Abstract
The shift from a hunter-gatherer to an agricultural mode of subsistence is believed to have been associated with profound changes in the burden and diversity of pathogens across human populations. Yet, the extent to which the advent of agriculture affected the evolution of the human immune system remains unknown. Here we present a comparative study of variation in the transcriptional responses of peripheral blood mononuclear cells to bacterial and viral stimuli between Batwa rainforest hunter-gatherers and Bakiga agriculturalists from Uganda. We observed increased divergence between hunter-gatherers and agriculturalists in the early transcriptional response to viruses compared with that for bacterial stimuli. We demonstrate that a significant fraction of these transcriptional differences are under genetic control and we show that positive natural selection has helped to shape population differences in immune regulation. Across the set of genetic variants underlying inter-population immune-response differences, however, the signatures of positive selection were disproportionately observed in the rainforest hunter-gatherers. This result is counter to expectations on the basis of the popularized notion that shifts in pathogen exposure due to the advent of agriculture imposed radically heightened selective pressures in agriculturalist populations.
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Data availability
The data that support the findings of this study are available at https://zenodo.org/record/2656662#.XMyCSi3MzOQ.
Code availability
All scripts required to run the analyses described in the manuscript can be found at https://github.com/GFHarrison/Natural-Selection-HG-and-AG-2019.
References
Diamond, J. & Bellwood, P. Farmers and their languages: the first expansions. Science 300, 597–603 (2003).
Greger, M. The human/animal interface: emergence and resurgence of zoonotic infectious diseases. Crit. Rev. Microbiol. 33, 243–299 (2007).
Pearce-Duvet, J. M. The origin of human pathogens: evaluating the role of agriculture and domestic animals in the evolution of human disease. Biol. Rev. Camb. Phil. Soc. 81, 369–382 (2006).
Wolfe, N. D., Dunavan, C. P. & Diamond, J. Origins of major human infectious diseases. Nature 447, 279–283 (2007).
Gignoux, C. R., Henn, B. M. & Mountain, J. L. Rapid, global demographic expansions after the origins of agriculture. Proc. Natl Acad. Sci. USA 108, 6044–6049 (2011).
Page, A. E. et al. Reproductive trade-offs in extant hunter-gatherers suggest adaptive mechanism for the Neolithic expansion. Proc. Natl Acad. Sci. USA 113, 4694–4699 (2016).
Black, F. L. Measles endemicity in insular populations: critical community size and its evolutionary implication. J. Theor. Biol. 11, 207–211 (1966).
Anderson, R. M. & May, R. M. Infectious Diseases of Humans: Dynamics and Control (Oxford Univ. Press, 1992).
Furuse, Y., Suzuki, A. & Oshitani, H. Origin of measles virus: divergence from rinderpest virus between the 11th and 12th centuries. Virol. J. 7, 52 (2010).
Matthijnssens, J. et al. Full genome-based classification of rotaviruses reveals a common origin between human Wa-Like and porcine rotavirus strains and human DS-1-like and bovine rotavirus strains. J. Virol. 82, 3204–3219 (2008).
Suzuki, Y. & Nei, M. Origin and evolution of influenza virus hemagglutinin genes. Mol. Biol. Evol. 19, 501–509 (2002).
Sundararaman, S. A. et al. Genomes of cryptic chimpanzee Plasmodium species reveal key evolutionary events leading to human malaria. Nat. Commun. 7, 11078 (2016).
Otto, T. D. et al. Genomes of all known members of a Plasmodium subgenus reveal paths to virulent human malaria. Nat. Microbiol. 3, 687-697 (2018).
Dounias, E. & Froment, A. When forest-based hunter-gatherers become sedentary: consequences for diet and health. UNASYLVA-FAO 57, 26-33 (2006).
Barreiro, L. B. & Quintana-Murci, L. From evolutionary genetics to human immunology: how selection shapes host defence genes. Nat. Rev. Genet. 11, 17-30 (2010).
Karlsson, E. K., Kwiatkowski, D. P. & Sabeti, P. C. Natural selection and infectious disease in human populations. Nat. Rev. Genet. 15, 379-393 (2014).
Perry, G. H. et al. Adaptive, convergent origins of the pygmy phenotype in African rainforest hunter-gatherers. Proc. Natl Acad. Sci. USA 111, E3596–E3603 (2014).
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).
Xu, G. J. et al. Comprehensive serological profiling of human populations using a synthetic human virome. Science 348, aaa0698 (2015).
McGeoch, D. & Davison, A. J. in Origin and Evolution of Viruses (eds Domingo, E., Webster, R. & Holland, J.) Ch. 17 (Academic Press, 1999).
McGeoch, D. J., Dolan, A. & Ralph, A. C. Toward a comprehensive phylogeny for mammalian and avian herpesviruses. J. Virol. 74, 10401–10406 (2000).
Van Blerkom, L. M. Role of viruses in human evolution. Am. J. Phys. Anthropol. 122, 14–46 (2003).
Barreiro, L. B. et al. Deciphering the genetic architecture of variation in the immune response to Mycobacterium tuberculosis infection. Proc. Natl Acad. Sci. USA 109, 1204–1209 (2012).
Fairfax, B. P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).
Nédélec, Y. et al. Genetic ancestry and natural selection drive population differences in immune responses to pathogens. Cell 167, 657–669 (2016).
Quach, H. et al. Genetic adaptation and neandertal admixture shaped the immune system of human populations. Cell 167, 643–656 (2016).
Yi, X. et al. Sequencing of 50 human exomes reveals adaptation to high altitude. Science 329, 75–78 (2010).
Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).
Patin, E. et al. The impact of agricultural emergence on the genetic history of African rainforest hunter-gatherers and agriculturalists. Nat. Commun. 5, 3163 (2014).
Lopez, M. et al. The demographic history and mutational load of African hunter-gatherers and farmers. Nat. Ecol. Evol. 2, 721-730 (2018).
Enard, D., Cai, L., Gwennap, C. & Petrov, D. A. Viruses are a dominant driver of protein adaptation in mammals. eLife 5, e12469 (2016).
Enard, D. & Petrov, D. A. RNA viruses drove adaptive introgressions between Neanderthals and modern humans. Preprint at bioRxiv https://doi.org/10.1101/120477 (2017).
Gonzalez, J. P., Nakoune, E., Slenczka, W., Vidal, P. & Morvan, J. M. Ebola and Marburg virus antibody prevalence in selected populations of the Central African Republic. Microbes Infect. 2, 39–44 (2000).
Johnson, E., Gonzalez, J.-P. & Georges, A. Filovirus activity among selected ethnic groups inhabiting the tropical forest of equatorial Africa. Trans. R. Soc. Trop. Med. Hyg. 87, 536–538 (1993).
Prezeworski, M., Coop, G. & Wall, J. D. The signature of positive selection on standing genetic variation. Evolution 59, 2312–2323 (2005).
Mellars, P. Why did modern human populations disperse from Africa ca. 60,000 years ago? A new model. Proc. Natl Acad. Sci. USA 103, 9381–9386 (2006).
Verdu, P. et al. Origins and genetic diversity of pygmy hunter-gatherers from Western Central Africa. Curr. Biol. 19, 312–318 (2009).
Storey, J. D. & Tibshirani, R. in Functional Genomics (eds Brownstein, M. J. and Kohdursky, A. B.) 149–157 (Springer, 2003).
Howie, B. N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).
Snyder-Mackler, N. et al. Social status alters immune regulation and response to infection in macaques. Science 354, 1041–1045 (2016).
Sams, A. J. et al. Adaptively introgressed Neandertal haplotype at the OAS locus functionally impacts innate immune responses in humans. Genome Biol. 17, 246–261 (2016).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Anders, S. et al. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor. Nat. Protoc. 8, 1765–1786 (2013).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47–e47 (2015).
Piasecka, B. et al. Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges. Proc. Natl Acad. Sci. USA 115, E488–E497 (2018).
Guo, Y., Zhao, S., Li, C.-I., Sheng, Q. & Shyr, Y. RNAseqPS: a web tool for estimating sample size and power for RNAseq experiment. Cancer Inform. 13, 1–5 (2014).
Bindea, G. et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25, 1091–1093 (2009).
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
Shabalin, A. A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).
Lindeman, R. H., Merenda, P. F. & Gold, R. Z. Introduction to Bivariate and Multivariate Analysis (Scott, Foresman and Co, 1980).
Grömping, U. Relative importance for linear regression in R: the package relaimpo. J. Stat. Softw. 17, 1–27 (2006).
Jeffrey, C. Genome-wide association study and meta-analysis finds over 40 loci affect risk of type 1 diabetes. Nat. Genet. 41, 703–707 (2009).
Szpiech, Z. A. & Hernandez, R. D. selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol. Biol. Evol. 31, 2824–2827 (2014).
Acknowledgements
The authors thank the Batwa and Bakiga communities and all individuals who participated in this study; also the Batwa Development Program, J. Byaruhanga, M. Magambo, P. Byamugisha, S. Twesigomwe, J. Safari and L. Busingye for expert assistance during the sample collection process in Uganda. We thank S. Nanyunja for technical laboratory assistance. We thank J. Tung and L.B.B. laboratory members for critical reading of the manuscript. We thank Calcul Québec and Compute Canada for providing access to the supercomputer Briaree from the University of Montreal. This work was supported by NIH R01-GM115656 to G.H.P and L.B.B., a fellowship from the Réseau de Médecine Génétique Appliquée and the Fonds de Recherche du Québec−Santé to G.F.H, and 1 F32 GM125228-638 01A1 to C.M.B. RNA-seq data have been deposited in Gene Expression Omnibus (accession number GSE120502). The 1M SNP genotype data are available at the European Genome–Phenome archive, www.ebi.ac.uk/ega/ (accession numbers EGAS00001000605 and EGAS00001000908).
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Contributions
L.B.B. and G.H.P conceived and coordinated the study, and performed field work in Uganda. S.L.N facilitated samples collection. J.B., A.D. and V.Y. performed cell culture experiments. G.F.H. and J.S. conducted most data analysis, with support from F.C.G. and C.M.B and input from co-authors. M.J.M, Y.L. and S.J.E. generated VirScan data. E.S. and L.Q.M. contributed to data generation. G.F.H, L.B.B. and G.H.P. wrote the paper with input from all co-authors.
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Supplementary information
Supplementary Figures
Supplementary Figs. 1–11.
Supplementary Table 1
Metadata for samples used in the study.
Supplementary Table 2
Results for identifying PopDE and PopDR genes.
Supplementary Table 3
Results from GSEA for popDE and PopDR genes.
Supplementary Table 4
Results from VirScan analysis.
Supplementary Table 5
Results from mapping of cis-eQTL.
Supplementary Table 6
Delta-PVE among PopDE genes.
Supplementary Table 7
Selection statistics for SNPs that are mapped cis-eQTL.
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Harrison, G.F., Sanz, J., Boulais, J. et al. Natural selection contributed to immunological differences between hunter-gatherers and agriculturalists. Nat Ecol Evol 3, 1253–1264 (2019). https://doi.org/10.1038/s41559-019-0947-6
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DOI: https://doi.org/10.1038/s41559-019-0947-6
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