synthetic lethality inactivating two interacting pathwaysinactivating two interacting pathways...
TRANSCRIPT
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Synthetic LethalitySynthetic Lethality
•Inactivating two interacting pathwaysInactivating two interacting pathwayscauses lethality (or sickness)causes lethality (or sickness)
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ProductProduct
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XViable!Viable!
X Viable!Viable!
Dead!Dead!
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Synthetic Lethality
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bViable Lethal
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bWild-type Viable
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• Synthetic Lethality Identifies Functional Relationships
• Large-Scale Synthetic Lethality Analysis Should Generate a Global Map of Functional Relationships between Genes and Pathways
• Gene Conservation = Genetic Network Conservation
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EssentialProduct
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EssentialProduct
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EssentialProduct
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EssentialProduct
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DeadDead
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GeneticInteractionNetwork
Similar Patterns of Genetic Interactions Identify Pathways or Complexes
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Scenarios That May Give Rise to Synthetic Interaction
• Interpretation depends on context• Each synthetic interaction must be interpreted on a case-by-case
basis (Guarente (1993) TIG, 9:362)
orA B or
regulates
A BA B
etc. etc.
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xxxbni1 XMating
MAT MATa
a/wild-type
Sporulation
MATa Haploid Selection(MFA1pr-HIS3)
Double Mutant Selection
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Synthetic Gene Array (SGA) Statistics
• 132 query gene mutations were crossed into ~4700 yeast deletion mutants.• Query genes derived from 3 basic functional groups: (1) actin/polarity/secretion,
(2) microtubule/mitosis, and (3) DNA synthesis/repair.• Number of interactions per query varied from 1 to 146 with an average of 36.• (Genes, Genetic Interactions): ~1000 nodes and ~4000 edges.• 17 to 41% false negative rate• False positive rate?• Data quality is good
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Making Sense of Genetic Interaction Network
• Correlation with GO annotations
• Hierarchical clustering groups according to their SGA profile– Useful for inferring function of unknown genes
• Correlation with protein-protein interactions?– Only 30/4039 encode physically-interacting proteins
• Statistical properties of genetic interaction network graph
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Network of GO Attributes
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ClusteringArray
Query
Cell polarity• Actin patches• Endocytosis• Cell wall synthesis• Cell integrity (PKC)
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Cell Polarity 20%
Cytokinesis 6%
Cell Wall Maintenance18%Cell Structure
6%
Mitosis16%
Unknown22%
OthersPCL1ELP2ELP3
Vesicular TransportSNC2VPS28YPT6
UnknownBBC1/YJL020c NBP2 TUS1YBL051cYBL062wYDR149cYHR111wYKR047wYLR190wYMR299cYNL119w
MitosisARP1ASE1DYN1DYN2JNM1PAC1NIP100NUM1
Cell Wall MaintenanceBCK1SLT2BNI4CHS3SKT5/CHS4CHS5CHS7FAB1SMI1
Cell StructureATS1PAC11YKE2/GIM1
Cell PolarityBEM1BEM2BEM4BUD6SLA1CLA4ELM1GIN4NAP1SWE1
CytokinesisBNR1CYK3SHS1
bni1: Genome-Wide Synthetic Lethality Screen
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Cell Polarity 20%
Cytokinesis 6%
Cell Wall Maintenance18%Cell Structure
6%
Mitosis16%
Unknown22%
OthersPCL1ELP2ELP3
Vesicular TransportSNC2VPS28YPT6
UnknownBBC1/YJL020c NBP2 TUS1YBL051cYBL062wYDR149cYHR111wYKR047wYLR190wYMR299cYNL119w
MitosisASE1ARP1DYN1DYN2JNM1PAC1PAC11NIP100NUM1
Cell Wall MaintenanceBCK1SLT2SMI1CHS3SKT5/CHS4CHS5CHS7BNI4SMI1
Cell StructureATS1PAC11YKE2/GIM1
Cell PolarityBEM1BEM2BEM4BUD6SLA1CLA4ELM1GIN4NAP1SWE1
CytokinesisBNR1CYK3SHS1
bni1: Genome-Wide Synthetic Lethality Screen
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DNA RepairASF1HPR5POL32RAD27RAD50SAE2SLX1MMS4/SLX2MUS81/SLX3SLX4WSS1
DNA SynthesisRNR1RRM3YNL218w
MeiosisCSM3
UnknownYBR094w
OthersPUB1RPL24ASWE1SIS2SOD1
sgs1 : Genome-Wide Synthetic Lethality Screen
(24 Interactions)
Chromatin StructureESC2ESC4TOP1
DNA Repair 46%
DNA Synthesis13%
Meiosis4%
Chromatin Structure13%
Cell Polarity4%
Unknown4%
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Cell PolarityCell Wall Maintenance Cell StructureMitosisChromosome StructureDNA Synthesis DNA RepairUnknownOthers
8 SGA Screens:291 Interactions204 Genes
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Extension of SGA: E-MAP• E-MAP = epistatic miniarray profiles• Quantitative measurement of phenotype (e.g. growth rate)
– Measure both aggravating and alleviating genetic interactions
• Hypomorphic alleles (not null mutations)• Focus on subset of genes• Maya Schuldiner/Jonathan Weissman
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Complex A
P
X
X X = NegativePositive=
Complex B
Complex C
Complex X
Complex Y
Complex Z
Organizing Complexes into Pathways Using Genetic Interactions
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“RNA World” E-MAP (600 genes)
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Positive Genetic Interactions
Negative Genetic Interactions
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Positive Genetic Interactions
Negative Genetic Interactions
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Proteasome Mutants Suppress Deletions in THP1/SAC3
WT
∆thp1∆thp1 ∆sem1
∆sem1
rpn11-DAmP∆thp1 rpn11-DAmP
∆thp1 rpt6 tsrpt6 ts
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Proteasome Mutants Suppress mRNA Export Defects of thp1∆
polyARNA
Nuclei
Merge
WT ∆thp1 ∆thp1∆sem1
polyARNA
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Proteasome is Required for Efficient polyA mRNA Export
WT ∆sem1
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Complex A
P
X
X X= synthetic lethalityepistatic/
suppressive=
Complex B
Complex C
Complex X
Complex Y
Complex Z
Organizing Complexes into Pathways Using Genetic Interactions
What about essential genes??????
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Essential vs. Non-essential Genes in Budding Yeast
Non-Essential Genes (~4800)
Essential Genes (~1050)
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3. Conditional point mutants
CREATING MUTANT ALLELES OF ESSENTIAL GENES
1. TET-Promoter Shut-Off Mutants
2. DAmP Alleles
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1. TET-Promoter SHUT-Off Strains
-Hughes and colleagues created a library of promoter-shutoff strains comprising nearly two-thirds of all essential genes in yeast (602 genes)
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1. TET-Promoter SHUT-Off Strains
-the library was subjected to morphological analysis, size profiling, drug sensitivity screening and microarray expression profiling
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1. TET-Promoter SHUT-Off Strains
Cell Morphology
Cell Size
Cdc53
rRNA Processing
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1. TET-Promoter SHUT-Off Strains
Gene Expression Analysis
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1. TET-Promoter SHUT-Off Strains
Ribosome Biogenesis
Ymr290c, Ykl014c, Yjr041c
Mitochondrial RegulationYol026c
Protein Secretion
Ylr440c
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1. Genetic Analsyis using the TET-Promoter SHUT-Off Strains
-30 different mutants X TET-promoter collection
-found many interactions between dissimilar genes
-claimed that there are five times as many “negative” genetic interactions for essential genes when compared to non-essential genes
-however, the cause of this may be due to the fact that the TET strains were very sick (and they were not quantitatively assessing the growth of the double mutant by considering the growth of the two single mutants)
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2. DAmP Alleles
(Schuldiner et al., Cell, 2005)
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2. DAmP Alleles
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3. Point Mutants of Essential Genes
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Genetic Profiling of Point Mutants Reveals Insight on Structure-Function
PCNA (Pol30)
-PCNA interacts with CAF-1, a three-subunit protein, to couple DNA replication or DNA repair to nucleosome deposition
-PCNA is important in many aspects of DNA metabolism, including DNA replication and DNA repair
-Two mutants of PCNA (pol30-8 and pol30-79) generated by Stillman and colleagues
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Genetic Profiling of Point Mutants Reveals Insight on Structure-Function
PCNA (Pol30)
-PCNA interacts with CAF-1, a three-subunit protein, to couple DNA replication or DNA repair to nucleosome deposition
-PCNA is important in many aspects of DNA metabolism, including DNA replication and DNA repair
-Two mutants of PCNA (pol30-8 and pol30-79) generated by Stillman and colleagues
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What is “Chemical Genetics?”
Chemical genetics is the use of exogenous ligands to alter the function of a single gene product within the context of a complex cellular environment.
Find ligands that affect a biological process (forward)Optimize ligands to study protein function (reverse)
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Forward Chemical Genetics
• Screening large sets of small molecules
• Goal is target identification
• Those that cause a specific phenotype of interest are used to isolate and identify the protein target
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Forward Chemical GeneticsTarget Identification
Plate with cells
Add one compoundper well
Select compound thatproduces phenotypeof interest
Identify proteinTarget(deconvolution)
N
N
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Reverse Chemical Genetics
• Screen for compounds that bind to a given protein
• Optimize for selectivity
• Goal is target function and validation
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NN
Reverse Chemical GeneticsTarget Validation
Find ligand forprotein of interestOptimize for selectivty
Add ligandto cells
Assay forphenotype
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FORWARD Chemical Genetic Studies in Yeast
1. Screening the deletion set for drug sensitivities
2. Comparing mutant profiles to drug profiles
3. Haploinsufficieny analysis
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Complex A
P
X
X= synthetic lethality
Complex B
Complex C
Complex X
Complex Y
Complex Z
Organizing Complexes into Pathways Using Genetic Interactions
X= Drug
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Alive
Alive
Dead
Alive
Alive
Dead
Synthetic Lethal Interactions Synthetic Chemical Interactions
Deletion Mutants Sensitive to a Particular Drug Shouldbe Synthetically Lethal with the Drug Target
Drug
Drug
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1. Screening the deletion set for drug sensitivities
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1. Screening the deletion set for drug sensitivities
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FORWARD Chemical Genetic Studies in Yeast
1. Screening the deletion set for drug sensitivities
2. Comparing mutant profiles to drug profiles
3. Haploinsufficieny analysis
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2. Comparing mutant profiles to drug profiles
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Parsons et al., 2004, Nature Biotechnology
1. Clustering of the Drug Profiles:
Camptothecin and Hydroxyurea have a similar mode of action: they both inhibit DNA replication
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RFA1RTT105POL30-79POL30-879POL32RAD27RFC5POL30ELG1RFA2PRI1RFC4CDC9TSA1CAMPTOTHECIN (15 g/ml)CAMPTOTHECIN (30 g/ml)
DNA Replication Factors
CAMPTOTHECIN: causes single-stranded DNA nicks and inhibits DNA replication
Also known as : Hycamtin (GlaxoSmithKline) and Camptosar (Pfizer)
-used as an anti-cancer agent
2. Comparison of drug profiles to mutant profiles:
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TUB3PAC2CIN1CIN2CIN4BENOMYL (15 g/ml)
Benomyl: a drug that targets microtubules and affects chromosome segregation
CIN1, CIN2, CIN4: genes required for microtubule stability
TUB3: alpha-tubulin
PAC2: tubulin chaperone
2. Comparison of drug profiles to mutant profiles:
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FORWARD Chemical Genetic Studies in Yeast
1. Screening the deletion set for drug sensitivities
2. Comparing mutant profiles to drug profiles
3. Haploinsufficieny analysis
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3. Haploinsufficieny Analysis
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Protein A
P
Protein B
Protein C
Reduced Levels of Protein A
Haploinsufficiency: Drug
Lethality!!!
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3. Haploinsufficieny Analysis
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TUB1/TUB1 vs. tub1/TUB1
25 ug/ml benomyl 50 ug/ml benomyl
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-used a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae
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Strategy for Global Haploinsufficiency Analysis Using Microarrays
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Comprehensive View of Fitness Profiles for 78 Compounds
No Drug-Specific Fitness Changes
Small Number of Highly Significant Outliers
Widespread Fitness Changes
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Molsidomine: potent vasodilator used clinically to treat angina
Erg7: Lanosterol synthase is a highly conserved and essential component of ergosterol biosynthesis
Overexpression of Erg7 results in Resistance to Molsidomine
Identification of Erg7 as the Target for Molsidomine
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5-Fluorouracil Targets rRNA Processing
5-Fluorouracil
-one of the most widely used chemotherapeutics for the treatment of solid tumors in cancer patients
-thought to affect DNA synthesis as a competitive inhibitor of thymidylate synthetase
Rrp6, Rrp41, Rrp46, Rrp44: ExosomeMak21, Ssf1, Nop4, Has1: rRNA Processing
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The yeast knockout collection
http://www-sequence.stanford.edu/group/yeast_deletion_project/deletions3.html
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Using the knockouts for microarrays
A Robust Toolkit for Functional Profiling of the Yeast Genome Pan et al. (2004) Mol Cell 16, 487
Takes advantage of the MATa/ heterozygous diploid collection identifies synthetic lethal interactions via diploid-based synthetic
lethality analysis by microarrays (“dSLAM”)
Uses dSLAM to identify those strains that upon knockout of a query gene, show growth defects
synthetic lethal (the new double mutant = dead) synthetic fitness (the new double mutant = slow growth)
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Step 1: Creating the haploid convertible heterozygotes
Important point:This HIS3 gene is only expressed in MATa haploids, not in MAThaploids or MATa/ diploids
So in other words, can select against MATa/ diploids to ensure you’re looking at only haploids later on.
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Step 2: Inserting the query mutation
Knockout one copy of your gene of interest (“Your Favorite Gene”) with URA3
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Step 3: Make new haploids and select for strains of interest
Sporulate to get new haploids
Select on –his medium to ensure only haploids survive (no diploids)
selects against query mutation so genotype is xxx::KanMX YFG1
selects for query mutation so genotype is xxx::KanMX yfg1::URA3
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Reminder about YKO construction
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U1 D1
U2 D2
Using common oligos U1 and U2 (or D1 and D2) amplifies the UPTAG (or DNTAG) sequence unique to each of the KOs
Step 4: Prepare genomic DNA and do PCR with common TAG sequences
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Step 4: Prepare genomic DNA and do PCR with common TAG sequences
The two different conditions are labeled with two different colors**
The labeled DNA is then incubated with a TAG microarray
**The PCR reactions create a mixture of TAGs (representing all the strains in the pool), since each KO has a unique set of identifier tags (UPTAG and DNTAG) bounded by common oligonucleotides
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Evidence this really works – part I
Strains
x-axis y-axis
XXX/xxx::KanMXCAN1/CAN1
XXX/xxx::KanMXCAN1/can1::MFA1pr-HIS3
On average, the intensity is the same before and after 1 copy of the CAN1 gene is knocked out
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Evidence this really works – part II
Strainsx-axis y-axis
DIPLOIDSXXX/xxx::KanMX
CAN1/can1::MFA1pr-HIS3
HAPLOIDSXXX or xxx::KanMXcan1::MFA1pr-HIS3
Red spots illustrate that fraction of the strains with KOs in essential genes, so when haploid, not present in pool
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Another variation: Drug sensitivity
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Another variation: Drug sensitivity
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Summary
If you can compare two different conditions and you have a way to stick things to slides, some sort of microarray is possible!
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HOW NOT TO LOOK AT INTERACTION DATA!!!!!!!!