Identification of genes associated with pan-vibrios resistance (PVR) trait of shrimp Litopenaeus vannamei through Genome-wide association study

Identification of genes associated with pan-vibrios resistance (PVR) trait of shrimp Litopenaeus vannamei through Genome-wide association study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of genes associated with pan-vibrios resistance (PVR) trait of shrimp Litopenaeus vannamei through Genome-wide association study Shuyang Wen, Chuhang Cheng, Jiayue Yin, Ying Lv, Xin Zhang, Bo Ma, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6178636/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Vibriosis caused by various Vibrio species is the most serious bacterial disease of shrimp. Due to the prevalence of pathogenic vibrios, genetic breeding of shrimps with the pan-vibrios resistance (PVR) trait has more practical significance for successful shrimp farming. To explore the genetic loci associated with the PVR trait of Litopenaeus vannamei , a genome-wide association study (GWAS) aiming at the PVR trait of the shrimp was conducted by using 300 shrimp individuals from various sources. After stringent screening, 243 single nucleotide polymorphisms (SNPs) corresponding to a selection threshold of -log10(p) value ≥ 2.5 were evaluated for their association with the PVR trait. Twenty candidate SNPs in genes and upstream region of genes (≤ 5000 bp) were screened out for further validation of the association. The genotypes of three SNPs (SNP15, SNP16, and SNP17) were different between G1 (uninfected) and G4/G5 groups (seriously infected), among which GG genotype of SNP15 was significantly associated with low vibrios load. The genotype combination of GG-TT-AA at the three SNPs was linked, and it was significantly associated with the strongest performance of the trait. Notably, three SNPs were found located in the intron region of a gene, LvCthrc1 . The genotype combination can lead to the disappearance of a donor splicing site of LvCthrc1 , which predictably generates a novel transcript affecting the gene function. The highest expression level of LvCthrc1 was observed in immune-related tissues such as hemocytes, gills, and hepatopancreas. This study first put forward the concept of the PVR trait and provides valuable molecular markers for the genetic selection on the trait of shrimp, L. vannamei . GWAS Litopenaeus vannamei pan-vibrio resistance SNPs LvCthrc1 gene Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Pacific white shrimp, Litopenaeus vannamei ( L. vannamei ), is the most farming shrimp species in the world, which accounts for more than 75% of global shrimp farming production (Garlock et al., 2024 ). However, with the extensive farming of the shrimp, bacterial diseases mainly caused by various pathogenic vibrios frequently break out and lead to huge economic loss (Maralit et al., 2018 ). It has been reported that vibriosis outbreaks in China, Vietnam, Malaysia, Mexico and Bangladesh have dramatically reduced shrimp production by about 60 percent in a short period (Noriega-Orozco et al., 2007 ; Chang et al., 2023 ; Liu et al., 2024 ). The prevention of vibrios infections primarily entails the use of antibiotics (Stalin and Srinivasan, 2016 ; Lu et al., 2021 ), immunity enhancement by immunoregulator (Chen et al., 2012 ; Chang et al., 2013 ) and genetic breeding (Zou and Liu, 2015 ; Kongchum et al., 2022 ; Luo et al., 2024 ). Among them, genetic breeding of shrimps has been considered as the most prominent approach for enhancing the resistance to the vibrio infection as it can fundamentally improve the vibrio-resistance trait of shrimps through genetic changes (Luo et al., 2024 ). In recent years, high-throughput sequencing technologies have propelled the rapid development of genetic breeding of animals including aquatic animals. Molecular marker-assisted selection (MAS) that mainly depends on the molecular marker mining acquired from high-throughput sequencing and sequencing data analysis has been frequently used in some aquatic animals, such as Ctenopharyngodon idellus , Cyprinus carpio , Eriocheir sinensis , and L. vannamei (Xiao et al., 2016 ; Fu and Liu, 2022 ; Zhang et al., 2024 ). Genome-wide association study (GWAS) plays an important role in the genetic mapping of complex traits and in the finding of genetic variations under the whole genome scale (Visscher et al., 2012 ). GWAS has been used to explore important loci for MAS aiming at the genetic selection of multiple traits in animals (Li et al., 2015 ). In the genetic breeding of shrimps, for instance, some SNPs associated with WSSV resistance (Robinson et al., 2014 ), growth traits, and sex determination (Guo et al., 2019 ) have been identified in shrimp, Penaeus monodon , through GWAS. Robinson et al ( 2014 ) first analyzed the correlation between WSSV resistance trait and SNPs in L. vannamei through using GWAS. Liu et al (2022) identified seven genes related to ammonia nitrogen tolerance in L. vannamei by the GWAS method. Whankaew et al ( 2024 ) identified 4 SNPs and 17 InDels in three varieties of L. vannamei , related to the tolerance of Acute Hepatopancreatic Necrosis Disease (AHPND). However, until now there is no further screening and verification of candidate SNPs found in the GWAS of vibrio-resistance trait in shrimps. In addition, nearly all the SNPs associated with vibrio resistance in shrimps were obtained to target the genetic improvement of AHPND tolerance, wherein only specific virulent strains of Vibrio species (such as V. parahaemolyticus ) were adopted (Yao et al., 2018 ; Kongchum et al., 2022 ; Luo et al., 2024 ). Vibrio is a genus of ubiquitous bacteria found in a wide variety of aquatic and marine habitats and at least 100 species have been recorded in this genus (Baker-Austin et al., 2018 ), among which over 15 Vibrio species have been reported as opportunistic pathogens to shrimps (Valente and Wan, 2021). Due to the prevalence of pathogenic vibrios in various marine environments, genetic breeding of shrimps with the pan-vibrios resistance (PVR) trait (resistance to wide range of Vibrio pathogens) has more practical significance for successful shrimp farming. In the present study, a GWAS of the PVR trait in 300 shrimp individuals with different sources was performed, and it generated 20 candidate SNPs potentially associated with the PVR trait. Further, genotypes of these candidate SNPs were differentiated in a validation group and their association with the PVR trait was analyzed. Finally, the genotype combination from a gene, LvChrc1 , was screened out, which were strongly associated with the PVR trait. This study put forward the concept of the PVR trait and provides valuable molecular markers for the genetic selection on this trait of shrimp L. vannamei , thereby facilitating the genetic breeding of shrimps toward the substantial improvement of antibacterial ability. Materials and methods 2.1 Shrimp sample collection Individuals of shrimp L. vannamei were collected from nine farms in Sanya (SY), Qionghai (QH), Fuzhou (FZ), Xiamen (XM), Ningde (ND), Zhanjiang (ZJ), Zhuhai (ZH), Shantou (ST) and Guangzhou (GZ) of China. 50 shrimp individuals (weight of 11 ± 4g) in each collected group (from one farm in one area) were used to analyze their performance of the PVR trait. In addition, 210 shrimps (weight of 10 ± 3g) were randomly collected from three farms in Maoming and were used to analyze their performance of the PVR trait for verifying the effectiveness of candidate SNP markers. 2.2 Evaluation of the PVR trait by vibrios load in hepatopancreas Each of shrimp hepatopancreas tissues (0.01g) were taken off and homogenized in 1ml of sterilized seawater, respectively, and then 100 µl of diluted homogenate of each sample was diluted in 10-fold. 100 µl of each dilution was spread onto a TCBS plate with triple repetition. TCBS plates were incubated at 30 ℃ for 24 h and bacterial colonies were calculated and converted into vibrios load in shrimps. Shrimp individuals were classed into five grades (G1, G2, G3, G4, and G5) according to vibrios load to reflect their PVR trait, among which the severity of vibrios infection progressively escalates from grade 1 to grade 5 (G1 to G5). Groups containing ≥ 10% of uninfected individuals are ruled out and finally, a total of 300 shrimp individuals from six groups with different infection levels were selected to comprise an analysis group. In the same way, 300 individuals mentioned above were also graded according to their vibrios load in the hepatopancreas and shrimps in G1 (no vibrios infection observed) and shrimps in G4 to G5 (relatively serious vibrios infection) were selected out to comprise a validation group. 2.3 DNA extraction and library preparation The genomic DNAs of all shrimp samples were extracted using the Marine Animals Genomic DNA Extraction Kit (TIANGEN, China). The genome of each sample was segmented using the HaeIII + Hpy166II restriction enzymes, and the resulting fragments were further processed to isolate the target fragments ranging in length from 314 to 394 bp. After passing quality control checks, the library was subjected to sequencing using specific length amplified fragment sequencing (SLAF-seq) in Biomarker Technologies Corporation (Beijing, China). 2.4 Genotyping and quality control Filtered reads were mapped to the reference genome of L. vannamei (ASM 378908) using BWA software (Li and Durbin 2010 ). GATK (McKenna et al., 2010 ) and SAMtools (Li et al., 2009) were used to develop the SNP tag intersection as the final reliable SNP tag dataset. Subsequently, SnpEff software (Gaudet et al., 2009 ) was used to analyze the location of mutation sites on the reference genome and the gene location information on the reference genome. The " check marker " function in the GenABEL package was used for quality control of genotyping SNPs (Aulchenko et al., 2007 ). The SNPs with low minor allele frequencies (MAF), low profile rates, and deviations from the Hardy-Weinberg were removed before analysis. In addition, the SNPs that were located in gene and within 5000 bp away from the gene are focused on. 2.5 Variant calling analysis and GWAS Combined with EMMAX software (Kang et al., 2010 ), the mixed linear model is used for correlation analysis, and the application model is as follows: $$\:\text{ｙ}＝\text{Ｗ}{\alpha\:}＋\text{ｘ}{\beta\:}＋{\mu\:}＋\text{ｅ}$$ GEMMA (Zoubarev et al., 2012 ) was used to calculate the kinship µ among samples. As a random effect, if there is a covariable, the W is a fixed effect, x is the genotype, and y is the phenotype. According to the P -value of the SNP, with -log10 (p) ≥ 2.5 as the significance standard, the corresponding Q-Q quantile map and Manhattan map are drawn by using the R qqman package (Paria et al., 2022 ). 2.6 Function analysis of g enes containing discrepant SNPs and Genotyping of discrepant SNPs in a validation group Genes containing discrepant SNPs revealed by GWAS were screened out according to the locations of the SNPs using the genomic information of L. vannamei (ASM 378908v1) and the functions of the genes were annotated using NCBI-NR database. The tag sequence information of the selected genes was obtained from the genome of L. vannamei (ASM 378908v1). Primer premier 6.0 software (Applied Biosystems, Norcross, GA) was used to design primers for PCR targeting DNA fragments near candidate SNP. Two forward primers were designed for each site, and fluorescent sequence tags of FAM (GAAGGTGACCAAGTTCATGCT) and HEX (GAAGGTCGGAGTCAACGGATT) were respectively added. All primers used in this study were designed by Primer premier 6.0 software and placed in Table S1 . Genotyping was performed through a method of competitive allele specific PCR (KASP) using a commercial STO Rox kit (Gudebio, Guangzhou). 2.7 Correlation analysis between genotypes and the performance of the PVR trait in a validation group The validation population selected 210 shrimp with extreme infection amount as resistance group (G1) and susceptible group (G4, G5) for analysis, including 72 shrimp. The correlation between genotypes and the performance of the PVR trait was manually analyzed. SNPs significantly associated with the PVR trait was further used to explore potential interactions among them by linkage disequilibrium (LD) analysis using Haploview software (Barrett et al., 2005 ). Based on the LD analysis, the correlation between the genotype combination and the performance of the PVR trait were also analyzed, which led to the finding of combined SNP markers. 2.8 Protein structure prediction of a target gene related to the PVR trait and expression levels of the gene Use SWISS - MODEL website ( https://swissmodel.expasy.org/ ) to predict 3D structure of the protein coded by a target gene related to the PVR trait. Total RNAs were extracted using RNA Easy Fast Tissue/Cell Kit (TIANGEN, China) and were reverse-transcribed into cDNAs using a Prime Script™II 1st Strand cDNA Synthesis Kit (Takara, Japan). The expression levels of the gene in the brain, eye stalk, hemocytes, gill, hepatopancreas, heart, muscle, intestine and stomach were detected by qRT-PCR using a RT-PCR kit (TaKaRa, China) and β-actin gene was used as the reference gene (Table S1 ). qRT-PCR was performed using Thermal Cycler Dice®Real Time System III (TaKaRa) under the following conditions: 95 ºC for 30 s, 40 cycles of 95 ºC for 5 s and 56 ºC for 30 s, reading of templates at 95 ºC for 15 s, and final melting curve from 60 to 95 ºC. Three biological replicates and three technical replicates were used for qRT-PCR, and the expression levels of the gene were calculated by 2 −ΔΔCT method (Livak and Schmittgen, 2001 ). 2.9 Prediction of splicing sites in intron regions from the genotype NetGene2 ( https://services.healthtech.dtu.dk/ ) was used for the SNP loci of the sequences of introns splicing sites prediction (confidence ≥ 0.85). Results 3.1 Grading the PVR trait of the shrimp individuals According to vibrios load in hepatopancreas, the PVR trait of the shrimp was quantified to five grades, G1 to G5 (Fig. 1a). Among 300 shrimp individuals, only 25 individuals in G1 (8.3%) exhibited no vibrios infection in hepatopancreas, manifesting their excellent performance of PVR trait, while 32 individuals in G5 (10.7%) exhibited serious infection in hepatopancreas, manifesting their weak performance of PVR trait (Fig. 1b). The typical bacterial colonies of different infection grades on the TCBS plates were showed (Fig. 1c). 3.2 GWAS and gene functional annotation of candidate SNP According to the comparison analysis, 18,184,608 SNP loci were obtained, 78.78% of SNPs located in the intergenic regions (distance from downstream gene > 5KB), while only 5.95% of SNPs located in the upstream regions (distance from downstream gene ≤ 5KB). Moreover, these SNPs were unevenly distributed in the genome, with the largest distribution in scaffolds, NW_020869133.1, NW_020869429.1, and NM_020870026.1 (Fig. 2). The Q-Q result showed the result is statistically significant with an efficient family structure correction, indicating the phenotypic data could fit the selected model well (Fig. 3a). The Manhattan map shows the results of GWAS, with a total of 243 SNPs above the dotted line divider (-log10 (p) ≥ 2.5, Fig. 3b). After focusing SNPs inside genes and promoter regions, a total of 20 SNPs potentially related to the PVR trait were identified. Annotate genes covering these sites are associated with immunity, DNA replication and metabolisms (Table 1). Table 1 The statistics of the associated SNPs to the PVR trait SNP Position Gene Gene function P (-log 10 (p)) SNP1 239608 protogenin-like, partial Encodes immunoglobulins 3.46 SNP2 483631 E3 ubiquitin-protein ligase RFWD3-like Involved DNA metabolic process; 3.15 SNP3 709567 discoidin domain-containing receptor A-like Participate in signaling 3.14 SNP4 390539 trafficking protein particle complex subunit 4-like Involved in autophagy and endoplasmic reticulum to Golgi vesicle-mediated transport. 3.04 SNP5 229720 methylmalonic aciduria and homocystinuria type D protein, mitochondrial-like isoform X1 Coding line stereoprotein, involved in vitamin B12 metabolism 3.03 SNP6 157824 sodium- and chloride-dependent GABA transporter 2-like Encodes transporters 2.87 SNP7 990978 60S acidic ribosomal protein P2 Involved in immune regulation 2.73 SNP8 450675 methyltransferase N6AMT1-like Participates in the methylation of release factor I 2.71 SNP9 44114 hemocyanin C chain-like Has immune, antibacterial function 2.61 SNP10 57624 cGMP-inhibited 3',5'-cyclic phosphodiesterase B Regulators 2.61 SNP11 91727 actin, muscle-like Involved in muscle contraction, cell movement, and cell division 2.59 SNP12 165399 protein timeless homolog involved in cell survival after damage or stress 2.53 SNP13 193075 lysophosphatidylcholine acyltransferase-like, partial Encodes 1-acyl-SN-glycerol-3-phosphoacyltransferase 2.51 SNP14 635323 HEAT repeat containing 1 homolog enables snoRNA binding 3.19 SNP15 635082 2.85 SNP16 635341 2.58 SNP17 635340 2.59 SNP18 53354 tetratricopeptide repeat protein 5-like isoform X2 Involved in immune regulation 2.85 SNP19 50514 2.53 SNP20 1198973 DNA-binding protein D-ETS-3-like isoform X3 Participate in cell multiplication, differentiation, etc 2.57 3.3 Genotyping of SNPs and validation of candidate SNPs and genotypes in a validation group To screen out SNPs and genotypes of the SNPs closely associated with the PVR trait, other batches of shrimps a total of 210 individuals were collected and graded according to the vibrios load in the hepatopancreas. 20 individuals in grade G1 and 52 individuals in grades, G4 and G5, total of 72 shrimp were grouped together to form a validation group. The genotyping of 20 SNPs in the validation group was performed using KASP and the association between the genotypes of SNPs and the performance of the PVR trait was also analyzed manually (Table S3). Only the genotypes of SNP15, SNP16 and SNP17 had preference between the low infection individuals and serious infection individuals (Table 2). Statistical analysis of the correlations between genotypes of three SNPs and vibrios load showed that only genotypes of SNP15 had significant differences in terms of vibrios load, among which genotype GG had the lowest vibrios load ( 0.05, Fig. 4). It indicated that the GG genotype of SNP15 was significantly associated with the PVR trait. Subsequently, LD analysis was performed on the 20 SNP sites. It manifested that there was a strong linkage disequilibrium (LD) among the three SNPs (SNP15, SNP16, SNP17), especially between SNP16 and SNP17 (D '=0.92; r 2 = 0.81, Fig. 5). Therefore, genotype combinations of the three SNP loci associated with the PVR trait were further analyzed to exploit potential robust SNP marker. The result indicated that the genotype combination of GG-TT-AA of the three SNPs all occurred in uninfected individuals (Table 3), which suggested that this genotype combination has a strong correlation with the PVR trait. Table 2 Statistic analysis SNPs associated with the PVR trait in the verification group SNP Genotype Number in χ2 P G4 and G5 G1 SNP15 GG 3 8 9.00 0.0027 AG 15 2 AA 34 10 SNP16 TT 15 11 3.57 0.058 CT 22 5 CC 15 4 SNP17 AA 14 11 3.97 0.046 AT 23 5 TT 15 4 Table 3 The vibrios load of different genotype combinations in the validation group (n=72） Num genotype combination Sample size Average vibrios load (±SE) 1 AA-CC-TT 12 7.31E+04 ± 0.32 2 AA-CT-AT 24 1.40E+05 ± 0.53 3 AA-TT-AA 8 7.39E+04 ± 0.21 4 AG-CC-TT 6 1.49E+05 ± 0.38 5 AG-CC-AA 1 3.08E+06 ± 0.00 6 AG-CT-AT 1 1.13E+06 ± 0.00 7 AG-TT-AA 7 2.72E+05 ± 0.33 8 AG-TT-AT 2 4.92E+06 ± 0.15 9 GG-TT-AA 8 0.00E+00 ± 0.00 10 GG-TT-TT 1 2.71E+06 ± 0.00 11 GG-CT-AT 1 2.53E+06 ± 0.00 12 GG-CT-AA 1 7.56E+05 ± 0.00 3.4 Structure prediction and tissue distribution of the gene harboring the three SNPs All the three SNPs were found in the intron region of a gene, LvCthrc1 , coding for a collagen triple helix repeat containing-1. The prediction of 3D structure of the protein showed that it contains a lot of repeated alpha helices, accounting for about 70.64% of the gene (Fig. 6a), it may be closely related to its function. The expression level of LvCthrc1 was relatively higher in hemocytes, hepatopancreas and gills (Fig. 6b), and the highest expression level of LvCthrc1 occurred in the hemocytes, which is five times more than that of the muscles. 3.5 Variations in SNPs changed the position of predicted splice sites A total of 13 splicing sites were identified, including 7 splicing donor sites and 6 splicing acceptor sites (Table S4). Notably, the genotype combination of GG-TT-AA can lead to the disappearance of a donor splicing site of LvCthrc1 (Fig. 7), which predictably generates a novel transcript that potentially affects protein structure and function. This splicing donor site located in the middle of SNP15 and SNP16, and close to SNP16 (distance < 10bp). Discussion Vibrios, as the most common aquatic bacteria, have caused serious harm and great economic loss in shrimp culture (Nguyen et al., 2021 ; Liu et al., 2024 ). Due to the high diversity and ubiquity of Vibrio species in the estuary and marine environments (Lee et al., 2015 ; Baker-Austin et al., 2018 ), the genetic breeding of shrimp L. vannamei resistant to extensive vibrios species has more practical significance. Likewise, it is likely that breeding materials of shrimps screened through the infection challenge by single or multiple vibrios species may not be capable of adapting to the complicated farming environments full of various vibrios (Noriega-Orozco et al., 2007 ). Based on this consideration, we were inclined to obtain the ideal breeding materials of shrimps from the actual farming environments instead of the infection challenge by specific vibrios species. In this study, the shrimp were continuously exposed to a diverse range of vibrios conditions throughout their growth period, it indicates that have taken up the challenge of mixed strains of vibrios. Hepatopancreas of shrimps is not only a digestive but also an immune organ of shrimp that is frequently invaded by pathogenic bacteria, viruses, and parasites. Diversified vibrios can be easily found in the farmed shrimp, L. vannamei. In long practices of farming and pathological examinations, we found that vibrios load in the hepatopancreas can reflect the healthy state and resistance ability of the shrimp, and similar findings were also reported by other researchers (Niu et al., 2018 ; Noriega-Orozco et al., 2007 ; Robinson et al., 2014 ). For another parasite pathogen, Enterocytozoon hepatopenaei (EHP), EHP load in the hepatopancreas of L. vannamei also reflects the resistance ability of the shrimp (Hakonsholm et al., 2020; Madesh et al., 2024 ; Tian et al., 2024 ). Therefore, in this study, vibrios load in the hepatopancreas of L. vannamei was adopted to quantify the performance of the PVR trait. The ratio of the uninfected shrimp individuals is not more than 10% in the test group and the validation group, which indicated that only a few individuals in a shrimp group have the strong resistance to vibrios infection, likely conferred by the genetic variations in these individuals. In this study, whole genomes of 300 shrimps containing five different vibrio-resistance levels (G1 to G5) were sequenced for GWAS. Through GWAS, 20 SNPs were first screened out, and these SNPs were annotated to the genes related to autophagy, DNA replication, and metabolic pathways. After KASP genotyping, three SNPs (SNP15, SNP16, and SNP17) were further screened out to be likely associated with the PVR trait, In addition, LD analysis is an important method to examine SNP-SNP interaction, which has been shown to play an important role in the selection of species for complex traits (Onay et al., 2006 ; Wang et al., 2013 ; He et al., 2014 ). Furthermore, all the three SNPs located in the promoter region of the LvCthrc1 gene also supported the LD of the three SNPs, which propelled the potential genotype combination that is closely associated with the PVR trait. The application of comminated molecular markers narrows the screening range and increases the accuracy of breeding materials (Barrett et al., 2005 ), which also theoretically matches the rule that most economic traits are controlled by a set of loci in a genome ( Lu et al., 2011 ; Maniatis et al., 2007 ). LvCthrc1 is one kind of HEAT repeat protein, which includes a mammalian target of rapamycin (mTOR) protein the mTOR, owning a common function of mediating protein-protein interactions (Kunz et al., 2000 ). mTOR plays an important role in various cellular activities such as immunity, and it is activated by the formation of polymers in mammalian cells through its N-terminal HEAT repeat region (Takahara et al., 2006 ). In addition, a HEAT repeat protein, ILITYHIA ( ILA ) in Arabidopsis , involves in the plant immune process, and the mutation of ILA leads to increased sensitivity to pathogens and systemic drug resistance defects in plants (Monaghan et al, 2010). The expression distribution of LvCthrc1 in the shrimp showed that the mRNAs were highly expressed in immune-related tissues such as hemocytes, gill and hepatopancreas, which are also frequently attacked by vibrios. Therefore, it can be speculated that LvCthrc1 may play a crucial role in the immune process of L. vannamei although the specific function of HEAT repeat proteins in shrimp has not been elucidated. Generally, introns can’t be transcribed into mRNAs and they are often considered as junk DNA regions (Palmer et al., 2019). However, recent studies have shown that introns are closely related to gene expression and cytoskeleton construction, and exert some influence on life activities (Jacob et al., 2017; Naro et al., 2017). InDels of introns in different cattle groups are extremely enriched in immune-related pathways (Jacob and Smith, 2017 ). Changes in body weight due to the SNPs in intron of RuvBL2 gene have also been found in shrimps (Zhang et al., 2019). SNPs in intron can also lead to the occurrence of different spliceosomes sourced from the same gene (Jo et al., 2015 ; Jacob et al., 2017; Eiholzer et al., 2020 ). In this study, the SNP loci result in alterations to the splicing donor site. The splicing donor site is not present in the resistance-associated GG-TT-AA genotype combination. The loss of this splicing site may potentially generate a novel transcript that affects the protein structure and function. Based on the link between the genotype combination and the alternation of the splicing site, we speculated that the potential novel transcript may confer the shrimp strong resistance to vibrios infection. However, the specific splicing and sequence information of the novel transcript remain unidentified. The existence of novel transcript and its function need to be verified in future. Conclusion In this study, the correlation between SNPs and the PVR trait of L. vannamei was analyzed. Twenty SNPs that potentially associated with the PVR trait were first obtained by using GWAS. The genotypes of three SNPs (SNP15, SNP16, and SNP17) were different between G1 and G4/G5 groups, which were found in located in the intron region of a gene, LvCthrc1 . The genotype combination of GG-TT-AA of the three SNPs was significantly associated with the strongest performance of the trait, which can also lead to the disappearance of a donor splicing site of LvCthrc1 and predictably generates a novel transcript. The highest expression level of LvCthrc1 was observed in immune-related tissues such as hemocytes, gills, and hepatopancreas. This study provides valuable molecular markers for the genetic selection on the PVR trait of shrimp L. vannamei . Declarations Data Availability Statement The data presented in this study are available on request from the corresponding author. Acknowledgments This research was supported by the Guangxi Natural Science Foundation project (2023GXNSFBA026356), the National Key Research and Development Program of China (2023YFD2401701), the Seed Industry Revitalization Project of Provincial Rural Revitalization Strategy Special Funds (2022-SPY-00-001), the Research on breeding technology of candidate species for Guangdong modern marine ranching (2024-MRB-00-001), and the Innovation Team Project of Guangdong Universities (2022KCXTD017). Author contributions All authors contributed to the study conception and approved the final manuscript. Shuyang Wen: Conceptualization, Data curation, Formal analysis, Validation, Writing - original draft; Chuhang Cheng: Funding acquisition; Methodology, Software; Jiayue Yin: Visualization, Writing - review & editing; Ying Lv: Project administration, Supervision; Xin Zhang: Project administration, Visualization; Bo Ma: Methodology; Yang Liu: Visualization; Yueshan Qiu: Visualization; Huteng He: Investigation; Peng Luo: Investigation, Writing - review & editing, Resources, Supervision; Lihong Yuan: Project administration, Funding acquisition, Writing - review & editing. Declaration of Competing Interest The authors declare that they have no known financial interests or personal relationships that could have influenced the work reported in this paper. References Aulchenko, Y.S., Ripke, S., Isaacs, A., van Duijn, C.M., 2007. GenABEL: An R library for genome-wide association analysis. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6178636","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":428008051,"identity":"2e86efea-a65d-4c60-8843-cd422ef9dfaa","order_by":0,"name":"Shuyang Wen","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Shuyang","middleName":"","lastName":"Wen","suffix":""},{"id":428008053,"identity":"e9bc856e-6297-4030-8dac-33f282249618","order_by":1,"name":"Chuhang Cheng","email":"","orcid":"","institution":"Guangxi Academy of Marine Sciences, Guangxi Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Chuhang","middleName":"","lastName":"Cheng","suffix":""},{"id":428008054,"identity":"4140ceb0-67d4-440e-89ac-7ed756e16943","order_by":2,"name":"Jiayue Yin","email":"","orcid":"","institution":"South China Sea Institute Of Oceanology","correspondingAuthor":false,"prefix":"","firstName":"Jiayue","middleName":"","lastName":"Yin","suffix":""},{"id":428008055,"identity":"7af58ba2-5148-4105-85e2-9898368b4726","order_by":3,"name":"Ying Lv","email":"","orcid":"","institution":"Beibu Gulf Marine Ecological Environment Field Observation and Research Station of Guangxi, Beibu Gulf University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Lv","suffix":""},{"id":428008056,"identity":"32beb04b-f1e9-4cb1-8f38-f3a1d09c77a4","order_by":4,"name":"Xin Zhang","email":"","orcid":"","institution":"South China Sea Institute Of Oceanology","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zhang","suffix":""},{"id":428008057,"identity":"cf2ffbef-852c-429e-8143-7cd709cfec26","order_by":5,"name":"Bo Ma","email":"","orcid":"","institution":"South China Sea Institute Of Oceanology","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Ma","suffix":""},{"id":428008058,"identity":"3ad8b76c-aee9-4258-9abd-b0bd1c4834f9","order_by":6,"name":"Yang Liu","email":"","orcid":"","institution":"South China Sea Institute Of Oceanology","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Liu","suffix":""},{"id":428008059,"identity":"2d823f3a-0d09-4676-884f-28b05d749f0b","order_by":7,"name":"Yueshan Qiu","email":"","orcid":"","institution":"Beibu Gulf Marine Ecological Environment Field Observation and Research Station of Guangxi, Beibu Gulf University","correspondingAuthor":false,"prefix":"","firstName":"Yueshan","middleName":"","lastName":"Qiu","suffix":""},{"id":428008060,"identity":"e37836b8-c03f-4a18-9a3e-691714231609","order_by":8,"name":"Huteng He","email":"","orcid":"","institution":"Xi'an Jiaotong-Liverpool University","correspondingAuthor":false,"prefix":"","firstName":"Huteng","middleName":"","lastName":"He","suffix":""},{"id":428008061,"identity":"04f35465-ca98-4537-988d-3195dd54d01f","order_by":9,"name":"Peng Luo","email":"","orcid":"","institution":"South China Sea Institute Of Oceanology","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Luo","suffix":""},{"id":428008062,"identity":"6098b36c-53aa-430d-805d-55c854d1801b","order_by":10,"name":"Lihong Yuan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYDACdh7GBwxsYKYBkVqYeZgNSNbCJkGaFoPDvMcqv5TdSWxgb94mwVBzhxgtfGm3Zc49S2zgOVYmwXDsGTFaeMxuS7YdTmyQyDGTYGw4TJyWYrAW+TckaGH8CLaFh0gtkod5jKUZzj0zbuNJK7ZIOEaEFr7jPYYff5Tdke1nP7zxxocaIrQoHABFDcMBSNQkENbAwCDfwMDA+AOoZRSMglEwCkYBTgAAiv86JLkJmJsAAAAASUVORK5CYII=","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":true,"prefix":"","firstName":"Lihong","middleName":"","lastName":"Yuan","suffix":""}],"badges":[],"createdAt":"2025-03-07 13:23:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6178636/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6178636/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78457210,"identity":"4c9572fa-c844-42e0-9a4c-b3f3076a1eeb","added_by":"auto","created_at":"2025-03-13 12:45:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":455392,"visible":true,"origin":"","legend":"\u003cp\u003eVibrios load of different infection grades. (a) Vibrios load of different infection grades in the test group; (b) Number of individuals with different levels of infection grades; (c) Bacterial colonies of typical individuals with different infection grades\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/e6b5c9f249f67056d05bc77c.png"},{"id":78456358,"identity":"bb954e75-ce0b-4d21-90a0-7491be57874c","added_by":"auto","created_at":"2025-03-13 12:37:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1130123,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of SNPs on the top 20 longest scaffolds across the chromosomes in \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e. The color bar represents the number of SNPs within 0.1 Mb window size with reference to the index shown on the right.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/ca3d66c93a4e058a82102466.png"},{"id":78457466,"identity":"54760d8d-08f7-4414-ad2b-2ea6d86223bf","added_by":"auto","created_at":"2025-03-13 12:53:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":468120,"visible":true,"origin":"","legend":"\u003cp\u003eGWAS of the PVR trait of the shrimp. (a) Q-Q map; (b) Manhattan map. The dashed blue lines and solid black lines are -lg (\u003cem\u003eP\u003c/em\u003e) =2.5 and -lg (\u003cem\u003eP\u003c/em\u003e) =5, respectively. Since the genome of \u003cem\u003eL. vannamei \u003c/em\u003eis not assembled at the chromosomal level, in this study, only the SNP distribution of the top 20 scaffold sequences with the longest splintering length was illustrated.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/870715262cf6c8b5497ac3c9.png"},{"id":78457208,"identity":"ce5bfd76-b47b-47bd-ac9d-649048b0fbaa","added_by":"auto","created_at":"2025-03-13 12:45:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":110455,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between genotypes of the three SNPs and vibrios load in the validation group\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/284031bc83d1263a20a6a45b.png"},{"id":78456368,"identity":"c22fee8a-9cc3-4e1e-85b5-43d48179c62e","added_by":"auto","created_at":"2025-03-13 12:37:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":174417,"visible":true,"origin":"","legend":"\u003cp\u003eLD analysis of the 20 SNPs. The circle in the lower left corner is r\u003csup\u003e2\u003c/sup\u003e, and the circle in the upper right corner is colored with the D 'value\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/9dd31b3c6ebaa5a13fa4ad39.png"},{"id":78456362,"identity":"ebb90731-cb9c-449b-ae9e-937c0ca49e49","added_by":"auto","created_at":"2025-03-13 12:37:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":347351,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of \u003cem\u003eLvCthrc1\u003c/em\u003e gene function (a) 3D structure of protein encoded by the gene \u003cem\u003eLvCthrc1\u003c/em\u003e (b) and the expression distribution of \u003cem\u003eLvCthrc1\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/f20e25968bd7b3e639cbd904.png"},{"id":78456369,"identity":"0bb1e733-b68e-4b16-9882-e591885a3054","added_by":"auto","created_at":"2025-03-13 12:37:04","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":253455,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction of the altered splicing site in the genotype combination. The bases with red color are the three SNPs\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/92ba005a3f856c57da374d46.png"},{"id":79280122,"identity":"be3bf8e1-7241-489c-b22b-348b75488ac9","added_by":"auto","created_at":"2025-03-26 13:16:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4992914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/2020e761-fdcf-46d1-b87f-97e8a077632d.pdf"},{"id":78456357,"identity":"586d2a22-8566-473f-b713-42fffb734c6d","added_by":"auto","created_at":"2025-03-13 12:37:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36059,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6178636/v1/74950ba117f5f03179df5f2e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of genes associated with pan-vibrios resistance (PVR) trait of shrimp Litopenaeus vannamei through Genome-wide association study","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePacific white shrimp, \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e (\u003cem\u003eL. vannamei\u003c/em\u003e), is the most farming shrimp species in the world, which accounts for more than 75% of global shrimp farming production (Garlock et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, with the extensive farming of the shrimp, bacterial diseases mainly caused by various pathogenic vibrios frequently break out and lead to huge economic loss (Maralit et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It has been reported that vibriosis outbreaks in China, Vietnam, Malaysia, Mexico and Bangladesh have dramatically reduced shrimp production by about 60 percent in a short period (Noriega-Orozco et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Chang et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The prevention of vibrios infections primarily entails the use of antibiotics (Stalin and Srinivasan, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), immunity enhancement by immunoregulator (Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Chang et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and genetic breeding (Zou and Liu, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kongchum et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Luo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Among them, genetic breeding of shrimps has been considered as the most prominent approach for enhancing the resistance to the vibrio infection as it can fundamentally improve the vibrio-resistance trait of shrimps through genetic changes (Luo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent years, high-throughput sequencing technologies have propelled the rapid development of genetic breeding of animals including aquatic animals. Molecular marker-assisted selection (MAS) that mainly depends on the molecular marker mining acquired from high-throughput sequencing and sequencing data analysis has been frequently used in some aquatic animals, such as \u003cem\u003eCtenopharyngodon idellus\u003c/em\u003e, \u003cem\u003eCyprinus carpio\u003c/em\u003e, \u003cem\u003eEriocheir sinensis\u003c/em\u003e, and \u003cem\u003eL. vannamei\u003c/em\u003e (Xiao et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fu and Liu, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Genome-wide association study (GWAS) plays an important role in the genetic mapping of complex traits and in the finding of genetic variations under the whole genome scale (Visscher et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). GWAS has been used to explore important loci for MAS aiming at the genetic selection of multiple traits in animals (Li et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In the genetic breeding of shrimps, for instance, some SNPs associated with WSSV resistance (Robinson et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), growth traits, and sex determination (Guo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) have been identified in shrimp, \u003cem\u003ePenaeus monodon\u003c/em\u003e, through GWAS. Robinson et al (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) first analyzed the correlation between WSSV resistance trait and SNPs in \u003cem\u003eL. vannamei\u003c/em\u003e through using GWAS. Liu et al (2022) identified seven genes related to ammonia nitrogen tolerance in \u003cem\u003eL. vannamei\u003c/em\u003e by the GWAS method. Whankaew et al (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) identified 4 SNPs and 17 InDels in three varieties of \u003cem\u003eL. vannamei\u003c/em\u003e, related to the tolerance of Acute Hepatopancreatic Necrosis Disease (AHPND). However, until now there is no further screening and verification of candidate SNPs found in the GWAS of vibrio-resistance trait in shrimps. In addition, nearly all the SNPs associated with vibrio resistance in shrimps were obtained to target the genetic improvement of AHPND tolerance, wherein only specific virulent strains of \u003cem\u003eVibrio\u003c/em\u003e species (such as \u003cem\u003eV. parahaemolyticus\u003c/em\u003e) were adopted (Yao et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kongchum et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Luo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). \u003cem\u003eVibrio\u003c/em\u003e is a genus of ubiquitous bacteria found in a wide variety of aquatic and marine habitats and at least 100 species have been recorded in this genus (Baker-Austin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), among which over 15 \u003cem\u003eVibrio\u003c/em\u003e species have been reported as opportunistic pathogens to shrimps (Valente and Wan, 2021). Due to the prevalence of pathogenic vibrios in various marine environments, genetic breeding of shrimps with the pan-vibrios resistance (PVR) trait (resistance to wide range of \u003cem\u003eVibrio\u003c/em\u003e pathogens) has more practical significance for successful shrimp farming.\u003c/p\u003e \u003cp\u003eIn the present study, a GWAS of the PVR trait in 300 shrimp individuals with different sources was performed, and it generated 20 candidate SNPs potentially associated with the PVR trait. Further, genotypes of these candidate SNPs were differentiated in a validation group and their association with the PVR trait was analyzed. Finally, the genotype combination from a gene, \u003cem\u003eLvChrc1\u003c/em\u003e, was screened out, which were strongly associated with the PVR trait. This study put forward the concept of the PVR trait and provides valuable molecular markers for the genetic selection on this trait of shrimp \u003cem\u003eL. vannamei\u003c/em\u003e, thereby facilitating the genetic breeding of shrimps toward the substantial improvement of antibacterial ability.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Shrimp sample collection\u003c/h2\u003e \u003cp\u003eIndividuals of shrimp \u003cem\u003eL. vannamei\u003c/em\u003e were collected from nine farms in Sanya (SY), Qionghai (QH), Fuzhou (FZ), Xiamen (XM), Ningde (ND), Zhanjiang (ZJ), Zhuhai (ZH), Shantou (ST) and Guangzhou (GZ) of China. 50 shrimp individuals (weight of 11\u0026thinsp;\u0026plusmn;\u0026thinsp;4g) in each collected group (from one farm in one area) were used to analyze their performance of the PVR trait. In addition, 210 shrimps (weight of 10\u0026thinsp;\u0026plusmn;\u0026thinsp;3g) were randomly collected from three farms in Maoming and were used to analyze their performance of the PVR trait for verifying the effectiveness of candidate SNP markers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Evaluation of the PVR trait by vibrios load in hepatopancreas\u003c/h2\u003e \u003cp\u003eEach of shrimp hepatopancreas tissues (0.01g) were taken off and homogenized in 1ml of sterilized seawater, respectively, and then 100 \u0026micro;l of diluted homogenate of each sample was diluted in 10-fold. 100 \u0026micro;l of each dilution was spread onto a TCBS plate with triple repetition. TCBS plates were incubated at 30 ℃ for 24 h and bacterial colonies were calculated and converted into vibrios load in shrimps. Shrimp individuals were classed into five grades (G1, G2, G3, G4, and G5) according to vibrios load to reflect their PVR trait, among which the severity of vibrios infection progressively escalates from grade 1 to grade 5 (G1 to G5). Groups containing\u0026thinsp;\u0026ge;\u0026thinsp;10% of uninfected individuals are ruled out and finally, a total of 300 shrimp individuals from six groups with different infection levels were selected to comprise an analysis group. In the same way, 300 individuals mentioned above were also graded according to their vibrios load in the hepatopancreas and shrimps in G1 (no vibrios infection observed) and shrimps in G4 to G5 (relatively serious vibrios infection) were selected out to comprise a validation group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 DNA extraction and library preparation\u003c/h2\u003e \u003cp\u003eThe genomic DNAs of all shrimp samples were extracted using the Marine Animals Genomic DNA Extraction Kit (TIANGEN, China). The genome of each sample was segmented using the HaeIII\u0026thinsp;+\u0026thinsp;Hpy166II restriction enzymes, and the resulting fragments were further processed to isolate the target fragments ranging in length from 314 to 394 bp. After passing quality control checks, the library was subjected to sequencing using specific length amplified fragment sequencing (SLAF-seq) in Biomarker Technologies Corporation (Beijing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.4 Genotyping and quality control\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eFiltered reads were mapped to the reference genome of \u003cem\u003eL. vannamei\u003c/em\u003e (ASM 378908) using BWA software (Li and Durbin \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). GATK (McKenna et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and SAMtools (Li et al., 2009) were used to develop the SNP tag intersection as the final reliable SNP tag dataset. Subsequently, SnpEff software (Gaudet et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) was used to analyze the location of mutation sites on the reference genome and the gene location information on the reference genome. The \"\u003cem\u003echeck marker\u003c/em\u003e\" function in the GenABEL package was used for quality control of genotyping SNPs (Aulchenko et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The SNPs with low minor allele frequencies (MAF), low profile rates, and deviations from the Hardy-Weinberg were removed before analysis. In addition, the SNPs that were located in gene and within 5000 bp away from the gene are focused on.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Variant calling analysis and GWAS\u003c/h2\u003e \u003cp\u003eCombined with EMMAX software (Kang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), the mixed linear model is used for correlation analysis, and the application model is as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{ｙ}＝\\text{Ｗ}{\\alpha\\:}＋\\text{ｘ}{\\beta\\:}＋{\\mu\\:}＋\\text{ｅ}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eGEMMA (Zoubarev et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) was used to calculate the kinship \u0026micro; among samples. As a random effect, if there is a covariable, the W is a fixed effect, x is the genotype, and y is the phenotype. According to the \u003cem\u003eP\u003c/em\u003e-value of the SNP, with -log10 (p)\u0026thinsp;\u0026ge;\u0026thinsp;2.5 as the significance standard, the corresponding Q-Q quantile map and Manhattan map are drawn by using the R qqman package (Paria et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.6 Function analysis of\u003c/b\u003e g\u003cb\u003eenes containing discrepant SNPs and Genotyping of discrepant SNPs in a validation group\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGenes containing discrepant SNPs revealed by GWAS were screened out according to the locations of the SNPs using the genomic information of \u003cem\u003eL. vannamei\u003c/em\u003e (ASM 378908v1) and the functions of the genes were annotated using NCBI-NR database. The tag sequence information of the selected genes was obtained from the genome of \u003cem\u003eL. vannamei\u003c/em\u003e (ASM 378908v1). Primer premier 6.0 software (Applied Biosystems, Norcross, GA) was used to design primers for PCR targeting DNA fragments near candidate SNP. Two forward primers were designed for each site, and fluorescent sequence tags of FAM (GAAGGTGACCAAGTTCATGCT) and HEX (GAAGGTCGGAGTCAACGGATT) were respectively added. All primers used in this study were designed by Primer premier 6.0 software and placed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Genotyping was performed through a method of competitive allele specific PCR (KASP) using a commercial STO Rox kit (Gudebio, Guangzhou).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Correlation analysis between genotypes and the performance of the PVR trait in a validation group\u003c/h2\u003e \u003cp\u003eThe validation population selected 210 shrimp with extreme infection amount as resistance group (G1) and susceptible group (G4, G5) for analysis, including 72 shrimp. The correlation between genotypes and the performance of the PVR trait was manually analyzed. SNPs significantly associated with the PVR trait was further used to explore potential interactions among them by linkage disequilibrium (LD) analysis using Haploview software (Barrett et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Based on the LD analysis, the correlation between the genotype combination and the performance of the PVR trait were also analyzed, which led to the finding of combined SNP markers.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.8 Protein structure prediction of a target gene related to the PVR trait and expression levels of the gene\u003c/b\u003e \u003c/p\u003e \u003cp\u003eUse SWISS - MODEL website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://swissmodel.expasy.org/\u003c/span\u003e\u003cspan address=\"https://swissmodel.expasy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to predict 3D structure of the protein coded by a target gene related to the PVR trait. Total RNAs were extracted using RNA Easy Fast Tissue/Cell Kit (TIANGEN, China) and were reverse-transcribed into cDNAs using a Prime Script\u0026trade;II 1st Strand cDNA Synthesis Kit (Takara, Japan). The expression levels of the gene in the brain, eye stalk, hemocytes, gill, hepatopancreas, heart, muscle, intestine and stomach were detected by qRT-PCR using a RT-PCR kit (TaKaRa, China) and \u003cem\u003eβ-actin\u003c/em\u003e gene was used as the reference gene (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). qRT-PCR was performed using Thermal Cycler Dice\u0026reg;Real Time System III (TaKaRa) under the following conditions: 95 \u0026ordm;C for 30 s, 40 cycles of 95 \u0026ordm;C for 5 s and 56 \u0026ordm;C for 30 s, reading of templates at 95 \u0026ordm;C for 15 s, and final melting curve from 60 to 95 \u0026ordm;C. Three biological replicates and three technical replicates were used for qRT-PCR, and the expression levels of the gene were calculated by 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method (Livak and Schmittgen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Prediction of splicing sites in intron regions from the genotype\u003c/h2\u003e \u003cp\u003eNetGene2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://services.healthtech.dtu.dk/\u003c/span\u003e\u003cspan address=\"https://services.healthtech.dtu.dk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for the SNP loci of the sequences of introns splicing sites prediction (confidence\u0026thinsp;\u0026ge;\u0026thinsp;0.85).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e\u003cstrong\u003e3.1 Grading the PVR trait of the shrimp individuals\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eAccording to vibrios load in hepatopancreas, the PVR trait of the shrimp was quantified to five grades, G1 to G5 (Fig.\u0026nbsp;1a). Among 300 shrimp individuals, only 25 individuals in G1 (8.3%) exhibited no vibrios infection in hepatopancreas, manifesting their excellent performance of PVR trait, while 32 individuals in G5 (10.7%) exhibited serious infection in hepatopancreas, manifesting their weak performance of PVR trait (Fig.\u0026nbsp;1b). The typical bacterial colonies of different infection grades on the TCBS plates were showed (Fig.\u0026nbsp;1c).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e3.2 GWAS and gene functional annotation of candidate SNP\u003c/h2\u003e\n \u003cp\u003eAccording to the comparison analysis, 18,184,608 SNP loci were obtained, 78.78% of SNPs located in the intergenic regions (distance from downstream gene\u0026thinsp;\u0026gt;\u0026thinsp;5KB), while only 5.95% of SNPs located in the upstream regions (distance from downstream gene\u0026thinsp;\u0026le;\u0026thinsp;5KB). Moreover, these SNPs were unevenly distributed in the genome, with the largest distribution in scaffolds, NW_020869133.1, NW_020869429.1, and NM_020870026.1 (Fig.\u0026nbsp;2). The Q-Q result showed the result is statistically significant with an efficient family structure correction, indicating the phenotypic data could fit the selected model well (Fig.\u0026nbsp;3a). The Manhattan map shows the results of GWAS, with a total of 243 SNPs above the dotted line divider (-log10 (p)\u0026thinsp;\u0026ge;\u0026thinsp;2.5, Fig.\u0026nbsp;3b). After focusing SNPs inside genes and promoter regions, a total of 20 SNPs potentially related to the PVR trait were identified. Annotate genes covering these sites are associated with immunity, DNA replication and metabolisms (Table\u0026nbsp;1).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e The statistics of the associated SNPs to the PVR trait\u0026nbsp;\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"593\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePosition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGene function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP (-log\u003csub\u003e10\u003c/sub\u003e (p))\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e239608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eprotogenin-like, partial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEncodes immunoglobulins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e483631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eE3 ubiquitin-protein ligase RFWD3-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInvolved DNA metabolic process;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e709567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ediscoidin domain-containing receptor A-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eParticipate in signaling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e390539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003etrafficking protein particle complex subunit 4-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInvolved in autophagy and endoplasmic reticulum to Golgi vesicle-mediated transport.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e229720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emethylmalonic aciduria and homocystinuria type D protein, mitochondrial-like isoform X1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCoding line stereoprotein, involved in vitamin B12 metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e157824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003esodium- and chloride-dependent GABA transporter 2-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEncodes transporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e990978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60S acidic ribosomal protein P2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInvolved in immune regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e450675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emethyltransferase N6AMT1-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eParticipates in the methylation of release factor I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ehemocyanin C chain-like\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHas immune, antibacterial function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecGMP-inhibited 3\u0026apos;,5\u0026apos;-cyclic phosphodiesterase B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRegulators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"586\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eactin, muscle-like\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInvolved in muscle contraction, cell movement, and cell division\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e165399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eprotein timeless homolog\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003einvolved in cell survival after damage or stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e193075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003elysophosphatidylcholine acyltransferase-like, partial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEncodes 1-acyl-SN-glycerol-3-phosphoacyltransferase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e635323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eHEAT repeat containing 1 homolog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eenables snoRNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e635082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e635341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e635340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003etetratricopeptide repeat protein 5-like isoform X2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eInvolved in immune regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSNP20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1198973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDNA-binding protein D-ETS-3-like isoform X3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eParticipate in cell multiplication, differentiation, etc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003e\u003cstrong\u003e3.3 Genotyping of SNPs and validation of candidate SNPs and genotypes in a validation group\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eTo screen out SNPs and genotypes of the SNPs closely associated with the PVR trait, other batches of shrimps a total of 210 individuals were collected and graded according to the vibrios load in the hepatopancreas. 20 individuals in grade G1 and 52 individuals in grades, G4 and G5, total of 72 shrimp were grouped together to form a validation group. The genotyping of 20 SNPs in the validation group was performed using KASP and the association between the genotypes of SNPs and the performance of the PVR trait was also analyzed manually (Table S3). Only the genotypes of SNP15, SNP16 and SNP17 had preference between the low infection individuals and serious infection individuals (Table\u0026nbsp;2). Statistical analysis of the correlations between genotypes of three SNPs and vibrios load showed that only genotypes of SNP15 had significant differences in terms of vibrios load, among which genotype GG had the lowest vibrios load (\u0026lt;\u0026thinsp;10\u003csup\u003e2\u003c/sup\u003e CFU/g), significantly different from other genotypes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;4). It indicated that the GG genotype of SNP15 was significantly associated with the PVR trait. Subsequently, LD analysis was performed on the 20 SNP sites. It manifested that there was a strong linkage disequilibrium (LD) among the three SNPs (SNP15, SNP16, SNP17), especially between SNP16 and SNP17 (D \u0026apos;=0.92; r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.81, Fig.\u0026nbsp;5). Therefore, genotype combinations of the three SNP loci associated with the PVR trait were further analyzed to exploit potential robust SNP marker. The result indicated that the genotype combination of GG-TT-AA of the three SNPs all occurred in uninfected individuals (Table\u0026nbsp;3), which suggested that this genotype combination has a strong correlation with the PVR trait.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eStatistic analysis SNPs associated with the PVR trait in the verification group\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber in\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eG4 and G5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eG1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSNP15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e9.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.0027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSNP16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSNP17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e The vibrios load of different genotype combinations in the validation group (n=72）\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003egenotype combination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAverage vibrios load (\u0026plusmn;SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAA-CC-TT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.31E+04 \u0026plusmn; 0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAA-CT-AT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.40E+05 \u0026plusmn; 0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAA-TT-AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.39E+04 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAG-CC-TT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.49E+05 \u0026plusmn; 0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAG-CC-AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.08E+06 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAG-CT-AT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.13E+06 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAG-TT-AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.72E+05 \u0026plusmn; 0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAG-TT-AT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.92E+06 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGG-TT-AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.00E+00 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGG-TT-TT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.71E+06 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGG-CT-AT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.53E+06 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGG-CT-AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.56E+05 \u0026plusmn; 0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003e3.4 Structure prediction and tissue distribution of the gene harboring the three SNPs\u003c/h2\u003e\n \u003cp\u003eAll the three SNPs were found in the intron region of a gene, \u003cem\u003eLvCthrc1\u003c/em\u003e, coding for a collagen triple helix repeat containing-1. The prediction of 3D structure of the protein showed that it contains a lot of repeated alpha helices, accounting for about 70.64% of the gene (Fig.\u0026nbsp;6a), it may be closely related to its function. The expression level of \u003cem\u003eLvCthrc1\u003c/em\u003e was relatively higher in hemocytes, hepatopancreas and gills (Fig.\u0026nbsp;6b), and the highest expression level of \u003cem\u003eLvCthrc1\u003c/em\u003e occurred in the hemocytes, which is five times more than that of the muscles.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003e3.5 Variations in SNPs changed the position of predicted splice sites\u003c/h2\u003e\n \u003cp\u003eA total of 13 splicing sites were identified, including 7 splicing donor sites and 6 splicing acceptor sites (Table S4). Notably, the genotype combination of GG-TT-AA can lead to the disappearance of a donor splicing site of \u003cem\u003eLvCthrc1\u003c/em\u003e (Fig.\u0026nbsp;7), which predictably generates a novel transcript that potentially affects protein structure and function. This splicing donor site located in the middle of SNP15 and SNP16, and close to SNP16 (distance\u0026thinsp;\u0026lt;\u0026thinsp;10bp).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eVibrios, as the most common aquatic bacteria, have caused serious harm and great economic loss in shrimp culture (Nguyen et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Due to the high diversity and ubiquity of \u003cem\u003eVibrio\u003c/em\u003e species in the estuary and marine environments (Lee et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Baker-Austin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the genetic breeding of shrimp \u003cem\u003eL. vannamei\u003c/em\u003e resistant to extensive vibrios species has more practical significance. Likewise, it is likely that breeding materials of shrimps screened through the infection challenge by single or multiple vibrios species may not be capable of adapting to the complicated farming environments full of various vibrios (Noriega-Orozco et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Based on this consideration, we were inclined to obtain the ideal breeding materials of shrimps from the actual farming environments instead of the infection challenge by specific vibrios species. In this study, the shrimp were continuously exposed to a diverse range of vibrios conditions throughout their growth period, it indicates that have taken up the challenge of mixed strains of vibrios. Hepatopancreas of shrimps is not only a digestive but also an immune organ of shrimp that is frequently invaded by pathogenic bacteria, viruses, and parasites. Diversified vibrios can be easily found in the farmed shrimp, \u003cem\u003eL. vannamei.\u003c/em\u003e In long practices of farming and pathological examinations, we found that vibrios load in the hepatopancreas can reflect the healthy state and resistance ability of the shrimp, and similar findings were also reported by other researchers (Niu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Noriega-Orozco et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Robinson et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For another parasite pathogen, \u003cem\u003eEnterocytozoon hepatopenaei\u003c/em\u003e (EHP), EHP load in the hepatopancreas of \u003cem\u003eL. vannamei\u003c/em\u003e also reflects the resistance ability of the shrimp (Hakonsholm et al., 2020; Madesh et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tian et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, in this study, vibrios load in the hepatopancreas of \u003cem\u003eL. vannamei\u003c/em\u003e was adopted to quantify the performance of the PVR trait. The ratio of the uninfected shrimp individuals is not more than 10% in the test group and the validation group, which indicated that only a few individuals in a shrimp group have the strong resistance to vibrios infection, likely conferred by the genetic variations in these individuals.\u003c/p\u003e \u003cp\u003eIn this study, whole genomes of 300 shrimps containing five different vibrio-resistance levels (G1 to G5) were sequenced for GWAS. Through GWAS, 20 SNPs were first screened out, and these SNPs were annotated to the genes related to autophagy, DNA replication, and metabolic pathways. After KASP genotyping, three SNPs (SNP15, SNP16, and SNP17) were further screened out to be likely associated with the PVR trait, In addition, LD analysis is an important method to examine SNP-SNP interaction, which has been shown to play an important role in the selection of species for complex traits (Onay et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; He et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Furthermore, all the three SNPs located in the promoter region of the \u003cem\u003eLvCthrc1\u003c/em\u003e gene also supported the LD of the three SNPs, which propelled the potential genotype combination that is closely associated with the PVR trait. The application of comminated molecular markers narrows the screening range and increases the accuracy of breeding materials (Barrett et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which also theoretically matches the rule that most economic traits are controlled by a set of loci in a genome ( Lu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Maniatis et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). \u003cem\u003eLvCthrc1\u003c/em\u003e is one kind of HEAT repeat protein, which includes a mammalian target of rapamycin (mTOR) protein the mTOR, owning a common function of mediating protein-protein interactions (Kunz et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). mTOR plays an important role in various cellular activities such as immunity, and it is activated by the formation of polymers in mammalian cells through its N-terminal HEAT repeat region (Takahara et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In addition, a HEAT repeat protein, \u003cem\u003eILITYHIA\u003c/em\u003e (\u003cem\u003eILA\u003c/em\u003e) in \u003cem\u003eArabidopsis\u003c/em\u003e, involves in the plant immune process, and the mutation of \u003cem\u003eILA\u003c/em\u003e leads to increased sensitivity to pathogens and systemic drug resistance defects in plants (Monaghan et al, 2010). The expression distribution of \u003cem\u003eLvCthrc1\u003c/em\u003e in the shrimp showed that the mRNAs were highly expressed in immune-related tissues such as hemocytes, gill and hepatopancreas, which are also frequently attacked by vibrios. Therefore, it can be speculated that \u003cem\u003eLvCthrc1\u003c/em\u003e may play a crucial role in the immune process of \u003cem\u003eL. vannamei\u003c/em\u003e although the specific function of HEAT repeat proteins in shrimp has not been elucidated.\u003c/p\u003e \u003cp\u003eGenerally, introns can\u0026rsquo;t be transcribed into mRNAs and they are often considered as junk DNA regions (Palmer et al., 2019). However, recent studies have shown that introns are closely related to gene expression and cytoskeleton construction, and exert some influence on life activities (Jacob et al., 2017; Naro et al., 2017). InDels of introns in different cattle groups are extremely enriched in immune-related pathways (Jacob and Smith, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Changes in body weight due to the SNPs in intron of \u003cem\u003eRuvBL2\u003c/em\u003e gene have also been found in shrimps (Zhang et al., 2019). SNPs in intron can also lead to the occurrence of different spliceosomes sourced from the same gene (Jo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Jacob et al., 2017; Eiholzer et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this study, the SNP loci result in alterations to the splicing donor site. The splicing donor site is not present in the resistance-associated GG-TT-AA genotype combination. The loss of this splicing site may potentially generate a novel transcript that affects the protein structure and function. Based on the link between the genotype combination and the alternation of the splicing site, we speculated that the potential novel transcript may confer the shrimp strong resistance to vibrios infection. However, the specific splicing and sequence information of the novel transcript remain unidentified. The existence of novel transcript and its function need to be verified in future.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, the correlation between SNPs and the PVR trait of \u003cem\u003eL. vannamei\u003c/em\u003e was analyzed. Twenty SNPs that potentially associated with the PVR trait were first obtained by using GWAS. The genotypes of three SNPs (SNP15, SNP16, and SNP17) were different between G1 and G4/G5 groups, which were found in located in the intron region of a gene, \u003cem\u003eLvCthrc1\u003c/em\u003e. The genotype combination of GG-TT-AA of the three SNPs was significantly associated with the strongest performance of the trait, which can also lead to the disappearance of a donor splicing site of \u003cem\u003eLvCthrc1\u003c/em\u003e and predictably generates a novel transcript. The highest expression level of \u003cem\u003eLvCthrc1\u003c/em\u003e was observed in immune-related tissues such as hemocytes, gills, and hepatopancreas. This study provides valuable molecular markers for the genetic selection on the PVR trait of shrimp \u003cem\u003eL. vannamei\u003c/em\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are available on request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Guangxi Natural Science Foundation project (2023GXNSFBA026356), the National Key Research and Development Program of China (2023YFD2401701), the Seed Industry Revitalization Project of Provincial Rural Revitalization Strategy Special Funds (2022-SPY-00-001), the Research on breeding technology of candidate species for Guangdong modern marine ranching (2024-MRB-00-001), and the Innovation Team Project of Guangdong Universities (2022KCXTD017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and approved the final manuscript. Shuyang Wen: Conceptualization, Data curation, Formal analysis, Validation, Writing - original draft; Chuhang Cheng: Funding acquisition; Methodology, Software; Jiayue Yin: Visualization, Writing - review \u0026amp; editing; Ying Lv: Project administration, Supervision; Xin Zhang: Project administration, Visualization; Bo Ma: Methodology; Yang Liu: Visualization; Yueshan Qiu: Visualization; Huteng He: Investigation; Peng Luo: Investigation, Writing - review \u0026amp; editing, Resources, Supervision; Lihong Yuan: Project administration, Funding acquisition, Writing - review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known financial interests or personal relationships that could have influenced the work reported in this paper.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAulchenko, Y.S., Ripke, S., Isaacs, A., van Duijn, C.M., 2007. 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Due to the prevalence of pathogenic vibrios, genetic breeding of shrimps with the pan-vibrios resistance (PVR) trait has more practical significance for successful shrimp farming. To explore the genetic loci associated with the PVR trait of \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e, a genome-wide association study (GWAS) aiming at the PVR trait of the shrimp was conducted by using 300 shrimp individuals from various sources. After stringent screening, 243 single nucleotide polymorphisms (SNPs) corresponding to a selection threshold of -log10(p) value\u0026thinsp;\u0026ge;\u0026thinsp;2.5 were evaluated for their association with the PVR trait. Twenty candidate SNPs in genes and upstream region of genes (\u0026le;\u0026thinsp;5000 bp) were screened out for further validation of the association. The genotypes of three SNPs (SNP15, SNP16, and SNP17) were different between G1 (uninfected) and G4/G5 groups (seriously infected), among which GG genotype of SNP15 was significantly associated with low vibrios load. The genotype combination of GG-TT-AA at the three SNPs was linked, and it was significantly associated with the strongest performance of the trait. Notably, three SNPs were found located in the intron region of a gene, \u003cem\u003eLvCthrc1\u003c/em\u003e. The genotype combination can lead to the disappearance of a donor splicing site of \u003cem\u003eLvCthrc1\u003c/em\u003e, which predictably generates a novel transcript affecting the gene function. The highest expression level of \u003cem\u003eLvCthrc1\u003c/em\u003e was observed in immune-related tissues such as hemocytes, gills, and hepatopancreas. This study first put forward the concept of the PVR trait and provides valuable molecular markers for the genetic selection on the trait of shrimp, \u003cem\u003eL. vannamei\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Identification of genes associated with pan-vibrios resistance (PVR) trait of shrimp Litopenaeus vannamei through Genome-wide association study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-13 12:36:59","doi":"10.21203/rs.3.rs-6178636/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"865b86db-870e-4f99-984c-087031a12045","owner":[],"postedDate":"March 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-26T13:08:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-13 12:36:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6178636","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6178636","identity":"rs-6178636","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}