Oct 12, 2007 Research Review Day 1 Josh Stuart, Ph.D. Biomolecular Engineering UCSC Research Review Day 2007 Biological Discovery From Biological Discovery From Genetic Network Perturbations Genetic Network Perturbations Reverse-Engineering Reverse-Engineering by Knocking Down by Knocking Down
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Oct 12, 2007 Research Review Day 1 Josh Stuart, Ph.D. Biomolecular Engineering UCSC Research Review Day 2007 Biological Discovery From Genetic Network.
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• Genome sequence provides complete parts lists• Allows targeting of specific genes
– Cloning
– RNA interference
• High-throughput technologies allow monitoring genome-wide responses to knock-down
• Phenotype gives clues about gene function
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What’s a knock-down?
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Genetic Knock-DownsRNA interference
RNAiA. Fire et. al 1998
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Two Examples
• Infer disease pathways
• Predict genetic interactions
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Reverse engineering by knocking-down
• Infer disease pathways
• Predict genetic interactions
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10Knock-downs to Understand Cancer Invasiveness
Lee Lab, GWUMC
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11Knock-downs to Understand Cancer Invasiveness
1. Identify knock-downs that reverse cancer invasion
2. Genome-wide expression under knock-downs
3. Infer invasiveness network
4. Predict new genes involved in process
Go to step 1.
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up-regulatedin knock-down
down-regulatedin knock-down
Sensitive, genome-wide phenotypes: DNA Microarrays
knock-down
normal cells
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DRYWET
Iterative invasiveness network strategy
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Infer Networkfrom Secondary Effects
Single Phenotype
Network GenesPerturbed by
RNAi or Knockout
Effect GenesMeasured by microarray
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Expression under
ee ee
ee eeAA
BB ∆A
∆Bee
Expression under
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Predictions for Colon Cancer Invasiveness
• Identified a putative signaling network• Expanded the list of candidates in the network• Testing candidates for loss-of-invasiveness
phenotype
conserved rolein cell-migration
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17V. cholera Networks
Yildiz Lab, UCSC
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New Biofilm genes
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Two Examples
• Infer disease pathways
• Predict genetic interactions
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Function from catastrophe• Most genes are nonessential• Genes knocked down together give phenotype• Can we infer function from knock-down combos?
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Gene Network Discovery
• build networks from all interactions
• discover function from a gene’s links
• understand bigger picture of gene regulation
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22Understanding Gene Function through Modifier ScreensUnderstanding Gene Function through Modifier Screens
Wild Type
A
B
C
X
A
B / R
C
XWild Type
A
B
C
X
D
E
F
Wild TypePhenotype Phenotype
Roy Lab, Univ Toronto
B --- RWithin Pathway Link
B --- FCross Pathway Link
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23Understanding Gene Function through Modifier Screens:Understanding Gene Function through Modifier Screens:Synthetic Genetic Array (SGA) analysis in Synthetic Genetic Array (SGA) analysis in S. cerevisiaeS. cerevisiae
arrayed library of ~4800 viable gene deletions
gene ‘x’deleted
Tong et al. (2001)
systematic generationof double mutants
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24Understanding Gene Function through Modifier Screens:Understanding Gene Function through Modifier Screens:Synthetic Genetic Array (SGA) analysis in Synthetic Genetic Array (SGA) analysis in S. cerevisiaeS. cerevisiae
Tong et al. (2001)
gene ‘x’deleted
systematic generationof double mutants
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25Synthetic Genetic Array (SGA) analysis in Metazoans?Synthetic Genetic Array (SGA) analysis in Metazoans?
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26Synthetic Genetic Array (SGA) analysis in Metazoans?Synthetic Genetic Array (SGA) analysis in Metazoans?
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high degree of biological conservation to other animals
small (~1 mm)
hermaphroditic
three day life cycle
the path to many fundamental discoveries
(-) control GFP(dsRNA)
The Nematode Worm The Nematode Worm Caenorhabditis elegansCaenorhabditis elegans
RNA interference (RNAi)
Roy Lab, Univ. Toronto
The Interaction Matrix of ~56,000 Growth ScoresThe Interaction Matrix of ~56,000 Growth Scores
The Interaction Matrix of ~56,000 Growth ScoresThe Interaction Matrix of ~56,000 Growth Scores
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30The SGI Network: 1246 Interactions among 461 GenesThe SGI Network: 1246 Interactions among 461 Genes
1246 synthetic genetic interactions- 842 (68%) between query genes and one of the genes in the signaling set - 421 (34%) between query genes and one of the genes in the LGIII set
Mining the Superimposed for Multiply-supported SubnetworksMining the Superimposed for Multiply-supported Subnetworks
verified interaction
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N2; Ø(RNAi) (DIC) N2; T20B12.7(RNAi) (DIC)
N2; Ø(RNAi) (Nile Red) N2; T20B12.7(Nile Red)
Genes in the Genes in the bar-1 bar-1 Subnetwork have a Shared PhenotypeSubnetwork have a Shared Phenotype
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N2; Ø(R
NAi) F2
bar-1
; Ø(R
NAi) F2
N2; Y48
E1B.5
(RNAi)
F1
N2; mrp
-5(R
NAi) F1
N2; F29
C12.4
(RNAi)
F1
N2; ZC39
5.10
(RNAi)
F2
N2; lin-
2(RNAi)
F2
N2; B04
32.3(
RNAi) F1
N2; T20
B12.7(
RNAi) F2
N2; efl-
1(RNAi)
F2
N2; lin-
39(R
NAi) F2
N2; C27F
2.10
(RNAi)
F2
N2; lin-
35(R
NAi) F2
N2; ogt
-1(R
NAi) F2
N2; prx
-5(R
NAi) F1
N2; T09
A5.5(
RNAi) F1
N2; ubc
-18(R
NAi) F1
N2; lin-
23(R
NAi) F1
N2; F54
C9.6(
RNAi) F1
N2; exo
-3(R
NAi) F1
N2; lin-
7(RNAi)
F2
N2; T01
E8.6(
RNAi) F1
0
0.2
0.4
0.6
0.8
1
1.2
Genotype
Nor
mal
ized
N2
Val
ues
Genes in the Genes in the bar-1 bar-1 Subnetwork have a Shared PhenotypeSubnetwork have a Shared Phenotype
75% of genes in subnetwork have altered fat levels.
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Analysis of the SGI NetworkAnalysis of the SGI Network
• Can we assign function to uncharacterized genes based on their neighborhood within the network?
• How do genetic interactions contribute to our understanding of the system?
• Can we assign function to uncharacterized genes based on their neighborhood within the network?
• How do genetic interactions contribute to our understanding of the system?
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• Identified 343 subnetworks• 47% are enriched for a specific GO category
• 46 subnetworks are bridged by SGI links• 19-fold enriched
or
SGICo-expressionWorm PhenotypeProtein-protein
What is the Connectivity of Synthetic Genetic Links within What is the Connectivity of Synthetic Genetic Links within the Superimposed Network?the Superimposed Network?