Volume 5 Supplement 4

Proceedings of the International Symposium on Animal Genomics for Animal Health (AGAH 2010)

Open Access

In silico analysis of candidate genes associated with humoral innate immune response in chicken

  • Anna Slawinska1Email author,
  • Andrzej Witkowski2,
  • Marek Bednarczyk1 and
  • Maria Siwek1
BMC Proceedings20115(Suppl 4):S36

DOI: 10.1186/1753-6561-5-S4-S36

Published: 3 June 2011

Abstract

Background

Production and function of natural antibodies (NAbs) constitutes an important mechanism of the humoral innate immunity in vertebrates. The level of NAbs in chicken is heritable and the genetic background has been partly investigated. However, to date the genetic determination of humoral innate immune response in avian species has not been fully described. The goal of this study was to propose a new set of candidate genes with a potential effect on the NAb phenotype for further SNP association study.

Methods

In silico analysis of positional and functional candidate genes covered 14 QTL regions associated with LPS, LTA & KLH NAbs and located on six chromosomes: GGA5, GGA6, GGA9, GGA14, GGA18 and GGAZ. The function of the genes was subsequently determined based on the NCBI, KEGG, Gene Ontology and InnateDB databases.

Results

As a result, the core panel of 38 genes participating in metabolic pathways of innate immune response was proposed. Most of them were assigned to chromosomes: GGA14, GGA5, GGA6 and GGAZ (13, 9, 8 and 5 genes, respectively). These candidate genes encode proteins predicted to play a role in (i) proliferation, differentiation and function of B lymphocytes; (ii) TLR signalling pathway, and (iii) MAP signalling cascade.

Conclusions

Proposed set of candidate genes is recommended to be included in the follow-up studies to model genetic networks of innate humoral immune response in chicken.

Background

Humoral innate immunity in vertebrates that establishes the first barrier against pathogens consists of two basic mechanisms – natural antibodies (NAbs) and complement system. Expanding the knowledge on this field of avian immunology might be of help to overcome the difficulties in poultry industry, struggling constantly with diseases outbreaks eg. Avian Influenza [1]. In chicken, the level of NAbs proved to be heritable [2]. However, the genetic determination of NAbs is not fully described as it lacks information on which genes can be considered as the regulators in the complicated network of NAbs creation and function. This study contributes to the discovery of genetic determination of humoral innate immunity as it lists the proposed positional and functional candidate genes that have the putative impact on the NAb phenotype.

Methods

Chromosomal regions for in silico candidate gene analysis were initially selected based on the location of the QTL associated with the NAb titres directed against LPS (lipopolysaccharide), LTA (lipoteichoic acid) and KLH (keyhole limpet hemocyanine) antigens in chicken. This step was performed based on results from two independent studies, i.e.

Study 1 – LPS and LTA NAb QTL detection study [3];

Study 2 – LPS and LTA NAb QTL validation study; KLH NAb detection study (data not published).

Study 2 was carried out within a new chicken reference population, set-up as a F2 cross between commercially selected breed (WL, White Leghorn) and a Polish, unselected native chicken breed (GP, Green-legged Partridgelike). For a candidate gene analysis reported here, the chromosomal regions of interest included QTL associated with LPS and LTA NAb titres that had been detected in study 1 and consecutively validated in study 2 as well as QTL associated with KLH NAb titres that had been detected in study 2. These QTL were located in the following chicken chromosomes: GGA5, GGA6, GGA9, GGA14, GGA18 and GGAZ. The regions of interest were designated based on the physical location of the microsatellite markers flanking the QTLs. The list of candidate genes within the QTL regions was prepared based on NCBI database [4], and gene function was assessed with KEGG [5], InnateDB [6] and Gene Ontology [7]. The genes meeting both the criteria, i.e. location within the QTL regions & function in innate immunity (including signalling pathways and B cell function) were listed in a panel of the candidate genes associated with humoral innate immune response.

Results

The results of the candidate gene analysis are presented in Table 1. Briefly, based on previously described criteria, the total number of 38 candidate genes located on six chromosomes was selected. The highest number of the candidate genes (13 genes) was located on GGA14; 9 genes were found on GGA5 and 8 – on GGA6. Lower number of candidate genes were found on GGAZ (5 genes), on GGA18 (2 genes) and on the GGA9 (1 gene).
Table 1

Positional and functional candidate genes associated with innate humoral immune response

Symbol

ID

Name

Ch

Metabolic Pathway

Gene Function

BLNK

395733

B cell linker

6

BCR

B-cell development

CARD11

416476

caspase recruitment domain family, member 11

14

BCR, TCR, NFκB

NFκB activation

CASP7

423901

caspase 7, apoptosis-related cysteine peptidase

6

BCR, TNFα

Apoptosis

CAT

423600

Catalase

5

NFκB

Regulation of NFκB activity

CD59

423148

CD59 molecule, complement regulatory protein

5

T cells

T cell activation, complement system inhibition

CD7

417346

T-cell antigen CD7 precursor

18

T cells

T cell activation, T and B cell interaction, component of mature T cells

CD82

423172

CD82 molecule

5

NFκB, p53

Binding of proteins in cell membrane

CIITA

427676

class II, major histcompability complex, transactivator

14

TLR, MHC

LRR binding, MHCII transcription activation

CXCL12

395180

chemokine (C-X-C motif) ligand 12

6

IL

Leukocyte activation, T cell proliferation, chemotaxis

FADD

423146

FAS (TNFRSF6)-associated via death domain

5

NFκB

Apoptosis, NFκB cascade activation, early development of T cells

FAS

395274

TNF receptor superfamily, member 6

6

TNFα, Fas, B and T cells

Ig production, immune response with (B cells) Homeostasis between B I T cells

FGF10

395432

fibroblast growth factor 10

Z

NFκB, MAPK

TLR activation, inflammatory cytokine secretion (with APC)

FGF8

396313

fibroblast growth factor 8

6

MAPK

MAPK cascade activation

FOS

396512

v-fos FBJ murine osteosarcoma viral oncogene homolog

5

TLR, BCR, TCR, MAPK, JNK, IL

Synthesis of AP-1 transcription factor

IGSF6

771906

immunoglobulin superfamily, mem. 6

14

B and T cells

Membrane receptor of T and B cells

IL20RB

768437

interleukin 20 receptor beta

14

Jak-STAT, IL

T and B cells proliferation and differentiation

IL21R

416586

interleukin 21 receptor

14

Jak-STAT, IL

T and B cells proliferation and differentiation

IL31RA

427140

interleukin 31 receptor A

Z

MAPK, Jak-STAT, IL

MAPKKK cascade, cytokine and chemokine signal transduction, monocyte and macrophage differentiation

IL4R

416585

interleukin 4 receptor

14

T cells, IL

Th2 lymhocyte differentation, cytokine receptor

IL6ST

395684

interleukin 6 signal transducer

Z

IL

Fragment of cytokine receptor complex

IL9R

416587

interleukin 9 receptor

14

Jak-STAT, IL

Jak and STAT activation, cytokine receptor

JAK2

374199

Janus kinase 2

Z

Jak-STAT, IL

Cytokine signalling

LITAF

374125

lipopolysaccharide induced TNF factor

14

TNFα

TNFα expression

MAP2K3

416496

Mitogen activated protein kinase kinase 3

14

MAPK, TLR, JNK, Fc, p38, TNFα, Jak-STAT, TRAIL

MAPKKK cascade

MAP2K4

417312

Mitogen activated protein kinase kinase 4

18

MAPK, TLR, Fas, JNK, Fc, TCR, Jak-STAT, TRAIL

MAP kinase activation, in response to different stimuli, survival signal for T cells

MAP3K1

427144

mitogen activated protein kinase kinase kinase 1

Z

MAPK, TLR, Fas, JNK, Fc, p38, NFκB, TCR, BCR, INFγ, TRAIL, TNFα

Integration of enzyme fosforylation in response to different factors

MAP3K 13

424876

mitogen-activated protein kinase kinase kinase 13

9

MAPK, JNK

Activation of different MAP kinases

MAPK8 IP3

426986

mitogen-activated protein kinase 8 interacting protein 3

14

MAPK, JNK

MAPK and JNK integration

NFKBIA

396093

nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha

5

TLR, BCR, TCR, NFκB

NFκB Inhibitor

PDCD4

374191

programmed cell death 4 (neoplastic transformation inhibitor)

6

JNK

Negative JNK regulation, expression of the gene under control of T cells

RAG2

423165

recombination activating gene 2

5

B and T cells

B and T cells differentiation, gene conversion in Ig

RBP4

396166

retinol binding protein 4, plasma

6

B cells

Activation of Ig secretion

SOCS1

416630

supressor of cytokine sygnalling 1

14

Jak-STAT, IL

Inhibition of cytokine secretion & Jak-STAT cascade

TCF7L2

395508

Transcription factor 7-like 2

6

WNT

WNT signalling

TGFB3

396438

transforming growth factor, beta 3

5

MAPK, TGFβ, GPCR

MAPK activation, growth factor activity

TNFRSF13B

770275

TNF receptor superfamily, member 13B

14

AP-1, NFκB, TNF

Key role in humoral immune response

TRAF6

423163

TNF receptor-associated factor 6

5

TNF, TLR, IL, NFκB, TCR

Signal transduction in many pathways, Th1 immune response, T cell activation

TRAF7

416555

TNF receptor-associated factor 7

14

TNF

MAPKKK cascade activation

Gene symbol, ID and name according to NCBI database; Ch - chromosome number, Metabolic Pathway and Gene Function based on GO and InnateDB.

It can be summarized that these candidate genes encode proteins predicted to play a role in:

(i) Proliferation, differentiation and function of B lymphocytes, e.g. CXCL12, BLNK, IL21R, RBP4, CD59, TNFRSF13B;

(ii) TLR signalling pathway, e.g. TRAF6, FADD, NFκBIA, CARD11, FAS, FGF8, TGFB, IL31RA;

(iii) MAP signalling cascade, e.g. MAP2K3, MAP2K4, MAP3K1, MAP3K13, MAPK8IP3.

Discussion

Immune response is a complicated process; encoded by multiple genes organized within the frames of functional networks rather than pathways and regulated by many interactions. However, prior to modelling the most probable genetic network, the information is needed on the genes that can be taken into account and their physiological function.

As mentioned above, the function of the proposed set of candidate genes was associated with three groups of cellular and physiological processes that can hypothetically affect innate humoral immune response in chicken. Briefly, production of antibodies, including NAbs takes place in B cells, stimulated by Th2 cytokines. Therefore, both B and T cells function is a crucial element in antibody release. CXCL12 gene is responsible for B cells proliferation [8]. CXCL12-/- knockout mice produced drastically reduced number of B cells and died during the perinatal period [9]. In turn, BLNK gene affects B cell development, which was completely inhibited in BLNK-/- knockout mouse [10]. Finally, IL21R and RBP4 genes are responsible for maintenance of mature B cells function. Knocked out mice (both IL21R-/- and RBP4-/-) expressed impaired production of antibodies [11, 12].

TLR signalling pathway is triggered when molecular patterns (such as LPS or LTA) are recognized. Some of the proposed candidate genes are involved in TLR pathway, just to mention TRAF6 and FADD, as well as genes affecting NFκB expression and function, such as NFκBIA, CARD11, TNFRSF13B and FAS[1315]. Furthermore, the analysis in silico pointed out a number of genes that activate MAPK cascade, a key signalling pathway initiated by TLR, for example FGF8, TGFB3 and IL31RA[14]. Additionally, the candidate gene set includes such genes as MAP2K3, MAPK8IP3, MAP3K13, MAP2K4 and MAP3K1, which are the members of MAPK signal transduction pathway [15].

Conclusions

Chicken immune response is one of the major areas recently studied in life science research related to livestock. So far, different approaches have been applied to dissect the genetic bases of avian health traits. Rapid development of technology supporting high-throughput genomic studies provided an excellent tool for fast and efficient genotyping. Still, the accurate gene selection can pose a problem. Therefore, the additional criteria, like validated QTL regions may be of assistance to list the proper genes that can be further on evaluated and contribute to genetic network modelling of humoral immune response in chicken. For that reason we proposed a panel of candidate genes related to the level of LPS, LTA & KLH NAbs in chicken.

Declarations

Acknowledgements

The study supported by the State Committee for Scientific Research (grant no. P 06D 012 30) and by the Integrated Regional Development Programme (grant no. SPS.IV-3040-UE/S05/2009)

This article has been published as part of BMC Proceedings Volume 5 Supplement 4, 2011: Proceedings of the International Symposium on Animal Genomics for Animal Health (AGAH 2010). The full contents of the supplement are available online at http://www.biomedcentral.com/1753-6561/5?issue=S4.

Authors’ Affiliations

(1)
Department of Animal Biotechnology, University of Technology and Life Sciences
(2)
Department of Biological Bases of Animal Production, University of Life Sciences

References

  1. Gauthier-Clerc M, Lebarbenchon C, Thomas F: Recent expansion of highly pathogenic avian influenza H5N1: a critical review. Int. J. Avian Sci. 2007, 149: 201-214.Google Scholar
  2. Parmentier HK, Lammers A, Hoekman JJ, de V Reilingh G, Zaanen ITA, Savelkoul HFJ: Different levels of natural antibodies in chickens divergently selected for specific antibody responses. Dev. Comp. Immunol. 2004, 28: 39-49. 10.1016/S0145-305X(03)00087-9.View ArticlePubMedGoogle Scholar
  3. Siwek M, Buitenhuis B, Cornelissen S, Nieuwland M, Knol EF, Crooijmans R, Groenen M, Parmentier H, van der Poel J: Detection of QTL for innate: non-specific antibody levels binding LPS and LTA in two independent populations of laying hens. Dev. Comp. Immunol. 2006, 30: 659-66. 10.1016/j.dci.2005.09.004.View ArticlePubMedGoogle Scholar
  4. National Center for Biotechnology Information: [http://www.ncbi.nlm.nih.gov]
  5. Kanehisa M, Goto S: KEGG: kyoto encyklopedia of genes and genomes. Nucleic Acids Res. 2000, 28: 27-30. 10.1093/nar/28.1.27.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Lynn DJ, Winsor GL, Chan C, Richard N, Laird MR, Barsky A, Gardy JL, Roche FM, Chan THW, Shah N, Lo R, Naseer M, Que J, Yau M, Acab M, Tulpan D, Whiteside MD, Chikatamarla A, Mah B, Munzner T, Hokamp K, Hancock REW, Brinkman FSL: InnateDB: facilitating systems-level analyses of the mammalian innate immune response. Mol. Syst. Biol. 2008, 4: 218-10.1038/msb.2008.55.PubMed CentralView ArticlePubMedGoogle Scholar
  7. Gene Ontology Consortium: Creating the gene ontology resource: design and implementation. Genome Res. 2001, 11: 1425-33. 10.1101/gr.180801.View ArticleGoogle Scholar
  8. Ma Q, Jones D, Borghesani PR, Segal RA, Nagasawa T, Kishimoto T, Bronson RT, Springer TA: Impaired B-lyphopoiesis, myelopoiesis, and derailed cerebellar neuron migration in CXCR4- and SDF-1-deficient mice. PNAS. 1998, 95: 9448-53. 10.1073/pnas.95.16.9448.PubMed CentralView ArticlePubMedGoogle Scholar
  9. Nagasawa T, Hirota S, Tachibana K, Takakura N, Nishikawa S, Kitamura Y, Yoshida N, Kikutani H, Kishimoto T: Defects of B-cell lymphopoiesis and bone-marrow myelopoiesis in mice lacking the CXC chemokine PBSF/SDF-1. Nature. 1996, 382: 635-8. 10.1038/382635a0.View ArticlePubMedGoogle Scholar
  10. Pappu R, Cheng AM, Li B, Gong Q, Chiu C, Griffin N, White M, Sleckman BP, Chan AC: Requirement for B Cell Linker Protein (BLNK) in B Cell Development. Science. 1999, 286: 1949-54. 10.1126/science.286.5446.1949.View ArticlePubMedGoogle Scholar
  11. Quadro L, Gamble MV, Vogel S, Lima AAM, Piantedosi R, Moore SR, Colantuoni V, Gottesman ME, Guerrant RL, Blaner WS: Retinol and Retinol-Binding Protein. Gut Integrity and Circulating Immunoglobulins. J Infect Dis. 2000, 182 Suppl 1: S97-S102. 10.1086/315920.View ArticlePubMedGoogle Scholar
  12. Ozaki K, Spolski R, Feng CG, Qi CF, Cheng J, Sher A, Morse HC, Liu C, Schwartzberg PL, Leonard WJ: A critical role for IL-21 in regulating immunoglobulin production. Science. 2002, 298: 1630-4. 10.1126/science.1077002.View ArticlePubMedGoogle Scholar
  13. Li X, Stark GR: NFκB-dependent signaling pathway. Exp. Hematol. 2002, 30: 285-96. 10.1016/S0301-472X(02)00777-4.View ArticlePubMedGoogle Scholar
  14. Cormican P, Lloyd AT, Downing T, Connell SJ, Bradley D, O'Farrelly C: The avian Toll-Like receptor pathway--subtle differences amidst general conformity. Dev Comp Immunol. 2009, 33: 967-73. 10.1016/j.dci.2009.04.001.View ArticlePubMedGoogle Scholar
  15. Lynn DJ, Lloyd AT, O'Farrelly C: In silico identification of components of the Toll-like receptor (TLR) signaling pathway in clustered chicken expressed sequence tags (ESTs). Vet Immunol Immunopathol. 2003, 93: 177-84. 10.1016/S0165-2427(03)00058-8.View ArticlePubMedGoogle Scholar
  16. Massagué J: Integration of Smad and MAPK pathways: a link and a linker revisited. Genes Dev. 2003, 17: 2993-7. 10.1101/gad.1167003.View ArticlePubMedGoogle Scholar
  17. Liu Y, Shepherd EG, Nelin LD: MAPK phosphatases-regulating the immune response. Nat. Rev. Immunol. 2007, 7: 202-12. 10.1038/nri2035.View ArticlePubMedGoogle Scholar

Copyright

© Slawinska et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement