Combinatorics of promoter regulatory elements determines gene expression profiles Yitzhak (Tzachi) Pilpel Priya Sudarsanam George Church DJ Club, Feb. 2001

Goals of study Identify regulatory networks on a genome- wide scale study the combinatorial nature of transcription regulation Propose causal link between promoter sequence elements and expression patterns

The current methodology for expression - regulatory motif analysis (Tavazoie et al.)

Collaboration ? Co-occurrence (AND) Redundancy (OR) In case of two motifs derived from a cluster

Two motifs derived from the same cell-cycle cluster Normalized expression level MCB and SCB Time MCB but not SCB SCB but not MCB Time

Is this motif necessarily non-functional ? In case of multiple clusters that give rise to a motif

Condition-specific TF-TF interaction can be identified (in cell cycle) Mcm1 Forkhead Forkhead & Mcm1 Time

Assigning promoters to motifs :ScanACE (Hughes et al.) Expression

A proposed reversed analysis method: ScanACE

To avoid circularity we generated expression-independent motif data set motifs derived from MIPs functional classification (Hughes J et al.) 40 motifs of known TFs were added (27 overlapped to the MIPs derived motifs)

Expression experiments used Cell cycle (Cho et al.) Sporulation (Chu et al.) Diauxic shift (DeRisi et al.) Heat shock (Eisen et al.) Cold shock (Eisen et al.) Reduction with dtt (Eisen et al.) MAPK signaling (Roberts et al.) NER (Jalinski et al.) Peroxide (Cohen et al.)

Ndt80 Putative motif Sporulation Cell-cycle Use a Diversity of expression data to diagnose motifs

The expression coherence score * * * * * * * * * * d ij Threshold d ij (top 5 %) Expression coherence=fraction of i,j pairs with d ij <Threshold d ij Gene Set 1 Gene Set 2

Identification of functional motifs

New significantly highly scoring motifs For a motif with 300 occurrences in URs the genome, the p-value for an expression coherence score of 0.1 is < 1e-12 P ( p) ~ BinomCDF(p,P,0.05), where p, and P are numbers of correlated pairs and total number of pairs, respectively

For two motifs, RRPE and PAC PAC RRPE

For every combination of N=2,3 motifs Calculate the expression coherence score of the orf that have the N motifs Calculate the expression coherence score of orfs that have every possible subset of N-1 motifs Test (statistically) the hypothesis the score of the orfs with N motifs is significantly higher than that of orfs that have any sub set of N-1 motifs

Ribosomal motifs Rap1-rRPE rRPE-PAC PAC-rPPS2...

Cell cycle and sporulation motifs Cell-cycle Sporulation

Motif combinations establish sequence-expression causality * * *

C.C Expression coherence 'MCB' 'cytok9' 'ndt80' 'Ume6' 'meiosis_3' 'SCB' 'CLB2' 'FKH1Sh' Cell-cycle Less than a minute on a PowerMac G4 (after pre-processing)

C.C Expression coherence 'MCB' 'cytok9' 'ndt80' 'Ume6' 'meiosis_n3' 'SCB' 'CLB2' 'FKH1Sh' Sporulation

From the literature: 1)Meiotic role of SWI6 in ( Nucleic Acids Res. 1998) 2) Role for MCB in sporulation (Nature Genetics 2001) Different role for MCB and SCB A potential role of SCB-fkh in giving rise to an Ndt80-type of response Ndt80’s only synergistic partners in sporulation are cell cycle motifs We add:

'Rap1' 'RPE6' 'PAC' 'rRPE' 'rRSE3' 'rRSE10' 'Abf1' 'REB1' 'CCA' 'RPN4' 'HAP234' 'LFTE17' 'Rap1' 'RPE6' 'PAC' 'rRPE' 'rRSE3' 'rRSE10' 'Abf1' 'REB1' 'CCA' 'RPN4' 'HAP234' 'LFTE17' NER

What can we infer about specific network architecture ? Asses the contribution of each motif in a combination Establish hierarchy motifs Identify the logical association between motifs: OR for cases of redundancy, and for cases of synergy

A global motif interaction map a1 22 11

What can we learns about global interaction ? Identify central motif players Suggest regulatory role of un-annotated motifs

Acknowledgments Priya Sudarsanam Barak Cohen John Aach Aimee Dudley Jason Hughes Rob Mitra Wayne Rindone Fritz Roth Uri Keich (UCSF) George Church

Genes defined by Motif Combination (GMC)