Phenotype and the Interaction of Genetic Perturbations

Phenotype and the Interaction ofGenetic Perturbations

Informatics for System Genetics


- Introduction- Generalized derivation of genetic-interaction networks- Generation of a yeast invasiveness network- Local and global interaction patterns


Introduction

Network element activities and phenotype

• microarray/proteomics: expression and physical interactions of each constituent• phenotype: a system variable• biomedicine

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

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.

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)

Genetic-Interaction Databases

Phenotype Ontologies

Open Microscopy Environment (Sorger Lab)

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


Generalized derivation of genetic-interaction networks

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.

Example

Hereford-Hartwell 1974

Hereford-Hartwell double mutant epistasis analysis

Hartwell: Synthetic Defects and Phenotype Buffering

Example

75 Phenotype Inequalities in 9 (A)Symmetric Interaction Modes


Generation of a yeast invasiveness network

Dimorphic Fungal PathogensDimorphic Fungal Pathogens

S. cerevisiae Magnaporthe grisea

Filamentous-Form System PropertiesFilamentous-Form System Properties

• altered cell-cycle progression

• cell elongation

• unipolar distal budding

• adhesion

• host (substrate) invasion

• altered metabolism

Key Pathways

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

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

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

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

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

Quantitation of Invasiveness

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.

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)

Inva

sive

nes

sQuantitative Phenotypes

Example: Image Data

Example: Data Analysis

Phenotype Error

Data Subset

Entire Network

Interaction-Mode Distribution

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


Local and global interaction patterns

Local Interaction,with Biological Processes

- Is there “monochromatic” interaction with modules?

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

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.

Global Interaction Patterns

- genetic-interaction complexity- map similarities among perturbations in interaction patterns

, , )( XxxP where

Xx

xP .1)(

)()(

),(log),(];[ 2 bPaP

baPbaPBAI

Aa Bb

and bits. 0];[];[ ABIBAI

and

Mutual Information

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

A Mutual-Information Network

A Mutual-Information Network

…suggests mutual information reflects similarities in the global effects of perturbations on molecular information flows.

PhenotypeGenetics

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

Network Visualization and

Modeling

Data AcquisitionPhenotypesMicroarrays

Proteomics,…

Pathway/Interaction Databases

Analysis Modules

NetworkRefinement

Network modeling by iterative refinement


Informatics for System Genetics

Becky Drees Marisa RaymondVesteinn Thorsson Iliana Avila-CampilloGreg Carter Paul ShannonAlex Rives Tim Galitski

Phenotype and the Interaction of Genetic Perturbations

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