Genome-wide scan for adaptive divergence and association with population-specific covariates

Genetics

Volumn 201, Issue 4, 2015, Pages 1555-1579

  Gautier, Mathieu ^a,b  

^a CENTRE DE BIOLOGIE ET DE GESTION DES POPULATIONS   (France)

^b LIRMM   (France)

Author keywords

Association studies; Bayesian statistics; Genome scan; Linkage disequilibrium; Pool Seq

Indexed keywords

ALB GENE; ARTICLE; CATTLE BREED; CONTROLLED STUDY; ECOTYPE; EDN3 GENE; GENE; GENE LINKAGE DISEQUILIBRIUM; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOTYPE; KIT GENE; KITLG GENE; LITTORINA; LITTORINA SAXATILIS; NONHUMAN; POPULATION GENETICS; PRIORITY JOURNAL; SINGLE NUCLEOTIDE POLYMORPHISM; ADAPTATION; ANIMAL; BIOLOGICAL MODEL; BOVINE; COMPUTER SIMULATION; FEMALE; GENETIC SELECTION; GENETIC VARIATION; GENOME; HUMAN; HUMAN GENOME; MALE; PROCEDURES;

ADAPTATION, BIOLOGICAL; ANIMALS; CATTLE; COMPUTER SIMULATION; FEMALE; GENETIC VARIATION; GENETICS, POPULATION; GENOME; GENOME, HUMAN; GENOTYPE; HUMANS; MALE; MODELS, GENETIC; SELECTION, GENETIC;

EID: 84957542370     PISSN: 00166731     EISSN: 19432631     Source Type: Journal    
DOI: 10.1534/genetics.115.181453     Document Type: Article

References (80)

1. Akey, J. M., G. Zhang, K. Zhang, L. Jin, and M. D. Shriver, 2002 Interrogating a high-density snp map for signatures of natural selection. Genome Res. 12: 1805-1814.
2. Allen, H. L., K. Estrada, G. Lettre, S. I. Berndt, M. N. Weedon et al., 2010 Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467: 832-838.
3. Balding, D. J., and R. A. Nichols, 1995 A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity. Genetica 96: 3-12.
4. Beaumont, M. A., 2005 Adaptation and speciation: What can f(st) tell us? Trends Ecol. Evol. 20: 435-440.
5. Beaumont, M. A., and D. J. Balding, 2004 Identifying adaptive genetic divergence among populations from genome scans. Mol. Ecol. 13: 969-980.
6. Beaumont, M. A., and R. A. Nichols, 1996 Evaluating loci for use in the genetic analysis of population structure. Proc. R. Soc. Lond. B Biol. Sci. 263: 1619-1626.
7. Bennett, D. C., and M. L. Lamoreux, 2003 The color loci of mice-a genetic century. Pigment Cell Res. 16: 333-344.
8. Bonhomme, M., C. Chevalet, B. Servin, S. Boitard, J. Abdallah et al., 2010 Detecting selection in population trees: the Lewontin and Krakauer test extended. Genetics 186: 241-262.
9. Cavalli-Sforza, L. L., 1966 Population structure and human evolution. Proc. R. Soc. Lond. B Biol. Sci. 164: 362-379.
10. Conrad, D. F., M. Jakobsson, G. Coop, X. Wen, J. D. Wall et al., 2006 A worldwide survey of haplotype variation and linkage disequilibrium in the human genome. Nat. Genet. 38: 1251-1260.
11. Coop, G., D. Witonsky, A. D. Rienzo, and J. K. Pritchard, 2010 Using environmental correlations to identify loci underlying local adaptation. Genetics 185: 1411-1423.
12. Davey, J. W., P. A. Hohenlohe, P. D. Etter, J. Q. Boone, J. M. Catchen et al., 2011 Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat. Rev. Genet. 12: 499-510.
13. De Mita, S., A.-C. Thuillet, L. Gay, N. Ahmadi, S. Manel et al., 2013 Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations. Mol. Ecol. 22: 1383-1399.
14. de Villemereuil, P., and O. E. Gaggiotti, 2015 A new FST-based method to uncover local adaptation using environmental variables. Methods Ecol. Evol. DOI: 10.1111/2041-210X.12418.
15. de Villemereuil, P., É. Frichot, É. Bazin, O. François, and O. E. Gaggiotti, 2014 Genome scan methods against more complex models: When and how much should we trust them? Mol. Ecol. 23: 2006-2019.
16. Dorshorst, B., A.-M.Molin, C.-J. Rubin, A. M. Johansson, L. Strömstedt et al., 2011 A complex genomic rearrangement involving the endothelin 3 locus causes dermal hyperpigmentation in the chicken. PLoS Genet. 7: e1002412.
17. Duforet-Frebourg, N., E. Bazin, and M. G. B. Blum, 2014 Genome scans for detecting footprints of local adaptation using a Bayesian factor model. Mol. Biol. Evol. 31: 2483-2495.
18. Excoffier, L., T. Hofer, and M. Foll, 2009 Detecting loci under selection in a hierarchically structured population. Heredity 103: 285-298.
19. Fariello, M. I., S. Boitard, H. Naya, M. SanCristobal, and B. Servin, 2013 Detecting signatures of selection through haplotype differentiation among hierarchically structured populations. Genetics 193: 929-941.
20. Flori, L., S. Fritz, F. Jaffrézic, M. Boussaha, I. Gut et al., 2009 The genome response to artificial selection: a case study in dairy cattle. PLoS One 4: e6595.
21. Foll, M., and O. Gaggiotti, 2008 A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180: 977-993.
22. Foll, M., O. E. Gaggiotti, J. T. Daub, A. Vatsiou, and L. Excoffier, 2014 Widespread signals of convergent adaptation to high altitude in Asia and America. Am. J. Hum. Genet. 95: 394-407.
23. Förstner, W., and B. Moonen, 2003 A metric for covariance matrices, pp. 299-309 in Geodesy-The Challenge of the 3rd Millennium, edited by E. W. Grafarend, F. W. Krumm, and V. S. Schwarze. Springer-Verlag, Berlin/Heidelberg, Germany.
24. Frichot, E., S. D. Schoville, G. Bouchard, and O. François, 2013 Testing for associations between loci and environmental gradients using latent factor mixed models. Mol. Biol. Evol. 30: 1687-1699.
25. Gautier, M., 2014 Using genotyping data to assign markers to their chromosome type and to infer the sex of individuals: a Bayesian model-based classifier. Mol. Ecol. Resour. 14: 1141-1159.
26. Gautier, M., L. Flori, A. Riebler, F. Jaffrézic, D. Laloé et al., 2009 A whole genome Bayesian scan for adaptive genetic divergence in West African cattle. BMC Genomics 10: 550.
27. Gautier, M., T. D. Hocking, and J.-L. Foulley, 2010a A Bayesian outlier criterion to detect SNPs under selection in large data sets. PLoS One 5: e11913.
28. Gautier, M., D. Laloë, and K. Moazami-Goudarzi, 2010b Insights into the genetic history of French cattle from dense SNP data on 47 worldwide breeds. PLoS One 5: 2948016.
29. Gautier, M., J. Foucaud, K. Gharbi, T. Cézard, M. Galan et al., 2013 Estimation of population allele frequencies from nextgeneration sequencing data: pool- vs. individual-based genotyping. Mol. Ecol. 22: 3766-3779.
30. Gelman, A., J. B. Carlin, H. S. Stern, and D. B. Rubin, 2003 Bayesian Data Analysis, Ed. 2. CRC Press, Cleveland, OH/Boca Raton, FL.
31. Gilks, W. R., S. Richardson, and D. J. Spiegelhalter, 1996 Markov Chain Monte Carlo in Practice. Chapman & Hall, London/New York.
32. Gompert, Z., M. L. Forister, J. A. Fordyce, C. C. Nice, R. J. Williamson et al., 2010 Bayesian analysis of molecular variance in pyrosequences quantifies population genetic structure across the genome of lycaeides butterflies. Mol. Ecol. 19: 2455-2473.
33. Grobet, L., L. J. Martin, D. Poncelet, D. Pirottin, B. Brouwers et al., 1997 A deletion in the bovine myostatin gene causes the double- muscled phenotype in cattle. Nat. Genet. 17: 71-74.
34. Guenther, C. A., B. Tasic, L. Luo, M. A. Bedell, and D. M. Kingsley, 2014 A molecular basis for classic blond hair color in Europeans. Nat. Genet. 46: 748-752.
35. Guillot, G., R. Vitalis, A. Le Rouzic, and M. Gautier, 2014 Detecting correlation between allele frequencies and environmental variables as a signature of selection. A fast computational approach for genome-wide studies. Spat. Stat. 8: 145-155.
36. Günther, T., and G. Coop, 2013 Robust identification of local adaptation from allele frequencies. Genetics 195: 205-220.
37. Guo, F., D. K. Dey, and K. E. Holsinger, 2009 A Bayesian hierarchical model for analysis of SNP diversity in multilocus, multipopulation samples. J. Am. Stat. Assoc. 104: 142-154.
38. Gutiérrez-Gil, B., J. J. Arranz, and P. Wiener, 2015 An interpretive review of selective sweep studies in Bos taurus cattle populations: identification of unique and shared selection signals across breeds. Front. Genet. 6: 167.
39. Hancock, A. M., D. B.Witonsky, A. S. Gordon, G. Eshel, J. K. Pritchard et al., 2008 Adaptations to climate in candidate genes for common metabolic disorders. PLoS Genet. 4: e32.
40. Hancock, A. M., D. B. Witonsky, G. Alkorta-Aranburu, C. M. Beall, A. Gebremedhin et al., 2011 Adaptations to climate-mediated selective pressures in humans. PLoS Genet. 7: e1001375.
41. Hasselman, B., 2015 geigen: Calculate Generalized Eigenvalues of a Matrix Pair (R package 1.5). Available at: https://cran.r-project.org/ web/packages/geigen/index.html.
42. Hayes, B. J., J. Pryce, A. J. Chamberlain, P. J. Bowman, and M. E. Goddard, 2010 Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits. PLoS Genet. 6: e1001139.
43. Jeffreys, H., 1961 Theory of Probability, Ed. 3. Oxford University Press, London/New York/Oxford.
44. Joost, S., A. Bonin, M. W. Bruford, L. Després, C. Conord et al., 2007 A spatial analysis method (sam) to detect candidate loci for selection: towards a landscape genomics approach to adaptation. Mol. Ecol. 16: 3955-3969.
45. Karim, L., H. Takeda, L. Lin, T. Druet, J. A. C. Arias et al., 2011 Variants modulating the expression of a chromosome domain encompassing plag1 influence bovine stature. Nat. Genet. 43: 405-413.
46. Kruschke, J., 2014 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Ed. 2. Academic Press, Amsterdam.
47. Kwon, W.-S., Y.-J. Park, E.-S. A. Mohamed, and M.-G. Pang, 2013 Voltage-dependent anion channels are a key factor of male fertility. Fertil. Steril. 99: 354-361.
48. Leinonen, T., R. J. S. McCairns, R. B. O'Hara, and J. Merilä, 2013 Q(st)-f(st) comparisons: evolutionary and ecological insights from genomic heterogeneity. Nat. Rev. Genet. 14: 179-190.
49. Lewontin, R. C., and J. Krakauer, 1973 Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74: 175-195.
50. Li, Y. F., J. C. Costello, A. K. Holloway, and M. W. Hahn, 2008 "Reverse ecology" and the power of population genomics. Evolution 62: 2984-2994.
51. Lipson, M., P.-R. Loh, A. Levin, D. Reich, N. Patterson et al., 2013 Efficient moment-based inference of admixture parameters and sources of gene flow. Mol. Biol. Evol. 30: 1788-1802.
52. Liu, Y., X. Qin, X.-Z. H. Song, H. Jiang, Y. Shen et al., 2009 Bos taurus genome assembly. BMC Genomics 10: 180.
53. Marin, J.-M., and C. P. Robert, 2014 Bayesian Essentials with R. Springer-Verlag, New York.
54. Nicholson, G., A. V. Smith, F. Jonsson, O. Gustafsson, K. Stefansson et al., 2002 Assessing population differentiation and isolation from single-nucleotide polymorphism data. J. R. Stat. Soc. B 64: 695-715.
55. Oleksyk, T. K., M. W. Smith, and S. J. O'Brien, 2010 Genomewide scans for footprints of natural selection. Philos. Trans. R. Soc. Lond. B Biol. Sci. 365: 185-205.
56. Paradis, E., J. Claude, and K. Strimmer, 2004 Ape: analyses of phylogenetics and evolution in r language. Bioinformatics 20: 289-290.
57. Pavlidis, P., J. D. Jensen, W. Stephan, and A. Stamatakis, 2012 A critical assessment of storytelling: gene ontology categories and the importance of validating genomic scans. Mol. Biol. Evol. 29: 3237-3248.
58. Peng, B., and M. Kimmel, 2005 simupop: a forward-time population genetics simulation environment. Bioinformatics 21: 3686-3687.
59. Picardo, M., and G. Cardinali, 2011 The genetic determination of skin pigmentation: kitlg and the kitlg/c-kit pathway as key players in the onset of human familial pigmentary diseases. J. Invest. Dermatol. 131: 1182-1185.
60. Pickrell, J. K., and J. K. Pritchard, 2012 Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8: e1002967.
61. Poncet, B. N., D. Herrmann, F. Gugerli, P. Taberlet, R. Holderegger et al., 2010 Tracking genes of ecological relevance using a genome scan in two independent regional population samples of Arabis alpina. Mol. Ecol. 19: 2896-2907.
62. Pritchard, J. K., J. K. Pickrell, and G. Coop, 2010 The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation. Curr. Biol. 20: R208-R215.
63. Pryce, J. E., B. J. Hayes, S. Bolormaa, and M. E. Goddard, 2011 Polymorphic regions affecting human height also control stature in cattle. Genetics 187: 981-984.
64. Qanbari, S., H. Pausch, S. Jansen, M. Somel, T. M. Strom et al., 2014 Classic selective sweeps revealed by massive sequencing in cattle. PLoS Genet. 10: e1004148.
65. R Core Team, 2015 R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna.
66. Riebler, A., L. Held, and W. Stephan, 2008 Bayesian variable selection for detecting adaptive genomic differences among populations. Genetics 178: 1817-1829.
67. Saldana-Caboverde, A., and L. Kos, 2010 Roles of endothelin signaling in melanocyte development and melanoma. Pigment Cell Melanoma Res. 23: 160-170.
68. Schlötterer, C., R. Tobler, R. Kofler, and V. Nolte, 2014 Sequencing pools of individuals - mining genome-wide polymorphism data without big funding. Nat. Rev. Genet. 15: 749-763.
69. Seitz, J. J., S. M. Schmutz, T. D. Thue, and F. C. Buchanan, 1999 A missense mutation in the bovine mgf gene is associated with the roan phenotype in Belgian blue and shorthorn cattle. Mamm. Genome 10: 710-712.
70. Seo, K., T. R. Mohanty, T. Choi, and I. Hwang, 2007 Biology of epidermal and hair pigmentation in cattle: a mini-review. Vet. Dermatol. 18: 392-400.
71. Signer-Hasler, H., C. Flury, B. Haase, D. Burger, H. Simianer et al., 2012 A genome-wide association study reveals loci influencing height and other conformation traits in horses. PLoS One 7: e37282.
72. Stinckens, A., M. Georges, and N. Buys, 2011 Mutations in the myostatin gene leading to hypermuscularity in mammals: Indications for a similar mechanism in fish? Anim. Genet. 42: 229-234.
73. Thomas, A., B. O'Hara, U. Ligges, and S. Sturtz, 2009 Making bugs open. R News 6: 12-17.
74. Vitalis, R., K. Dawson, and P. Boursot, 2001 Interpretation of variation across marker loci as evidence of selection. Genetics 158: 1811-1823.
75. Vitalis, R., M. Gautier, K. J. Dawson, and M. A. Beaumont, 2014 Detecting and measuring selection from gene frequency data. Genetics 196: 799-817.
76. Vitti, J. J., S. R. Grossman, and P. C. Sabeti, 2013 Detecting natural selection in genomic data. Annu. Rev. Genet. 47: 97-120.
77. Wei, T., 2013 corrplot: Visualization of a Correlation Matrix (R package version 0.73). Available at: https://cran.r-project.org/ web/packages/corrplot/index.html.
78. Weir, B. S., L. R. Cardon, A. D. Anderson, D. M. Nielsen, and W. G. Hill, 2005 Measures of human population structure show heterogeneity among genomic regions. Genome Res. 15: 1468-1476.
79. Westram, A. M., J. Galindo, M. A. Rosenblad, J. W. Grahame, M. Panova et al., 2014 Do the same genes underlie parallel phenotypic divergence in different Littorina saxatilis populations? Mol. Ecol. 23: 4603-4616.
80. Xu, L., D. M. Bickhart, J. B. Cole, S. G. Schroeder, J. Song et al., 2015 Genomic signatures reveal new evidences for selection of important traits in domestic cattle. Mol. Biol. Evol. 32: 711-725.