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8/14/2019 2009-09-08_Wiltshire IPIT Seminar Slides
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Genetic variation in mice: modeling disease,
pharmacogenetics, and basic biology
Tim Wiltshire
School of Pharmacy
University of North CarolinaChapel Hill
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How do we efficiently annotate the function of all the genes in the mammalian
genome?
Goal: Genome-wide functional genomics
What do we know about gene function?
40234 entries in
Entrez Gene
19709 genes
(49%) have zero
linked references
31672 genes (78%) have five
or fewer linked references
Fraction of all Citations Accounted forby Highly-Cited Genes
TP53
TNF
APOE
MTHFR
HLA-DRB1
IL6
ACE
TGFB1
EGFR
VEGFA
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How should we use the genetic variation in mice as a model for
Annotating gene function and discovery in disease status,
pharmacogenetics, and basic biology?
Traditional genetics F2 crosses, recombinant inbred strains (RI),knockouts, transgenics.
Inbred strains genetic variation of the inbred strains, haplotype mapping.
New RI initiatives - A new set of comprehensive RI strains
Outbred strains most closely model human populations
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F2 Two parental strains are crossed to produce
F1 generation. Brother-sister matings of F1
mice produce F2 generation, a random
shuffling of parental strains genomes. Requires a very large set of mice (~200),
each genetically unique Utility of genotype data, which is a huge
undertaking for such a large set, is limited to
the life of the mouse
RI Two parental strains are crossed to produce
F1 generation. Brother-sister matings are
carried out for 20 generations until genomic
pattern is fixed. Each mouse from a given RI line is
genetically identical Genotyping only has to be done once and
can be applied to any phenotype Number of lines and strain crosses available
from an RI cross is limited, decreasing the
possible resolution in mapping the trait and
the number of traits that can be examined
Genetic diversity through mating
Both methods require months or
years to define candidate region
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Nature Genetics 36:1133, 2004
Mammalian Genome 13:175, 2002
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129S1/SvImJ NOD/LtJ
A/J NZO/HlLtJ
C57BL/6J PWK/PhJ
CAST/EiJ WSB/EiJ
Parental Strains
Randomization of Variation through Meiosis
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CAST WSBC57BL6 PWKA/J 129S1 NZONOD
Representative CC genome
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The CC has many Independent Iterations
High Statistical Power
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X
Infinitely Reproducible
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CC Population ~ Human PopulationCC Population ~ Human Population
SNPs Insertion/deletions
20 x 106 1 x 106
50 x 106 4 x 106
Human
CC
CAST/EiJ WSB/EiJC57BL6/J PWK/PhJA/J 129S1/SvIm NZO/HlLtNOD/Lt
Captures 90% of the variation present in the mouse!Captures 90% of the variation present in the mouse!
The variation is randomly distributed across the genomeThe variation is randomly distributed across the genome
(there are no blind spots)(there are no blind spots)
Yang et al. 2007 Nature Genetics 39, 1100Roberts et al. 2007 Mammalian Genome 18, 473
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How should we use the genetic variation in mice as a model for
disease status, pharmacogenetics, and basic biology?
Traditional genetics F2 crosses, recombinant inbred strains (RI),knockouts, transgenics.
Inbred strains genetic variation of the inbred strains, haplotype mapping.
Whole animal studies Cell-based studies mouse embryonic fibroblasts (MEFs), hepatocytes,
macrophages
New RI initiatives - A new set of comprehensive RI strains
Outbred strains most closely model human populations
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12
Inter-strain phenotypic variance
Hamilton, Frankel (Cell, 2001)Hamilton, Frankel (Cell, 2001)
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Clinical Phenotypes
0
5
10
15
20
25
30
35
A/J
CZECHII/EiJ
129S1/SvImJ
NZO/HLLTJ
LP/J
BALB/cByJ
KK/HlJ
SEA/GnJ
DBA/2J
PWD/Ph
LG/J
RIIIS/J
SM/J
CE/J
MRL/MPJ
NZB/BlNJ
CBA/J
I/LnJ
SJL/J
PL/J
AKR/J
C3H/HeJ
BUB/BnJ
SWR/J
DDY
NON/LtJ
MA/MyJ
P/J
WSB/EiJ
BTBR_
T+_
tf/
FVB/NJ
PERA/EiJ
C58/J
C57BL/6J
NOR/LTJ
C57BR/cdJ
NOD/LtJ
NZW/LacJ
PercentTimeinCenter
Female
Male
0
10
20
30
40
50
60
70
NON/LtJ
C5
7BR/cdJ
DBA/2J
C58/J
C3H/HeJ
LG/J
CE/J
WSB/EiJ
MRL/MpJ
SWR/J
P/J
A/J
RIIIS/J
NZ
O/HILtJ
FVB/NJ
BA
LB/cByJ
BTBR
T+tf/J
BUB/BnJ
C
57BL/6J
AKR/J
PL/J
I/LnJ
MA/MyJ
CBA/J
NOD/LtJ
129S
1/SvlmJ
SM/J
KK/HIJ
N
ZB/BINJ
SJL/J
NZW
PctImmob
ility
Female
Male
Open Field Center Time
Tail Suspension Immobility
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0
0.2
0.4
0.6
0.8
1
1.2
PERA
/EiJ
C58/J
C57
L/J
C57BL/10J
C57BL
/6J
BALB
/cJ
C3H/HeJ
WSB/EiJ
LP/J
NZW/LacJ
CB
A/J
DBA
/2J
129S1/SvImJ
A/J
C57BLKS/J
PL/J
DBA
/1J
SEA/G
nJ
C57BR/cdJ
BTBRT+
tf/J
AK
R/J
I/LnJ
NZB/B
lNJ
S
M/J
strain mean sd
PERA/EiJ 1 0
C58/J 0.8 0.41
C57L/J 0.7 0.47
C57BL/10J 0.6 0.503
C57BL/6J 0.361 0.487
BALB/cJ 0.25 0.444
C3H/HeJ 0.222 0.428
WSB/EiJ 0.214 0.426
LP/J 0.111 0.323
NZW/LacJ 0.111 0.323
CBA/J 0.105 0.315DBA/2J 0.105 0.315
129S1/SvImJ 0.1 0.308
A/J 0.1 0.308
C57BLKS/J 0.0938 0.296
PL/J 0.0769 0.277
DBA/1J 0.0556 0.236
SEA/GnJ 0.0556 0.236
C57BR/cdJ 0.0526 0.229
BTBR T+ tf/J 0.04 0.2
AKR/J 0 0
I/LnJ 0 0
NZB/BlNJ 0 0
SM/J 0 0
Quantitative Traits
Susceptibility to developing gallstones
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Chr Pos 129S1/SvImJ A/J AKR/J BALB/cByJ BTBR_T+_tf/J BUB/BnJ C3H/HeJ
1 171297027 T C C T C C T
1 171297120 G G A G A G G
1 171297250 C T T C T T C
1 171297364 T C C T C C T1 171297418 G G G G G G G
1 171297467 C C T C T C C
1 171297468 C C C C C C C
Inferred haplotype patterns can then be related back to the observed phenotype values
across the same set of strains
CTG
ANOVA analysis: Identify associations
between shared haplotypes and phenotypes
129S1/SvI 120.7 A/J 67.3
BALB/cBy 105.4 AKR/J 84.6
C3H/HeJ 120.1 BTBR_T+ 110.2
FVB/NJ 116.5 BUB/BnJ 67.8
NZB/BlNJ 165.5 C57BL/6J 71.7
NZW/LacJ 130.7 C57BLKS/ 78.6
C57L/J 80
CAST/EiJ 67.1
CBA/J 85.4
CZECHII/E 81.3
DBA/2J 63.4
I/LnJ 93.4
JF1/Ms 88.8
MA/MyJ 122.9
MOLF/EiJ 81.6
MSM/Ms 103.2
NOD/LtJ 103PL/J 97
RIIIS/J 48.8
SEA/GnJ 82
SJL/J 76
SM/J 94.7
SWR/J 91.2
126.4833 84.34783
TCG
logP
Genome Location
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HDL phenotype analysis - measurement of HDL cholesterol levels 34 mouse strains
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IH Groups at ApoA2 Locus
0
100
200
T
C
(m
g
/d
l)
CTG TCG129S1/SvImJ 120.7 AKR/J 84.6
BALB/cByJ 105.4 BTBR_T+_tf/J 110.2
C3H/HeJ 120.1 BUB/BnJ 67.8
FVB/NJ 116.5 C57BL/6J 71.7
NZB/BlNJ 165.5 C57BLKS/J 78.6
NZW/LacJ 130.7 C57L/J 80
CAST/EiJ 67.1
CBA/J 85.4
CZECHII/EiJ 81.3
DBA/2J 63.4I/LnJ 93.4
JF1/Ms 88.8
MA/MyJ 122.9
MOLF/EiJ 81.6
MSM/Ms 103.2
NOD/LtJ 103
PL/J 97
RIIIS/J 48.8
SEA/GnJ 82
SJL/J 76
SM/J 94.7
SWR/J 91.2
126.4833 85.12273
Inferred Haplotype Groups atApoA2locus
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0
5
10
15
20
25
30
35
A/J
129S1/SvImJKK
/HlJ
NZO/HILtJ
BALB
/cByJ
DBA/2JSM
/J
RIIIS/J
NZB/BlNJ
MRL/MpJAKR/JCE/J
BUB/BnJSJ
L/JLG/JCBA/JPL/J
SWR/J
C3H/HeJ
BTBR
_T+_tf/JP/J
MA/M
yJ
NON/LtJC58/J
WSB/EiJ
FVB/NJ
C57BL/
6J
NOD/LtJ
C57BR/
cdJ
PercentTimein
Center
Female
Male
The use of haplotype association mapping to identify clinical
QTL (cQTL)
0
50
100
150
200
250
Nucleus
Accumbens
Amygdala Hippocampus Prefrontal Cortex
IntensityLevel
Hap Group 1Hap Group 2
**
*
0
5
10
15
20
25
30
1 2
PctTimeCenter
Haplotype Group
Identification of clinical
QTL and expression
difference for open field
behavior
logP
Genome Location
Grm7
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Whole-genome association analysis of urethane-induced lung adenoma incidencein laboratory inbred mice.The scatter plots were drawn for -log(P) against SNP positions in the chromosomes. The twohorizontal gray lines indicate the significance levels of -log(P) = 4.8 and -log(P) = 6.2. Thearrows indicate the genomic regions with -log(P) > 4.8. These refined genomic regions withsignificant associations are within 10 Mb of one or more QTLs (such as Sluc18, Pas1, Sluc23and Pas10, and Sluc26) for chemically induced lung cancer detected by previous linkagestudies.
Candidate lung tumor susceptibility genes identifiedthrough whole-genome association analyses in inbredmice.Liu et.al. Nature Genetics38, 888 - 895 (2006)
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Whole organism phenotypes
gene expression
biomarkers
identification of biological networks
Anxiety
and
Depression
Gene expression analysis
Biomarker analysis
Haplotype association
mapping
Clinical phenotypes
What phenotypes can be used?
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Gene Expression as a Phenotype
Mendelian or complex?
0
200
400
600
800
1000
1200
1400
1600
1800
2000
BALB/cByJ
SWR/JCE/J
NON/LtJ
BTBR
T+tf/JPL/J
FVB/NJ
SJL/JSM
/J
C3H/HeJ
C57BL/6J
MA/MyJ
NZO/HILtJP/J
129S1/SvImJ
CBA/J
KK/HlJ
BUB/BnJA/J
I/LnJ
NZW/LacJ
NOD/LtJ
C58/J
AKR/J
C57BR/cdJ
MRL/MpJ
RIIIS/J
WSB/EiJ
DBA/2J
Intensity
0
500
1000
1500
2000
2500
3000
BALB/cByJ
CE/J
NON/LtJ
AKR/J
C57BL/6J
BTB
R_
T+_
tf/J
PL/J
129S1/SvImJ
BUB/BnJ
SM/J
A/J
NOD/LtJ
WSB/EiJ
I/LnJ
C58/J
DBA/2J
NZW/LacJ
C3H/HeJ
SWR/J
MA/MyJ
CBA/J
C57BR/cdJ
RIIIS/J
KK/HlJ
FVB/NJ
P/J
SJL/J
Intensity
Glutamate transporter (Slc1a1)hippocampus
Catechol-o-methyltransferase (Comt) hippocampus
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Using gene expression differences between strains
to identify gene networks
Probe X
1 2 3 4 5 6 7 8 9 10 11 12 13 14 1516 171819 X
-LogP
Significance
Threshold
Chr
Chr1
ChrX
Probe X
Probe Y
Probe Z
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Cis - local regulationcis-QTLband
trans-QTL
band
Visualizing eQTL Results
Trans - non-local
regulation through
diffusable factors
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Catechol-O-Methyltransferase (COMT) cis-QTL in Nucleus
Accumbens
Haplotype mapping ofexpression data forCOMT probesetexpression in nucleus
accumbens
0
500
1000
1500
2000
2500
3000
Intensity
1 2
Haplotype Group
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Cis - local regulationcis-QTLband
trans-QTL
band
Visualizing eQTL Results
Trans - non-local
regulation through
diffusable factors
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functional
enrichment
otherknowledge:
expression,
literature,
knowninteractions,e
tc
Gene Ontology KEGG pathway
functional
enrichment
otherknowledge:
expression,
literature,
knowninteractions,e
tc
Gene Ontology KEGG pathway
Schema of trans-band analysis
Trans-regulator candidates functional
enrichment
otherknowledge:
expression,
literature,
knowninteractions,e
tc
Gene Ontology KEGG pathway
GeneID -logP
15502 5.3074559 4.66
107652 4.4219357 4.40
212862 4.3073074 4.30
107652 4.23
14828 4.12108946 4.09
>transband at chr=3, pos=46,624,006
Biological hypothesis
Putative
Regulator
putative targets
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Enrichment Analysis
Rank Name logp Description
1 C1qa 3.17 complement component 1, q subcomponent, alpha polypeptide
2 Gdap10 3.12 gangl ios ide-induced di fferent iat ion-assoc iated-protein 10
3 1500011K16Rik 3.09 RIKEN cDNA 1500011K16 gene
4 4633402C03Rik 3.07 gnf1m29444_at
5 Cradd 3.03 CASP2 and RIPK1 domain containing adaptor with death domain
6 Onecut1 3.03 one cut domain, family member 1
7 Npm3 3.01 nucleoplasmin 3
8 Ccdc22 2.99 DNA segment, Chr X, Immunex 40, expressed
9 Gtpbp4 2.95 GTP binding protein 4
10 Rarres 1 2.93 retinoic ac id rec eptor res ponder (taz arotene induc ed) 1
11 Bad 2.92 Bcl-associated death promoter
12 Gab1 2.89 growth factor rec eptor bound protein 2-assoc iated protein 1
13 Mtap 2.87 methylthioadenosine phosphorylase
14 Apcs 2.84 serum amyloid P-component
15 Pex6 2.80 peroxisomal biogenesis factor 6
16 Chd8 2.78 chromodomain helicase DNA binding protein 8
17 Bnip2 2.77 BCL2/adenovirus E1B 19kDa-interacting protein 1, NIP2
18 AA407659 2.71 expressed sequence AA40765919 Ankfy1 2.71 ankyrin repeat and FYVE domain containing 1
20 Bap1 2.68 Brca1 associated protein 1
21 Hs3s t3b1 2.68 heparan sul fate (glucosamine) 3-O-sul fot rans ferase 3B1
22 A430005L14Rik 2.67 RIKEN cDNA A430005L14 gene
23 Akt1 2.65 thymoma viral proto-oncogene 1
24 Myh9 2.63 myosin, heavy polypeptide 9, non-muscle
25 Casp3 2.63 caspase 3, apoptosis related cysteine protease
Transband occurrence of
apoptosis: 5/25 = 20%
Background occurrence of
apoptosis: 100/6247 = 1.6%
Enrichment = 12.5x
Significance by hypergeometric
distribution: p < 10-4
Chr 19, 52.7 MB
Fi did t l t f t b d i di ti
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Interactions between Gsk3b with trans-band targets
*Gray-genes are from trans-band targets
Five candidate regulators from transband in adipose tissue(GO: Integrin signaling)Name Description LOCUSLINK_ACCS
4932425I24Rik RIKEN cDNA 4932425I24 gene 320214
Cox17 cytochrome c oxidase, subunit XVII assembly protein homolog (yeast) 12856
Gsk3b glycogen synthase kinase 3 beta 56637
Nr1i2 nuclear receptor subfamily 1, group I, member 2 18171
Popdc2 popeye domain containing 2 64082
Known ns-SNP
Known drug target
Enzastaurin
-/A Frame-shifting variation
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0
5
10
15
20
25
30
35
A/J
CZECHII/EiJ
129S1/SvImJ
NZO/HLLTJ
LP/J
BALB/cByJ
KK/HlJ
SEA/GnJ
DBA/2J
PWD/Ph
LG/J
RIIIS/J
SM/J
CE/J
MRL/MPJ
NZB/BlNJ
CBA/J
I/LnJ
SJL/J
PL/J
AKR/J
C3H/HeJ
BUB/BnJ
SWR/J
DDY
NON/LtJ
MA/MyJ
P/J
WSB/EiJ
BTBR_
T+_
tf/
FVB/NJ
PERA/EiJ
C58/J
C57BL/6J
NOR/LTJ
C57BR/cdJ
NOD/LtJ
NZW/LacJ
PercentTimeinCenter
Female
Male
0
50
100
150
200
250
Nucleus
Accumbens
Amygdala Hippocampus Prefrontal Cortex
IntensityLevel
Hap Group 1
Hap Group 2
***
Integration of phenotype and expression data
0
5
10
15
20
25
30
1 2
PctTimeCenter
Haplotype Group
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In Silico Pharmacogenetics: WarfarinMetabolismGuo et al. Nat Biotechnol. 2006 May; 24(5): 531536.
Haplotype-based genetic analysis of warfarin metabolites. A representative set of haplotype blockshaving the highest correlation with this data set. For each predicted block, the chromosomal location,number of SNPs within a block, its gene symbol and an indicator of gene expression in liver are shown.
The haplotype for each strain is represented by a colored block, and is presented in the same order asthe phenotypic data in the top panel. The calculated p-value measures the probability that straingroupings within an individual block would have the same degree of association with the phenotypic databy random chance. In the gene expression column, a green square indicates the gene is expressed inliver tissue, while a gray square indicates that it is unknown.
The log-transformation of the measuredcombined amount of 7-hydroxywarfarin (7-OH)and its glucuronidated metabolite (M8) as a %of the total amount of drug and metabolites foreach of 13 inbred strains.
http://www.pubmedcentral.nih.gov/redirect3.cgi?&&auth=0PAzguH5yIdOV0EofPPd9YV_WnR8OjszgXMikOAFV&reftype=publisher&artid=1459533&iid=130971&jid=319&FROM=Article%7CFront%20Matter&TO=Content%20Provider%7CArticle%7CRestricted%20Access&article-id=1459533&journal-id=319&rendering-type=normal&&http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&retmode=ref&cmd=prlinks&id=16680137http://www.pubmedcentral.nih.gov/redirect3.cgi?&&auth=0PAzguH5yIdOV0EofPPd9YV_WnR8OjszgXMikOAFV&reftype=publisher&artid=1459533&iid=130971&jid=319&FROM=Article%7CFront%20Matter&TO=Content%20Provider%7CArticle%7CRestricted%20Access&article-id=1459533&journal-id=319&rendering-type=normal&&http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&retmode=ref&cmd=prlinks&id=166801378/14/2019 2009-09-08_Wiltshire IPIT Seminar Slides
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Haplotype Associated Mapping case study
Fig. 1. Serum ALT measured in human volunteers
taking daily oral doses of APAP (4g/day).
(A) Lines represent per subject daily serum ALT (U/L)
values 14 days prior to clinic admission and throughout
the 14-day duration of the study. Subjects were
considered responders if peak serum ALT reached
greater than 1.5-fold higher than the average of their
baseline values (average of values obtained for days
-14 and 1-3; N = 22). ALT elevations were observed
following the start of treatment on day 4 and continued
to fall beyond treatment cessation on day 11.
(B) Daily ALT (U/L) values of non-responder volunteersreceiving APAP treatment were not significantly different
from those receiving placebo (N = 9).
(C) The peak ALT fold change (over baseline) reached
over the course of treatment per subject number is
plotted for both non-responder (white bars) and
responder (black bars) individuals. Horizontal line
represents a 1.5-fold increase over the subjects pre-
treatment baseline.
Mouse population-guided resequencing reveals
that variants in CD44 contribute to
acetaminophen-induced liver injury in humansAlison H. Harrill, Paul B. Watkins, Stephen Su, Pamela K. Ross, David E. Harbourt,
Ioannis M. Stylianou, Gary A. Boorman, Mark W. Russo, Richard S. Sackler, Steven C.
Harris, , Philip C. Smith , Raymond Tennant, Molly Bogue, Kenneth Paigen, Christopher
Harris, Tanupriya Contractor, Timothy Wiltshire, Ivan Rusyn and David W. Threadgill
Genome Research 2009
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(A) Representative APAP-treated mice of
strains CAST/EiJ, SM/J, C57BL/6J, DBA/2J,
and B6C3F1/J showing varying levels of
centrilobular necrosis.
(B) A percent necrosis score (mean S.E.) ofH&E stained liver sections.
(D) Serum ALT levels (mean S.E.) in mice
sacrificed 24 hours after dosing
Whole-genome association analysis and targeted
sequencing determined that polymorphisms in Ly86,
Cd44, Cd59a, and Capn8 correlate strongly with liver
injury.
Variation in the orthologous human gene, CD44, is
associated with susceptibility to acetaminophen in two
independent cohorts.
I f t bilit ith l ti i l t
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0
510
15
20
25
30
35
C57BL/6J
DBA/2J
A/J
AKR/J
CBA/J
C3H/HeJ
HeLa
%G
FPPositives
1
10
100
1000
10000
100000
256
128
64
32
16 8 4 2 1
Max / min expression fold-change
Frequency
0.01%
0.10%
1.00%
10.00%
100.00%
Cumu
lative
frequency
Cellular Genetics
Develop cell-based assay system for MEFs
from 30 strains.
What cell types?
What phenotypes to measure?
Infectability with lentiviral vectors
High content imaging
Gene expression profiling
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a.
c.
Purify MEFs from 30 different strains
Seed in 96 wells and grow in
or 1% serum for 72hrs
At end of each timepoint, stain cells
with JC-1 and measure flourescence
with facs
Technical replicates for 1% FBS 24hr
Interday replicates for 1% FBS 24hr
Heritability:
64.7%
Interday replicates for 1% FBS 72hr
Strain distribution pattern of mitochondrial membrane potential
across 30 different strains
G f it h d i l b t ti l
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ScatterPlot
cumulativeposition
0 5 00 00 00 00 1 00 00 00 00 0 1 50 00 00 00 0 2 00 00 00 00 0 2 50 00 00 00 0
0
2
3
4
d.ScatterPlot
cumuativeposition
2 1 41 5 00 0 00 2 1 42 0 00 0 00 2 1 42 5 00 0 00 2 1 43 0 00 0 00 2 1 43 5 00 0 00 2 1 44 0 00 0 00 2 1 44 5 00 0 00 2 1 45 0 00 0 00
0
1
2
3
4
Chromosome 15: Gene name: Fbxl7
Genome scan for mitochondrial membrane potential
0
10000
20000
30000
40000
50000
60000
70000
ctrl siRNA 1 siRNA 2 siRNA 3 siRNA 4
P = 1.02E-08
nmolO2/m
in/1x10^6cells
0.E+00
1.E+04
2.E+04
3.E+04
4.E+04
0 1 2 3 4 5 6 7
Days
Growth Curve of siFbxl7 treated MEFs
ctrl siRNA 3
0
20
40
60
80
100
120
140
0 1 2 3 4 5
ncrease
days
Percentage Increase of MitochondriaSuperoxide over ctrl siRNA
siRNA knockdown ofFbxl7
P-ampk (Thr 175) P-p53 (Ser15)
total p53
Ctrl siRNA 3
tubulintubulin
total ampka
Ctrl siRNA 3
p21
Ctrl siRNA 3
Eff t f h Fb l7 k kd i ll li
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Effect of huFbxl7 knockdown in cancer cell lines
GM1600(gliobastoma)
LnCAP(prostate)
Colo741(colorectal)
Hs587t(mammary)
mRNA knockdown cell proliferation mito. membrane potential
MEF C t t i it A
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MEF Cytotoxicity Assay 32 Inbred MEF Cell Lines
100 Compounds; 9 concentrations, 4 multiplexed assays
Data capture BD Pathway 435 high content imaging system
3.7 uM Vinblastine-10.41 uM Vinblastine-1 33.3 uM Vinblastine-1
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Hoescht G21-0.41 uM
Vinblastine-1
Hoescht G19-33.3 uM
Vinblastine-1
Hoescht G20-3.7 uM
Vinblastine-1
Mito Red G21-0.41 uMVinblastine-1 Mito Red G20-3.70 uMVinblastine-1 Mito Red G19-33.3 uMVinblastine-1
DNA Content, Nuclear Count & Size
Mitochondrial Membrane Potential Changes (Intensity)
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CY5 G19-33.3 uM
Vinblastine-1
CY5 G20-3.7 uM
Vinblastine-1
CY5 G21-0.41 uM
Vinblastine-1
FITC G20-3.7 uM
Vinblastine-1
FITC G21-0.41 uM
Vinblastine-1
FITC G19-33.3 uM
Vinblastine-1
Cell Morphology & Permeability
Cytochrome C Localization and Release
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0
10
20
30
40
50
60
70
80
-5 -4.5 -4 -3.5 -3 -2.5 -2 -1.5 -1 -0.5
Millions
log[Docetaxel] (mM)
RFU
LP/J
C57BL/6J
C57L/J
CBA/J
MRL/MpJ
NON/ShiLtJ
SEA/GnJ
BUB/BnJ
C57BR/cdJ
CZECHII/EiJ
WSB/EiJ
NOD/ShiLtJ
RIIIS/J
SWR/J
AKR/J
LG/J
I/LnJ
NOR/LtJ
BTBRT+tf/J
SJL/J
DBA/2J
0
10
20
30
40
50
60
70
80
90
-0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1
Million
log[Acetaminophen] (mM)
RFU
LP/J
C57BL/6J
MRL/MpJ
SEA/GnJ
C57BR/cdJ
CZECHII/EiJ
WSB/EiJ
NOD/ShiLtJ
RIIIS/J
AKR/J
CE/J
NZO/HILtJ
LG/J
I/LnJ
NOR/LtJ
SM/J
BALBc/ByJ
BTBRT+tf/J
PL/J
SJL/J
129S1/SvImJ
A/J
DBA/2J
MEF cell viability studies
Alomar blue analysis
Whole well measurement
Strain specific phenotypic differences
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Summary
Inbred strains can provide genetic variation that models human variation.
The use of a mouse model allows for control of environmental variation.
All phenotypes measured show variability across inbred mouse strains.
Whole organism studies can be used to model disease status.
Cellular genetics can be used for cell function, toxicogenomics, pharmacogenetics.
Future directions
Improve the haplotype map across the inbred strains
Screening drugs and toxicants in cell-based assays
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Acknowledgements
GNFSerge Batalov
Andrew Su
Chunlei Wu
Jeff Janes
Dave DelanoStephen Su
Joe Bass (Northwestern U.)
Bev Paigen (JAX)
Mat Pletcher (Pfizer)
Lisa Tarantino (UNC)
Russell Thomas (Hamner Inst)
collaborators
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Genome-wide Distribution of Variation
PP