Combinatorics of promoter regulatory elements determines gene expression profiles Yitzhak (Tzachi)...
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Transcript of Combinatorics of promoter regulatory elements determines gene expression profiles Yitzhak (Tzachi)...
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
.
Time Point 1
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
Nor
mal
ized
exp
ress
ion
leve
l
0 5 10 15-3
-2
-1
0
1
2
3
4
MCB andSCB
0 5 10 15-3
-2
-1
0
1
2
3
4
Time
MCB but notSCB
0 5 10 15-4
-3
-2
-1
0
1
2
3
4
SCB but notMCB
TimeTime
.
Time Point 1
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 ForkheadForkhead & Mcm1
0 5 10 15-3
-2
-1
0
1
2
3
4
0 5 10 15-3
-2
-1
0
1
2
3
4
Time Time Time
0 5 10 15-3
-2
-1
0
1
2
3
4
Assigning promoters to motifs :ScanACE(Hughes et al.)
Expression
.
Time Point 1
A proposed reversed analysis method:ScanACE
ScanACE
To avoid circularity we generated expression-independent motif data set
• 327 - 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.)
.
0 2 4 6 8-3
-2
-1
0
1
2
3
time
.
0 5 10 15-3
-2
-1
0
1
2
3
4
time
.
0 2 4 6 8-3
-2
-1
0
1
2
3
time
Ndt80.
0 5 10 15-3
-2
-1
0
1
2
3
4
time
Putativemotif
Sporulation Cell-cycleUse a Diversity of expression data to diagnose motifs
The expression coherence score
*
**
*
*
*
*
**
*dij
Threshold dij (top 5 %)
Expression coherence=fraction of i,j pairs with dij <Threshold dij
Gene Set 1 Gene Set 2
Identification of functional motifs
0
0.05
0.1
0.15
0.2
0.25
0.3
cell cycle
sporulation
diauxic shift
heat shock
MAPK
NER
0.00
5.00
10.00
15.00
20.00
25.00
30.00
cell cycle
sporulation
diauxic shift
temp shift
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
.
0.06 0.1 0.14 0.18 0.22 0.260
50
100
150
200
RRPE-PAC
Expression coherence
PACRRPE
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
Rap1rRSE3
rRPE
PAC
LYS
rRSE10
RPE58 RPE49
RPE34
OCSE15
RPE57
RPE69
RPE21
RPE6
RPE72
CCA
MERE17
RPE8
RPE17
Rap1-rRPErRPE-PACPAC-rPPS2...
Cell cycle and sporulation motifs
MCB
SCB
Ndt80
SSF
Mcm1
Middlesporulation
G1-Scell cycle
G1-Scell cycle
G2-Mcell cycle
G2-Mcell cycle
Cell-cycle
Sporulation
Motif combinations establish sequence-expression causality
2
222
11 1 11
1
12121212
* *
*
53
53 5465
5
546
54
InterGMC
123456
123456
Intra-GMC
0.3
0.6
0.9
1.2
1.5
1.8
1-C
.C
0.2
0.4
0.6
0.8
1
Exp
ress
ion
cohe
renc
e 'MCB' 'cytok9' 'ndt80' 'Ume6' 'meiosis_3' 'SCB' 'CLB2' 'FKH1Sh'
Cell-cycle
Less than a minuteon a PowerMac G4(after pre-processing)
0
0.3
0.6
0.9
1.2
1.5
1.8
1-C
.C
0.2
0.4
0.6
0.8
1
Exp
ress
ion
cohe
renc
e '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:
.
0.3
0.6
0.9
1.2
1.5
0.2
0.4
0.6
0.8
'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
RPN4
Abf1
HAP2-3-4
STRE
MCB
Gcr1FKH1
Rap1
MERE11 MERE4
rRSE3rRPE
rRSE10CCA
LFTE17
OCSE15
Mcm1
FKH1Sh
SCB
Leu3
GCN4
PAC
RPE6
LYS14
cytokinesis9
Cell cycleRibosomalproteinsrRNAtranscriptiona.ametabolismStressEnergy
ChromosomeStructure
a1
2
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
1 2 3 . . . NGMC1
GMC1
GMC2
GMC2
GMC1
GMC1
GMC1
GMC1
GMC1
Genes defined by Motif Combination (GMC)