1. A PPROACHING THE G ENOME - G ENETIC M ARKERS, L INKAGE AND A SSOCIATION G ENETICS 202 Jon Bernstein Department of Pediatrics October 8, 2015

2. Session Goals Develop an understanding of genetic markers and what they can be used for Learn how structural variants in chromosomes have aided the identification of genetic loci associated with various diseases Understand in conceptual terms how a linkage study is performed Understand in conceptual terms how an association study is performed and how they are related to SNP based risk assessment

3. Lecture Outline Mapping genes by the stumble upon method ◦ Chromosomal anomalies and CNVs in gene discovery Introduction to genetic markers ◦ Linkage studies ◦ Association studies

4. Current knowledge of gene – disease relationships

5. Matching genotypes and phenotypes It must be in there somewhere…. Stanford Cytogenetics Lab

6. What do methods for matching genotypes and phenotypes have in common? Based on statistical evidence ◦ Core question is: Is a genotype occurring with a phenotype more than would be expected by chance  Can be looked at in families  Unrelated individuals

7. Sanlaville and Verloes, EJHG, 2007 The story of CHARGE www.chargesyndrome.org

9. Nature Genetics, September, 2004, PMID: 15300250

10. Microduplications and deletions as CNVs Copy number variant (CNV) ◦ A gain or loss of a contiguous block of DNA  1Kb to several Mb ◦ Referred to as a “variant” as this does not imply pathogenicity

11. CNVs are a part of normal genetic variation If the human genome project was completed in 2003, why are widespread CNVs reported later?

12. What if you cannot find a rare cytogenetic abnormality ? Mapping traits to genes by ◦ Linkage studies ◦ Association studies

13. Mapping DNA, Mapping traits to DNA In general, the closer two loci are together the less likely it is that they will be separated by a random break in the chromosome they are on. AB C

14. Fig 9.2 Crossing over between paired homologous chromosomes in the first division of meiosis produces recombination between genetic loci New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

15. The effect of multiple meioses on a chromosome http://hapmap.ncbi.nlm.nih.gov/originhaplotype.html.en

16. Genetic Markers Variable or polymorphic DNA elements that are readily assessed by molecular biology methods Facilitate the differentiation of one copy of a locus from the other http://hapmap.ncbi.nlm.nih.gov/originhaplotype.html.en

17. Common types of DNA polymorphism used as markers New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

18. Figure 1 : Paternity testing using microsatellite markers. This test includes samples from the mother (top row), the child (middle row), and the alleged father (bottom row). The maternal marker that has been passed to the child is 6. This means that the other marker present for the child (7) must have been inherited from the father. The alleged father matches the child, since one of his markers is indeed 7. Paternity testing using genetic markers Adams, J. (2008) Paternity testing: blood types and DNA. Nature Education 1(1) 7,9 6,9.3 6,7

19. Non-paternity versus UPD UPD Studies and genetic markers

20. New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011 Looking for linkage between a marker and a disease locus Informative vs Uninformative Markers (Can we tell which marker segregated with the trait) Recombinant and non- recombinant genotypes Marker Trait locus 2 2 Marker Trait locus 4 2

21. Looking for a gene linked to dyschromatosis on chromosome 1 Determine the odds/relative likelihood of the pedigree (affected/unaffected status) given the genotyping results in each family. Results are expressed as a log of odds or LOD score. ◦ A score of one means ten times more likely ◦ Cutoff score of three typically used (1000 times more likely) Zhang et al., Journal of Investigative Dermatology, 2003, (120) 776-180.

22. Fig 9.6 Pedigrees of the three families used by Miyamura et al. (2003) to map the dyschromatosis gene (Part 1) New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

23. Linkage analysis results High LOD scores at multiple markers in the center of the region of interest on chromosome 1q.

24. Fig 9.6 Pedigrees of the three families used by Miyamura et al. (2003) to map the dyschromatosis gene (Part 1) New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

25. Fig 9.7 Haplotypes of seven individuals from the three pedigrees in Figure 9.6 New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

26. www.genereviews.org Using linkage in clinical diagnostics Used when mutation not identified or gene unknown at a locus Caveats ◦ Recombination can occur ◦ Family members must be phenotyped correctly

27. What types of diseases is linkage best for Show Mendelian inheritance High heritability High penetrance Genetically homogenous Manolio et al., Nature, October, 2009

28. What types of diseases are best studied by GWAS? Common Relatively high heritability Caused by variants of moderate effect Manolio et al., Nature, October, 2009

29. Association Studies – An Alternative to linkage Look for a statistical association between a genetic variant and a trait or disease. ◦ Can look at genetic variants at a few loci or thousands at a time.

30. Genome Wide Association Studies (GWAS) Often done as case control studies in which associations between thousands of genetic loci and a traits or traits are tested for simultaneously. Based on the hypothesis that ancestral common variants are associated with common disease.

31. Where do common genetic variants come from? New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011 Data from census.gov, graph from Wikipedia entry on World Population

32. Linkage Disequilibrium (LD) and Haplotypes in Association Studies LD: Nonrandom association of alleles at 2 or more loci Haplotype: A group of adjacent genetic elements of a chromosome that is transmitted together http://hapmap.ncbi.nlm.nih.gov/originhaplotype.html.en

33. Routinely done on specialized DNA arrays 500K – 1M+ SNPs on a single chip SNP Genotyping – Rapid Assessment of Many Markers LaFramboise T Nucl. Acids Res. 2009;37:4181-4193

34. Haplotype blocks LD blocks vary in size across the genome, but are estimated to be on the order of 10-50kb Buzas B et al. Mol Genet Genomics. 2004 Dec;272(5):519-29. PMID: 15503142 ADRA1A locus at 8p21.2

35. Manolio, NEJM, July 2010, PMID: 20647212 P<5×10 −8

36. Fig 13.8 An overview of genetic susceptibility factors identified by genome-wide association studies (Part 1) New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

37. Fig 13.8 An overview of genetic susceptibility factors identified by genome-wide association studies (Part 2 – key) New Clinical Genetics 2e Andrew Read and Dian Donnai ISBN: 9781904842804 © Scion Publishing Ltd, 2011

38. Pitfalls in GWAS False negatives ◦ Inaccurate phenotyping  Miscategorization of cases and controls ◦ Other potential causes  Genetic heterogeneity  The presence of many genetic contributors makes each association harder to detect False Positives ◦ Population stratification AffectedUnaffected Variant545 No Variant545 AffectedUnaffected Variant100 No Variant090 AffectedUnaffected Variant55 No Variant45 No association Complete association Random assignment of affected

39. Sample GWAS Results Controls vs controls Healthy individuals of different ancestry (multiple groups) Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007 Jun 7;447(7145):661-78. PMID: 17554300

40. GWAS Results for Personal Risk Assessment Identification of SNPs associated with disease can be used to assess the risk of individuals who were not in the original study.

41. GWAS Results for Personal Risk Assessment Chen, Rui et al. Cell, Volume 148, Issue 6, 1293 – 1307, PMID: 22424236

42. Ancestry informative markers Rosenberg et al., PLOS Genetics, December 2006, PMID: 17194221 1384 individuals, 1200 markers (729 microsatellite and 471 insertion/deletion)

43. The “Heritability Gap” Nature, October, 2009

44. Potential explanations of the heritability gap Rare variants play a significant role in common diseases There are numerous genes each with small effect in the etiology of common diseases ◦ Genetic heterogeneity ◦ Small effect size There are significant gene-gene and gene-environment interactions Heritability has been overestimated

45. New Methods for Discovering Disease Gene Associations Structural variant (CNV) based association studies Rare single nucleotide variant association studies Enable the detection and study of rare variants not present in ancestral populations

46. CNVs as an Example of Rare Variants and Common Disease Nature 461, 747-753 (8 October 2009)

47. Exome based rare variant discovery – Kabuki syndrome and MLL2 Ng SB et al. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat Genet. 2010. PMID: 20711175

48. Lecture Summary A number of strategies have been used to develop our current knowledge about relationships between genes and disease ◦ Structural chromosome variants ◦ Linkage ◦ Association Genetic markers are variable or polymorphic elements within DNA that allow the differentiation of corresponding regions on homologous chromosomes

49. Review Question Both linkage studies and GWAS studies are likely to produce false negative results when ◦ A)There is high heritability ◦ B) There is genetic heterogeneity ◦ C) The disease is common ◦ D) There is population stratification

50. Review Question To be most useful in conducting linkage and association studies, DNA markers should ideally be? ◦ A) Homozygous ◦ B) Highly polymorphic ◦ C) Very widely spaced in the genome ◦ D) Very rare in the population