1. Common variation, GWAS & PLINK
Jeff Barrett

2. What are the goals of disease genetics?
For a given disease, we would like to:
Predict if someone will get sick, how bad it will be, and what treatment will work.
Test hypotheses about relationships to other diseases and traits.
Understand the biology of the disease so we can design better treatments and diagnostics.

3. Variation is fundamental to these goals
Twin and family studies don’t directly measure the variation at all.
Linkage studies only measure enough variation to trace inheritance in families.

4. Manuel mentioned why this is (I think)?

5. Variation is fundamental to these goals
Twin and family studies don’t directly measure the variation at all.
Linkage studies only measure enough variation to trace inheritance in families.
Association studies measure all the variation in the individuals being studied.

6. A note on terminology…
SNP (single nucleotide polymorphism): a site in the genome where some individuals differ from the reference sequence.
Indel: a small insertion or deletion of non-reference sequence
Structural variant: large deletion, insertion, or rearrangement
Variant: any of the above
Polymorphism: a “reasonably common” variant
Mutation: a newly arisen variant in a given genome
Allele: version of a variant

7. What creates genetic variation?
The two processes that increase genetic diversity in a population are mutation, which introduces novel variants into the population, and recombination, which re-shuffles the existing patterns of variation. The fate of new mutations is affected by drift, selection and population history. We care about the patterns left behind by these forces, and their affect on disease studies.

8. How much variation is there?

9. The history of human populations

10. How much variation is there?

11. The history of human populations
1000 Genomes, Nature, 2012

12. The history of human populations
Band et al, PLoS Genet, 2013

13. The history of human populations
Novembre et al, Nature, 2008

14. Population variant frequency example I

15. Population variant frequency example II
Lim et al, PLoS Genet, 2014

16. Consequences of mutation & recombination
Genetic variants are correlated because they share a history of inheritance.
In the absence of recombination this correlation would extend a great distance along chromosomes.
Recombination breaks down this correlation over successive generations, leaving a narrower and narrower window of correlation.

17. Chromosome 7
Chromosome 20

18. Chromosome 7
Chromosome 20
SNP 1
SNP 2

19. Quantifying LD
Expected assuming
independence
Observed in data

20. Chromosome 7
Chromosome 20
SNP 1
SNP 2

21. Quantifying LD

22. D’ for common SNPs in 100kb

23. r2 for common SNPs in 100kb

24. LD patterns as historical record

25. Consequences of mutation & recombination
Genetic variants are correlated because they share a history of inheritance.
In the absence of recombination this correlation would extend a great distance along chromosomes.
Recombination breaks down this correlation over successive generations, leaving a narrower and narrower window of correlation.
Under certain assumptions (random mating, neutral evolution, homogenous recombination) we can model exactly how narrow this is.

26. Theoretical vs. empirical correlation
Reich et al, Nature 2001

27. Correlation pattern driven by heterogeneous recombination

28. An LD map of the human genome

29. How can we use the HapMap to design disease studies?

30. How can we use the HapMap to design disease studies?

31. Correlation used to design genome-wide association studies
Barrett and Cardon, Nat Genet, 2006

32. Can also combine information from multiple SNPs

33. Imputation: concept

36. Genome-wide association studies (GWAS)
CA, IB, JCB, NS, EZ

38. r2 = correlation to true cause
Power ∝ Nβp(1-p)r2
N = sample size
β = effect size
p = frequency
r2 = correlation to true cause

39. Common variation
Rare
variation
Abundance
~ 107
109?
Population specific? No
Often
Correlation
High
Low
Selection
Unlikely
Possible
Best technology
Array genotyping
Sequencing

40. Matching biological questions to technologies
In my disease what role does…
common variation in Europeans play? GWAS
common variation in non-European populations? GWAS 2.0
low frequency variation play? GWAS 2.0
rare or private variation play? sequencing

41. History of IBD gene mapping
Describe immunochip, dozen diseases, ~100 confirmed fine-mapping loci (complete as of 2010)

42. A note on software
PLINK Magma Metal Haploview Evoker … R
python

43. /faculty/barrett/2017/gwas-practical