Phenotype and the Interaction of Genetic Perturbations Informatics for System Genetics.
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Transcript of Phenotype and the Interaction of Genetic Perturbations Informatics for System Genetics.
![Page 1: Phenotype and the Interaction of Genetic Perturbations Informatics for System Genetics.](https://reader030.fdocuments.us/reader030/viewer/2022032723/56649d125503460f949e5a56/html5/thumbnails/1.jpg)
Phenotype and the Interaction ofGenetic Perturbations
Informatics for System Genetics
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Phenotype and the Interaction ofGenetic Perturbations
- Introduction- Generalized derivation of genetic-interaction networks- Generation of a yeast invasiveness network- Local and global interaction patterns
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Phenotype and the Interaction ofGenetic Perturbations
Introduction
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Network element activities and phenotype
• microarray/proteomics: expression and physical interactions of each constituent• phenotype: a system variable• biomedicine
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Directed Perturbations
• Many systems have deletion projects/consortia/databases– yeast, worm, mouse, fly
• Molecular biology methods can target large numbers of genes – antisense oligos, including morpholinos– RNA interference– inducible promoters
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RNAi
Fraser et al. (Nature 408, p. 35, 2000) targeted 90% of genes on C. elegans chromosome I using RNA interference experiments, and classified resulting phenotypes.
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Synthetic Genetic Array analysis• Systematic
construction of double deletion mutants
• A mutant is crossed to an array of ~5000 deletion mutants.
• Observing synthetic lethal genetic interactions, generated a network of 291 interactions between 204 genes.
• Tong et al. (Science 294, p. 2364, 2001)
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SGA
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Genetic-Interaction Databases
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Phenotype Ontologies
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Open Microscopy Environment (Sorger Lab)
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What’s Needed
-Parallel advances in in concepts and computational methods
- Generalized derivation of genetic-interaction networks
- Quantitative (at least ordered) phenotype data
- Analysis of local and global interaction patterns
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Phenotype and the Interaction ofGenetic Perturbations
Generalized derivation of genetic-interaction networks
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Genetic Interaction
- Interaction of two genetic perturbations in the determination of a phenotype
- Observed in the phenotypes of four genotypes:1) a reference genotype, the “wild type”2) a perturbed genotype, A3) a perturbed genotype, B, with a perturbation of a
different gene4) a doubly perturbed genotype, AB.
- Perturbations may be of any form (null, loss-of-function, gain-of-function, dominant-negative, etc.).
- Two perturbations can interact in different ways for different phenotypes or under different environmental conditions.
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Example
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Hereford-Hartwell 1974
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Hereford-Hartwell double mutant epistasis analysis
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Hartwell: Synthetic Defects and Phenotype Buffering
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Example
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75 Phenotype Inequalities in 9 (A)Symmetric Interaction Modes
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Phenotype and the Interaction ofGenetic Perturbations
Generation of a yeast invasiveness network
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Dimorphic Fungal PathogensDimorphic Fungal Pathogens
S. cerevisiae Magnaporthe grisea
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Filamentous-Form System PropertiesFilamentous-Form System Properties
• altered cell-cycle progression
• cell elongation
• unipolar distal budding
• adhesion
• host (substrate) invasion
• altered metabolism
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Key Pathways
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Transformation of Knockout Strains with
Multicopy Plasmids
• We transformed 118 homozygous diploid knockout strains plus a wildtype control
strain with plasmids for constitutive overexpression of genes involved in regulation of
filamentous growth.
Large-scale Genetic Perturbation
Ras2
Rsr1
Cdc42
Flo8
Kss1Ste11Ste12
Phd1
Msn1Gln3
Bem1
Tec1
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Strains:Diploid 1278b mutants transformed with multicopy plasmids
Phenotype:•Agar invasion
Conditions:High glucose, low nitrogen
Wash Assay for agar invasion:
prewash colony
postwash colony
Phenotype Analysis
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yyyxxx X
Mating
MAT MATa
a/
Sporulation
Haploid SelectionP-MFA1::HIS3
Homozygous Double Mutant
xxxyyy
Mat xxx::HygMX x
Mata yyy::KanMX
Matxxx::HygMX yyy::KanMX
Mata xxx::NatMX x
Mat yyy::KanMX
Mata xxx::NatMX yyy::KanMX
Mate and select for HygR NatR to get diploid xxx yyy
Strain Construction
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Strains are pinned onto solid media in a 384-spot format.
Each strain is represented by 4 independent constructions.
4 replicates of each plate are pinned.
Each plate contains 48 spots of a wildtype vector control strain.
Phenotype Analysis
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Analysis of agar invasion phenotypes of diploid mutant strains on low-nitrogen media
Pin strains onto low-nitrogen media
Incubate 4 days at 30o C
Scan plate Scan washed plate
Wash plate
Prewash image Postwash image
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Quantitation of Invasiveness
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Agar invasion phenotypes of diploid mutant strains on low-nitrogen media
flo1
flo11
bud6
tpk2
Prewash image Postwash image
hmi1
bud8
rim9
dia4dfg16isw1
InvasiveNon-Invasive Hyper
Agar invasion can be visualized in the composite image.
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Phenotype Data AnalysisI. Calculate ratios of postwash signal/prewash signal
Raw data file from dapple processed to ID spots and subtract background.
Output contains X = prewash signal and Y = postwash signal for each spot.
Calculate the ratio Y/X for each spot.
II. Normalize data to allow comparison of strains on different plates
Each plate contains 48 wildtype controls.
Calculate the median Y/X ratio for the wildtype vector controls on each plate = Mn for plate n.
The correction factor for plate n is [median (all M values)/Mn].
III. Phenotype Error = MAX(MAD, 10%MAD)
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Inva
sive
nes
sQuantitative Phenotypes
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Example: Image Data
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Example: Data Analysis
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Phenotype Error
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Data Subset
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Entire Network
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Interaction-Mode Distribution
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Error Parameter Insensitivity
Effect of error model on distribution of interaction classes
0
100
200
300
400
500
600
700
800
900
0 10 20 30 40 50 60 70 80 90 100
Percentile MAD
# o
f in
tera
cti
on
s
non-interacting
asynthetic
suppression
synthetic
epistatic
conditional
double nonmonotonic
single nonomonotonic
additive
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Phenotype and the Interaction ofGenetic Perturbations
Local and global interaction patterns
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Local Interaction,with Biological Processes
- Is there “monochromatic” interaction with modules?
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Gene Form Interaction Biological Process ‑log10P
PBS2 null additive signal transduction 2.99
PBS2 null additive small GTPase mediated signal transduction
2.96
STE12 gf single-nonmonotonic to
protein targeting 2.87
STE11 da noninteractive cell cycle 2.73
PHD1 gf hypostatic to invasive growth 2.68
PDE2 null noninteractive protein amino acid phosphorylation
2.56
HSL1 null suppressed by cell wall organization and biogenesis
2.52
STE20 gf single-nonmonotonic to
protein targeting 2.31
EGT2 null conditioned by invasive growth 2.30
ISW1 null suppresses small GTPase mediated signal transduction
2.30
CLB1 null noninteractive protein metabolism 2.30
STE11 da suppresses cell surface receptor linked signal transduction
2.28
BEM1 gf conditioned by nucleobase, nucleoside, nucleotide and nucleic acid metabolism
2.25
PBS2 null additive RAS protein signal transduction
2.24
PBS2 null additive sporulation 2.24
TEC1 gf synthetic intracellular signaling cascade 2.19
IPK1 null additive M phase 1.95
TEC1 null epistatic to metabolism 1.94
TEC1 gf conditioned by carbohydrate metabolism 1.94
TEC1 gf conditioned by RAS protein signal transduction
1.94
BUD4 null noninteractive establishment of cell polarity 1.94
HMS1 null noninteractive protein amino acid phosphorylation
1.83
YGR045C
null noninteractive protein amino acid phosphorylation
1.83
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Local Interaction, with Biological Processes
As noted for epistasis and synthesis…the results suggest there are characteristic network mechanisms to be found underlying the various modes of genetic interaction.
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Global Interaction Patterns
- genetic-interaction complexity- map similarities among perturbations in interaction patterns
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Global Interaction Patterns
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, , )( XxxP where
Xx
xP .1)(
)()(
),(log),(];[ 2 bPaP
baPbaPBAI
Aa Bb
and bits. 0];[];[ ABIBAI
and
Mutual Information
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Global Interaction Patterns
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Gene1a Gene2a Commonb Mutual Info.c -log10P
STE20(gf) STE12(gf) 99 1.8 16.3
PBS2(lf) HOG1(lf) 101 1.2 14.1
CDC42(gf) BEM1(gf) 99 1.0 9.5
STE20(gf) CDC42(gf) 100 1.5 9.2
PBS2(lf) HSL1(lf) 95 1.5 8.9
STE12(gf) CDC42(gf) 101 1.5 8.0
FLO8(gf) STE20(gf) 100 1.3 6.7
STE20(gf) TEC1(gf) 99 0.9 6.6
STE12(gf) GLN3(gf) 99 1.4 6.3
TEC1(gf) BEM1(gf) 95 0.7 5.0
SFL1(lf) HOG1(lf) 75 0.8 4.8
STE12(gf) BEM1(gf) 97 0.8 4.4
CDC42(gf) GLN3(gf) 101 1.3 4.3
HOG1(lf) HSL1(lf) 99 0.9 4.3
CDC42(gf) PBS2(lf) 86 1.0 3.5
FKH2(lf) YAP1(lf) 18 2.2 3.5
TEC1(gf) CDC42(gf) 99 0.8 3.3
ISW1(lf) YAP1(lf) 17 2.4 3.3
RGS2(lf) MID2(lf) 15 2.3 3.3
STE20(gf) GLN3(gf) 98 1.2 3.3
YJL142C(lf) YAP1(lf) 17 2.1 3.2
EGT2(lf) RGS2(lf) 16 2.1 3.1
STE12(gf) TEC1(gf) 98 0.8 3.0
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A Mutual-Information Network
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A Mutual-Information Network
…suggests mutual information reflects similarities in the global effects of perturbations on molecular information flows.
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PhenotypeGenetics
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Priorities
1) continuing advances in quantitative phenotype measurement and ontologies
2) reinforcement or revision of genetic-interaction mode definitions based on relevance to network mechanisms
3) extension of all genetic-interaction modes beyond phenotype ordering to incorporate parameters derived from phenotype magnitudes
4) comparative genetic-interaction analyses of multiple alleles (with different effects on function) of individual genes to learn how different levels of gene activity impact the network
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Network Visualization and
Modeling
Data AcquisitionPhenotypesMicroarrays
Proteomics,…
Pathway/Interaction Databases
Analysis Modules
NetworkRefinement
Network modeling by iterative refinement
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Phenotype and the Interaction ofGenetic Perturbations
Informatics for System Genetics
Becky Drees Marisa RaymondVesteinn Thorsson Iliana Avila-CampilloGreg Carter Paul ShannonAlex Rives Tim Galitski