Inferring the age of a fixed beneficial allele

Molecular Ecology

Volumn 25, Issue 1, 2016, Pages 157-169

  Ormond, Louise ^a,b   Foll, Matthieu ^a,b,c   Ewing, Gregory B ^a,b   Pfeifer, Susanne P ^a,b   Jensen, Jeffrey D ^a,b  

^a EPFL   (Switzerland)

^b SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^c INTERNATIONAL AGENCY FOR RESEARCH ON CANCER   (France)

Author keywords

adaptation; ecological genetics; population genetics empirical; population genetics theoretical

Indexed keywords

ADAPTATION; ALLELE; ANIMAL; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENE FREQUENCY; GENE LINKAGE DISEQUILIBRIUM; GENETICS; HAIR; MOUSE; MUTATION; PIGMENTATION; POPULATION GENETICS;

ADAPTATION, BIOLOGICAL; ALLELES; ANIMALS; BAYES THEOREM; COMPUTER SIMULATION; GENE FREQUENCY; GENETICS, POPULATION; HAIR; LINKAGE DISEQUILIBRIUM; MICE; MODELS, GENETIC; MUTATION; PIGMENTATION;

EID: 84954075331     PISSN: 09621083     EISSN: 1365294X     Source Type: Journal    
DOI: 10.1111/mec.13478     Document Type: Article

References (46)

1. Bank C, Ewing GB, Ferrer-Admettla A, Foll M, Jensen JD, (2014) Thinking too positive? Revisiting current methods of population genetic selection inference. Trends in Genetics, 30, 540-546
2. Beaumont MA, Zhang W, Balding DJ, (2002) Approximate Bayesian computation in population genetics. Genetics, 162, 2025-2035
3. Bjorn-Helge M, Wehrens R, (2007) The pls package: principal component and partial least squares regression in R. Journal of Statistical Software, 18, 1-23
4. Box G, Cox D, (1964) An analysis of transformations. Journal of the Royal Statistical Society, 26, 211-243
5. Chen H, Slatkin M, (2013) Inferring selection intensity and allele age from multilocus haplotype structure. G3 (Bethesda), 3, 1429-1442
6. Chen H, Hey J, Slatkin M, (2015) A hidden Markov model for investigating recent positive selection through haplotype structure. Theoretical Population Biology, 99, 18-30
7. Csillery K, Francois O, Blum M, (2012) abc: an R package for approximate Bayesian computation (ABC). Methods in Ecology and Evolution, 3, 475-479
8. Ewing G, Hermisson J, (2010) MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus. Bioinformatics, 26, 2064-2065
9. Excoffier L, Dupanloup I, Huerta-Sánchez E, Sousa VC, Foll M, (2013) Robust demographic inference from genomic and SNP data. PLoS Genetics, 9, e1003905
10. Fay JC, Wu CI, (2000) Hitchhiking under positive Darwinian selection. Genetics, 155, 1405-1413
11. Feng D, Tierney L, (2015) Package "misc3d", CRAN repository
12. Foll M, Poh YP, Renzette N, et al. (2014) Influenza virus drug resistance: a time-sampled population genetics perspective. PLoS Genetics, 10, e1004185
13. Gutenkunst RN, Hernandez RD, Williamson SH, Bustamante CD, (2009) Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genetics, 5, e1000695
14. Hermisson J, Pennings PS, (2005) Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics, 169, 2335-2352
15. Jensen JD, (2014) On the unfounded enthusiasm for soft selective sweeps. Nature Communications, 5, 5281
16. Jensen JD, Kim Y, DuMont VB, Aquadro CF, Bustamante CD, (2005) Distinguishing between selective sweeps and demography using DNA polymorphism data. Genetics, 170, 1401-1410
17. Jensen JD, Thornton KR, Bustamante CD, Aquadro CF, (2007) On the utility of linkage disequilibrium as a statistic for identifying targets of positive selection in nonequilibrium populations. Genetics, 176, 2371-2379
18. Joyce P, Marjoram P, (2008) Approximately sufficient statistics and bayesian computation. Statistical Applications in Genetics and Molecular Biology, 7, Article26
19. Kaplan NL, Hudson RR, Langley CH, (1989) The "hitchhiking effect" revisited. Genetics, 123, 887-899
20. Kim Y, Nielsen R, (2004) Linkage disequilibrium as a signature of selective sweeps. Genetics, 167, 1513-1524
21. Linnen CR, Kingsley EP, Jensen JD, Hoekstra HE, (2009) On the origin and spread of an adaptive allele in deer mice. Science, 325, 1095-1098
22. Linnen CR, Poh YP, Peterson BK, et al. (2013) Adaptive evolution of multiple traits through multiple mutations at a single gene. Science, 339, 1312-1316
23. Malaspinas AS, Malaspinas O, Evans SN, Slatkin M, (2012) Estimating allele age and selection coefficient from time-serial data. Genetics, 192, 599-607
24. Mathieson I, McVean G, (2013) Estimating selection coefficients in spatially structured populations from time series data of allele frequencies. Genetics, 193, 973-984
25. McVean GA, (2002) A genealogical interpretation of linkage disequilibrium. Genetics, 162, 987-991
26. McVean G, (2007) The structure of linkage disequilibrium around a selective sweep. Genetics, 175, 1395-1406
27. Orr HA, Betancourt AJ, (2001) Haldane's sieve and adaptation from the standing genetic variation. Genetics, 157, 875-884
28. Pavlidis P, Jensen JD, Stephan W, (2010) Searching for footprints of positive selection in whole-genome SNP data from nonequilibrium populations. Genetics, 185, 907-922
29. Peter BM, Huerta-Sanchez E, Nielsen R, (2012) Distinguishing between selective sweeps from standing variation and from a de novo mutation. PLoS Genetics, 8, e1003011
30. Poh YP, Domingues VS, Hoekstra HE, Jensen JD, (2014) On the prospect of identifying adaptive loci in recently bottlenecked populations. PLoS ONE, 9, e110579
31. Przeworski M, (2002) The signature of positive selection at randomly chosen loci. Genetics, 160, 1179-1189
32. Przeworski M, (2003) Estimating the time since the fixation of a beneficial allele. Genetics, 164, 1667-1676
33. Przeworski M, Coop G, Wall JD, (2005) The signature of positive selection on standing genetic variation. Evolution, 59, 2312-2323
34. Slatkin M, (2008) A Bayesian method for jointly estimating allele age and selection intensity. Genetics Research (Cambridge), 90, 129-137
35. Steinrücken M, Bhaskar A, Song YS, (2014) A novel spectral method for inferring general diploid selection from time series genetic data. The Annals of Applied Statistics, 8, 2203-2222
36. Stephan W, Wiehe THE, Lenz MW, (1992) The effects of strongly selected substitutions on neutral polymorphisms: analytical results based on diffusion theory. Theoretical Population Biology, 41, 237-254
37. Stephan W, Song YS, Langley CH, (2006) The hitchhiking effect on linkage disequilibrium between linked neutral loci. Genetics, 172, 2647-2663
38. Tajima F, (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123, 585-595
39. Tavaré S, Balding DJ, Griffiths RC, Donnelly P, (1997) Inferring coalescence times from DNA sequence data. Genetics, 145, 505-518
40. Thornton K, (2003) Libsequence: a C++ class library for evolutionary genetic analysis. Bioinformatics, 19, 2325-2327
41. Thornton KR, Jensen JD, (2007) Controlling the false-positive rate in multilocus genome scans for selection. Genetics, 175, 737-750
42. Thornton KR, Jensen JD, Becquet C, Andolfatto P, (2007) Progress and prospects in mapping recent selection in the genome. Heredity, 98, 340-348
43. Venables WN, Ripley BD, (2002) Modern Applied Statistics with S, 4th edn. Springer, New York
44. Voight BF, Kudaravalli S, Wen X, Pritchard JK, (2006) A map of recent positive selection in the human genome. PLoS Biology, 4, e72
45. Wegmann D, Leuenberger C, Excoffier L, (2009) Efficient approximate Bayesian computation coupled with Markov chain Monte Carlo without likelihood. Genetics, 182, 1207-1218
46. Wegmann D, Leuenberger C, Neuenschwander S, Excoffier L, (2010) ABCtoolbox: a versatile toolkit for approximate Bayesian computations. BMC Bioinformatics, 11, 116