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Some current issues in QTL identification

Some current issues in QTL identification. Lon Cardon Wellcome Trust Centre for Human Genetics University of Oxford. Acknowledgements: Goncalo Abecasis Stacey Cherny Twin course faculty. LOD. Positional Cloning. Genetics. Chromosome Region. Association Study. Sib pairs. Genomics.

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Some current issues in QTL identification

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  1. Some current issues in QTL identification Lon Cardon Wellcome Trust Centre for Human Genetics University of Oxford Acknowledgements: Goncalo Abecasis Stacey Cherny Twin course faculty

  2. LOD Positional Cloning Genetics Chromosome Region Association Study Sib pairs Genomics Candidate Gene Selection/ Polymorphism Detection Mutation Characterization/ Functional Annotation Physical Mapping/ Sequencing

  3. Inflammatory Bowel Disease Genome Screen Hampe et al., Am J Hum Genet, 64:808-816, 1999

  4. Inflammatory Bowel Disease Genome Screen Hampe et al., Am J Hum Genet, 64:808-816, 1999

  5. Susceptibility locus mapped for Crohn’s Disease

  6. Genome Screens for Linkage in Sib-pairs 1997/98 1999 - Diabetes (IDDM + NIDDM) - Asthma/atopy - Osteoporosis - Obesity - Multiple Sclerosis - Rheumatoid arthritis - Systemic lupus erythematosus - Ankylosing spondylitis - Epilepsy - Inflammatory Bowel Disease - Celiac Disease - Psychiatric Disorders (incl. Scz, bipolar) - Behavioral traits (incl. Personality, panic) - others missed... • - NIDDM • Asthma/atopy • Psoriasis • Inflammatory Bowel Disease • - Osteoporosis/Bone Mineral Density • - Obesity • - Epilepsy • - Thyroid disease • - Pre-eclampsia • - Blood pressure • - Psychiatric disorders (incl. Scz, bipolar) • Behavioral traits (incl. smoking, alcoholism, • autism) • - Familial combined hyperlipidemia • - Tourette syndrome • - Systemic lupus erythematosus • - others missed…

  7. 0 Well, at least < 5 Human QTL Linkage  Gene Identification Successes

  8. Why so few successes in human QTL mapping? • Many valid reasons proposed: • Phenotypic complexity (not measured well) • Genetic complexity (many genes of small effect, GxE, • epistasis) • Genotype error • Sampling design • Statistical methods • …. Most linkage studies have been under-powered (and over-hyped)

  9. QTL Mapping has very low power ! 1000 sibs, no parents: markers every 10 cM, each marker H=0.8 QTL h2=0.33 Kruglyak L, Lander ES. (1995). Am J Hum Genet 57: 439-454

  10. Increasing power to detect linkage in sib-pairs • Phenotypic selection • Carey & Williamson, 1991, AJHG • Eaves & Meyer, 1994, Behav Genet • Cardon & Fulker, 1994, AJHG • Risch & Zhang, 1996, AJHG

  11. Information Score for Additive Gene Action (p=0.5) 350 300 250 Information score 200 150 100 10 8 6 1 2 3 Sib 2 4 4 5 6 7 2 8 9 10 Decile ranking - Sib 1

  12. Linkage Analysis of QTLs-Summary- • Spotted history. Few, if any, bona fide successes • Power has been large problem • Of the few replicated loci, most have used some form of selection • EDAC, other selection schemes from large cohorts now underway • Genome-scans coming soon • Promising beginning for QTL linkage mapping

  13. LOD Positional Cloning Genetics Chromosome Region Association Study Sib pairs Genomics Candidate Gene Selection/ Polymorphism Detection Mutation Characterization/ Functional Annotation Physical Mapping/ Sequencing

  14. Association Analysis • Simple genetic basis • Short unit of resemblance • Population-specific • One of easiest genetic study • designs • Correlate allele frequencies with traits/diseases • At core of monogenic & oligo/polygenic trait models • Widely used in past 20 years • HLA, candidate genes, pharmacogenetics, positional cloning

  15. Angiotensin-1 Converting Enzyme Keavney et al. (1999) Hum Mol Gen, 7:1745-1751

  16. T-5991C T-3892C T-93C G2215A G2350A A-5466C A-240T T1237C I/D 4656(CT)3/2 Evidence for Linkage

  17. T-5991C T-3892C T-93C G2215A G2350A A-5466C A-240T T1237C I/D 4656(CT)3/2 Results of ACE analysis using VC association model

  18. Alzheimers and ApoE4 Roses, Nature 2000

  19. Association Resolution by Position Roses, Nature 2000

  20. Decay of Linkage Disequilibrium in a Small Set of Genes

  21. Toward a linkage disequilibrium map of the human genome LD/haplotype map objective: find regions of high and low ancestral conservation to clarify signal/noise in allelic association studies History of LD studies in humans: • > 10 year ago, emphasis mainly on theory • LD measures, decay, population comparisons, … • 1989: 1st use of LD for disease mapping: Cystic Fibrosis • Recent years, gene-based haplotypes used widely for monogenic mapping • Last 2 years: larger scale assessment of common alleles • in reference populations

  22. Reich et al, Nature 2001 Eaves et al, Nat Genet 2000 Taillon-Miller et al, Nat Genet 2000 Haplotype Map: Data/Interpretations Distribution of pairwise LD  ‘average extent of LD’ LD differences in genes Stephens et al, Science 2001 Johnson et al, Nat Genet 2001 Abecasis et al, AJHG 2001

  23. Haplotype Map: Data/Interpretations Local patterns of LD … Conserved haplotype segments ... ‘Blocks’ 5q31. Daly et al, Nat Genet 2001 MHC class II. Jeffreys et al, Nat Genet 2001 Chr21. Patil et al, Science 2001

  24. Current Status: Data/Interpretations • How to define ‘useful’ LD is still unclear • Easier to focus on pairwise LD rather than haplotypes. • Is this efficient? • For common alleles, D’ measure, LD extends ~ 50-60 kb on average • For rare alleles, ? • There is great variability in regional patterns of LD • Explanations, predictors yet unknown • Haplotype blocks are detectable and present broadly • Size of blocks? How best to define them? Utility of htSNPs?

  25. Human Genome Haplotype Map • NIH/TSC/Wellcome Trust funded international collaboration (likely) • follow-on from human sequencing project & SNP consortium • Hierarchical strategy • ‘sparse-map’ then more fine • Initially use available SNPs • Multiple populations • some family-based, most likely to be unrelateds • Aim is to catalog regions of high LD down to very fine-scale (ie., find big and small blocks)

  26. Human Chromosome 22 • First human chromosome to be “fully” sequenced • Extensive knowledge of genomic landscape • Abundance of SNPs and other variants/bp ~34.5 Mb on q-arm; p-arm mostly structural RNA; 679 genes on q Dunham et al, Nature, 1999

  27. Samples • 7 x 3 generation CEPH families • 77 Individuals • 59 founder chromosomes • 1505 SNPs successfully genotyped • 90 Unrelated Caucasian Individuals • 1286 SNPs genotyped (1261 overlapping with CEPHs) • 51 Unrelated Estonian Individuals • 908 SNPs genotyped (594 overlapping with CEPHs)

  28. N = 1505 markers. Median spacing = 15.07kb. 4 gaps > 200 kb. Smallest = 12 bp; largest = 293 kb.

  29. N=1505

  30. Variability in Pairwise LD D’ r2

  31. Decay of LD on chromosome 22 Means inCEPHs, Unrelateds, Combined &EstonianSamples

  32. Representing LD along a chromosome • Following several trends in genetics, genotyping technology outpaced ability to analyze LD information… • How to characterize regions of ‘interesting’ linkage disequilibrium? • Simply examine average levels across region/chromosome? • Fit models to data, look at expectations & specific predictions • Consider ‘interesting’ LD tracts as long runs of LD – borrow from extant statistical approaches • Look for ‘blocks’ of LD in the genome

  33. LD Along Chromosome 22 Average D’ D’ Half-Life Disequilibrium Fingerprint

  34. Chromosome 22 Haplotype Blocks Plus 3 individual blocks: Position SNPs Haplos Length 4.6-4.8 M 11 6 231 kb 8.2-8.4 M 8 4 264 kb 34.3 M 11 3 82 kb

  35. Chr22 High LD: 22-27 Mb

  36. Chr22 Low LD: 27-32 Mb

  37. Microsatellite distance 1 Mb/cM Recombination Pattern on Chromosome 22 60 50 40 cM 30 20 10 0 0 5 10 15 20 25 30 35 Sequence Position (Mb)

  38. Microsatellite distance 1 Mb/cM Recombination and Gene Density on Chromosome 22 Gene Density

  39. Linkage Disequilibrium Map of Chromosome 22 - Summary - • LD ‘half-length’ ~ 50 kb, but depends on measure & what is “useful” LD • Family & unrelated samples yield consistent patterns • Different analytical tools provide complementary views of long blocks • 15% chromosome 22 in long LD blocks in these samples (40% in shorter blocks) • Why? Selection, selective sweeps? Chromosome structure? Popln age? • LD correlated with gene-density, GC content and related repeats. • Gene/GC correlations almost entirely collinear with genetic distance. • LD patterns can immediately assist positional association studies: • Prioritise candidate regions. • Use extant genetic maps and simple repeat structures in design & power.

  40. Mapping QTLs in families: Summary • Linkage and association studies follow directly from fundamental biometrical principles. • Linkage studies of complex traits can work: All principles of this course apply • - power, study design, careful phenotype selection/modelling, • comparison of statistical models • New information about LD patterns should facilitate association studies • - help form a priori hypotheses and guide replication. 16th Annual Course on Methodology for Twins and Families Advanced workshop: Boulder, Colorado, March 2003

  41. http://ibgwww.colorado.edu/twins2001/schedule.html

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