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Modeling Combinatorial Intervention Effects in Transcription Networks. (The Sound of One-Hand Clapping). Achim Tresch Computational Biology Gene Center Munich. The Question. If two hands clap and there is a sound; what is the sound of one hand?. (Japanese Kōan). Kōan

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Presentation Transcript
slide1
Modeling Combinatorial Intervention Effects in Transcription Networks

(The Sound of One-Hand Clapping)

Achim TreschComputational Biology

Gene Center Munich

slide2
The Question

If two hands clap and there is a sound;

what is the sound of one hand?

(Japanese Kōan)

Kōan

A paradoxical anecdoteor riddle, used in Zen Buddhism to demonstrate the inadequacy of logical reasoning and to provoke enlightenment.

slide3
Synthetic Genetic Interactions

How to define “Interaction“ mathematically?

GrowthYB of single manipulation of B

ΔB

GrowthYA of single manipulation of A

Synthetic Genetic Array

ΔA

Growth YABof double manipulation of A and B

ΔA ΔB

modified after Collins, Krogan et al., Nature 2007

slide4
Synthetic Genetic Interactions

Phenotype Measurement YBof single perturbation

How to define “Interaction“ mathematically?

ΔB

ΔA

Phenotype Measurement YAof single perturbation

Phenotype Measurement YABof double perturbation

The interaction score SAB is a function of the two single perturbations and the combined perturbation,

ΔA ΔB

SAB= SAB (YA ,YB ,YAB )

slide5
Synthetic Genetic Interactions

Common Interaction Scores

Define an expected phenotype of the double perturbation as a function f(YA ,YB ) of the single perturbation phenotypes YA and Yb. The interaction score SAB is then the deviation from the expected phenotype

SAB= YAB - f(YA ,YB )

Common choices for f :f = min(YA ,YB ) (v. Liebig´s minimum rule for plant growth)

f = YA ·YB(chemical equilibrium a + b ↔ ab , [a][b] = [ab])

f = YA + YB (log version of YA ·YB ) f = log2[(2YA - 1)(2YB - 1) + 1](essentially the same as YA + YB )

Results crucially depend on f

Interaction Scores are not very reliable

Mani, Roth et al., PNAS 2007

slide6
Synthetic Genetic Interactions

Breakthrough: Combine a set of weak predictors to create a strong predictor (guilt by association = correlation of interaction scores)

Pan, Boeke et al., Cell 2006

Collins, Krogan et al., Nature 2007

Cartoon by Van de Peppel et al, Mol. Cell 2005

slide7
Synthetic Genetic Interactions

Take home message: Two components are likely to interact (physically) whenever they have the same interaction partners

Costanzo M, Myers CL, Andrews BJ, Boone C, et al.: Science 2010

slide8
Screening for TF interactions

If two hands clap and there is a sound;

what is the sound of one hand?

ΔA

One manipulation

High dimensionalreadout

slide9
Genetic interactions from one perturbation

Step 1: Construct a transcription factor - target graph

a) From ChIP binding experiments

Harbison, Fraenkel, Young et al. Nature 2004MacIsaac, Fraenkel et al. BMC Bioinformatics 2006

b) From protein binding arrays, followed by PWM-based predictions

Ansari et al., Nature Methods 2010

Berger, Bulyk et al., Nature Biotech 2006

slide10
Genetic interactions from one perturbation

Step 1: Construct a transcription factor - target graph

Intersection size of target sets of TF1 and TF2 can be used alone to assess TF cooperativity. (Beyer, Ideker et al., PlOS Comp. Biol 2006)

slide11
Genetic interactions from one perturbation

Step 2: Combine TF-target information and expression data

~2.000 target genes

118 transcription factors

Established Methods for the detection of univariate TF activity :

GSEA (Subramanian, Tamayo PNAS 2005)

Globaltest (Goemann, Bioinformatics 2004)

MGSEA (Bauer, Gagneur, Nucl. Acids Res. 2010)

and many more …

Common Idea: A TF is active if its set of target genes shows significantly altered expression.

To quantify this, various tests are constructed.

Graph obtained from MacIsaac et al. (BMC Bioinformatics 2006)

slide12
Genetic interactions from one perturbation

Step 3: Given TF1 and TF2, group genes into 4 interaction classes

TF1

TF1

Binding sites

Synthesis rates during salt stress

TF 1

TF 2

gene 1

TF2

TF2

TF 1 is active

gene 2

TF 2 is active

gene 3

TF 1+2 active

gene 4

time

Antagonistic interaction of TF 1+2

slide13
Genetic interactions from one perturbation

Step 3: Given TF1 and TF2, group genes into 4 interaction classes

Binding sites

Synthesis rates during salt stress

TF 1

TF 2

gene 1

TF 1 is inactive

gene 2

TF 2 is inactive

gene 3

TF 1+2 active

gene 4

time

Synergistic interaction of TF1+2

slide14
Genetic interactions from one perturbation

Step 4: Use these 4 groups to define an interaction score

For any pair of transcription factors T1 and T2, we perform a logistic regression.

(for all genes g)

Our interaction score for the pair (T1,T2) is then β12.

slide15
Genetic interactions from one perturbation

Step 4: Use these 4 groups to define an interaction score

Binding sites

Example:

TF 1

TF 2

gene 1

TF 1 is active

gene 2

TF 2 is active

gene 3

TF 1+2 active

gene 4

time

Antagonistic interaction

slide16
Application: Osmotic stress in yeast

Use the guilt by association trick to construct an interaction matrix for all transcription factors using only a two group microarray comparison!

Inclusion criterion: only TFs with >70 targets

„One hand clapping“

Miller, Tresch, Cramer et al., Mol. Syst. Biol. 2010, in revision

slide17
Application: Osmotic stress in yeast

Validation with BioGRID database:

Among 84 TFs under consideration (with enough targets), 3486 potential interactions

Exist. Only 97 interactions are recorded.

slide18
Application: Osmotic stress in yeast

Validation with BioGRID database:

Single interactions scores don‘t work well

Profile correlations do work

slide19
Genetic interactions from one intervention

One hand clapping can be applied to: Microarray data, Pol II ChIP data, nascent RNA data

Application to a similar dataset leads to similar results:

(Mitchell, Pilpel at al. Nature 2009):

3 stress responses:

osmotic stress NaCl, osmotic stress KCl, heat shock

slide20
Acknowledgements

Gene Center Munich:

Patrick CramerDietmar MartinBjörn Schwalb

Sebastian Dümcke

slide21
My Answer

Two hands clap and there is a sound;

what is the sound of one hand?

It is similar for transcription factors that interact.

Systems Buddhism

Zen Biology

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