Dissecting and fine-mapping trans-eQTL hotspotskbroman/presentations/ncsu2017.pdf · Dissecting and...
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Dissecting and fine-mapping trans-eQTL hotspots Karl Broman Biostatistics & Medical Informatics University of Wisconsin–Madison, USA kbroman.org github.com/kbroman @kwbroman Slides: bit.ly/ncsu2017
Transcript of Dissecting and fine-mapping trans-eQTL hotspotskbroman/presentations/ncsu2017.pdf · Dissecting and...
Dissecting and fine-mappingtrans-eQTL hotspots
Karl Broman
Biostatistics & Medical InformaticsUniversity of WisconsinMadison, USA
kbroman.orggithub.com/kbroman@kwbromanSlides: bit.ly/ncsu2017
http://kbroman.orghttps://github.com/kbromanhttps://twitter.com/kwbromanhttp://bit.ly/ncsu2017
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daviddeen.com
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http://daviddeen.com
Intercross
P1 P2
F1 F1
F2
4
QTL mapping
0
2
4
6
8
Chromosome
LOD
sco
re
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
5
QTL mapping
0
2
4
6
8
Chromosome
LOD
sco
re
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
BB BR RR
0.8
0.9
1.0
1.1
5
6
B6 BTBR, Lepob/obislet
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
7
B6 BTBR, Lepob/obislet
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
adipose
QTL position (cM)P
robe
pos
ition
(cM
)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
gastroc
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
hypo
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
kidney
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
liver
QTL position (cM)
Pro
be p
ositi
on (
cM)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1516171819
X
8
Chr 6islet
LOD
sco
re
0 20 40 60 80 1000
25
50
75
100
125
150
175
Position (cM)
adipose
LOD
sco
re0 20 40 60 80 100
0
25
50
75
100
125
150
175
Position (cM)
gastroc
LOD
sco
re
0 20 40 60 80 1000
25
50
75
100
125
150
175
Position (cM)
hypo
LOD
sco
re
0 20 40 60 80 1000
25
50
75
100
125
150
175
Position (cM)
kidney
LOD
sco
re
0 20 40 60 80 1000
25
50
75
100
125
150
175
Position (cM)
liver
LOD
sco
re0 20 40 60 80 100
0
25
50
75
100
125
150
175
Position (cM)
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Consider the non-recombinants
QTL
10
Consider the non-recombinants
QTL
10
Islet c6 PCs
Principal component 1
Prin
cipa
l com
pone
nt 2
3 2 1 0 1 2 3
0.8
0.6
0.4
0.2
0.0
0.2
0.4
0.6
0.8
1.0
BB
BR
RR
11
Islet c6 PCs
Principal component 1
Prin
cipa
l com
pone
nt 2
3 2 1 0 1 2 3
0.8
0.6
0.4
0.2
0.0
0.2
0.4
0.6
0.8
1.0
BB
BR
RR
recombinant
11
Fine-mapping the c6 locus
Mouse
Pos
ition
(M
bp)
145.73144.91
141.52
135.27
QTL
BB BR RR
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Fine-mapping the c6 locus
Mouse
Pos
ition
(M
bp)
145.73144.91
141.52
135.27
QTL
BB BR RR
Mouse
Pos
ition
(M
bp)
145.24
142.42
141.52
139.94
QTL
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Fine-mapping the c6 locus
Mouse
Pos
ition
(M
bp)
145.73144.91
141.52
135.27
QTL
BB BR RR
Mouse
Pos
ition
(M
bp)
145.24
142.42
141.52
139.94
QTL
Mouse
Pos
ition
(M
bp)
142.42
142.28
141.97
141.52
QTL
Slco1a6
Slco1a5Iapp
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Is it one QTL?
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Consider the QTL effects
BB BR RR
d
a
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eQTL effects: Islet c6
signed LOD
QTL pos (cM)
200
150
100
50
0
50
100
150
200
75 80 85 90 95 100 105
sign
ed L
OD
sco
re
0.5 0.0 0.5
0.5
0.0
0.5
Inheritance Pattern
Additive effect
Dom
inan
ce e
ffect
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eQTL effects: Kidney c13
signed LOD
QTL pos (cM)
60
50
40
30
20
10
0
10
20
30
40
50
60
45 50 55 60 65 70 75
sign
ed L
OD
sco
re
0.2 0.1 0.0 0.1 0.2
0.2
0.1
0.0
0.1
0.2
Inheritance Pattern
Additive effect
Dom
inan
ce e
ffect
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eQTL effects: Islet c2
signed LOD
QTL pos (cM)
150
100
50
0
50
100
150
45 55 65 75 85 95
sign
ed L
OD
sco
re
0.2 0.1 0.0 0.1 0.2
0.2
0.1
0.0
0.1
0.2
Inheritance Pattern
Additive effect
Dom
inan
ce e
ffect
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eQTL effects: Liver c17
signed LOD
QTL pos (cM)
150
100
50
0
50
100
150
6 8 10 14 18 22 26
sign
ed L
OD
sco
re
0.4 0.2 0.0 0.2 0.4
0.4
0.2
0.0
0.2
0.4
Inheritance Pattern
Additive effect
Dom
inan
ce e
ffect
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eQTL effects: Adipose c10
signed LOD
QTL pos (cM)
200
150
100
50
0
50
100
150
200
38 42 46 50 54 58
sign
ed L
OD
sco
re
0.4 0.2 0.0 0.2 0.4
0.4
0.2
0.0
0.2
0.4
Inheritance Pattern
Additive effect
Dom
inan
ce e
ffect
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Compare the recombinantsand non-recombinants.
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LDA & PCA: Islet c6
Linear Discriminant 1
Line
ar D
iscr
imin
ant 2
15 10 5 0 5 10 15
4
2
0
2
LDA
Principal Component 1
Prin
cipa
l Com
pone
nt 2
3 2 1 0 1 2 3
1.0
0.5
0.0
0.5
1.0
PCA
BB BR RR Recombinant
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LDA & PCA: Islet c2
Linear Discriminant 1
Line
ar D
iscr
imin
ant 2
10 5 0 5 10
2
0
2
4
6
LDA
Principal Component 1
Prin
cipa
l Com
pone
nt 2
1.5 1.0 0.5 0.0 0.5 1.0 1.5
0.5
0.0
0.5
PCA
BB BR RR Recombinant
22
LDA & PCA: Kidney c13
Linear Discriminant 1
Line
ar D
iscr
imin
ant 2
6 4 2 0 2 4
2
0
2
4
LDA
Principal Component 1
Prin
cipa
l Com
pone
nt 2
3 2 1 0 1 21.0
0.5
0.0
0.5
1.0
PCA
BB BR RR Recombinant
23
LDA & PCA: Liver c17
Linear Discriminant 1
Line
ar D
iscr
imin
ant 2
5 0 5 10
2
0
2
4
LDA
Principal Component 1
Prin
cipa
l Com
pone
nt 2
2 1 0 1 2
1.5
1.0
0.5
0.0
0.5
1.0
PCA
BB BR RR Recombinant
24
LDA & PCA: Adipose c10
Linear Discriminant 1
Line
ar D
iscr
imin
ant 2
5 0 5 1010
5
0
5
LDA
Principal Component 1
Prin
cipa
l Com
pone
nt 2
1 0 1 2 3
1.0
0.5
0.0
0.5
1.0
PCA
BB BR RR Recombinant
25
Formal test for 1 vs 2 QTL
Consider a set of traits mapping to common eQTL
Multivariate QTL analysis with 1 or 2 QTL
With 2-QTL model, each trait affected by one or theother QTL
Order traits by estimated QTL location when consideredseparately
Consider cut points of the list, assign first group to oneQTL and second group to other.
P-value: parametric bootstrap or stratifiedpermutation
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1 vs 2 QTL: Kidney c13
LOD profile
Map position (cM)
LOD
sco
re
50 55 60 650
50
100
150
200
LOD diff by cutpoint
cut point
LOD
diff
10 20 30 400
10
20
30
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1 vs 2 QTL: Islet c6
LOD profile
Map position (cM)
LOD
sco
re
80 85 90 950
100
200
300
LOD diff by cutpoint
cut point
LOD
diff
10 20 30 400.0
0.5
1.0
1.5
2.0
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1 vs 2 QTL: Islet c2
LOD profile
Map position (cM)
LOD
sco
re
50 60 70 80 900
100
200
300
400
LOD diff by cutpoint
cut point
LOD
diff
10 20 30 400
20
40
60
80
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1 vs 2 QTL: Liver c17
LOD profile
Map position (cM)
LOD
sco
re
5 10 15 20 250
50
100
150
200
250
LOD diff by cutpoint
cut point
LOD
diff
10 20 30 400
5
10
15
20
25
30
1 vs 2 QTL: Adipose c10
LOD profile
Map position (cM)
LOD
sco
re
40 45 50 550
100
200
300
400
500
LOD diff by cutpoint
cut point
LOD
diff
10 20 30 400
20
40
60
80
100
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Summary Fine-mapping a trans-eQTL hotspot
Consider the non-recombinants Predict QTL genotype of recombinants
Mendelian trait Fine-map by traditional means
Large-effect locus on chr 6 Affects expression of 8% of genes Effects specific to pancreatic islets Looks to be Slco1a6
Dissecting a trans-eQTL hotspot Sign of eQTL effect Degree of dominance Compare recombinants and non-recombinants Formal statistical test
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AcknowledgmentsUniv. WisconsinMadison
Jianan Tian Brian YandellAlan Attie Angie OlerMark Keller Mary RabagaliaAimee Teo Broman Kathryn SchuelerChristina Kendziorski Donald Stapleton
Univ. Kansas Medical CenterBruno Hagenbuch Wen Zhao
Merck & Co., Inc.Amit Kulkarni
Mt. SinaiEric Schadt
NIH: R01 GM074244, R01 DK066369
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Slides: bit.ly/ncsu2017
kbroman.orggithub.com/kbroman@kwbroman
Tian J et al. (2015) Identification of the bile acid transporter Slco1a6as a candidate gene that broadly affects gene expression in mousepancreatic islets. Genetics 201:12531262
Tian J et al. (2016) The dissection of expression quantitative traitlocus hotspots. Genetics 202:15631574
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http://bit.ly/ncsu2017http://kbroman.orghttps://github.com/kbromanhttps://twitter.com/kwbromanhttps://www.biostat.wisc.edu/~kbroman/publications/islet_chr6.pdfhttps://www.biostat.wisc.edu/~kbroman/publications/islet_chr6.pdfhttps://www.biostat.wisc.edu/~kbroman/publications/islet_chr6.pdfhttps://www.biostat.wisc.edu/~kbroman/publications/transbandpaper_wsupp.pdfhttps://www.biostat.wisc.edu/~kbroman/publications/transbandpaper_wsupp.pdf
