, Volume 61, Issue 4, pp 303–314 | Cite as

Contrasting evolution of diversity at two disease-associated chicken genes

  • Tim Downing
  • David J. Lynn
  • Sarah Connell
  • Andrew T. Lloyd
  • AK Fazlul Haque Bhuiyan
  • Pradeepa Silva
  • Arifa N. Naqvi
  • Rahamame Sanfo
  • Racine-Samba Sow
  • Baitsi Podisi
  • Cliona O’Farrelly
  • Olivier Hanotte
  • Daniel G. BradleyEmail author
Original Paper


There have been significant evolutionary pressures on the chicken during both its speciation and its subsequent domestication by man. Infectious diseases are expected to have exerted strong selective pressures during these processes. Consequently, it is likely that genes associated with disease susceptibility or resistance have been subject to some form of selection. Two genes involved in the immune response (interferon-γ and interleukin 1-β) were selected for sequencing in diverse chicken populations from Pakistan, Sri Lanka, Bangladesh, Kenya, Senegal, Burkina Faso and Botswana, as well as six outgroup samples (grey, green, red and Ceylon jungle fowl and grey francolin and bamboo partridge). Haplotype frequencies, tests of neutrality, summary statistics, coalescent simulations and phylogenetic analysis by maximum likelihood were used to determine the population genetic characteristics of the genes. Networks indicate that these chicken genes are most closely related to the red jungle fowl. Interferon-γ had lower diversity and considerable coding sequence conservation, which is consistent with its function as a key inflammatory cytokine of the immune response. In contrast, the pleiotropic cytokine interleukin 1-β had higher diversity and showed signals of balancing selection moderated by recombination, yielding high numbers of diverse alleles, possibly reflecting broader functionality and potential roles in more diseases in different environments.


Chicken Interleukin 1 beta Interferon gamma Selection Population genetics 



This work is supported by Government of Ireland Department of Agriculture FIRM grant 04/R + D/D/295. We would like to thank the Department of Ornithology and Mammalogy, Californian Academy of Sciences (San Francisco, USA) and Donal Campion, Wallslough Farm (Co. Kilkenny, Ireland) for bird samples and Karsten Hokamp (Trinity College, University of Dublin) for help in implementing LDhat.

Supplementary material

251_2009_359_MOESM1_ESM.doc (3.4 mb)
Supplementary material 1 (DOC 3.40 MB)


  1. Akey JM, Eberle MA, Rieder MJ, Carlson CS, Shriver MD, Nickerson DA, Kruglyak L (2004) Population history and natural selection shape patterns of genetic variation in 132 genes. PLoS Biol 2(10):e286PubMedCrossRefGoogle Scholar
  2. Anisimova M, Bielawski JP, Yang Z (2001) Accuracy and power of the likelihood ratio test in detecting adaptive molecular evolution. Mol Biol Evol 18:1585–1592PubMedGoogle Scholar
  3. Ardell DH (2004) SCANMS: adjusting for multiple comparisons in sliding window neutrality tests. Bioinformatics 20(12):1986–1988PubMedCrossRefGoogle Scholar
  4. Balkissoon D, Staines K, McCauley J, Wood J, Young J, Kaufman J, Butter C (2007) Low frequency of the Mx allele for viral resistance predates recent intensive selection in domestic chickens. Immunogenetics 59(8):687–691PubMedCrossRefGoogle Scholar
  5. Berlin S, Qu L, Li X, Yang N, Ellegren H (2008) Positive diversifying selection in avian Mx genes. Immunogenetics 60(11):689–697PubMedCrossRefGoogle Scholar
  6. Betrán E, Rozas J, Navarro A, Barbadilla A (1997) The estimation of the number and the length distribution of gene conversion tracts from population DNA sequence data. Genetics 146(1):89–99PubMedGoogle Scholar
  7. Bratt J, Palmblad J (1997) Cytokine-induced neutrophil-mediated injury of human endothelial cells. J Immunol 159(2):912–918PubMedGoogle Scholar
  8. De Nardo D, Masendycz P, Ho S, Cross M, Fleetwood AJ, Reynolds EC, Hamilton JA, Scholz GM (2005) A central role for the Hsp90.Cdc37 molecular chaperone module in interleukin-1 receptor-associated-kinase-dependent signaling by Toll-like receptors. J Biol Chem 280(11):9813–9822PubMedCrossRefGoogle Scholar
  9. Depaulis F, Veuille M (1998) Neutrality tests based on the distribution of haplotypes under an infinite-site model. Mol Biol Evol 15(12):1788–1790PubMedGoogle Scholar
  10. Duret L, Arndt PF (2008) The impact of recombination on nucleotide substitutions in the human genome. PLoS Genet 4(5):e1000071PubMedCrossRefGoogle Scholar
  11. Ellegren H (2005) The avian genome uncovered. Trends Ecol Evol 20(4):180–186PubMedCrossRefGoogle Scholar
  12. Eriksson J, Larson G, Gunnarsson U, Bed’hom B, Tixier-Boichard M, Strömstedt L, Wright D, Jungerius A, Vereijken A, Randi E, Jensen P, Andersson L (2008) Identification of the yellow skin gene reveals a hybrid origin of the domestic chicken. PLoS Genet 4(2):e1000010PubMedCrossRefGoogle Scholar
  13. Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred II. Error probabilities. Genome Res 8(3):186–194PubMedGoogle Scholar
  14. Ewing B, Hillier L, Wendl MC, Green P (1998) Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res 8(3):175–185PubMedGoogle Scholar
  15. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131(2):479–491PubMedGoogle Scholar
  16. Fay JC, Wu CI (2000) Hitchhiking under positive Darwinian selection. Genetics 155(3):1405–1413PubMedGoogle Scholar
  17. Ferrer-Costa C, Gelpi J, Zamakola L, Parraga I, de la Cruz X, Orozco M (2005) PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics 21:3176–3178PubMedCrossRefGoogle Scholar
  18. Fu YX (1997) Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147(2):915–925PubMedGoogle Scholar
  19. Fu YX, Li WH (1993) Statistical tests of neutrality of mutations. Genetics 133(3):693–709PubMedGoogle Scholar
  20. Fumihito A, Miyake T, Sumi S, Takada M, Ohno S, Kondo N (1996) One subspecies of the red junglefowl (Gallus gallus gallus) suffices as the matriarchic ancestor of all domestic breeds. Proc Natl Acad Sci USA 91(26):12505–12509CrossRefGoogle Scholar
  21. Fumihito A, Miyake T, Takada M, Shingu R, Endo T, Gojobori T, Kondo N, Ohno S (1994) Monophyletic origin and unique dispersal patterns of domestic fowls. Proc Natl Acad Sci USA 93(13):6792–67925CrossRefGoogle Scholar
  22. Goetschy JF, Zeller H, Content J, Horisberger MA (1989) Regulation of the interferon-inducible IFI-78K gene, the human equivalent of the murine Mx gene, by interferons, double-stranded RNA, certain cytokines, and viruses. J Virol 63(6):2616–2622PubMedGoogle Scholar
  23. Gordon D, Abajian C, Green P (1998) Consed: a graphical tool for sequence finishing. Genome Res 8(3):195–202PubMedGoogle Scholar
  24. Gyorfy Z, Ohnemus A, Kaspers B, Duda E, Staeheli P (2003) Truncated chicken interleukin-1beta with increased biologic activity. J Interferon Cytokine Res 23(5):223–228PubMedCrossRefGoogle Scholar
  25. Hou ZC, Xu GY, Su Z, Yang N (2007) Purifying selection and positive selection on the myxovirus resistance gene in mammals and chickens. Gene 396(1):188–195PubMedCrossRefGoogle Scholar
  26. Hudson RR (1987) Estimating the recombination parameter of a finite population model without selection. Genet Res 50(3):245–250PubMedGoogle Scholar
  27. Hudson RR (2001) Two-locus sampling distributions and their application. Genetics 159(4):1805–1817PubMedGoogle Scholar
  28. Hudson RR (2002) Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics 18(2):337–338PubMedCrossRefGoogle Scholar
  29. Hudson RR, Kaplan NL (1985) Statistical properties of the number of recombination events in the history of a sample of DNA sequences. Genetics 111(1):147–164PubMedGoogle Scholar
  30. Hughes AL, Packer B, Welch R, Chanock SJ, Yeager M (2005) High level of functional polymorphism indicates a unique role of natural selection at human immune system loci. Immunogenetics 57(11):821–827PubMedCrossRefGoogle Scholar
  31. International Chicken Genome Sequencing Consortium (2004a) Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature 432:695–716CrossRefGoogle Scholar
  32. International Chicken Polymorphism Map Consortium (2004b) A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms. Nature 432:717–722CrossRefGoogle Scholar
  33. Janardhana V, Ford ME, Bruce MP, Broadway MM, O’Neil TE, Karpala AJ, Asif M, Browning GF, Tivendale KA, Noormohammadi AH, Lowenthal JW, Bean AG (2007) IFN-gamma enhances immune responses to E. coli infection in the chicken. J Interferon Cytokine Res 27(11):937–946PubMedCrossRefGoogle Scholar
  34. Jensen JD, Wong A, Aquadro CF (2007) Approaches for identifying targets of positive selection. Trends Genet 23(11):568–577PubMedCrossRefGoogle Scholar
  35. Johnson PL, Slatkin M (2005) Inference of population genetic parameters in metagenomics: a clean look at messy data. Genome Res 16(10):1320–1327CrossRefGoogle Scholar
  36. Kaiser P (2007) The avian immune genome—a glass half-full or half-empty? Cytogenet Genome Res 117:221–230PubMedCrossRefGoogle Scholar
  37. Kaiser P, Rothwell L, Goodchild M, Bumstead N (2004) The chicken proinflammatory cytokines interleukin-1beta and interleukin-6: differences in gene structure and genetic location compared with their mammalian orthologues. Anim Genet 35(3):169–175PubMedCrossRefGoogle Scholar
  38. Kaiser VB, van Tuinen M, Ellegren H (2007) Insertion events of CR1 retrotransposable elements elucidate the phylogenetic branching order in galliform birds. Mol Biol Evol 24(1):338–347PubMedCrossRefGoogle Scholar
  39. Kanginakudru S, Metta M, Jakati RD, Nagaraju J (2008) Genetic evidence from Indian red jungle fowl corroborates multiple domestication of modern day chicken. BMC Evol Biol 8:174PubMedCrossRefGoogle Scholar
  40. Kelly JK (1997) A test of neutrality based on interlocus associations. Genetics 146(3):1197–1206PubMedGoogle Scholar
  41. Kim H, Schmidt CJ, Decker KS, Emara MG (2003) A double-screening method to identify reliable candidate non-synonymous SNPs from chicken EST data. Anim Genet 34(4):249–254PubMedCrossRefGoogle Scholar
  42. Kogut MH, Rothwell L, Kaiser P (2005a) IFN-gamma priming of chicken heterophils upregulates the expression of proinflammatory and Th1 cytokine mRNA following receptor-mediated phagocytosis of Salmonella enterica serovar enteritidis. J Interferon Cytokine Res 25(2):73–81PubMedCrossRefGoogle Scholar
  43. Kogut MH, He H, Kaiser P (2005b) Lipopolysaccharide binding protein/CD14/ TLR4-dependent recognition of salmonella LPS induces the functional activation of chicken heterophils and up-regulation of pro-inflammatory cytokine and chemokine gene expression in these cells. Anim Biotechnol 16(2):165–181PubMedCrossRefGoogle Scholar
  44. Kogut MH, Swaggerty C, He H, Pevzner I, Kaiser P (2006) Toll-like receptor agonists stimulate differential functional activation and cytokine and chemokine gene expression in heterophils isolated from chickens with differential innate responses. Microbes Infect 8(7):1866–1874PubMedCrossRefGoogle Scholar
  45. Lee BT, Tan TW, Ranganathan S (2003) MGAlignIt: a web service for the alignment of mRNA/EST and genomic sequences. Nucleic Acids Res 31(13):3533–3536PubMedCrossRefGoogle Scholar
  46. Li XY, Qu LJ, Yao JF, Yang N (2006) Skewed allele frequencies of an Mx gene mutation with potential resistance to avian influenza virus in different chicken populations. Poult Sci 85(7):1327–1329PubMedGoogle Scholar
  47. Liu YP, Wu GS, Yao YG, Miao YW, Luikart G, Baig M, Beja-Pereira A, Ding ZL, Palanichamy MG, Zhang YP (2006) Multiple maternal origins of chickens: out of the Asian jungles. Mol Phylogenet Evol 38(1):12–19PubMedCrossRefGoogle Scholar
  48. Long JE, Huang LN, Qin ZQ, Wang WY, Qu D (2004) IFN-gamma increases efficiency of DNA vaccine in protecting ducks against infection. World J Gastroenterol 11(32):4967–4973Google Scholar
  49. Madge LA, Pober JS (2000) A phosphatidylinositol 3-kinase/Akt pathway, activated by tumor necrosis factor or interleukin-1, inhibits apoptosis but does not activate NFkappaB in human endothelial cells. J Biol Chem 275(20):15458–15465PubMedCrossRefGoogle Scholar
  50. McVean G, Awadalla P, Fearnhead P (2002) A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160(3):1231–1241PubMedGoogle Scholar
  51. Ng PC, Henikoff S (2003) SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res 31(13):3812–3814PubMedCrossRefGoogle Scholar
  52. Nickerson DA, Tobe VO, Taylor SL (1997) PolyPhred: automating the detection and genotyping of single nucleotide substitutions using fluorescence-based resequencing. Nucleic Acids Res 25(14):2745–2751PubMedCrossRefGoogle Scholar
  53. Nielsen R, Yang Z (1998) Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics 148:929–936PubMedGoogle Scholar
  54. Nishibori M, Shimogiri T, Hayashi T, Yasue H (2005) Molecular evidence for hybridization of species in the genus Gallus except for Gallus varius. Anim Genet 36(5):367–375PubMedCrossRefGoogle Scholar
  55. Notredame C, Higgins DG, Heringa J (2000) T-Coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 302(1):205–217PubMedCrossRefGoogle Scholar
  56. Okamura M, Lillehoj HS, Raybourne RB, Babu US, Heckert RA (2004) Cell-mediated immune responses to a killed Salmonella enteritidis vaccine: lymphocyte proliferation, T-cell changes and interleukin-6 (IL-6), IL-1, IL-2, and IFN-gamma production. Comp Immunol Microbiol Infect Dis 27(4):255–272PubMedCrossRefGoogle Scholar
  57. Quesada H, Ramirez UE, Rozas J, Aguade M (2006) Large-scale adaptive hitchhiking upon high recombination in Drosophila simulans. Genetics 165(2):895–900Google Scholar
  58. Ramensky V, Bork P, Sunyaev S (2002) Human non-synonymous SNPs: server and survey. Nucleic Acids Res 30(17):3894–900PubMedCrossRefGoogle Scholar
  59. Ronald J, Akey JM (2005) Genome-wide scans for loci under selection in humans. Hum Genomics 2(2):113–125PubMedGoogle Scholar
  60. Rozas J, Rozas R (1999) DnaSP version 3: an integrated program for molecular population genetics and molecular evolution analysis. Bioinformatics 15(2):174–175PubMedCrossRefGoogle Scholar
  61. Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19(18):2496–2497PubMedCrossRefGoogle Scholar
  62. Sadeyen JR, Trotereau J, Velge P, Marly J, Beaumont C, Barrow PA, Bumstead N, Lalmanach AC (2004) Salmonella carrier state in chicken: comparison of expression of immune response genes between susceptible and resistant animals. Microbes Infect 6(14):1278–1286PubMedCrossRefGoogle Scholar
  63. Schneider S, Roessli D, Excoffier L (2000) Arlequin: a software for population genetics data analysis, ver 2.000. Genetics and Biometry Lab, Department of Anthropology, University of GenevaGoogle Scholar
  64. Schoenborn JR, Wilson CB (2007) Regulation of interferon-gamma during innate and adaptive immune responses. Adv Immunol 96:41–101PubMedCrossRefGoogle Scholar
  65. Schaffner SF, Foo C, Gabriel S, Reich D, Daly MJ, Altshuler D (2005) Calibrating a coalescent simulation of human genome sequence variation. Genome Res 15(11):1576–1583PubMedCrossRefGoogle Scholar
  66. Simon A, Fäh J, Haller O, Staeheli P (1991) Interferon-regulated Mx genes are not responsive to interleukin-1, tumor necrosis factor, and other cytokines. J Virol 65(2):968–971PubMedGoogle Scholar
  67. Smith CK, Kaiser P, Rothwell L, Humphrey T, Barrow PA, Jones MA (2004) Campylobacter jejuni-induced cytokine responses in avian cells. Infect Immun 73(4):2094–2100CrossRefGoogle Scholar
  68. Spangelo BL, Farrimond DD, Pompilius M, Bowman KL (2000) Interleukin-1 beta and thymic peptide regulation of pituitary and glial cell cytokine expression and cellular proliferation. Ann N Y Acad Sci 917:597–607PubMedCrossRefGoogle Scholar
  69. Stephens M, Sloan JS, Robertson PD, Scheet P, Nickerson DA (2006) Automating sequence-based detection and genotyping of SNPs from diploid samples. Nat Genet. 38(3):375–381PubMedCrossRefGoogle Scholar
  70. Stephens M, Smith N, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989PubMedCrossRefGoogle Scholar
  71. Tajima F (1983) Evolutionary relationship of DNA sequences in finite populations. Genetics 105(2):437–460PubMedGoogle Scholar
  72. Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123(3):585–595PubMedGoogle Scholar
  73. Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24(8):1596–1599PubMedCrossRefGoogle Scholar
  74. Watterson GA (1975) On the number of segregation sites. Theor Popul Biol 7:256–276PubMedCrossRefGoogle Scholar
  75. Weining KC, Sick C, Kaspers B, Staeheli P (1998) A chicken homolog of mammalian interleukin-1 beta: cDNA cloning and purification of active recombinant protein. Eur J Biochem 258(3):994–1000PubMedCrossRefGoogle Scholar
  76. West B, Zhou BX (1989) Did chickens go north? New evidence for domestication. World’s Poult Sci J 45(3):205–218CrossRefGoogle Scholar
  77. Worley K, Gillingham M, Jensen P, Kennedy LJ, Pizzari T, Kaufman J, Richardson DS (2008) Single locus typing of MHC class I and class II B loci in a population of red jungle fowl. Immunogenetics 60(5):233–247PubMedCrossRefGoogle Scholar
  78. Yang Z (1997) PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci 13:555–556PubMedGoogle Scholar
  79. Yang Z (2002) Inference of selection from multiple species alignments. Curr Opin Genet Dev 12:688–694PubMedCrossRefGoogle Scholar
  80. Yang Z, Lu Z, Wang A (2001) Study of adaptive mutations in Salmonella typhimurium by using a super-repressing mutant of a trans regulatory gene purR. Mutat Res 484(1–2):95–102PubMedGoogle Scholar
  81. Ye X, Avendano S, Dekkers JC, Lamont SJ (2006) Association of twelve immune-related genes with performance of three broiler lines in two different hygiene environments. Poult Sci 85(9):1555–1569PubMedGoogle Scholar
  82. Zhou H, Buitenhuis AJ, Weigend S, Lamont SJ (2001) Candidate gene promoter polymorphisms and antibody response kinetics in chickens: interferon-gamma, interleukin-2, and immunoglobulin light chain. Poult Sci 80(12):1679–1689PubMedGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Tim Downing
    • 1
  • David J. Lynn
    • 2
  • Sarah Connell
    • 1
  • Andrew T. Lloyd
    • 3
  • AK Fazlul Haque Bhuiyan
    • 4
  • Pradeepa Silva
    • 5
  • Arifa N. Naqvi
    • 6
  • Rahamame Sanfo
    • 7
  • Racine-Samba Sow
    • 8
  • Baitsi Podisi
    • 9
  • Cliona O’Farrelly
    • 3
  • Olivier Hanotte
    • 10
  • Daniel G. Bradley
    • 1
    Email author
  1. 1.Smurfit Institute of Genetics, Trinity CollegeUniversity of DublinDublinIreland
  2. 2.Department of Molecular Biology and BiochemistrySimon Fraser UniversityBritish ColumbiaCanada
  3. 3.School of Biochemistry and Immunology, Trinity CollegeUniversity of DublinDublinIreland
  4. 4.Bangladesh Agricultural UniversityMymensinghBangladesh
  5. 5.University of PeradeniyaPeradeniyaSri Lanka
  6. 6.PARCIslamabadPakistan
  7. 7.INERAOuagadougouBurkina Faso
  8. 8.ISRADakarSenegal
  9. 9.Department of Agricultural ResearchGaboroneBotswana
  10. 10.International Livestock Research InstituteNairobiKenya

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