qtl studies: past, present and future nick martin queensland institute of medical research boulder...
TRANSCRIPT
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QTL studies: past, present and future
Nick MartinQueensland Institute of Medical Research
Boulder workshop: March 10, 2006
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Using genetics to dissect metabolic pathways: Drosophila eye color
Beadle & Ephrussi, 1936
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Beadle and Ephrussi, 1936
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First (unequivocal) positional cloning of a complex disease QTL !
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Finding QTLs
Linkage
Association
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Linkage analysis
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Thomas Hunt Morgan – discoverer of linkage
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Linkage = Co-segregation
A2A4
A3A4
A1A3
A1A2
A2A3
A1A2 A1A4 A3A4 A3A2
Marker allele A1
cosegregates withdominant disease
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Linkage Markers…
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For continuous measures
Unselected sib pairs1.00
0.25
0.75
0.50
IBD = 0 IBD = 1 IBD = 2
Co
rre
lati
on
be
twee
n s
ibs
0.00
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Human OCA2 and eye colour
Zhu et al., Twin Research 7:197-210 (2004)
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First genome-wide linkage scan for Intelligence
Posthuma et al., AJHG, in press
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VAR 1 VAR 2 VAR 3
G
G G G
E
E E E
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Effect of multivariate analysis on linkage power
Am. J. Hum. Genet., 72:561-570, 2003
Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait
Angela Marlow, Simon Fisher, Clyde Francks, Laurence MacPhie, Stacey Cherny, Alex Richardson, Joel Talcott, John Stein, Anthony Monaco, and Lon Cardon
Multivariate and univariate linkage analysis of six reading-related measures on chromosome 18
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0
1
2
3
4
5
0 20 40 60 80 100
0
0.25
0.5
0.75
1E
mp
iric
al p
oin
twis
e-l
og10P
Information content
cM
Chromosome 20
D20
S17
3D
20S
171
UT
1772
TT
TA
093
UT
254
D20
S10
0G
AT
A45
B10
D20
S19
6T
AT
T03
1A
AT
269
D20
S17
8
AD
AM
33
House dust miteAtopy
Bronchial Hyperrespons.FEV1
AsthmaAirway Obstruction
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European Journal of Human Genetics (almost in press)
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Ridge count
The size of prints can be measured by counting the number of ridges from the triradii to the core
Ridge count can be summed over all fingers to give a total ridge count Diagram from Holt, 1968
Highly heritable:MZ r = .94 CI .89 - .96
DZ r = .42 CI .34 - .50
A .82 CI .56 - .95
D .11 CI .00 - .37
E .07 CI .05 - .10
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TRC vs Multivariate (-LOG10p)
(Univariate , Multivariate )21 2
5
Univariate
Multivariate
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Chromosome 1Similar ‘drop chi-squares’for pleiotropic QTLs
Resulting in a very
conservative test
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Chromosome 7 …
Evidence of
developmental fields?
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Science 268: 1584-1589 (1995)
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1 2 3 4 5 6 7 8 9 102
46
810100
150
200
250
300
350
Decile ranking - Sib 1
Sib 2
Info
rma
tio
n s
core
Information Score for Additive Gene Action (p=0.5)
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Distribution of entire sample Distribution of selected sample
Scatterplots of the distribution of neuroticism scores for each sibling pair
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Am. J. Hum. Genet., 72:000, 2003Linkage Analysis of Extremely Discordant and Concordant Sibling Pairs Identifies Quantitative-Trait Loci That Influence Variation in the Human Personality Trait Neuroticism Jan Fullerton, Matthew Cubin, Hemant Tiwari, Chenxi Wang, Amarjit Bomhra, Stuart Davidson, Sue Miller, Christopher Fairburn, Guy Goodwin, Michael Neale, Simon Fiddy, Richard Mott, David B. Allison, and Jonathan Flint
The -logP values (vertical axis) for the Visscher-Hopper regression are shown. The cumulative distance is given at the bottom, and chromosome numbers are given at the top. The two dotted, horizontal lines represent the empirically derived genome wide significance thresholds (5% and 1%).
Multipoint linkage analysis of the genome for individual variation in neuroticism
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Limits of fine mapping a quantitative traitAttwood LD & Heard-Costa NL. Genetic Epidemiology 24:99-106, 2003
Information for marker density 0.5, 1, 2, 10cM scan
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Twin 1 pheno-
type
Twin 2pheno-
type
E
D
A
Q Q
A
D
ErMZ = 1, rDZ = ̂
rMZ = 1, rDZ = 0.5
rMZ = 1, rDZ = 0.25
q q
a a
c ce e
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But why do we use the average sib values of
ra = 0.5 rd = 0.25
when we can estimate the (almost) exact values for each sib pair from marker data ?
Are there any advantages in doing so ?
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Mean IBD sharing across the genome for the jth sib pair was based on IBD estimated from Merlin every
centimorgan and averaged at all 3491 points
3491/ˆˆ3491
1)()(
i
ijaja
3491/ˆ3491
1)(2)(
i
ijjd p
additive
dominance
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Application
• Phenotype = height
Number of sibpairs with phenotypesand genotypes
Adolescent cohort 931Adult cohort 2444Combined 3375
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Mean and SD of genome-wide additive relationships
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Mean and SD of genome-wide dominance relationships
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Additive and dominance relationships correlation = 0.91 (n= 4401)
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Models
F = Family effect
A = Genome-wide additive genetic
E = Residual
Full model F + A + E
Reduced model F + E)(ˆ ja
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Cohort F+A (95% CI)
Adolescent 0.80 (0.36 – 0.90)
Adult 0.80 (0.61 – 0.86)
Combined 0.80 (0.62 – 0.85)
►Estimates of MZ correlation from fullsibs!PLOS Genetics, in press
Sampling variances are large
And now for IQ! Anyone got sibpairs with IQ + genome scan?
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Linkage
Doesn’t depend on “guessing gene” Works over broad regions (good for getting
in right ball-park) and whole genome (“genome scan”)
Only detects large effects (>10%) Requires large samples (10,000’s?) Can’t guarantee close to gene
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Association More sensitive to small effects Need to “guess” gene/alleles
(“candidate gene”) or be close enough for linkage disequilibrium with nearby loci
May get spurious association (“stratification”) – need to have genetic controls to be convinced
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Variation: Single Nucleotide Polymorphisms
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Melanoma genome-wide association study
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Comparison of Affymetrix 10k, 100k, 500k SNP chips
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• Examined expression levels of ~8000 genes on CEPH families– Used expression levels as ‘phenotypes’– Linked expression phenotypes with CEPH microsatellites
• Found evidence for linkage for many phenotypes• Follow-up SNP genotyping also showed some association
• Found many cis- linkages (linkage region overlaps location of gene whose expression is phenotype), but also many trans
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No LinkageNo Association
Linkage genome scan4,000 highly polymorphic markers
Association genome scan1,000,000 diallelic markers
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+ LinkageNo Association
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+ Linkage+ Association
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No Linkage+ Association
Yes, genome-wide association will work (…sometimes…)
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Challenges to come?
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Role of miRNA (binding sites) in disease ?
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Comparative Genomics= differences in DNA sequence Human-Human 1:1000 = 0.1%
Human-Mouse 1:8 = 15%
Human-Chimp 1:100 = 1%
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Which genes have evolved fastest?
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Even for “simple” diseasesthe number of alleles is large
Ischaemic heart disease (LDR) >190 Breast cancer (BRAC1) >300 Colorectal cancer (MLN1) >140
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[Science 2004]
Complex disease: common or rare alleles?
Increasing evidence for Common Disease – Rare Variant
hypothesis (CDRV)
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EPIGENETIC DISCORDANCE IN
IDENTICAL TWINS
The missing “environment” ?
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Discordant caudal duplication in MZ twins1 2 3 4 5 6 7 8 9 10 11LTR
CpG Island
308 bp
181 bp
Axin
Twin 1- unaffected < Twin 2 - affected > Controls [e.g.]
Emma Whitelaw, Suyinn Chong Department of Biochemistry
University of Sydney
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Other studies on MZ discordance Epilepsy (with S. Berkovic, L. Vadlamudi)
Schizophrenia (with B.Mowry, N.Hayward)
Depression (with A. Petronis, D. Boomsma, P. McGuffin)
Asthma (with M.Ferreira, E.Whitelaw)
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Per ardua ad astra
(Through hard work to the **genesgenes**)