Bayesian approaches in evolutionary quantitative genetics

Journal of Evolutionary Biology

Volumn 21, Issue 4, 2008, Pages 949-957

  O'Hara, R B ^a   Cano, J M ^a   Ovaskainen, O ^a   Teplitsky, C ^a,b   Alho, J S ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

^b MUSÉUM NATIONAL D'HISTOIRE NATURELLE   (France)

Author keywords

Bayesian analysis; Evolution; Hierarchical models; Quantitative genetics; Statistics

Indexed keywords

ANIMAL; BAYESIAN ANALYSIS; DATA SET; EVOLUTIONARY BIOLOGY; GENETICS; GENOMICS; HIERARCHICAL SYSTEM; PLANT BREEDING; WILD POPULATION;

ANIMAL; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER; EVOLUTION; HUMAN; REVIEW;

ANIMALS; BAYES THEOREM; COMPUTERS; EVOLUTION; HUMANS; MODELS, GENETIC;

ANIMALIA;

EID: 45149119119     PISSN: 1010061X     EISSN: 14209101     Source Type: Journal    
DOI: 10.1111/j.1420-9101.2008.01529.x     Document Type: Review

References (81)

1. Beaumont, M.A. Rannala, B. 2004. The Bayesian revolution in genetics. Nat. Rev. Genet. 5:251 261.
2. Bennewitz, J., Morgades, O., Preisinger, R., Thaller, G. Kalm, E. 2007. Variance component and breeding value estimation for reproductive traits in laying hens using a Bayesian threshold model. Poultry Sci. 86:823 828.
3. Beraldi, D., McRae, A.F., Gratten, J., Slate, J., Visscher, P.M. Pemberton, J.M. 2007. Mapping quantitative trait loci underlying fitness-related traits in a free-living sheep population. Evolution 61:1403 1416.
4. Blasco, A. 2001. The Bayesian controversy in animal breeding. J. Anim. Sci. 79:2023 2046.
5. Cano, J.M., Laurila, A., Palo, J. Merilä, J. 2004. Population differentiation in G matrix structure due to natural selection in Rana temporaria. Evolution 58:2013 2020.
6. Charmantier, A. Garant, D. 2005. Environmental quality and evolutionary potential: lessons from wild populations. Proc. R. Soc. Lond. B 272:1415 1425.
7. Coulson, T., Kruuk, L.E.B., Tavecchia, G., Pemberton, J. Clutton-Brock, T.H. 2003. Estimating selection on neonatal traits in red deer using elasticity path analysis. Evolution 57:2879 2892.
8. Csilléry, K., Johnson, T., Beraldi, D., Clutton-Brock, T.H., Coltman, D., Hansson, B., Spong, G. Pemberton, J. 2006. Performance of marker-based relatedness estimators in natural populations of outbred vertebrates. Genetics, 173:2091 2101.
9. Damgaard, L.H. 2007. How to use Winbugs to draw inferences in animal models. J. Anim. Sci. 85:1363 1368.
10. Evanno, G., Castella, E. Goudet, J. 2006. Evolutionary aspects of population structure for molecular and quantitative traits in the freshwater snail Radix balthica. J. Evol. Biol. 19:1071 1082.
11. Falconer, D.S. MacKay, T.F.C. 1996. Introduction to Quantitative Genetics, 4th edn. Longman, Essex, UK.
12. Fisher, R.A. 1918. The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinburgh 52:399 433.
13. Gasbarra, D., Pirinen, M., Sillanpää, M.J., Salmela, E. Arjas, E. 2007. Estimating genealogies from unlinked marker data: a Bayesian approach. Theor. Popul. Biol. 72:305 322.
14. Gelman, A.J. 2006. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1:515 534.
15. Gelman, A., Carlin, J.B., Stern, H.S. Rubin, D.B. 2004. Bayesian Data Analysis, 2nd edn. Chapman & Hall/CRC, Boca Raton, FL.
16. Gianola, D. Fernando, R.L. 1986. Bayesian methods in animal breeding theory. J. Anim. Sci. 63:217 244.
17. Gianola, D. Foulley, J.L. 1983. Sire evaluation for ordered categorical data with a threshold model. Genet. Sel. Evol. 15:201 223.
18. Gianola, D., Perez-Enciso, M. Toro, M.A. 2003. On marker-assisted prediction of genetic value: beyond the ridge. Genetics 163:347 365.
19. Gilks, W.R., Richardson, S. Spiegelhalter, D.J. 1995. Markov Chain Monte Carlo in Practice. Chapman & Hall/CRC, London, UK.
20. Gustafson, P. 2004. Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments. Chapman & Hall/CRC, London, UK.
21. Hadfield, J.D. 2008. Estimating evolutionary parameters when viability selection is operating. Proc. R. Soc. Lond. B 275:723 734.
22. Hadfield, J.D., Richardson, D.S. Burke, T. 2006. Towards unbiased parentage assignment: combining genetic, behavioural and spatial data in a Bayesian framework. Mol. Ecol. 15:3715 3730.
23. Hanski, I. Saccheri, I. 2006. Molecular-level variation affects population growth in a butterfly metapopulation. PLoS Biol. 4:719 726.
24. Henderson, C.R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics 31:423 447.
25. Holder, M. Lewis, P.O. 2003. Phylogeny estimation: traditional and Bayesian approaches. Nat. Rev. Genet. 43:275 284.
26. Hurme, P., Sillanpää, M.J., Arjas, E., Repo, T. Savolainen, O. 2000. Genetic basis of climatic adaptation in Scots Pine by Bayesian quantitative trait locus analysis. Genetics 156:1309 1322.
27. Jensen, J., Wang, C.S., Sorensen, D.A. Gianola, D. 1994. Bayesian-inference on variance and covariance components for traits influenced by maternal and direct genetic-effects, using the Gibbs sampler. Acta Agric. Scand. Anim. Sci 44:193 201.
28. van Kleunen, M. Ritland, K. 2005. Estimating heritabilities and genetic correlations with marker-based methods: an experimental test in Mimulus guttatus. J. Hered. 96:368 375.
29. Knopp, T., Crochet, P.-A., Cano Arias, J.M. Merilä, J. 2007. Contrasting levels of variation in neutral and quantitative genetic loci on Island populations of moor frogs (Rana arvalis). Conserv. Genet. 8:45 56.
30. Knott, S.A., Sibly, R.M., Smith, R.H. Møller, H. 1995. Maximum likelihood estimation of genetic parameters in life-history studies using the 'Animal Model'. Funct. Ecol. 9:122 126.
31. Kovač, M. Groeneveld, E. 2003. VCE-5 user's guide and reference manual version 5.1. Department of Animal Sciences, University of Ljubljana, Slovenia.
32. Kruuk, L.E.B. 2004. Estimating genetic parameters in natural populations using the 'animal model'. Philos. Trans. R. Soc. Lond. B 359:873 890.
33. Kruuk, L.E.B., Clutton-Brock, T.H., Slate, J., Pemberton, J.H., Brotherstone, S. Guinness, F.E. 2000. Heritability of fitness in a wild mammal population. Proc. Natl Acad. Sci. 97:698 703.
34. Lauritzen, S.L. Spiegelhalter, D.J. 1988. Local computations with probabilities on graphical structures and their application to expert systems. J. R. Stat. Soc. B 50:157 224.
35. Lee, Y. Nelder, J.A. 2006. Double hierarchical generalized linear models (with discussion). J. R. Stat. Soc. A 55:139 185.
36. Lush, J.L. 1937. Animal Breeding Plans. Iowa State University Press, Ames, IA.
37. Lynch, M. Walsh, B. 1998. Genetics and Analysis of Quantitative Traits. Sinauer, Sunderland, MA.
38. Merilä, J. Björklund, M. 1995. Fluctuating asymmetry and measurement error. Syst. Biol. 44:97 101.
39. Merilä, J. Crnokrak, P. 2001. Comparison of marker gene and quantitative genetic differentiation among populations. J. Evol. Biol. 14:892 903.
40. Merilä, J., Kruuk, L.E.B. Sheldon, B. 2001. Cryptic evolution in a wild bird population. Nature 412:76 79.
41. Merilä, J., Söderman, F., Räsänen, K., Laurila, A. O'Hara, R. 2004. Local adaptation and genetics of acid-stress tolerance in the moor frog. Conserv. Genet. 5:513 522.
42. Milner, J.M., Albon, S.D., Illius, A.W., Pemberton, J.M. Clutton-Brock, T.H. 1999. Repeated selection of morphometric traits in the Soay sheep on St Kilda. J. Anim. Ecol. 68:472 488.
43. Misztal, I., Tsuruta, S., Strabel, T., Auvray, B., Druet, T. Lee, D.H. 2002. BLUPF90 and related programs (BGF90). Proc. 7th World Congr. Genet. Appl. Livest. Prod., Montpellier, France. Communication No. 28-07.
44. O'Hara, R.B. 2005. Comparing the effects of genetic drift and fluctuating selection on genotype frequency changes in the scarlet tiger moth. Proc. R. Soc. Lond. B 272:211 217.
45. ST estimates: problems and some solutions. Genetics 171:1331 1339.
46. Oliehoek, P.A., Windig, J.J., van Arendonk, J.A.M. Bijma, P. 2006. Estimating relatedness between individuals in general populations with a focus on their use in conservation programs. Genetics 173:483 496.
47. Ovaskainen, O., Cano, J.M. Merilä, J. 2008. A Bayesian framework for comparative quantitative genetics. Proc. R. Soc. Lond. B 275:669 678.
48. Pakkasmaa, S., Merilä, J. O'Hara, R.B. 2003. Genetic and maternal effect influences on viability of common frog tadpoles under different environmental conditions. Heredity 91:117 124.
49. Palo, J.U., O'Hara, R.B., Laugen, A.T., Laurila, A., Primmer, C.R. Merilä, J. 2003. Latitudinal divergence of common frog (Rana temporaria) life history traits by natural selection: evidence from a comparison of molecular and quantitative genetic data. Mol. Ecol. 12:1963 1978.
50. Patterson, H.D. Thompson, R. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58:545 554.
51. Postma, E. 2006. Implications of the difference between true and predicted breeding values for the study of natural selection and micro-evolution. J. Evol. Biol. 19:309 320.
52. Ritland, K. 1996. Marker-based method for inferences about quantitative inheritance in natural populations. Evolution 50:1062 1073.
53. Ros, M., Sorensen, D., Waagepetersen, R., Dupont-Nivet, M., SanCristobal, M., Bonnet, J.-C. Mallard, J. 2004. Evidence for genetic control of adult weight plasticity in the snail Helix aspersa. Genetics 168:2089 2097.
54. Shaw, R.G. 1987. Maximum-likelihood approaches applied to quantitative genetics of natural-populations. Evolution 41:812 826.
55. Sillanpää, M. Bhattacharjee, M. 2006. Association mapping of complex trait loci with context-dependent effects and unknown context variable. Genetics 174:1597 1611.
56. Slate, J., Visscher, P.M., MacGregor, S., Stevens, D., Tate, M.L. Pembertom, J.M. 2002. A genome scan for quantitative trait loci in a wild population of red deer (Cervus elaphus). Genetics 162:1863 1873.
57. Sorensen, D. Gianola, D. 2002. Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. Springer-Verlag, New York.
58. Sorensen, D.A., Wang, C.S., Jensen, J. Gianola, D. 1994. Bayesian-analysis of genetic change due to selection using Gibbs sampling. Genet. Sel. Evol. 26:333 360.
59. Spiegelhalter, D.J., Abrams, K. Myles, J.P. 2004. Bayesian Approaches to Clinical Trials and Health Care Evaluation. John Wiley & Sons, Chichester, UK.
60. Spitze, K. 1993. Population-structure in Daphnia obtusa- quantitative genetic and allozymic variation. Genetics 135:367 374.
61. Steinsland, I. Jensen, H. 2005. Making Inference from Bayesian Animal Models Utilising Gaussian Markov Random Field Properties. Preprint, Statistics No. 10/2005, Norwegian University of Science and Technology, Trondheim, Norway. Available at: http://www.math.ntnu.no/preprint/statistics/2005/S10-2005.pdf.
62. Thomas, A., O'Hara, B., Ligges, U. Sturtz, S. 2006. Making BUGS Open. R News 6:12 17.
63. Thompson, R. 2008. Estimation of quantitative genetic parameters. Proc. R. Soc. Lond. B 275:679 686.
64. van Tienderen, P.H. 2000. Elasticities and the link between demographic and evolutionary dynamics. Ecology 81:666 679.
65. Van Dongen, S. 2001. Modelling developmental instability in relation to individual fitness: a fully Bayesian latent variable model approach. J. Evol. Biol. 14:552 563.
66. Van Dongen, S. 2006a. Prior specification in Bayesian statistics: three cautionary tales. J. Theor. Biol. 242:90 100.
67. Van Dongen, S. 2006b. Fluctuating asymmetry and developmental instability in evolutionary biology: past, present and future. J. Evol. Biol. 19:552 563.
68. Van Dongen, S. 2007. What do we know about the heritability of developmental instability? Answers from a Bayesian model. Evolution 61:1033 1042.
69. Van Dongen, S. Talloen, W. 2007. Phenotypic and genetic variations and correlations in multitrait developmental instability:a multivariate Bayesian model applied to Speckled Wood butterfly (Pararge aegeria) wing measurements. Genet. Res. 89:155 163.
70. Van Tassel, C.P. Van Vleck, L.D. 1996. Multiple-trait Gibbs sampler for animal models: flexible programs for Bayesian and likelihood-based (co)variance component inference. J. Anim. Sci. 74:2586 2597.
71. Waldmann, P. 2004. A quantitative genetic method for estimating developmental instability. Evolution 58:238 244.
72. Waldmann, P., García-Gil, M.R. Sillanpää, M.J. 2005. Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris. Heredity 94:623 629.
73. Wang, C.S., Rutledge, J.J. Gianola, D. 1993. Marginal inferences about variance components in a mixed linear model using Gibbs sampling. Genet. Sel. Evol. 25:41 62.
74. Wang, C.S., Rutledge, J.J. Gianola, D. 1994. Bayesian-analysis of mixed linear-models via Gibbs sampling with an application to litter size in Iberian pigs. Genet. Sel. Evol. 26:91 115.
75. Whitlock, M. 1998. The repeatability of fluctuating asymmetry: a revision and extension. Proc. R. Soc. Lond. B 265:1429 1431.
76. Wilson, A.J., Pemberton, J.M., Pilkington, J.G., Coltman, D.W., Mifsud, D.V., Clutton-Brock, T.H. Kruuk, L.E.B. 2006. Environmental coupling of selection and heritability limits evolution. PLoS Biol. 4:e216.
77. Wright, S. 1921a. Systems of mating. I. The biometric relations between parents and offspring. Genetics 6:111 123.
78. Wright, S. 1921b. Systems of mating. II. The effects of inbreeding on the genetic composition of a population. Genetics 6:124 143.
79. Wright, S. 1921c. Systems of mating. III. Assortative mating based on somatic resemblance. Genetics 6:144 161.
80. Yi, N. Xu, S. 2000. Bayesian mapping of quantitative trait loci under the identity-by-descent-based variance component model. Genetics 156:411 422.
81. Yu, J., Pressoir, G., Briggs, W.H., Bi, I.V., Yamasaki, M., Doebley, J.F., McMullen, M.D., Gaut, B.S., Nielsen, D.M., Holland, J.B., Kresovich, S. Buckler, E.S. 2005. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38:203 208.