Abstract
Despite its critical role in the defense against microbial infection and tumor development, little is known about the range of nucleotide and haplotype variation at IFN-γ, or the evolutionary forces that have shaped patterns of diversity at this locus. To address this gap in knowledge, we examined sequence data from the IFN-γ gene in 1461 individuals from 15 worldwide populations. Our analyses uncovered novel patterns of variation in distinct African populations, including an excess of high frequency-derived alleles, unusually long haplotype structure surrounding the IFN-γ gene, and a “star-like” genealogy of African-specific haplotypes carrying variants previously associated with infectious disease. We also inferred a deep time to coalescence of variation at IFN-γ (~ 0.8 million years ago) and ancient ages for common polymorphisms predating the evolution of modern humans. Taken together, these results are congruent with a model of positive selection on standing variation in African populations. Furthermore, we inferred that common variants in intron 3 of IFN-γ are the likely targets of selection. In addition, we observed a paucity of non-synonymous substitutions relative to synonymous changes in the exons of IFN-γ in African and non-African populations, suggestive of strong purifying selection. Therefore, we contend that positive and purifying selection have influenced levels of diversity in different regions of IFN-γ, implying that these distinct genic regions are, or have been, functionally important. Overall, this study provides additional insights into the evolutionary events that have contributed to the frequency and distribution of alleles having a role in human health and disease.
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References
Schoenborn JR, Wilson CB. Regulation of interferon-gamma during innate and adaptive immune responses. Adv Immunol. 2007;96:41–101.
Newport MJ, Finan C. Genome-wide association studies and susceptibility to infectious diseases. Brief Funct Genom. 2011;10:98–107.
Schroder K, Hertzog PJ, Ravasi T, Hume DA. Interferon-gamma: an overview of signals, mechanisms and functions. J Leukoc Biol. 2004;75:163–89.
Zaidi MR, Merlino G. The two faces of interferon-gamma in cancer. Clin Cancer Res. 2011;17:6118–24.
Chevillard C, Moukoko CE, Elwali NE, Bream JH, Kouriba B, Argiro L, et al. IFN-gamma polymorphisms (IFN-gamma + 2109 and IFN-gamma + 3810) are associated with severe hepatic fibrosis in human hepatic schistosomiasis (Schistosoma mansoni). J Immunol. 2003;171:5596–601.
Gonsky R, Deem RL, Landers CJ, Haritunians T, Yang S, Targan SR. IFNG rs1861494 polymorphism is associated with IBD disease severity and functional changes in both IFNG methylation and protein secretion. Inflamm Bowel Dis. 2014;20:1794–801.
Henri S, Chevillard C, Mergani A, Paris P, Gaudart J, Camilla C, et al. Cytokine regulation of periportal fibrosis in humans infected with Schistosoma mansoni: IFN-gamma is associated with protection against fibrosis and TNF-alpha with aggravation of disease. J Immunol. 2002;169:929–36.
King T, Lamb T. Interferon-gamma: the Jekyll and Hyde of malaria. PLoS Pathog. 2015;11:e1005118.
D’Ombrain MC, Robinson LJ, Stanisic DI, Taraika J, Bernard N, Michon P, et al. Association of early interferon-gamma production with immunity to clinical malaria: a longitudinal study among Papua New Guinean children. Clin Infect Dis. 2008;47:1380–7.
Gun SY, Claser C, Tan KS, Renia L. Interferons and interferon regulatory factors in malaria. Mediat Inflamm. 2014;2014:243713.
Dodoo D, Omer FM, Todd J, Akanmori BD, Koram KA, Riley EM. Absolute levels and ratios of proinflammatory and anti-inflammatory cytokine production in vitro predict clinical immunity to Plasmodium falciparum malaria. J Infect Dis. 2002;185:971–9.
Inoue S, Niikura M, Mineo S, Kobayashi F. Roles of IFN-gamma and gammadelta T cells in protective immunity against blood-stage malaria. Front Immunol. 2013;4:258.
Ansari A, Hasan Z, Dawood G, Hussain R. Differential combination of cytokine and interferon- gamma + 874 T/A polymorphisms determines disease severity in pulmonary tuberculosis. PLoS One. 2011;6:e27848.
Abhimanyu BM, Jha P, Indian Genome Variation C. Footprints of genetic susceptibility to pulmonary tuberculosis: cytokine gene variants in north Indians. Indian J Med Res. 2012;135:763–70.
Lio D, Marino V, Serauto A, Gioia V, Scola L, Crivello A, et al. Genotype frequencies of the + 874T-- > A single nucleotide polymorphism in the first intron of the interferon-gamma gene in a sample of Sicilian patients affected by tuberculosis. Eur J Immunogenet. 2002;29:371–4.
Lee SW, Chuang TY, Huang HH, Lee KF, Chen TT, Kao YH, et al. Interferon gamma polymorphisms associated with susceptibility to tuberculosis in a Han Taiwanese population. J Microbiol Immunol Infect. 2015;48:376–80.
Shen C, Jiao WW, Feng WX, Wu XR, Xiao J, Miao Q, et al. IFNG polymorphisms are associated with tuberculosis in Han Chinese pediatric female population. Mol Biol Rep. 2013;40:5477–82.
Hu Y, Wu L, Li D, Zhao Q, Jiang W, Xu B. Association between cytokine gene polymorphisms and tuberculosis in a Chinese population in Shanghai: a case-control study. BMC Immunol. 2015;16:8.
He J, Wang J, Lei D, Ding S. Analysis of functional SNP in ifng/ifngr1 in Chinese Han population with tuberculosis. Scand J Immunol. 2010;71:452–8.
Sun Y, Lu Y, Li T, Xie L, Deng Y, Li S, et al. Interferon gamma + 874T/A polymorphism increases the risk of hepatitis virus-related diseases: evidence from a meta-analysis. PLoS ONE. 2015;10:e0121168.
Al-Kholy W, Elsaid A, Sleem A, Fathy H, Elshazli R, Settin A. TNF-alpha - 308 G>A and IFN-gamma + 874 A>T gene polymorphisms in Egyptian patients with lupus erythematosus. Meta Gene. 2016;9:137–41.
Kim K, Cho SK, Sestak A, Namjou B, Kang C, Bae SC. Interferon-gamma gene polymorphisms associated with susceptibility to systemic lupus erythematosus. Ann Rheum Dis. 2010;69:1247–50.
Lee YH, Bae SC. Association between interferon-gamma + 874 T/A polymorphism and susceptibility to autoimmune diseases: a meta-analysis. Lupus. 2016;25:710–8.
Ottum PA, Arellano G, Reyes LI, Iruretagoyena M, Naves R. Opposing roles of interferon-gamma on cells of the central nervous system in autoimmune neuroinflammation. Front Immunol. 2015;6:539.
Salih MA, Fakiola M, Abdelraheem MH, Younis BM, Musa AM, ElHassan AM, et al. Insights into the possible role of IFNG and IFNGR1 in Kala-azar and Post Kala-azar Dermal Leishmaniasis in Sudanese patients. BMC Infect Dis. 2014;14:662.
Manry J, Laval G, Patin E, Fornarino S, Tichit M, Bouchier C, et al. Evolutionary genetics evidence of an essential, nonredundant role of the IFN-gamma pathway in protective immunity. Hum Mutat. 2011;32:633–42.
Ko WY, Kaercher KA, Giombini E, Marcatili P, Froment A, Ibrahim M, et al. Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations. Am J Hum Genet. 2011;88:741–54.
Ko WY, Rajan P, Gomez F, Scheinfeldt L, An P, Winkler CA, et al. Identifying Darwinian selection acting on different human APOL1 variants among diverse African populations. Am J Hum Genet. 2013;93:54–66.
Ranciaro A, Campbell MC, Hirbo JB, Ko WY, Froment A, Anagnostou P, et al. Genetic origins of lactase persistence and the spread of pastoralism in Africa. Am J Hum Genet. 2014;94:496–510.
Tishkoff SA, Reed FA, Ranciaro A, Voight BF, Babbitt CC, Silverman JS, et al. Convergent adaptation of human lactase persistence in Africa and Europe. Nat Genet. 2007;39:31–40.
Campbell MC, Ranciaro A, Zinshteyn D, Rawlings-Goss R, Hirbo J, Thompson S, et al. Origin and differential selection of allelic variation at TAS2R16 associated with salicin bitter taste sensitivity in Africa. Mol Biol Evol. 2014;31:288–302.
Crawford NG, Kelly DE, Hansen MEB, Beltrame MH, Fan S, Bowman SL, et al. Loci associated with skin pigmentation identified in African populations. Science. 2017;358:pii: eaan8433.
Bamshad M, Wooding SP. Signatures of natural selection in the human genome. Nat Rev Genet. 2003;4:99–111.
Lewontin RC. The interaction of selection and linkage. I. General considerations; heterotic models. Genetics. 1964;49:49–67.
Fay JC, Wu CI. Hitchhiking under positive Darwinian selection. Genetics. 2000;155:1405–13.
Tajima F, Nei M. Estimation of evolutionary distance between nucleotide sequences. Mol Biol Evol. 1984;1:269–85.
Marth GT, Czabarka E, Murvai J, Sherry ST. The allele frequency spectrum in genome-wide human variation data reveals signals of differential demographic history in three large world populations. Genetics. 2004;166:351–72.
Voight BF, Adams AM, Frisse LA, Qian Y, Hudson RR, Di Rienzo A. Interrogating multiple aspects of variation in a full resequencing data set to infer human population size changes. Proc Natl Acad Sci USA. 2005;102:18508–13.
Cox MP, Morales DA, Woerner AE, Sozanski J, Wall JD, Hammer MF. Autosomal resequence data reveal Late Stone Age signals of population expansion in sub-Saharan African foraging and farming populations. PLoS ONE. 2009;4:e6366.
Hudson RR, Slatkin M, Maddison WP. Estimation of levels of gene flow from DNA sequence data. Genetics. 1992;132:583–9.
Vitti JJ, Grossman SR, Sabeti PC. Detecting natural selection in genomic data. Annu Rev Genet. 2013;47:97–120.
Zhang Z, Li J, Zhao XQ, Wang J, Wong GK, Yu J. KaKs_Calculator: calculating Ka and Ks through model selection and model averaging. Genom Proteom Bioinform. 2006;4:259–63.
McDonald JH, Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 1991;351:652–4.
Oleksyk TK, Smith MW, O’Brien SJ. Genome-wide scans for footprints of natural selection. Philos Trans R Soc Lond B Biol Sci. 2010;365:185–205.
Voight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome. PLoS Biol. 2006;4:e72.
Szpiech ZA, Hernandez RD. selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol Biol Evol. 2014;31:2824–7.
Ma Y, Ding X, Qanbari S, Weigend S, Zhang Q, Simianer H. Properties of different selection signature statistics and a new strategy for combining them. Hered (Edinb). 2015;115:426–36.
Tang K, Thornton KR, Stoneking M. A new approach for using genome scans to detect recent positive selection in the human genome. PLoS Biol. 2007;5:e171.
Campbell MC, Tishkoff SA. African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu Rev Genom Hum Genet. 2008;9:403–33.
Griffiths RC, Tavare S. Ancestral inference in population genetics. Stat. Sci.1994;9:307–319.
Mukherjee S, Sarkar-Roy N, Wagener DK, Majumder PP. Signatures of natural selection are not uniform across genes of innate immune system, but purifying selection is the dominant signature. Proc Natl Acad Sci USA. 2009;106:7073–8.
Kumar A, Ghosh B. A single nucleotide polymorphism (A -- > G) in intron 3 of IFNgamma gene is associated with asthma. Genes Immun. 2008;9:294–301.
Barreiro LB, Quintana-Murci L. From evolutionary genetics to human immunology: how selection shapes host defence genes. Nat Rev Genet. 2010;11:17–30.
Kwiatkowski DP. How malaria has affected the human genome and what human genetics can teach us about malaria. Am J Hum Genet. 2005;77:171–92.
Hughes AL, Verra F. Very large long-term effective population size in the virulent human malaria parasite Plasmodium falciparum. Proc Biol Sci. 2001;268:1855–60.
Tanabe K, Mita T, Jombart T, Eriksson A, Horibe S, Palacpac N, et al. Plasmodium falciparum accompanied the human expansion out of Africa. Curr Biol. 2010;20:1283–9.
Karlsson EK, Kwiatkowski DP, Sabeti PC. Natural selection and infectious disease in human populations. Nat Rev Genet. 2014;15:379–93.
McManus KF, Taravella AM, Henn BM, Bustamante CD, Sikora M, Cornejo OE. Population genetic analysis of the DARC locus (Duffy) reveals adaptation from standing variation associated with malaria resistance in humans. PLoS Genet. 2017;13:e1006560.
Gomez F, Tomas G, Ko WY, Ranciaro A, Froment A, Ibrahim M, et al. Patterns of nucleotide and haplotype diversity at ICAM-1 across global human populations with varying levels of malaria exposure. Hum Genet. 2013;132:987–99.
Sirugo G, Hennig BJ, Adeyemo AA, Matimba A, Newport MJ, Ibrahim ME, et al. Genetic studies of African populations: an overview on disease susceptibility and response to vaccines and therapeutics. Hum Genet. 2008;123:557–98.
Adenowo AF, Oyinloye BE, Ogunyinka BI, Kappo AP. Impact of human schistosomiasis in sub-Saharan Africa. Braz J Infect Dis. 2015;19:196–205.
Al-Salem W, Herricks JR, Hotez PJ. A review of visceral leishmaniasis during the conflict in South Sudan and the consequences for East African countries. Parasit Vectors. 2016;9:460.
Russell SB, Smith JC, Huang M, Trupin JS, Williams SM. Pleiotropic effects of immune responses explain variation in the prevalence of fibroproliferative diseases. PLoS Genet. 2015;11:e1005568.
Manry J, Laval G, Patin E, Fornarino S, Itan Y, Fumagalli M, et al. Evolutionary genetic dissection of human interferons. J Exp Med. 2011;208:2747–59.
Wang Z, Zhong M, Fu M, Dou T, Bian Z. Evidence of positive selection at signal peptide region of interferon gamma. Biosci Biotechnol Biochem. 2014;78:588–92.
Messer PW, Petrov DA. Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol Evol. 2013;28:659–69.
Hermisson J, Pennings PS. Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation. Methods Ecol Evol. 2017;8:700–16.
Kelley JL. Systematic underestimation of the age of selected alleles. Front Genet. 2012;3:165.
Fu W, Akey JM. Selection and adaptation in the human genome. Annu Rev Genom Hum Genet. 2013;14:467–89.
Peter BM, Huerta-Sanchez E, Nielsen R. Distinguishing between selective sweeps from standing variation and from a de novo mutation. PLoS Genet. 2012;8:e1003011.
Barrett RD, Schluter D. Adaptation from standing genetic variation. Trends Ecol Evol. 2008;23:38–44.
Fumagalli M, Sironi M, Pozzoli U, Ferrer-Admetlla A, Pattini L, Nielsen R. Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution. PLoS Genet. 2011;7:e1002355.
Stahl JL, Cook EB, Graziano FM, Barney NP. Differential and cooperative effects of TNFalpha, IL-1beta, and IFNgamma on human conjunctival epithelial cell receptor expression and chemokine release. Invest Ophthalmol Vis Sci. 2003;44:2010–5.
Sironi M, Clerici M. The hygiene hypothesis: an evolutionary perspective. Microbes Infect. 2010;12:421–7.
Vasseur E, Boniotto M, Patin E, Laval G, Quach H, Manry J, et al. The evolutionary landscape of cytosolic microbial sensors in humans. Am J Hum Genet. 2012;91:27–37.
Cagliani R, Sironi M. Pathogen-driven selection in the human genome. Int J Evol Biol. 2013;2013:204240.
Magitta NF, Boe Wolff AS, Johansson S, Skinningsrud B, Lie BA, Myhr KM, et al. A coding polymorphism in NALP1 confers risk for autoimmune Addison’s disease and type 1 diabetes. Genes Immun. 2009;10:120–4.
Jin Y, Mailloux CM, Gowan K, Riccardi SL, LaBerge G, Bennett DC, et al. NALP1 in vitiligo-associated multiple autoimmune disease. N Engl J Med. 2007;356:1216–25.
Raj T, Kuchroo M, Replogle JM, Raychaudhuri S, Stranger BE, De Jager PL. Common risk alleles for inflammatory diseases are targets of recent positive selection. Am J Hum Genet. 2013;92:517–29.
Genomes Project C, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65.
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–8.
Gay J, Myers S, McVean G. Estimating meiotic gene conversion rates from population genetic data. Genetics. 2007;177:881–94.
Librado P, Rozas J. DnaSPv5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25:1451–2.
Bandelt HJ, Forster P, Rohl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16:37–48.
Sabeti PC, Reich DE, Higgins JM, Levine HZ, Richter DJ, Schaffner SF, et al. Detecting recent positive selection in the human genome from haplotype structure. Nature. 2002;419:832–7.
Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–5.
Weir CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38:1358–70.
Acknowledgements
We thank the Center for Computational Biology and Bioinformatics (CCBB) at Howard University for providing cluster computational resources for this project. This work was supported by the Start-up Funds of Howard University to M.C. Campbell.
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Campbell, M.C., Smith, L.T. & Harvey, J. Population genetic evidence for positive and purifying selection acting at the human IFN-γ locus in Africa. Genes Immun 20, 143–157 (2019). https://doi.org/10.1038/s41435-018-0016-1
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DOI: https://doi.org/10.1038/s41435-018-0016-1
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