Modeling Com binatorial I ntervention Effects in Transcription Netw - PowerPoint PPT Presentation

Modeling Com binatorial I ntervention Effects in Transcription Netw orks ( The Sound of One-Hand Clapping) Achim Tresch Com putational 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 A paradoxical anecdote or riddle, used in Zen Buddhism to demonstrate the inadequacy of logical reasoning and to provoke enlightenment.

Synthetic Genetic I nteractions How to define “ Interaction “ Growth Y B of single mathematically? Δ B manipulation of B Growth Y A of single Synthetic manipulation of A Genetic Array Δ A Growth Y AB of double manipulation Δ A of A and B Δ B modified after Collins, Krogan et al., Nature 2007

Synthetic Genetic I nteractions How to define “ Interaction “ Phenotype Measurement Y B mathematically? Δ B of single perturbation Phenotype Measurement Y A Phenotype of single perturbation Measurement Y AB of double perturbation Δ A The interaction score S AB is a function of the two single perturbations and the Δ A combined perturbation, Δ B S AB = S AB (Y A ,Y B ,Y AB )

Synthetic Genetic I nteractions Common Interaction Scores Define an expected phenotype of the double perturbation as a function f(Y A ,Y B ) of the single perturbation phenotypes Y A and Y b . The interaction score S AB is then the deviation from the expected phenotype S AB = Y AB - f(Y A ,Y B ) Common choices for f : f = min(Y A ,Y B ) (v. Liebig s minimum rule for plant growth) (chemical equilibrium a + b ↔ ab , [a][b] = [ab]) f = Y A ·Y B f = Y A + Y B (log version of Y A ·Y B ) f = log 2 [( 2 YA - 1 )( 2 YB - 1 ) + 1 ] (essentially the same as Y A + Y B ) Results crucially Interaction Scores depend on f are not very reliable Mani, Roth et al., PNAS 2007

Synthetic Genetic I nteractions 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

Synthetic Genetic I nteractions 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

Screening for TF interactions If two hands clap and there is a sound; what is the sound of one hand? Δ A One manipulation High dimensional readout

Genetic interactions from one perturbation Step 1: Construct a transcription factor - target graph a) From ChIP binding experiments Harbison, Fraenkel, Young et al. Nature 2004 MacIsaac, 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

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)

Genetic interactions from one perturbation Step 2: Combine TF-target information and expression data ~2.000 118 transcription Established Methods for the target genes factors 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)

Genetic interactions from one perturbation Step 3: Given TF1 and TF2, group genes into 4 interaction classes Binding sites TF 1 TF 2 Synthesis rates during salt stress gene 1 TF 1 is active gene 2 TF1 TF 2 is active gene 3 TF2 TF 1+2 active TF1 TF2 gene 4 time Antagonistic interaction of TF 1+2

Genetic interactions from one perturbation Step 3: Given TF1 and TF2, group genes into 4 interaction classes Binding sites TF 1 TF 2 Synthesis rates during salt stress 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

Genetic interactions from one perturbation Step 4: Use these 4 groups to define an interaction score For any pair of transcription factors T 1 and T 2 , we perform a logistic regression.   P ( g is induced )   β log ~   0   P ( g is not induced ) + β ⋅ Ind ( g is a target of TF1 ) 1 + β ⋅ Ind ( g is a target of TF2) (for all genes g) 2 + β ⋅ Ind ( g is a target of TF1 and TF2) 12 Our interaction score for the pair ( T 1 , T 2 ) is then β 12 .

Genetic interactions from one perturbation Step 4: Use these 4 groups to define an interaction score β + β ⋅ → + β ⋅ → + β ⋅ → . . . ~ Ind ( TF g ) Ind ( TF g ) Ind ( TF , TF g ) 0 1 1 2 2 12 1 2 Binding sites Example: β 0 < TF 1 TF 2 0 gene 1 β ~ 0 β + β > TF 1 is 0 0 1 active gene 2 β + β ~ 0 1 TF 2 is β + β > 0 0 2 active gene 3 β + β ~ 0 2 β + β + β + β < 0 0 1 2 12 β < β − β + β − β + β < ( ) ( ) 0 12 0 0 1 0 1 TF 1+2 gene 4 active time β + β + β + β ~ 0 1 2 12 Antagonistic interaction

Application: Osm otic 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

Application: Osm otic stress in yeast Validation with BioGRID database: Among 84 TFs under consideration (with enough targets), 3486 potential interactions Exist. Only 97 interactions are recorded.

Application: Osm otic stress in yeast Validation with BioGRID database: Single interactions scores Profile correlations don‘t work well do work

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 (Mitchell, Pilpel at al. Nature 2009): leads to similar results: 3 stress responses: osmotic stress NaCl, osmotic stress KCl, heat shock

Acknow ledgem ents Gene Center Munich: Patrick Cramer Dietmar Martin Björn Schwalb 20 Sebastian Dümcke

Zen Biology Systems Buddhism My Answ er Two hands clap and there is a sound; what is the sound of one hand? It is similar for transcription factors that interact.