Complex Trait Genetics in Animal Models. Will Valdar Oxford University

Transcription

1 Complex Trait Genetics in Animal Models Will Valdar Oxford University

2 Mapping Genes for Quantitative Traits in Outbred Mice Will Valdar Oxford University

3 What s so great about mice? Share ~99% of genes with humans ~90% of the two genomes can be portioned into regions of conserved synteny Shorter lifespans You can do invasive experiments You can breed them as you like control the genetics

4 What is an inbred strain? F20 generation F = 99% BALB/c

5

6 one inbred strain

7 two inbred strains

8 Mouse model of anxiety

9 Mouse model of anxiety Anxious mouse Non anxious mouse

10 F2 cross Generation F0 F1 F2

11 anxious about average non-anxious

12 Quantitative Trait Locus anxious about average non-anxious

13 Quantitative Trait Locus anxious about average non-anxious

14 Quantitative Trait Locus anxious about average non-anxious

15 Quantitative Trait Locus anxious about average non-anxious QTL snp

16 Linear models Also known as ANOVA ANCOVA regression multiple regression linear regression

17 x QTL snp

18 x y ax QTL snp

19 x y ax QTL snp

20 x y ax a a QTL snp

21 Hypothesis testing H 0 : y H 1 : y ax

22 Hypothesis testing H 0 : y ~ 1 y H 1 : y ~ 1 + x y ax

23 Hypothesis testing H 0 : y ~ 1 y H 1 : y ~ 1 + x y ax H 1 vs H 0 : Does x explain a significant amount of the variation?

24 Hypothesis testing H 0 : y ~ 1 y H 1 : y ~ 1 + x y ax H 1 vs H 0 : Does x explain a significant amount of the variation? likelihood ratio LOD score

25 Hypothesis testing H 0 : y ~ 1 y H 1 : y ~ 1 + x y ax H 1 vs H 0 : Does x explain a significant amount of the variation? LOD score likelihood ratio Chi Square test p-value logp

26 Hypothesis testing H 0 : y ~ 1 y H 1 : y ~ 1 + x y ax H 1 vs H 0 : Does x explain a significant amount of the variation? LOD score likelihood ratio Chi Square test p-value logp linear models only SS explained / SS unexplained F-test (or t-test)

27 Hypothesis testing H 0 : y ~ 1 + x1 y a 1 x 1 H 1 : y ~ 1 + x1 + x2 y a x a x H 1 vs H 0 : Does x2 explain a significant amount of the variation after accounting for x1? or is x2 significant conditional on x1?

28 F2 cross Generation F0 F1 F2

29 QTL

30 logp QTL

31 QTL logp highly significant snp non significant snp

32 logp QTL

33 logp QTL

34 Chromosome scan for F2 QTL goodness of fit (logp) significance threshold 0 200Mb position along whole chromosome (Mb) Typical chromosome

35 Advanced intercross lines (AILs) F0 F1 F2 F3 F4 Darvasi & Soller (1995) Genetics

36 F12 cross F0 F1 F2 F12

37 Chromosome scan for F12 QTL goodness of fit (logp) significance threshold 0 200Mb position along whole chromosome (Mb) Typical chromosome

38 Practical 1. Fitting a linear model to test a marker-phenotype association 2. Single marker association on an F2 3. Permutation test 4. Single marker association on an AIL (F12) 5. Conditional modelling of loci Start Firefox, File->Open and go to F:\valdar\ThursdayAfternoonAnimals\practical.R Start R

39 Practical: F2 cross Bonferroni = 2.6 permutation ~ 2.1 uncorrected = 1.3

40 Practical: F2 cross Bonferroni = 2.6 permutation ~ 2.1 uncorrected = 1.3 generalized extreme value (GEV) distribution

41 Practical: F12 phenotype ~ MARKER

42 Practical: F12 phenotype ~ MARKER phenotype ~ m37 + MARKER

43 Practical: F12 phenotype ~ MARKER phenotype ~ m37 + MARKER phenotype ~ MARKER

44 Practical: F12 phenotype ~ MARKER phenotype ~ m37 + MARKER phenotype ~ MARKER phenotype ~ m37 + MARKER

45 Practical: F12 phenotype ~ MARKER phenotype ~ m37 + MARKER phenotype ~ MARKER phenotype ~ m37 + MARKER phenotype ~ m37 + m29 + MARKER

46 F2 F18 F18 multilocus approach

47 F2 F18 F18 multilocus approach

48 F2 breeding in a small population F18 F18 multilocus approach

49 F2 population structure gross genetic differences between groups where groups = families F18 multilocus approach

50 F2 population structure gross genetic differences between groups where groups = families multilocus approach

51 Heterogeneous Stocks

52 Heterogeneous Stock Pseudo-random mating for 50 generations Avg. Distance Between Recombinations: HS ~2 cm

53 Heterogeneous Stock F2 Intercross x Pseudo-random mating for 50 generations F1 Avg. Distance Between Recombinations: HS ~2 cm F2 intercross ~30 cm F2

54 124 Phenotypes Anxiety [24] Asthma [13] Biochemistry [15] Bone Morphology [23] Diabetes [16] Haematology [15] Immunology [9] Weight/size related [8] Wound Healing [1]

55 Intraperitoneal Glucose Tolerance Test

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57

58 How to select peaks: a simulated example

59 How to select peaks: a simulated example Simulate 7 x 5% QTLs (ie, 35% genetic effect) + 20% shared environment effect + 45% noise = 100% variance

60 Simulated example

61 phenotype ~?

62 phenotype ~ peak 1 +? condition on 1 peak

63 condition on 2 peaks phenotype ~ peak 1 + peak 2 +?

64 condition on 3 peaks phenotype ~ peak 1 + peak 2 + peak 3 +?

65 condition on 4 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 +?

66 condition on 5 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 +?

67 condition on 6 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 +?

68 condition on 7 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 + peak 7 +?

69 condition on 8 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 + peak 7 + peak 8 +?

70 condition on 9 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 + peak 7 + peak 8 + peak 9 +?

71 condition on 10 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 + peak 7 + peak 8 + peak 9 + peak 10 +?

72 condition on 11 peaks phenotype ~ peak 1 + peak 2 + peak 3 + peak 4 + peak 5 + peak 6 + peak 7 + peak 8 + peak 9 + peak 10 + peak 11 +?

73 Peaks chosen by forward selection

74 Bootstrap sampling 10 subjects

75 Bootstrap sampling sample with replacement subjects bootstrap sample from 10 subjects

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77 Forward selection on a bootstrap sample

78 Forward selection on a bootstrap sample

79 Forward selection on a bootstrap sample

80 Bootstrap evidence mounts up

81 Model Inclusion Probability In 1000 bootstraps

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84 854 loci in all phenotypes, 84 diabetes loci

85 854 loci in all phenotypes, 84 diabetes loci

86 Servin B, Stephens M (2007)

87 Bayesian Multiple QTL modelling Kilpikari R, Sillanpaa MJ (2003) Bayesian analysis of multilocus association in quantitative and qualitative traits. Genet Epidemiol 25: Yi N (2004) A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci. Genetics 167: Servin B, Stephens M (2007) Imputation-based analysis of association studies: candidate regions and quantitative traits. PLoS Genet 3: e114 Fridley BL (2008) Bayesian variable and model selection methods for genetic association studies. Genet Epidemiol.

88 The Collaborative Cross Heterogeneous Stocks (HS) Collaborative Cross outbreed outbred population recombinant inbred lines Churchill et al 2004; Broman 2005; Valdar et al 2006