claim 1 in breeding tilapia resistant to Streptococcus agalactiae disease.

4. Use of a product detecting the SNP marker combination according to claim 1 in identifying resistance of tilapia to Streptococcus agalactiae or in breeding tilapia resistant to Streptococcus agalactiae.

5. A method for identifying resistance to Streptococcus agalactiae in tilapia, characterized in that: Determine the genotype of the sample to be tested, wherein the genotype is the genotype of the SNP marker combination according to claim 1.

6. The method according to claim 5, characterized in that Based on time-of-flight mass spectrometry, using Perform genotyping.

7. The method according to claim 6, characterized in that The PCR primer sequences used were selected from SEQ ID NOs: 1-33.

8. A method for breeding tilapia resistant to Streptococcus agalactiae disease, characterized in that: The genotype of the SNP marker combination according to claim 1 is determined in the individual to be tested, and individuals with the dominant genotype are selected to be used as parents for breeding to obtain offspring with improved resistance to Streptococcus agalactiae disease.

9. The method according to claim 8, characterized in that Based on time-of-flight mass spectrometry, using Perform genotyping.

10. The method according to claim 9, characterized in that The PCR primer sequences used were selected from SEQ ID NOs: 1-33.

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