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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

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

Candidate Gene Selection/

Polymorphism Detection

Mutation Characterization/

Functional Annotation

Physical Mapping/

Sequencing


Inflammatory Bowel Disease Genome Screen

Hampe et al., Am J Hum Genet, 64:808-816, 1999


Inflammatory Bowel Disease Genome Screen

Hampe et al., Am J Hum Genet, 64:808-816, 1999



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…


Human qtl linkage gene identification successes

0

Well, at least < 5

Human QTL Linkage  Gene Identification Successes


Why so few successes in human qtl mapping
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

h2=0.33

Kruglyak L, Lander ES. (1995). Am J Hum Genet 57: 439-454


Increasing power to detect linkage in sib pairs
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


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


Linkage analysis of qtls summary
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


LOD

Positional Cloning

Genetics

Chromosome Region

Association Study

Sib pairs

Genomics

Candidate Gene Selection/

Polymorphism Detection

Mutation Characterization/

Functional Annotation

Physical Mapping/

Sequencing


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, 7:1745-1751


Evidence for linkage

T-5991C

T-3892C

T-93C

G2215A

G2350A

A-5466C

A-240T

T1237C

I/D

4656(CT)3/2

Evidence for Linkage


Results of ace analysis using vc association model

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


Alzheimers and ApoE4

Roses, Nature 2000




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


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


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 ~ 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?


  • 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)


Human chromosome 22
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
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.




Decay of LD on chromosome 22

Means inCEPHs, Unrelateds, Combined &EstonianSamples


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


Ld along chromosome 22
LD Along Chromosome 22

Average D’

D’ Half-Life

Disequilibrium Fingerprint


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




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)


Microsatellite distance

1 Mb/cM

Recombination and Gene Density on

Chromosome 22

Gene

Density


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.

16th Annual Course on Methodology for Twins and Families

Advanced workshop: Boulder, Colorado, March 2003



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