A general linear model-based approach for inferring selection to climate

BMC Genetics

William Amos³  Toomas Kivisild¹  Irene Gallego Romero²  Luca Pagani¹  Srilakshmi M Raj⁴ 

[1]Department of Biological Anthropology, Henry Wellcome Building, University of Cambridge, Fitzwilliam Street, Cambridge, UK

[2]Department of Human Genetics, University of Chicago, Chicago, IL, USA

[3]Department of Zoology, University of Cambridge, Cambridge, UK

[4]Present address: Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA

关键词: Population genetics;    Environmental adaptation;    Natural selection;    Human evolution;    Adaptation;    Climate;   

Others  :  1086658
DOI  :  10.1186/1471-2156-14-87

 received in 2013-02-27, accepted in 2013-09-11,  发布年份 2013

【 摘 要 】

Background

Many efforts have been made to detect signatures of positive selection in the human genome, especially those associated with expansion from Africa and subsequent colonization of all other continents. However, most approaches have not directly probed the relationship between the environment and patterns of variation among humans. We have designed a method to identify regions of the genome under selection based on Mantel tests conducted within a general linear model framework, which we call MAntel-GLM to Infer Clinal Selection (MAGICS). MAGICS explicitly incorporates population-specific and genome-wide patterns of background variation as well as information from environmental values to provide an improved picture of selection and its underlying causes in human populations.

Results

Our results significantly overlap with those obtained by other published methodologies, but MAGICS has several advantages. These include improvements that: limit false positives by reducing the number of independent tests conducted and by correcting for geographic distance, which we found to be a major contributor to selection signals; yield absolute rather than relative estimates of significance; identify specific geographic regions linked most strongly to particular signals of selection; and detect recent balancing as well as directional selection.

Conclusions

We find evidence of selection associated with climate (P < 10^-5) in 354 genes, and among these observe a highly significant enrichment for directional positive selection. Two of our strongest 'hits’, however, ADRA2A and ADRA2C, implicated in vasoconstriction in response to cold and pain stimuli, show evidence of balancing selection. Our results clearly demonstrate evidence of climate-related signals of directional and balancing selection.

【 授权许可】

   
2013 Raj et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]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(11):e1002355.
• [2]Coop G, Pickrell JK, Novembre J, Kudaravalli S, Li J, Absher D, Myers RM, Cavalli-Sforza LL, Feldman MW, Pritchard JK: The role of geography in human adaptation. PLoS Genet 2009, 5(6):e1000500.
• [3]Wells JC, Stock JT: The biology of the colonizing ape. Am J Phys Anthropol 2007, Suppl 45:191-222.
• [4]Allen JA: The influence of physical conditions in the genesis of species. Radic Rev 1877, 1:108-140.
• [5]Bergmann C: Über die Verhältnisse der wärmeökonomie der Thiere zu ihrer Grösse. Göttinger Studien 1847, 3:595-708.
• [6]Ruff CB: Morphological adaptation to climate in modern and fossil hominids. Am J Phys Anthropol 1994, 37:65-107.
• [7]Jablonski NG, Chaplin G: The evolution of human skin coloration. J Hum Evol 2000, 39(1):57-106.
• [8]Leonard WR, Snodgrass JJ, Sorensen MV: Metabolic adaptation in indigenous siberian populations. Annu Rev Anthropol 2005, 34:451-471.
• [9]Auton A, Bryc K, Boyko AR, Lohmueller KE, Novembre J, Reynolds A, Indap A, Wright MH, Degenhardt JD, Gutenkunst RN, et al.: Global distribution of genomic diversity underscores rich complex history of continental human populations. Genome Res 2009, 19(5):795-803.
• [10]Voight BF, Kudaravalli S, Wen X, Pritchard JK: A map of recent positive selection in the human genome. PLoS Biol 2006, 4(3):e72.
• [11]Sabeti PC, Reich DE, Higgins JM, Levine HZ, Richter DJ, Schaffner SF, Gabriel SB, Platko JV, Patterson NJ, McDonald GJ, et al.: Detecting recent positive selection in the human genome from haplotype structure. Nature 2002, 419(6909):832-837.
• [12]Sabeti PC, Varilly P, Fry B, Lohmueller J, Hostetter E, Cotsapas C, Xie X, Byrne EH, McCarroll SA, Gaudet R, et al.: Genome-wide detection and characterization of positive selection in human populations. Nature 2007, 449(7164):913-918.
• [13]Pickrell JK, Coop G, Novembre J, Kudaravalli S, Li JZ, Absher D, Srinivasan BS, Barsh GS, Myers RM, Feldman MW, et al.: Signals of recent positive selection in a worldwide sample of human populations. Genome Res 2009, 19(5):826-837.
• [14]Xue Y, Zhang X, Huang N, Daly A, Gillson CJ, Macarthur DG, Yngvadottir B, Nica AC, Woodwark C, Chen Y, et al.: Population differentiation as an indicator of recent positive selection in humans: an empirical evaluation. Genetics 2009, 183(3):1065-1077.
• [15]Akey JM: Constructing genomic maps of positive selection in humans: where do we go from here? Genome Res 2009, 19(5):711-722.
• [16]Beckman G, Birgander R, Sjalander A, Saha N, Holmberg PA, Kivela A, Beckman L: Is p53 polymorphism maintained by natural selection? Hum Hered 1994, 44(5):266-270.
• [17]Cavalli-Sforza LL, Menozzi P, Piazza P: The history and geography of human genes. Princeton, NJ: Princeton University Press; 1994.
• [18]Young JH, Chang YP, Kim JD, Chretien JP, Klag MJ, Levine MA, Ruff CB, Wang NY, Chakravarti A: Differential susceptibility to hypertension is due to selection during the out-of-africa expansion. PLoS Genet 2005, 1(6):e82.
• [19]Prugnolle F, Manica A, Charpentier M, Guegan JF, Guernier V, Balloux F: Pathogen-driven selection and worldwide HLA class I diversity. Curr Biol 2005, 15(11):1022-1027.
• [20]Hancock AM, Alkorta-Aranburu G, Witonsky DB, Di Rienzo A: Adaptations to new environments in humans: the role of subtle allele frequency shifts. Philos Trans R Soc Lond B Biol Sci 2010, 365(1552):2459-2468.
• [21]Hancock AM, Witonsky DB, Alkorta-Aranburu G, Beall CM, Gebremedhin A, Sukernik R, Utermann G, Pritchard JK, Coop G, Di Rienzo A: Adaptations to climate-mediated selective pressures in humans. PLoS Genet 2011, 7(4):e1001375.
• [22]Hancock AM, Witonsky DB, Ehler E, Alkorta-Aranburu G, Beall C, Gebremedhin A, Sukernik R, Utermann G, Pritchard J, Coop G, et al.: Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency. Proc Natl Acad Sci U S A 2010, 107(Suppl 2):8924-8930.
• [23]Hancock AM, Witonsky DB, Gordon AS, Eshel G, Pritchard JK, Coop G, Di Rienzo A: Adaptations to climate in candidate genes for common metabolic disorders. PLoS Genet 2008, 4(2):e32.
• [24]Coop G, Witonsky D, Di Rienzo A, Pritchard JK: Using environmental correlations to identify loci underlying local adaptation. Genetics 2010, 185(4):1411-1423.
• [25]Prugnolle F, Manica A, Balloux F: Geography predicts neutral genetic diversity of human populations. Curr Biol 2005, 15(5):R159-R160.
• [26]Scherer S: Guide to the human genome. Woodbury, NY: Cold Spring Harbor Laboratory Press; 2011.
• [27]Clark AG, Hubisz MJ, Bustamante CD, Williamson SH, Nielsen R: Ascertainment bias in studies of human genome-wide polymorphism. Genome Res 2005, 15(11):1496-1502.
• [28]Albrechtsen A, Nielsen FC, Nielsen R: Ascertainment biases in SNP chips affect measures of population divergence. Mol Biol Evol 2010, 27(11):2534-2547.
• [29]Barrett JC: Haploview: visualization and analysis of SNP genotype data. Cold Spring Harb Protoc 2009, 2009(10):pdb ip71.
• [30]Amos W, Bryant C: Using human demographic history to infer natural selection reveals contrasting patterns on different families of immune genes. Proc Biol Sci 2011, 278(1711):1587-1594.
• [31]Ramachandran S, Deshpande O, Roseman CC, Rosenberg NA, Feldman MW, Cavalli-Sforza LL: Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa. Proc Natl Acad Sci U S A 2005, 102(44):15942-15947.
• [32]Betti L, Balloux F, Amos W, Hanihara T, Manica A: Distance from Africa, not climate, explains within-population phenotypic diversity in humans. Proc Biol Sci 2009, 276(1658):809-814.
• [33]Liu H, Prugnolle F, Manica A, Balloux F: A geographically explicit genetic model of worldwide human-settlement history. Am J Hum Genet 2006, 79(2):230-237.
• [34]Manica A, Amos W, Balloux F, Hanihara T: The effect of ancient population bottlenecks on human phenotypic variation. Nature 2007, 448(7151):346-348.
• [35]Amos W, Flint J, Xu X: Heterozygosity increases microsatellite mutation rate, linking it to demographic history. BMC Genet 2008, 9:72.
• [36]Huffmeier U, Lascorz J, Traupe H, Bohm B, Schurmeier-Horst F, Stander M, Kelsch R, Baumann C, Kuster W, Burkhardt H, et al.: Systematic linkage disequilibrium analysis of SLC12A8 at PSORS5 confirms a role in susceptibility to psoriasis vulgaris. J Invest Dermatol 2005, 125(5):906-912.
• [37]Leonard WR, Sorensen MV, Galloway VA, Spencer GJ, Mosher MJ, Osipova LP, Spitsyn VA: Climatic influences on basal metabolic rates among circumpolar populations. Am J Hum Biol 2002, 14:609-620.
• [38]Grossman SR, Shylakhter I, Karlsson EK, Byrne EH, Morales S, Frieden G, Hostetter E, Angelino E, Garber M, Zuk O, et al.: A composite of multiple signals distinguishes causal variants in regions of positive selection. Science 2010, 327(5967):883-886.
• [39]Honda M, Suzuki M, Nakayama K, Ishikawa T: Role of alpha2C-adrenoceptors in the reduction of skin blood flow induced by local cooling in mice. Br J Pharmacol 2007, 152(1):91-100.
• [40]Kohli U, Muszkat M, Sofowora GG, Harris PA, Friedman EA, Dupont WD, Scheinin M, Wood AJ, Stein CM, Kurnik D: Effects of variation in the human alpha2A- and alpha2C-adrenoceptor genes on cognitive tasks and pain perception. Eur J Pain 2010, 14(2):154-159.
• [41]Fraser HB: Gene expression drives local adaptation in humans. Genome Res 2013, 23(7):1089-1096.
• [42]Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, Ramachandran S, Cann HM, Barsh GS, Feldman M, Cavalli-Sforza LL, et al.: Worldwide human relationships inferred from genome-wide patterns of variation. Science 2008, 319(5866):1100-1104.
• [43]Rasmussen M, Li Y, Lindgreen S, Pedersen JS, Albrechtsen A, Moltke I, Metspalu M, Metspalu E, Kivisild T, Gupta R, et al.: Ancient human genome sequence of an extinct Palaeo-Eskimo. Nature 2010, 463(7282):757-762.
• [44]The International HapMap Consortium: Integrating common and rare genetic variation in diverse human populations. Nature 2010, 467(7311):52-58.
• [45]Behar DM, Yunusbayev B, Metspalu M, Metspalu E, Rosset S, Parik J, Rootsi S, Chaubey G, Kutuev I, Yudkovsky G, et al.: The genome-wide structure of the Jewish people. Nature 2010, 466(7303):238-242.
• [46]Metspalu M, Gallego Romero I, Yunusbayev B, Chaubey G, Mallick CB, Hudjashov G, Nelis M, Magi R, Metspalu E, Remm M, et al.: Shared and unique components of human population structure and genome-wide signals of positive selection in South Asia. Am J Hum Genet 2011, 89(6):731-744.
• [47]Kistler R, Kalnay E, Collins W, Saha S, White G, Woollen J, Chelliah M, Ebisuzaki W, Kanamitsu M, Kousky V, et al.: The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation. Bull Am Meteorol Soc 2001, 82:247-268.
• [48]Weir BS, Cockerham C: Estimating F-statistics for the analsyis of population structure. Evolution 1984, 38(6):1358-1370.