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Association Analysis of SNPs in the 3’-UTR of the MyD88 Gene with Resistance to Salmonella Pullorum Infection in Chickens

PJZ_52_3_849-856

 

 

Association Analysis of SNPs in the 3’-UTR of the MyD88 Gene with Resistance to Salmonella Pullorum Infection in Chickens

Peng Ren1, Xian-Qing Liu1, Chao-Wu Yang2,3, Hua-Rui Du2,3, Xiao-Song Jiang2,3 and Yi-Ping Liu1*

1Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu Campus, Chengdu 611130, China

2Sichuan Animal science academy, Chengdu 610066, China

3Animal Breeding and Genetics Key Laboratory of Sichuan Province, Chengdu 610066, China.

ABSTRACT

Pullorum disease is caused by Salmonella Pullorum and does a great loss to the poultry industry. As a universal innate immune gene, Myeloid differentiation primary response gene 88 (MyD88) can activate the nuclear factor-κB (NF-κB) pathway and regulate downstream gene expression. Single nucleotide polymorphisms (SNPs) in the coding regions (CDS) of the MyD88 gene have also been reported to be associated with inter-subject differences in responses to Salmonella Pullorum infection in chickens. However, whether the 3’-untranslated region (3’-UTR) of the MyD88 gene is associated with resistance to Salmonella Pullorum infection still remains unknown. In this study, a total of eight SNPs, including three novel mutations [SNP4 (A4812316G), SNP6 (C4813363A) and SNP7 (C4813618T)] and five known loci, were found within 3292 bp sequenced fragments. The allele frequency and genotype frequency of SNP4 (A4812316G) were found to be significantly different (P<0.05) between the case and control groups. However, no significant differences were found in the haplotypes of SNP1 and SNP2 (P>0.05). These results suggest that SNP4 (A4812316G) in the 3’-UTR of the MyD88 gene is linked to genetic resistance to Salmonella Pullorum infection and may provide an important reference for the marker-assisted selection of chickens during disease-resistance breeding.


Article Information

Received 04 June 2019

Revised 30 July 2019

Accepted 06 August 2019

Available online 24 February 2020

Authors’ Contribution

PR designed the study and wrote the article. XQL involved in the data analysis. CWY and HRD helped in sample collection. XSJ helped in preparation of the manuscript. YPL helped in conceiving and designing the study.

Key words

MyD88 gene, 3` Untranslated region, Salmonella Pullorum, SNPs, Polymorphisms

DOI: https://dx.doi.org/10.17582/journal.pjz/20190604100628

* Corresponding author: liuyp578@yahoo.com

0030-9923/2020/0003-0849 $ 9.00/0

Copyright 2020 Zoological Society of Pakistan



INTRODUCTION

Salmonella Pullorum is one of the common bacterial diseases that limited the rapid development of the poultry industry (Barrow et al., 2003). Though many studies related to genetic resistance have been carried out during the past few decades (Severens, 1944; Li et al., 2010; Li et al., 2018), the identification of resistance genes and the determination of their underlying mechanisms against Salmonella Pullorum infection remain to be studied (Wigley, 2004). However, in recent years, accumulating evidence has shown that innate immune genes may play important roles in Salmonella Pullorum infection (Peng et al., 2010; Ramasamy et al., 2014; Qiu et al., 2017). Some evidence showed the importance of the MyD88 gene in Salmonella Pullorum infection (Arques et al., 2009; Li et al., 2010; Liu et al., 2015). Other research also showed that deletion of the MyD88 gene could substantially delay the innate immune response (Aderem and Ulevitch, 2000). The multiprotein complex of the MyD88-IRAK (Interleukin-1 receptor-associated kinase) family is used by receptors of Interleukin-1 (IL-1), Interleukin-18 (IL-18) and Interleukin-33 (IL-33), which are important for inflammation and host defenses (Netea et al., 2012).

During infection, the host inflammatory response is initiated by pattern-recognition receptors (PRRs), which recognize pathogen-associated molecular patterns (PAMPs), conserved structures of the pathogenic microorganisms. The toll-like receptor (TLR) family is a major class of PRRs that leads to nuclear factor-κB (NF-κB) translocation and transactivation (Moynagh, 2005). Most TLR signaling involves the adaptor molecule MyD88 (Myeloid differentiation factor 88), and it plays a key role in maintaining the normal response of innate immunity that has been frequently reported during pathogen infections (Naiki et al., 2005). The function of MyD88 gene in the innate immune response against bacterial infection is largely known (Tauszigdelamasure et al., 2002; Serbina et al., 2003; Woods et al., 2008). Adenine- and uridine-rich elements (AREs) have been found in the 3’-UTR of certain messenger RNAs (mRNAs), and due to the function of AREs in the 3’-UTR (Kuersten and Goodwin, 2003; Barreau et al., 2006), it has been speculated that innate immune genes may be involved in regulating transcription and translation in the innate immune system (Sun and Ding, 2006; West et al., 2011). Despite being studied broadly among different species (Stockhammer et al., 2009; Issac et al., 2018), the role of the highly conserved MyD88 gene in the response to Salmonella Pullorum infection remains elusive. Identification of SNPs located outside the typical structure of the MyD88 gene, including the N-terminal death domain, C-terminal toll-interleukin 1 receptor (TIR) domain, and intermediate domain, and further studies focusing on the MyD88 untranslated region are necessary (Netea et al., 2012).

Innate immune-mediated disease resistance is closely related to genetic factors. As a key factor in innate immunity, the relevance of the MyD88 gene to Salmonella Pullorum infection remains unclear. To further explore the potential association between the MyD88 gene and genetic resistance to Salmonella Pullorum infection, 81 case and 90 control samples (infected or uninfected with Salmonella Pullorum) from local Qing Jiao Ma hens were collected to conduct an association study between the SNPs in the 3’-UTR of the MyD88 gene and the resistance to Salmonella Pullorum infection in chickens.

 

MATERIALS AND METHODS

Salmonella Pullorum detection and sample collection

Experimental hens at the age of 300 days are a pure line of local Qing Jiao Ma chickens from the Poultry Breeding Farm, Sichuan Agricultural University. Based on case-control design, the whole blood glass plate agglutination method (SN/T 1222-2003, AQSIQ) was used to test for Salmonella Pullorum infection (Liu et al., 2015), which is quick and less costly, exerting the greatest value on a flock basis. Following common laying hen immunization program, chickens were vaccinated timely of immunization. In this study, 2,200 Qing Jiao Ma hens have been tested at the time of 300 days of age, among which 81 infected subjects were collected as the cases and 90 uninfected subjects were collected as controls. The blood samples were collected from a vein under the wings of the chickens and stored at -20 °C for further use. All procedures carried out in this experiment were reviewed and approved by the Institutional Animal Care and Use Committee of Sichuan Agricultural University, China.

DNA extraction and pool construction

Genomic DNA from the blood samples was extracted by using the standard phenol/chloroform method. After the extracted DNA was tested by Nano Drop (ND-2000, Thermo Scientific) as previously described (Liu et al., 2019), the DNA samples were diluted to the level of (100 ± 3) ng/μL. A case DNA pool and a control one were composed of 30 samples that each contains 2μL DNA selected at random, respectively.

Primer design

A primer designing tool in NCBI (http://www.ncbi.nlm.nih.gov/ tools/primer-blast) was used for primer designing, and five primer pairs were designed to cover the 3’-UTR of the MyD88 gene according to the genomic sequence of Gallus gallus (GenBank accession number: NM_001030962). Primer pairs were designed after analysis by Oligo 7 (http://www.oligo.net/downloads.html). The primer sequences are shown in Table I.

PCR amplification and sequencing

Polymerase chain reaction (PCR) amplification was conducted using a 25 μL reaction mixture containing 50-100 ng of DNA, 0.3 μL of each forward and reverse primer, and 15 μL of 2× Taq PCR Master Mix (Tiangen Biotech Co., China). The procedure was carried out with 1 cycle of denaturalization at 96 °C for 4 minutes; 36 cycles of 98 °C for 40 seconds, 50-60 °C (optimal annealing temperature of each primer pair, listed in Table I) for 30 seconds, and 72 °C for 1 minute; and a final cycle of 72 °C for 8 minutes. All PCR products of the DNA pools and individuals were directly sequenced by the Shanghai Sangon Biotechnology Company (Shanghai, China).

Statistical analysis

Sequence variations, compositions and variable sites were identified using Chromas software and DNASTAR software (DNASTAR Inc., Madison, WI, USA). Hardy-Weinberg equilibrium, pairwise linkage disequilibrium (D’) and association analyses were conducted with Haploview software (version 3.32; http://www.broad.mit.edu/mpg/haploview/). The determination of allele frequency differences in the MyD88 gene between the case and control groups were performed by chi-squared test using R software (version 3.0.2, The R Foundation for Statistical Computing). In previous study, odds ratio (OR) and 95% confidence interval calculations were performed to determine the resistance or susceptibility to Salmonella Pullorum infection (Liu et al., 2015).

 

Table I. The primer sequences of the 3’-UTR used for amplification.

Name

Ampl-icon size (bp)

Sequence (5’-3’)

Target

region

Production

(bp)

Annealing temperature (°C)

P1

23

F: CTACTTAATTCAGCGAGCAATAG

Start - 1978

894

59.0

20

R: ACAAACTGGACCCACTTAGG

P2

25

F: ACCCTTTAATAGAAACTCAGTCTTG

1869 - 2616

768

54.6

21

R: CGAGTTTGTGAGCCTACCCTA

P3

20

F: GGTGCTGTTGCTGCTTCCTC

2531 - 3521

1012

54.0

22

R: CACATCTCAAGTGCCAAACCAC

P4

19

F: CATACCCAACTTGTGCGTT

3479 - 3978

521

52.5

22

R: ACTCCATTTTGTCATTCAGAGA

P5

20

F: GTAAAATCCAGCTTATGCAC

3907 - End

499

59.6

20

R: ATTCCTCACTAACACTTCCT

 

Table II. Change in alleles in the 3’-UTR.

Markers

ID

Position

Obs HET

Expt HET

Allele change

HWE (P)

MAF

SNP1

rs317890917

4810191

0.457

0.412

A>G

0.4784

0.330

SNP2

rs14131328

4810253

0.258

0.349

A>G

0.5507

0.327

SNP3

rs14131329

4810257

0.405

0.419

C>T

0.4578

0.354

SNP4

A4812316G

4812316

0.481

0.481

A>G

0.8340

0.342

SNP5

rs14131331

4810276

0.436

0.483

C>T

0.8480

0.368

SNP6

C4813363A

4813363

0.471

0.477

C>A

0.8152

0.409

SNP7

C4813618T

4813618

0.474

0.483

C>T

0.6792

0.111

SNP8

rs312369633

4813635

0.072

0.082

C>T

0.9977

0.146

 

Obs HET, observed heterozygosity; Expt HET, expected heterozygosity; HWE (P), P value of the Hardy-Weinberg equilibrium test; MAF, minimum allele frequency.

 

RESULTS

Sequencing the 3’-UTR of the MyD88 gene

In total, eight SNPs were detected in the 3’-UTR of the MyD88 gene: three novel mutations located in the chicken genome, named A4812316G (SNP4), C4813363A (SNP6) and C4813618T (SNP7), and five known SNPs (http://www.ncbi.nlm.nih.gov/projects/SNP), named SNP1, SNP2, SNP3, SNP5, and SNP8.

The Hardy-Weinberg equilibrium

Eight SNPs were analyzed with the Hardy-Weinberg equilibrium (HWE) test, and the results were shown in Table II. The observed heterozygosity of all SNPs was at a general level as expected. All the eight SNPs fit the assumption of the Hardy-Weinberg equilibrium (P>0.05). The minor allele frequency (MAF) of the SNPs was greater than 0.01.

Allele and genotype frequency of the mutated loci

The results of the allele and genotype frequency analyses of the 8 SNPs in the case and control groups were shown in Tables III and IV. The allelic distributions did not significantly differ between cases and controls in the 3’-UTR except SNP4 (A4812316G, P=0.0315, χ2=4.625). Table III shows that all of the OR values were less than 1, including the data for SNP4. In addition, the genotype distribution of SNP4 was significantly different between the case and control groups in the analysis of resistance to Salmonella Pullorum infection (P<0.05).

Association between haplotypes and susceptibility to Salmonella Pullorum

There were no significant differences in the linkage disequilibrium (LD) structures of the 8 SNPs between the cases and controls (Fig. 1). There was only one block which was in strong linkage disequilibrium state (D>0.8). The analysis of the haplotypes showed that the haplotype

 

Table III. Allele frequency of mutations in the 3’-UTR.

Markers

Alleles

χ2, P value

OR

95% CI

SNP1 (rs317890917)

A

G

χ2=0.115

P=0.7344

0.9249

0.8392-1.1316

Cases

55 (0.340)

107 (0.660)

Controls

58 (0.322)

122 (0.678)

SNP2 (rs14131328)

A

G

χ2=0.048

P=0.8269

0.9508

0.8480-1.1409

Cases

54 (0.333)

108 (0.667)

Controls

58 (0.322)

122 (0.678)

SNP3 (rs14131329)

T

C

χ2=3.029

P=0.0818

0.6739

0.7408-1.0198

Cases

65 (0.401)

97 (0.599)

Controls

56 (0.311)

124 (0.689)

SNP4 (A4812316G)

G

A

χ2=4.625

P=0.0315

0.6088

0.531-0.9759

Cases

116 (0.716)

46 (0.284)

Controls

109 (0.606)

71 (0.394)

SNP5 (rs14131331)

C

T

χ2=1.424

P=0.2327

0.765

0.7689-1.0669

Cases

65 (0.401)

97 (0.599)

Controls

61 (0.339)

119 (0.661)

SNP6 (C4813363A)

C

A

χ2=0.074

P=0.786

0.925

0.5882-1.4942

Cases

135 (0.833)

27 (0.167)

Controls

148 (0.822)

32 (0.178)

SNP7 (C4813618T)

C

T

χ2=1.9

P=0.1681

0.6149

0.3473-1.2097

Cases

148 (0.914)

14 (0.086)

Controls

156 (0.867)

24 (0.133)

SNP8 (rs312369633)

C

T

χ2=2.655

P=0.1032

0.6057

0.8499-1.0163

Cases

29 (0.179)

133 (0.821)

Controls

21 (0.117)

159 (0.883)

 

OR, odds ratio; CI, confidence interval. When the p-value of the Chi-square test is less than 0.05, the maximum value of the 95% CI less than 1 means resistance effect.

groups GG and AA in block one of the 3’-UTR had no significant association with Salmonella Pullorum infection between the cases and controls (Table V).

 

DISCUSSION

Sequencing the 3’-UTR of the MyD88 gene

A previous study revealed that 2 SNPs in the coding region (CDS) of the MyD88 gene were significantly associated with susceptibility to Salmonella Pullorum infection (Liu et al., 2015). In addition, further evidence confirmed that higher expression of TLR signaling activation via MyD88-dependent pathway is more beneficial to chicken mononuclear cells mediated innate immunity (Karnati et al., 2015). Therefore, the 8 SNPs located in the 3’-UTR of the MyD88 gene were predicted to be potential alleles in the follow-up studies.


 

Table IV. Genotype frequency of mutations in the 3’-UTR.

Markers

Genotypes

χ2, P value

SNP1 (rs317890917)

AA

AG

GG

χ2=0.12

P=0.9398

Cases

8 (0.099)

39 (0.481)

34 (0.420)

Controls

8 (0.089)

42 (0.467)

40 (0.444)

SNP2 (rs14131328)

AA

AG

GG

χ2=0.06

P=0.9705

Cases

8 (0.099)

38 (0.469)

35 (0.432)

Controls

8 (0.089)

42 (0.467)

40 (0.444)

SNP3 (rs14131329)

TT

TC

CC

χ2=3.50

P=0.1734

Cases

13 (0.161)

39 (0.481)

29 (0.358)

Controls

11 (0.122)

34 (0.378)

45 (0.500)

SNP4 (A4812316G)

GG

GA

AA

χ2=6.31

P=0.0426

Cases

40 (0.494)

36 (0.444)

5 (0.062)

Controls

36 (0.400)

37 (0.411)

17 (0.189)

SNP5 (rs14131331)

TT

TC

CC

χ2=1.52

P=0.4681

Cases

28 (0.346)

41 (0.506)

12 (0.148)

Controls

39 (0.433)

41 (0.456)

10 (0.111)

SNP6 (C4813363A)

CC

CA

AA

χ2=2.98

P=0.3118

Cases

54 (0.667)

27 (0.333)

0 (0.000)

Controls

61 (0.678)

26 (0.289)

3 (0.033)

SNP7 (C4813618T)

TT

TC

CC

χ2=1.86

P=0.4302

Cases

1 (0.012)

12 (0.148)

68 (0.840)

Controls

2 (0.022)

20 (0.222)

68 (0.756)

SNP8 (rs312369633)

TT

TC

CC

χ2=4.76

P=0.0599

Cases

53 (0.654)

27 (0.333)

1 (0.013)

Controls

71 (0.789)

17 (0.189)

2 (0.022)

 

P, P value of the Chi-square test.

 

Table V. Haplotype analysis of the 8 SNPs.

Haplotype groups

Frequency (cases)

Frequency (control)

χ2

P value

Block 1

GG

0.660

0.678

0.115

0.7344

AA

0.333

0.322

0.048

0.8269

 

P, P value of the Chi-square test.

 

Highly conserved in its CDS, the MyD88 gene plays a key role in the innate immune response. Though multiple previous studies have reported that the MyD88 gene may be involved in the response to pathogenic bacteria infection, most of these studies were performed at the gene expression level (Peng et al., 2010; Li et al., 2017). To reveal the role of the MyD88 gene in resistance to Salmonella Pullorum infection, we analyzed the 3’-UTR of the MyD88 gene in local Qing Jiao Ma hens (infected or uninfected with Salmonella Pullorum). Meanwhile, a growing number of studies have shown that the 3’-UTR plays a considerable role in mRNA stability and the efficiency of translation (Cok and Morrison, 2001; Wang et al., 2006). The AREs of the 3’-UTR speed up the degradation of mRNA in Cyclooxygenase-2 (COX-2) (Sureban et al., 2007). Collectively, SNPs of the 3’-UTR in the MyD88 gene have been speculated to have an association with the regulation of the innate immune response to Salmonella Pullorum infection (Tsai et al., 2004).

The Hardy-Weinberg equilibrium

The Hardy–Weinberg principle, also known as the Hardy-Weinberg equilibrium, states that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences, such as mate choice, mutations, selection, genetic drift, gene flow and meiotic drive (Salanti and Ioannidisb, 2008). Recently, Hardy-Weinberg tests performed in marker-disease association studies have been used for genotyping. The results showed that all these 8 SNPs fit the assumption of the HWE, and they can be used for further analysis. When analyzing the MAF of the 8 SNPs, the effects of selection and foreign blood were found to be eliminated from the chicken population. In other words, these SNPs are sporadic mutations and are vital in genetic breeding.

Allele and genotype frequency of the mutated loci

The odds ratio (OR) value is an important index to quantify how strongly the presence or absence of one property is associated with the presence or absence of another property in a given population (Cornfield, 1951). When the p-value of the Chi-square test is less than 0.05 (the OR value is meaningful), the maximum value of the 95% CI less than 1 means resistance effect (Liu et al., 2015). This suggested that the polymorphisms of SNP4 might have a significant correlation with resistance to Salmonella Pullorum infection. Besides the SNPs of MyD88, multiple genotypes of the innate immunity genes, including the Avian β-defensins and Cytokines SNPs, were previously reported to be associated with resistance to Salmonella infection (Sadeyen et al., 2006). It would be quite interesting to unravel the associations between resistance to disease and SNPs in other genes, particular those with the ability to fight against infections (Yu et al., 2018; Zhang et al., 2019).

Association between haplotypes and susceptibility to Salmonella Pullorum

It is known that the association between haplotype and disease is more effective than a single mutation analysis (Durrant et al., 2004). In past decades, haplotypes have repeatedly been used for analyses of the disease associations found in wild and domesticated populations of chickens (Hosomichi et al., 2008). Furthermore, studies have indicated linkage of the ability to respond to Salmonella infection with particular MHC class I or class II haplotypes in inbred lines of chickens (Liu et al., 2002; Eimes et al., 2010). Another study revealed the regulating effect of the 3’-UTR of chMAVS on mRNA by choosing two representative 3’-UTR haplotypes (Yu et al., 2014). It is notable that none of the haplotype groups showed significant associations with Salmonella Pullorum infection in our study. A possible explanation is that the effects of the SNPs in the haploid type groups canceled each other out due to potential interactions between genes, leading to no significant link between haplotypes and disease resistance.

 

CONCLUSION

In this study, we detected a significant novel mutation (SNP4) of the 3’-UTR in the MyD88 gene between the cases and controls. This finding suggests that SNP4 (A4812316G) may have an effect on the individual immune. But further functional studies are necessary to evaluate the molecular mechanism caused by polymorphisms of the 3’-UTR of MyD88 gene. Our results provide some clues to help better understand the potential role of genetic resistance to Salmonella Pullorum infection in poultry breeding.

 

ACKNOWLEDGMENTS

This work was supported by the Open Fund of Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province (Grant No. 2016NYZ0043, 2017JZ0033).

 

Statement of conflict of interest

The authors declare no conflict of interest.

 

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Pakistan Journal of Zoology

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