2009-09-08_wiltshire ipit seminar slides

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


2/44

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


3/44

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


4/44

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


25/44

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


Schema of trans-band analysis

Trans-regulator candidates functional

enrichment

otherknowledge:

expression,

literature,

knowninteractions,e

tc


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=16680137


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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


34/44

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


35/44

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


38/44

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

2009-09-08_wiltshire ipit seminar slides

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