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Neuroimmunol Neuroinflammation 2016;3:274-82.10.20517/2347-8659.2016.21© 2016 OAE Publishing Inc.
Open AccessTopic: Infectious Disease of Central Nervous System

Screening of genetic loci predisposing to herpes simplex virus infection on mouse chromosome 17

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1Depatment of Neurology, Xinqiao Hospital, the Third Military Medical University, Chongqing 400037, China.

2Depatment of Neurology, the First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China.

Correspondence Address: Prof. Wen Huang, Depatment of Neurology, Xinqiao Hospital, the Third Military Medical University, Chongqing 400037, China. E-mail: huang_wen@163.com

    ...

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License (http://creativecommons.org/licenses/by-nc-sa/3.0/), which allows others to remix, tweak and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

    Abstract

    Aim: The herpes simplex virus (HSV), one of the most common viruses infecting humans, is featured by a high infection rate and usually causes complex disorders difficult to diagnose and treat. Disease progression is always combined with the specific interaction between organism and environment, but genetic factors play a decisive role in most pathogenic processes. Like most human disorders, individual difference has also been involved in the pathogenesis of HSV infection. The present study aimed to screen the potential gene loci that regulates human predisposition to HSV infection.

    Methods: With reference to previous studies, inbred mouse lines with significantly distinct predisposition to HSV infection were chosen for gene loci screening. Gene sites on mouse chromosome 17 associated with susceptibility to HSV infection were then identified by correlation analysis and genome-wide scanning technique.

    Results: Genes affecting the vulnerability of mice to HSV infection were mapped to three regions on the 17th mouse chromosome, D17MIT51.1, D17MIT39.1 and the region between D17MIT180.1 and D17MIT184.

    Conclusion: The results suggest that the mouse genetic background plays an important role in its susceptibility to HSV-1 infection, which might be regulated by multiple predisposing quantitative trait loci.

    Introduction

    As an infection relapse could confer severe consequence in the pathogenicity of herpes simplex virus (HSV) infection, avoiding infection and preventing recurrence after treatment is of great importance. Individual differences involved in the pathogenesis of HSV infection in mice have been long studied. Several reports related to HSV infection susceptibility further pointed to the role of genetic background in the HSV infection process.[1-5] To further analyze the susceptibility to HSV infection in different inbred mouse lines, we scanned the 17th mouse chromosome for gene sites associated with it using the correlation analysis and genome-wide scanning technique.

    Methods

    Genomic DNA extraction

    Firstly, 50-100 frozen tissue samples were weighed, grinded into powder in liquid nitrogen using a grinding bowel and pestle, and then immediately mixed with 1 mL Tripure. Tissue sample powder was then further homogenized 10 times using a homogenizing drill on ice for 20 min until no tissue fluid particles was visible, centrifuged at the speed of 12,000 g at 4 ℃, for 10 min. The homogenate was then kept at room temperature for 5 min to make sure the nuclear protein was totally separated. Each milliliter homogenate was mixed with 0.3 mL chloroform and shaken vigorously at 4 ℃ for 15 s, kept at room temperature for 2-15 min, then Centrifuged at 12,000 g at 4 ℃, for 15 min. To get high quality DNA, the upper layer of colorless aqueous liquid after centrifugation was removed. Each milliliter homogenate was mixed with 0.2 mL 100% ethanol which was stored at 4 ℃, mixed completely by rotating the bottle upside down several times and kept at room temperature for 2-3 min for DNA precipitation. After centrifuging at 2,000 g for 5 min at 4 ℃, the upper layer liquid was removed with a pipette carefully. Each milliliter sample solution was then mixed with 1 mL of 0.1 mol/L sodium citrate dissolved in 10% ethanol, kept at room temperature for 30 min with frequent mixing, and centrifuged at 4 ℃ for 5 min at 2,000 g again. The upper layer liquid was collected, mixed with 75% ethanol, and kept at room temperature for 30 min with frequent mixing. Then, after centrifuging at 4 ℃ and 2,000 g for 5 min, the upper layer liquid was removed and the DNA sample was dried in the air or vacuum for 5-10 min. Finally, we dissolved the DNA with 50 uL TE solution, pipetted out 1 uL sample for color comparison and another 10 uL for electrophoresis, and the residual was stored at -20 ℃ for further analysis. DNA samples were diluted with 90 uL MQ water and analyzed with ultraviolet spectrophotometer. The OD260 value, OD280 value and OD260/280 value were used for calculating the concentration of DNA.

    Primer design and synthesis

    Primer design referenced information from the mouse genome program (detailed information can be viewed on the website of Jackson Laboratory), which was designed by Shanghai Jikang Biotechnology Limited Company [Table 1]. The detailed information about PCR reaction system and PCR reaction condition can be seen in Table 2.

    Table 1

    Primer sequences for scanning microsatellite loci on the 17th chromosome of mouse genome

    Loci namePrimer sequenceGenetic distance (cM)
    D17MIT245.1ForwardFAM-TGTGCTCTGGCTAGGGAGTT3
    ReverseCACATTCATATGTACACACACATGC
    D17MIT143.2ForwardFAM-CTTACAAGCATCCTGTGGAACTC5
    ReverseGAGGACCAACAGTCAAACATAGC
    D17MIT46ForwardFAM-TCCACCCCACTACCTGACTC11.7
    ReverseCCCTTCTGATGACCACAGGT
    D17MIT146.1ForwardFAM-CTGTCAGCAGAACGTTCCTTAGT17.1
    ReverseCCAACTCAAGCCTTACATAGTGG
    D17MIT51.1ForwardFAM-TCTGCCCTGTAACAGGAGCT22.9
    ReverseCTTCTGGAATCAGAGGATCCC
    D17MIT10.1ForwardFAM-TGCACTTGCATAAGGAAAAC24.5
    ReverseGACTTTGGGGCCTACTTATG
    D17MIT180.1ForwardFAM-AGACACTGTCTAAAAACACAAGATGG29.4
    ReverseTTGTGTTCATATGCATGTGTGC
    D17MIT20.1ForwardFAM-AGAACAGGACACCGGACATC34.3
    ReverseTCATAAGTAGGCACACCAATGC
    D17MIT184ForwardFAM-TGCACTACCCAAACATGCAT38.5
    ReverseACTTCTGACAGGAAGCATCCA
    D17MIT93.1ForwardFAM-TGTCCTTCGAGTGTTTGTGTG44.5
    ReverseTCCCCGGTGAATGAGTTATC
    D17MIT39.1ForwardFAM-CCTCTGAGGAGTAACCAAGCC45.3
    ReverseCACAGAGTTCTACCTCCAACCC
    D17MIT122.1ForwardFAM-TCTCTTCACTGCAATGGAACA51.9
    ReverseGAACCTATAGGCTCTTGAATAGATGG
    Table 2

    PCR reaction system and PCR reaction condition

    PCR reaction system (total volume: 10 uL)
     Non-enzyme water5.4 μL
     10 × PCR buffer1.0 uL
     Mg2+ (25 mmol/L)0.5 uL
     dNTP (each 2.5 mmol/L)1.0 μL
     P1 (5 pM)0.5 uL
     P2 (5 pM)0.5 uL
     Template DNA (30-50 ng/uL)1.0 uL
     Ex-Taq enzyme (5 U/μL)0.1 μL
    PCR reaction condition
     95°C5 min
     94°C30 s
     Time30 s
     72°C30 s
     Repeat the 2nd to 4th steps for totally 38 cycles
     72°C10 min
     Store at 4°C

    Microsatellite loci detection

    First, 1 mL Hi-Di Formamide was mixed with 50 uL GeneScan -500 LIZ Size Standard, then mixed with 9.5 uL polymerase chain reaction (PCR) product, which was diluted 20 times. Tubes containing the above solution were placed in the PCR instrument for degeneration at 95 ℃ for 5 min, kept on ice for more than 5 min. Using an ABI PRISMTM 310 genetic analyzer of the ABI Company for electrophoresis, the voltage was set to 15 KV and run at 60 ℃ for 28 min. The samples were then collected for further analysis.

    Electrophoresis data processing

    By using the software Genescan (311) and Genetyper (3.7), we could get the detected fragment size. The equipment was provided by ABI Company; the PCR amplification reagents by Baosheng Bioengineering Limited Company; and the fluorescent primers by Shanghai Jikang Biotechnology Limited Company.

    Results

    Scanning 12 microsatellite spots on the 17th chromosome of two mouse lines

    The differences of 12 microsatellite loci between two inbred mouse lines BALB/C and C57BL/6 were first scanned. Among the loci scanned, seven of them were significantly different: D17MIT245.1, D17MIT46, D17MIT51.1, D17MIT180.1, D17MIT20. 1, D17MIT184 and D17MIT39.1 [Table 3; Figure 1].

    Table 3

    Microsatellite loci scanning using BALB/C and C57BL/6 inbred mice

    Microsatellite lociBALB/C susceptibleC57BL/6 tolerant
    D17MIT245.1194202
    D17MIT143.2112112
    D17MIT46218236
    D17MIT146.1166166
    D17MIT51.1152154
    D17MIT10.1155155
    D17MIT180.1139137
    D17MIT20.1163175
    D17MIT184126128
    D17MIT93.1155155
    D17MIT39.186104
    D17MIT122.1141141

    Figure 1. The microsatellite loci scanned using two mouse lines. A: D17MIT245.1; B: D17MIT143.2; C: D17MIT46; D: D17MIT46.1; E: D17MIT51.1; F: D17MIT10.1; G: D17MIT180.1; H: D17MIT20.1; I: D17MIT18; J: D17MIT93; K: D17MIT39.1; L: D17MIT122.1

    Scanning microsatellite loci on the 17th chromosome using three inbred mouse lines

    To minimize false-positives among the above seven sites obtained using the two inbred mouse lines, we further searched the literature and found that another inbred mouse line, DBA-2, had similar susceptibility to HSV infection as BALB/C mice. Therefore, scanning these three inbred mouse lines for microsatellite loci led to the exclusion of two of the above seven loci, D17MIT245.1 and D17MIT46. Our updated scanning results showed that D17MIT51.1, D17MIT39.1 and the genomic region between D17MIT180.1 and D17MIT184 were mouse microsatellite regions affecting susceptibility to HSV infection [Table 4; Figure 2].

    Table 4

    Microsatellite loci scanning using BALB/C, DBA-2 and C57BL/6 inbred mice

    Microsatellite lociSusceptibleTolerant
    BALB/CDBA-2C57BL/6
    D17MIT245.1194200202
    D17MIT143.2112112112
    D17MIT46218208236
    D17MIT146.1166166166
    D17MIT51.1152152154
    D17MIT10.1155149155
    D17MIT180.1139139137
    D17MIT20.1163163175
    D17MIT184126126128
    D17MIT93.1155169155
    D17MIT39.18686104
    D17MIT122.1141123141

    Figure 2. The microsatellite loci scan results of two DBA-2 mouse lines. A: D17MIT245.1; B: D17MIT143.2; C: D17MIT46; D: D17MIT46.1; E: D17MIT51.1; F: D17MIT10.1; G: D17MIT180.1; H: D17MIT20.1; I: D17MIT18; J: D17MIT93; K: D17MIT39.1; L: D17MIT122.1

    Bioinformatic analysis of genes in the HSV infection susceptibility regions on chromosome 17

    For identifying potential genes involved in the susceptibility of mice to HSV infection, we used bioinformatics to analyze the genes localized in these regions. Based on the above results, bioinformatic analysis found approximately 140 genes in the positive sites D17MIT51.1, D17MIT39.1 and the region between D17MIT180.1 and D17MIT184 [Tables 5-7]. Among those genes, there were about 33 human homologous genes that showed some of the following characteristics: (1) containing many quantitative trait loci, such as epididymal fat pad weight quantitative trait loci (QTL) 3, subcutaneous fat pad weight QTL 4, spleen weight QTL 9, etc.; (2) containing some genes related to the important physiological functions of the body such as Mut methylmalonyl-Coenzyme A mutase; (3) containing genes related to the developmental and physiological function such as early growth adjusted QTL 2, early growth QTL 5, etc.; (4) containing genes associated with some diseases such as the Down syndrome critical region gene 1-like 1, MSM lymphoma resistance 1, etc.; (5) containing mouse tissue associated antigen H-2.

    Table 5

    Bioinformatics of genes in microsatellite loci D17MIT51.1 region

    No.Mouse genomeCorresponding human genesFunctions
    1Epididymal fat pad weight QTL 3QTL
    2Subcutaneous fat pad weight QTL 4QTL
    3Spleen weight QTL 9QTL
    4Early growth adjusted QTL 2QTL
    5Early growth QTL 5QTL
    6Pulmonary adenoma susceptibility 12QTL
    7Weight 6 weeks QTL 11QTL
    8Weight 10 weeks QTL 12QTL
    9DNA segment, Chr 17, Hunter 19
    10DNA segment, Chr 17, Hunter 20
    11DNA segment, Chr 17, Hunter 21
    12Down syndrome critical region gene 1-like 1DSCR1L1
    13Fat pad 7QTL
    14Mandibular morphogenesis 1QTL
    15MSM lymphoma resistance 1QTL
    16Bystin-likeBYSL
    17DNA segment, Chr 17, ERATO Doi 191, expressed
    18DNA segment, Chr 17, ERATO Doi 763, expressed
    17Methylmalonyl-Coenzyme A mutaseMUT
    18Neuroscience mutagenesis facility, 318
    19Cysteine-rich secretory protein 2CRISP2
    20DNA segment, Chr 17, Tubingen 37
    21DNA segment, Chr 17, Tubingen 16
    22Ventral midbrain iron content 9QTL
    23Soft tissue heal 11QTL
    24DNA segment, Chr 17, Tubingen 37
    25Gastritis type A susceptibility locus 4QTL
    26H2 (histocompatibility-2, MHC)Complex/cluster/region
    27Histocompatibility 2, Q regionComplex/cluster/region
    28Long bones 10QTL
    29Lymphoma latency accelerationQTL
    30Leishmaniasis resistance 1QTL
    31Locomotor activity 2QTL
    32T cell receptor beta variable 4, control 1QTL
    33T-cell receptor induced activation 3QTL
    34Modifier of Odc1QTL
    35UVB induced immunosuppression 2QTL
    36Cleidocranial dysplasiaComplex/cluster/region detail
    37Ectonucleotide Pyrophosphatase/phosphodiesterase 5ENPP5
    38T-complex-associated testis expressed 1TCTE1
    39Xenotropic murine leukemia virus 57
    Table 6

    Bioinformatics of genes in microsatellite loci D17MIT39.1 region on the 17 mouse chromosome

    No.Mouse genomeCorresponding human genesFunctions
    1Laminin receptor 9
    2Proteoglycan induced arthritis 20QTL detail
    3Ribosomal protein L19, related sequence 8pseudogene
    4T-cell integration locus
    5Xanthine dehydrogenaseXDHxanthine dehydrogenase
    6Sine oculis-related homeobox 2 homolog (Drosophila)SIX2
    7Sine oculis-related homeobox 3 homolog (Drosophila)SIX3
    8MutS homolog 2 (E. coli)MSH2DNA mismatch repair protein, eukaryotic MSH2 type
    9Carcass protein in high growth mice 3QTL
    10DNA segment, Chr 17, XREFdb 57
    Table 7

    Bioinformatics of genes in microsatellite loci from D17MIT180.1 to D17MIT184 region

    No.Mouse genomeCorresponding human genesFunctions
    1High mobility group nucleosomal binding domain 1, related sequence 8
    2Cyclin D3CCND3
    3Ecotropic viral integration site 14
    4High mobility group nucleosomal binding domain 2. related sequence 4
    5DNA segment, Chr 17, Roswell Park 11, expressed
    6Transplantation-specific integration cluster 1
    7Body weight 2
    8DNA segment, Chr 17, CEPH 9
    9DNA segment, Chr 17, Le Roy 1
    10DNA segment, Chr 17, Tubingen 40
    11P300/CBP-associated factorPCAF
    12Progastricsin (pepsinogen C)PGC
    13Thymus specific insertion locus
    14Meprin 1 alpha ;MGI:96963MEP1A
    15DNA segment, Chr 17, Seldin 7
    16Macrophage migration inhibitory factor, pseudogene 8Pseudogene
    17Cerebellar cAMP 8QTL
    18DNA segment, Chr 17, John C. Schimenti 39
    19DNA segment, Chr 17, National Cardiovascular Center, Shionogi 7
    20DNA segment, Chr 17, National Cardiovascular Center, Shionogi 34
    21DNA segment, Chr 17, XREFdb 556
    22abdominal fat weight 3QTL
    23DNA segment, Chr 17, Abbott 3
    24DNA segment, Chr 17, Birkenmeier 8
    25DNA segment, Chr 17, Tubingen 20
    26Heligmosomoides polygyrus nematode resistance 7QTL
    27Heligmosomoides polygyrus nematode resistance 7QTL
    28Obesity and body weight QTL 4QTL
    29RAB5A, member RAS oncogene familyRAB5A
    30Skin tumor susceptibility 10QTL
    31DNA segment, Chr 17, Brigham Young University 2
    32High density lipoprotein (HDL) level 4QTL
    33Vav 1 oncogeneVAV1
    34Nrtn ;neurturin;NRTN
    35Creatine kinase, brain, related sequence 2
    36Epstein-Barr virus induced gene 3EBI3
    37DNA segment, Chr 17, Hunter 24
    38Ephrin A5EFNA5
    39RAS-like, family 2, locus 3
    40Protein tyrosine phosphatase, receptor type, SPTPRS
    41Abdominal fat percentage 1QTL
    42P. chabaudi malaria resistance QTL 7
    43Caseinolytic peptidase, ATP-dependent, proteolytic subunit homolog (E. coli)CLPP
    44Plasmacytoma susceptibility 5
    45Ribosomal protein L32, related sequence 7Pseudogene
    46Sulfotransferase family, cytosolic, 1C, member 1
    47DNA segment, Chr 17, Tubingen 23
    48Complement component 3C3
    49CD86 expression in activated macrophagesQTL
    50DNA segment, Chr 17, Hunter 15
    51DNA segment, Chr 17, University of California at Los Angeles 2
    52EGF-like module containing, mucin-like, hormone receptor-like sequence 1EMR1
    53EGF-like module containing, mucin-like, hormone receptor-like sequence 4EMR4
    54Modifier of obesity 4QTL
    55Fer (fms/fps related) protein kinase, testis specific 1
    56tubulin, beta 4TUBB4
    57DNA segment, Chr 17, ERATO Doi 599, expressed
    58DNA segment, Chr 17, Hunter 16
    59SH3-domain GRB2-like 1SH3GL1
    60Thin fur
    61Abdominal fat percent QTL 6QTL
    62Early somite stage arrest 15a
    63HDL QTL 29QTL
    64KH-type splicing regulatory proteinKHSRP
    65Regulatory factor X, 2 (influences HLA class II expression)RFX2
    66Skeletal muscle weight 5QTL
    67DNA segment, Chr 17, Wayne State University 104, expressedC19orf10
    68DNA segment, Chr 17, XREFdb 173
    69Immune response 5
    70Feminization 1 homolog a (C. elegans)FEM1A
    71DNA segment, Chr 17, Indiana University Medical 1
    72DNA segment, Chr 17, John C. Schimenti 20
    73DNA segment, Chr 17, XREFdb 181
    74Laminin, alpha 1LAMA1
    75RalA binding protein 1RALBP1
    76Twisted gastrulation homolog 1 (Drosophila)TWSG1
    77Protein tyrosine phosphatase, receptor type, MPTPRM
    78Age related hearing loss 3QTL
    79Stathmin 1, related sequence 2pseudogene
    80Abdominal fat weight QTL 7QTL
    81DNA segment, Chr 17, Birkenmeier 9
    82DNA segment, Chr 17, Brigham and Women’s Genetics 1496 expressed

    Discussion

    It has been widely observed that different species or even individuals of the same species show differences in response to infection, but the explanation for this phenomenon is still rather controversial. There have been reports suggesting that the genetic background might play an important role.[1,6-8] The causative factors for different responses to infection, the possible ways of intervention, the revolutionary changes of infection prevention, and the control that resulted from those changes have aroused great interest among the scientific community. In this study, we analyzed the genetic background that contributes to the HSV infection susceptibility.

    The Herpes virus genus (Herpesviridae) is among the enveloped, linear, double-stranded DNA viruses that widely exist in nature. Approximately 100 HSV species have already been identified or partially identified. Among them, two HSV species, SV-1 and HSV-2, that share 50% homology, have been closely associated with humans. According to statistics provided by the WHO, approximately 70% of the total population worldwide carries HSV antibodies and more than one-third suffers from recurrent HSV infection. Along with its high prevalence rate, a variety of human diseases are closely related with HSV infection, including human herpes labialis, herpes conjunctivitis, 20 herpes zoster encephalitis and other diseases causing great harm to human health. HSV encephalitis is the most common, sporadic, viral encephalitis, accounting for 10-20% of acute, viral, encephalitis and 60-80% of natural mortality. Understanding the complex and specific characteristics of HSV infection-related diseases has been a scientifically and socially pressing need that has led to overcoming the recent difficulties in diagnosis and treatment.

    As a viral disease seriously affecting human health with an increasing incidence in recent years, herpes simplex virus 1 (HSV-1) infection typically generates uncomfortable, watery blisters on the skin or mucous membranes of the mouth and lips,[9,10] potentially leads to encephalitis with remarkable sequelae, or vesicle eruption on genital organs.[11] More importantly, the eruption of these blisters and vesicles are frequently attributed to the long-term latent infection of HSV-1 in the nervous system.[12] Although the human HSV infection rate is very high, it is difficult to fully attract people’s attention, so it’s difficult for us to associate HSV infection with genetic background. Therefore, most of the previous HSV infection studies focused on the acquired immune response after infection, showing that T cell-mediated immune response plays an important role in resisting HSV-1 infection,[13,14] and immune suppressed or immune deficient individuals are vulnerable to opportunistic herpes virus infection.[15] Furthermore, recent studies[16,17] suggested that innate immune response plays a key role in limiting the spread of the virus. The development of innate immune germ line occurs earlier than acquired immune response system,[18] and these two mechanisms function differently. This is undoubtedly an important point that genetic backgrounds play an important role in HSV infection. Meanwhile, the clinical symptoms of acute infection, as well as the long-term pathologic processes induced by recurrent latent infection, have been shown to closely correlate with the complex viral genome structures and the molecular mechanism of viral gene transcriptional regulation and replication.[19,20]

    In fact, as early as 1975, Lopez[1] reported that there are significant differences in the genetic backgrounds of inbred mice that had significantly different reactions to the same or similar HSV infection, which undoubtedly suggested that genetic background might be an important factor for susceptibility to infection. This mechanism revealed by Lopez has also been confirmed by other studies.[2,3] Also, there was a follow-up study on the relationship between the genetic background and susceptibility to HSV infection. Zawatzky et al.[21] showed that compared with susceptible DBA/2 mice, the relatively tolerant C57BL/6 mice could produce more interferons in the immune response when it comes to HSV-1 infection. But Brenner et al.[22] showed that there is no significant difference in the immune response to HSV infection among those two mouse lines. If the findings in mortality after infection phenotype, Simmons et al.[23] reported that only one gene loci functions in this process, while Kastrukoff et al.[24] reported that there were two loci separated in the role. We are inclined to believe that from the viewpoint of a gene associated with genetic background, it is undoubtedly that genetic background plays an important role in the phenotypic susceptibility to HSV infection. Since the genetic background is polygenic, and HSV has no apparent genetic background, the susceptibility of HSV infection itself is very likely regulated by more than one gene controlling quantitative traits.

    By bioinformatics analysis, our results suggest that approximately 140 genes were found in the area of D17MIT51.1, D17MIT39.1 and the genomic region between D17MIT180.1 and D17MIT184, and functions of the majority of those genes are not fully revealed. There is a possibility that the above sites are related to the susceptibility to HSV infection, especially the growth-related genes which are highly suggestive of the importance of genetic background. Among these 140 genes, there were about 33 genes homologous to human genes. Their main functions include binding with other partners, regulating a variety of physiological processes, and the modulation of the phosphorylation process of various enzymes and coenzymes.

    Based on our experimental results and bioinformatics analysis, the genetic background might play an important role in susceptibility to HSV infection, which is also consistent with most previous studies. It is worth noting that our finding is likely to be a quantitative trait locus, and may not be a particular system or population-specific mechanism. It is just a hint of this phenomenon in a particular system or population which has a relative higher or lower incidence in another race or ethnic groups. This is not consistent with some previous research.

    In summary, the biological information and related data analysis suggest that these genes have important physiological and pathological functions. However, up to now, their associations with HSV susceptibility infection have not been reported, suggesting that they could be potential candidate genes that contributed to the different susceptibility to HSV infection.

    Because HSV infection phenotypes have not been clearly defined yet, some issues are far from a consensus. For instance, whether the differences in response to HSV infection really exist and whether the genetic background plays a role in it. All these issues will undoubtedly limit the objectivity of this research. It is also necessary to validate the results in the present study by expanding the sample size, further investigating the role of the regulatory regions in regulating susceptibility to HSV infection. Furthermore, the functions of genes near these microsatellite loci, as well as their functions in regulating susceptibility, deserve further investigation.

    Financial support and sponsorship

    Nil.

    Conflicts of interest

    There are no conflicts of interest.

    Patient consent

    There is no patient involved.

    Ethics approval

    Ethics approval was obtained prior to the commencement of the study.

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