netbiosig2013-keynote esti yeger-lotem
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Decoding the Tissue-Specificity
of Hereditary Diseases by using Tissue Interactomes
Esti Yeger-Lotem
Layout
• Human tissue interactomes – extensive up-to-date resource
• Decoding the tissue-specificity
of hereditary diseases
• Our open web-tool
Familial Parkinson disease: SNCA aberration
P1 P2
P3
From a global human interactome to tissue interactomes
• Known protein-protein interactions (PPIs) - however no tissue context!
• Use tissue expression data – Filter interactome per tissue – Most studies relied on GNF: the microarray study of
Su et al, PNAS 2004, (e.g., Lehner 2008)
• New large-scale data emerging (e.g., Sandberg 2009, Albrecht 2011) – RNA-Seq data &
protein large-scale data available!
P1
P2
P3
66 tissues
78 tissues
GNF HPA RNA-Seq 16
tissues
16 tissue expressomes
Integrating tissue expression data
• Protein=gene, no splice-variants • Used stringent cutoffs for
expression
Tissue GNF HPA RNA- seq
Adipose 2,533 N/A 10,269
Adrenal 2,498 7,235 10,822
Brain 4,335 7,692 10,925
Breast N/A 6,526 10,698
Colon 2,807 7,244 10,519
Heart 3,345 6,189 9,827
Kidney 2,025 7,672 10,945
Liver 2,531 6,202 8,842
Lung 3,010 7,465 11,063
Lymph Node 2,441 6,183 10,973
Ovary 1,567 5,111 11,165
Prostate 3,075 6,508 11,250
Skeletal Muscle 1,751 5,805 8,851
Testis 3,176 7,744 12,567
Thyroid 3,360 6,982 10,938
White Blood Cells 5,750 N/A 9,466
Median 2,807 6,754 10,873
66 tissues
78 tissues
GNF HPA RNA-Seq 16
tissues
16 tissue expressomes
Integrating tissue expression data
• ~70% overlap between RNA-seq & GNF or HPA • Single resource not enough
66 tissues
78 tissues
GNF HPA RNA-Seq 16
tissues
16 tissue expressomes
Integrating tissue expression data
• Matching tissues correlated significantly (best match)
1
10
100
1000
10000
100000
100 1000 10000 100000
Gene expression level (GNF)
RP
KM
(R
NA
-se
q)
66 tissues
78 tissues
GNF HPA RNA-Seq 16
tissues
16 tissue expressomes
Integrating tissue expression data
Tissue Com-bined
GNF HPA RNA- seq
Adipose 10,859 2,533 N/A 10,269
Adrenal 13,592 2,498 7,235 10,822
Brain 14,000 4,335 7,692 10,925
Breast 12,669 N/A 6,526 10,698
Colon 13,312 2,807 7,244 10,519
Heart 12,766 3,345 6,189 9,827
Kidney 13,662 2,025 7,672 10,945
Liver 11,958 2,531 6,202 8,842
Lung 13,853 3,010 7,465 11,063
Lymph Node 13,185 2,441 6,183 10,973
Ovary 12,918 1,567 5,111 11,165
Prostate 13,586 3,075 6,508 11,250
Skeletal Muscle 11,736 1,751 5,805 8,851
Testis 14,819 3,176 7,744 12,567
Thyroid 13,518 3,360 6,982 10,938
White Blood Cells 10,844 5,750 N/A 9,466
Median 13,248 2,807 6,754 10,873
Tissue expressed gene: detected in ≥ 1 sample
66 tissues
78 tissues
Su et al HPA RNA-Seq 16
tissues
MINT BIOGRID DIP INTACT
16 tissue expressomes Global human interactome
Integrating expression & interactions
11,225 proteins (52% of proteins), 67,439 interactions
66 tissues
78 tissues
HPA RNA-Seq 16
tissues
MINT BIOGRID DIP INTACT
16 tissue expressomes Global human interactome
Integrating expression & interactions
PPI in tissue if both proteins are expressed
GNF
0
5
10
15
20
25
30
35
40
45
50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Perc
enta
ge o
f tot
al se
t
Number of expressing tissues
GNF HPA RNA-seq CombinedEnriched for basic cellular processes (translation elongation, ..)
1. Most genes are globally expressed or tissue specific
0
5000
10000
15000
20000
25000
30000
2. A common core network dominates all
tissue interactomes
> 50% of proteins & PPIs in each tissue appear in all tissues - 26,370 interactions, 4,989 proteins
Genes PPIs
3. Tissue hub proteins: persistent regulators
• 451 tissue hubs: Hubs = proteins with top number of interactions (5%, > 45 interactions)
• Highly enriched for regulatory processes - transcription regulation (42%, p<10-15) - protein kinase cascade (12%, p<10-8) - also relative to core proteins
• Much of the regulatory components are similar across tissues
Number of PPIs 30 45 150
Hubs
Tissues
4. PPI degree and expression levels are correlated across all tissues
Gene2
Gene3
Gene4
Gene1
Gene1
Gene1
Gene2
Gene6
Gene4
Gene3
Gene8
Gene9
Gene10
Gene1 Gene1
0
5
10
15
20
1 2 3 4 5 6 7 8 9 10
Deg
ree
RPKM percentile
Adipose
Spearman r= 0.98 • Previously shown in yeast
von Mering et al, Nature 2002
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Adipose
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Adrenal
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Brain
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Breast
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Heart
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Kidney
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Liver
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Colon
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Lymph Node
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Lung
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Ovary
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Prostate
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Skeletal Muscle
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Testis
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Thyroid
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
WBC
4. PPI degree and expression levels are correlated across all tissues
Layout
• Tissue interactomes – extensive up-to-date resource
• Decoding the tissue-specificity
of hereditary diseases
• Our open web-tool
Familial Parkinson disease: SNCA aberration
Familial Parkinson disease: SNCA aberration
SNCA expression
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16Number of expressing tissues
Perc
enta
ge o
f tot
al 342 hereditary diseases
266 causal disease genes
The enigmatic tissue-specific manifestation of hereditary diseases
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16Number of expressing tissues
P
• Hereditary diseases - causal genes associations: OMIM, COSMIC • Disease-tissue associations: Lage et al, PNAS 2008
Barshir et al, in revision
0
10
20
30
40
50
60
disease tissues non disease tissues
Factors governing tissue-specificity (TS)
Disease tissues Other expressing tissues
63% of the genes, p<10-4
Expression level (RPKM)
0
0.5
1
1.5
2
2.5
Disease tissues Other expressing tissues
Med
ian
num
ber o
f TS-
PPI o
f di
seas
e ge
nes
Tissue-specific PPIs
21% of the genes, p<10-4
Barshir et al, in revision
TS-PPIs illuminate disease-related mechanisms
Hereditary breast cancer predisposition BRCA1 network in breast
Familial lung adenocarcinoma EGFR network in lung
Muscular dystrophy DAG1 network in muscle
14-16 tissues
4-13 tissues
1-3 tissues
Protein expressed in:
~90% PPIs filtered out
Barshir et al, in revision
Factors distribution across hereditary diseases
TS-PPIs 15%
TS-PPIs + elevated
expression 12%
Elevated expression:
33%
Unknown 33%
Disease genes tissue-
specific: 7%
Barshir et al, in revision
Layout
• Tissue interactomes – extensive up-to-date resource
• Decoding the tissue-specificity
of hereditary diseases
• Our open web-tool
Familial Parkinson disease: SNCA aberration
Barshir et al, NAR 2013
TissueNet: an open database
14-16 tissues
4-13 tissues
1-3 tissues
Protein expressed in:
http://netbio.bgu.ac.il/tissuenet
Disease/Stimulus
Differentially expressed genes
Genetic screening (mutations)
Known protein-DNA interactions
Known protein-protein interactions
Interactome (~60,000 edges)
Identifying signaling pathways
Identify regulatory pathways connecting
screening data
ResponseNet
Yeger-Lotem et al, Nature Genetics 2009
The ResponseNet web-server http://netbio.bgu.ac.il/respnet
Basha et al, Nucleic Acids Research 2013
Mutations
Diff. exp. genes
Human tissue interactomes
Identifying context-sensitive pathways
http://netbio.bgu.ac.il/ContextNet
Thanks!
Marie Curie International Reintegration Grant
TissueNet Galila Agam Haim Belmaker Assaf Rudich Vered Chalifa-Caspi Inbar plaschkes
My lab @ BGU Ruth Barshir Omer Basha Alex Lan Ilan Smoly Shoval Tirman Amir Eluk Omer Schwartz
ContextNet Michal Ziv-Ukelson
ResponseNet Ernest Fraenkel Susan Lindquist
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