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

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

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

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

Susceptibility locus mapped for Crohn’s Disease

Genome Screens for Linkage in Sib-pairs 1997/98 - 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…

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

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)

QTL Mapping has very low power ! 1000 sibs, no parents: markers every 10 cM, each marker H=0.8 QTL h 2 =0.33 Kruglyak L, Lander ES. (1995). Am J Hum Genet 57:

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 Equivalent full sample N for 200 selected pairs from 10,000 (QTL allele freq =.2) ConcordantDiscordantCombined Additive Recessive Dominant

Decile ranking - Sib 1 Sib 2 Information score Information Score for Additive Gene Action (p=0.5)

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

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

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

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

Evidence for Linkage A-5466CA-240TT1237CI/D4656(CT)3/2 T-5991CT-3892CT-93CG2215AG2350A

Results of ACE analysis using VC association model A-5466CA-240TT1237CI/D4656(CT)3/2 T-5991CT-3892CT-93CG2215AG2350A

Alzheimers and ApoE4 Roses, Nature 2000

Association Resolution by Position Roses, Nature 2000

PPAR  and NIDDM Altshuler et al Nat Genet 2000 ACE and MI Keavney et al Lancet 2000

Relationship Between LD and Physical Distance

Decay of Linkage Disequilibrium in a Small Set of Genes

Toward a linkage disequilibrium map of the human genome > 10 year ago, emphasis mainly on theory - LD measures, decay, population comparisons, … 1989: 1 st 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 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:

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

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

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 ~ 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?

Human Genome Haplotype Map 1.NIH/TSC/Wellcome Trust funded international collaboration (likely) -follow-on from human sequencing project & SNP consortium 2.Hierarchical strategy -‘sparse-map’ then more fine -Initially use available SNPs 3.Multiple populations -some family-based, most likely to be unrelateds 4.Aim is to catalog regions of high LD down to very fine-scale (ie., find big and small blocks)

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

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)

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

N=1505

D’ r2r2 Variability in Pairwise LD

Decay of LD on chromosome 22 Means in CEPHs, Unrelateds, Combined & Estonian Samples

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? 1.Simply examine average levels across region/chromosome? 2.Fit models to data, look at expectations & specific predictions 3.Consider ‘interesting’ LD tracts as long runs of LD – borrow from extant statistical approaches 4.Look for ‘blocks’ of LD in the genome

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

Plus 3 individual blocks: PositionSNPsHaplosLength M kb M kb 34.3 M kb Chromosome 22 Haplotype Blocks

Chr22 High LD: Mb

Chr22 Low LD: Mb

Recombination Pattern on Chromosome 22 1 Mb/cM Microsatellite distance Sequence Position (Mb) cM

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

Correlations between LD and Sequence Features Correlations refer to all informative (freq >.20) marker pairs within 150 kb

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.

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. 16 th Annual Course on Methodology for Twins and Families Advanced workshop: Boulder, Colorado, March 2003