qtl studies: past, present & (bright?) future. overview a brief history of ‘genetic...
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QTL studies: past, present & (bright?)
future
Overview
• A brief history of ‘genetic variation’• Summary of detected QTL
– plants– livestock– humans
• Modelling distribution of QTL effects• From QTL to causal mutations• Three success stories
[Galton, 1889]
(early 1900s)Inheritance of quantitative traits
Biometricians vs. Mendelians
(Pearson) (Bateson)
The height vs. pea debate
Do continuously varying traits have the same hereditary and evolutionary properties as discrete characters?
Yes!
t
m-a m+d m+a
Trait
m-a m+d m+a
Trait
[Fisher, Wright]
Multiple-factor hypothesis• (Many) independently segregating loci
– Continuous (Gaussian) distribution of genotypes
• Environmental variation– ‘Regression towards mediocrity’ [Galton, 1889]
• trait in progeny is not the average of trait in parents • R = h2 S
• Linear models & multivariate normality– Livestock breeders [Henderson]– BLUP(A)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Fre
qu
ency
-3 -2 -1 0 1 2 3
Genotype value
Three bi-allelic additive loci
©Jeremy Stockton
©Roslin Institute
Lynch & Walsh (1998)
• Summary of 52 experiments (222 traits), mostly from inbred founder lines– in 45% of traits a QTL explaining >20% of
phenotypic variation– in 84% of traits all QTLs explained >20% of
the phenotypic variation– in 33% of traits all QTLs explained >50% of
the phenotypic variation
Reported QTL in pigs
• 15 experimental crosses– N from 200 to 1000
• multiple QTL for growth, fatness, carcass traits and reproduction
• nearly all chromosomes covered
• QTL explain 3 to 20% of F2 variance
[Bidanel & Rothschild 2002]
A90k
A17w
L 14w
R 14w
A40k
A
L 14w
A40k
A17w
A40k
A17w
A100k
A22w
A60k
A95k
....
R 26w
L 100k
A40k
A,L,T,F
L 14w
A95k
A95k
A22w
A105k
A90
L 115k
M95k
R 14w
A115k
A80k
A70k
A85k
A100k
A70k
A70k
A60k
R 100k
A13w
F100k
X2 80k
R 115k
T100k
A100k
L 100k
T115k
A115k
A70k
S,M,
A80k
L 100k
A90k
A80
A60k
A13w
A115k
L 115k
A90k
A110k
A80k
L 14w
R 115k
A13w
A90k
R 115k
L 115k
A90k
T115k
L 115k
A115k
A90k
L 115k
A17w
A115k
MC4R
IGF2
RN
RYR1
HFAB
0
20
40
60
80
100
120
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160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 X
Leng
th (c
M)
SSC
Xyz : X = A (average), L (lumbar), R (last rib), T (tenth-rib), S (shoulder), M (mid-back), F (first-rib) backfat thickness at xx kg (k) or xx weeks (w) of age; Locus names (in bold characters) : MC4R = melanocortin-4 receptor locus; IGF2 = insulin growth factor 2; RYR1 = ryanodine receptor locus ; HFAB = heart fatty acid binding protein locus; PIT1 = regulatory factor locus; RN = “acid meat” locus.
Backfat thickness
[Bidanel & Rothschild 2002]
How many QTLs are there and how many can we detect?
• Theory– Distribution of effects & experimental sample
size (Otto & Jones, 2000)
• Data– Model reported QTL effects from experiments
(Hayes & Goddard 2001)
Potential distributions of allelic effects. Each curve describes a gamma distribution with mean µ = 1 but with different coefficients of variation (C). The QTL underlying a particular phenotypic difference represent draws from the appropriate distribution, as illustrated by the circles under the x-axis. Only those QTL above the threshold of detection ( = 0.8, thin vertical line) are likely to be detected (solid circles). Those below the threshold are likely to remain undetected (open circles).
[Otto & Jones 2000]
The expected number of detected loci as a function of the number of underlying loci. The expected number of detected loci is equal to n times the fraction of the probability density function, g[x, µ, C] given by (13), that lies above . It is plotted as a function of the number of underlying loci for a bell-shaped distribution (C = 0.5; dot-dashed curve), an exponential distribution (C = 1; solid curve), and an L-shaped distribution (C = 2; dashed curve). (A) = 10% of D, as was typical in our studies with a large number of QTL and 200 F2's. (B) = 5% of D, as was
typical in our studies with a large number of QTL and 500 F2's.
[Otto & Jones 2000]
Distribution of QTL effects in livestock
0
1
2
3
4
5
0 0.25 0.5 0.75 1 1.25 1.5
Effect (phenotypic SD)
De
ns
ity
[Hayes and Goddard, 2001]
Proportion of genetic variance explained by QTLs
0
10
20
30
40
50
60
70
80
90
100
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Size of QTL (phenotypic SD)
Pro
p.
va
ria
nc
e e
xp
lain
ed
by
QT
L
ab
ov
e t
his
siz
e
[Hayes and Goddard, 2001]
From QTL to gene
• Paradigm– Linkage– Fine-mapping (IBD/LD)– Association– Function
Positional Cloning of Complex Traits
LO
D
Sib pairs Chromosome Region Association Study
Genetics
GenomicsPhysical Mapping/Sequencing
Candidate Gene Selection/Polymorphism Detection
Mutation Characterization/Functional Annotation
Identified causal polymorphisms
• 41 (< March 2004)– 31 in mammals
• 17 outbred populations– 14 in humans
– 2 in pigs (RN, IGF2)
– 1 in dairy cattle (DGAT1)
• Few ‘proven’ with functional assays or through transgenics
[Korstanje & Piagen 2001; Glazier et al. 2002]
[Korstanje & Piagen 2002]
Identified QTLs in mammals
[Korstanje & Piagen 2002]
[Glazier et al. 2002]
Botstein & Risch (2003), Nature Genetics
Is the nature of genetic variation for quantitative traitsdifferent???
Three success stories of QTL identification in farm animals
• IGF2 in pigs
• DGAT in dairy cows
• Callipyge in sheep
Van Laere et al. (2003). Nature 425:832-836
• QTL Linkage peak on chr. 2p for muscle mass– Wild Boar x Large White cross– Pietran x Large White cross
• IGF2 = candidate– IGF2 is paternally imprinted in mice and man
• QTL = paternally imprinted– Sire’s allele expressed
[Nezer et al. 1999; Jeon et al. 1999]
Effects etc.
• Wild boar cross– 20-30 % of variance explained– ~3% difference in Lean Meat %
• Pietran cross– ~2% difference in % Lean Cuts– ~5 mm difference in backfat
• Confidence interval ~4 cM (= small!!!)• No sequence variants in coding parts of IGF2
could explain the observed effects
[Nezer et al. 1999]
Fine-mapping using haplotype sharing (Nezer et al. 2003)
• Marker-assisted segregation analysis– Assume bi-allelic QTL
– Assume that ‘favourable’ allele Q appeared by mutation or migration ~50-100 years ago
– Assume known effect (2% of ‘lean cuts’)
– Determine QTL genotype status of 20 boars
– Look for shared haplotype on Q chromosomes
• Identified shared haplotype of ~250 kb– Contained 2 paternally imprinted genes (INS and IGF2)
Qq boars
Q
q
QQ or qq boars
Genotype deducedFrom Qq haplotypes
All Q chromosome share a 90 kb common haplotype notpresent on q chromosomes
[Nezer et al. 2003]
Resequencing 3 Q and 8 q chromosomes for 28.5 Kb spanning INS-IGF2 identifies 33 putative QTN
[M. Georges]
Resequencing a heterozygous, non-segregating Hampshire sire identifies a recombination excluding TH-IGF2(I1) (- 9 candidate QTN)
[M. Georges]
Resequencing a heterozygous, non-segregating Large White x Meishan sire identifies the QTN
[M. Georges]
Pig-q AGCCAGGGACGAGCCTGCCCGCGGCGGCAGCCGGGCCGCGGCTTCGCCTAGGCTCGCAGCGCGGGAGCGCGTGGGGCGCGGCGGCGGCGGGGAGPig-Q .......................................................A......................................Human ....G.....T.......T.C...T...G..TC...............................AG...A.........A.T....AG......Mouse ...T.........T......C.......T...T....C..A................G...TCT...............A.G............
INS IGF2TH
12 3 1 2 3 4a 54b 6 7 8 9
CpGislandDMR1
q
Q
P208 (ref.)
LW3
LRJ
H205
H254
M220
LW1224
LW1461
LW209
LW419
LW197
EWB
LW33361
LW463
JWB
%(G+C)
Genes
Van Laere, Fig. 1A
SWC9
14
QTN is guanine to adenine substitution in IGF2-intron3 nucleotide 3072
DGAT in dairy cows
• Genome scan suggested QTL for fat% in milk on chromosome 14
• IBD fine-mapping reduced region to 3 cM
• Association / linkage disequilibrium identifies causative mutation
• Mutation is an amino acid changing SNP in the DGAT1 gene
There are large QTL out there!
QTL explains > 50% (!) of genetic variance in fat%QTL allele is commonQTL acts additively
Callipyge mutation in sheep(major gene, not QTL)
Gene action: “Polar overdominance”
[Freking et al. 1998][1st allele from dad 2nd from mum]
Callipyge summary
• Gene action impossible to work out without genetic markers
• Causal mutation is non-coding
• How common is imprinting for QTL?
[Glazier et al. 2002]