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Characterization of transcriptional responses to environmental stress by differential location analysis. Junguk Hur School of Informatics & Center for Genomics and Bioinformatics. Indiana University Bloomington, IN. OVERVIEW. Overview. Background / Motivation - PowerPoint PPT Presentation
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Indiana UniversityBloomington, IN
Junguk HurSchool of Informatics &
Center for Genomics and
Bioinformatics
Characterization of Characterization of transcriptional responses to transcriptional responses to
environmental stress by environmental stress by differential location analysisdifferential location analysis
Capstone Presentation Junguk Hur05-26-2006 2
OVERVIEW
Background / Motivation
Location Analysis / Differential Binding
TF Response Classification
Comparison with Microarray
Conclusion / Future Work
Overview
Capstone Presentation Junguk Hur05-26-2006 3
Central Dogma
http://campus.queens.edu/faculty/jannr/bio103/tests/TEST2Help.htm
Overview
Background
Capstone Presentation Junguk Hur05-26-2006 4
Transcriptional Regulation
Albert et al., Molecular Cell Biology of the Cell
Overview
Background
Capstone Presentation Junguk Hur05-26-2006 5
Transcriptional RegulationOverview
Background
Transcription Factors
Capstone Presentation Junguk Hur05-26-2006 6
Response to EnvironmentOverview
Background
Broach et al. Curr Opin Microbiol 2004
Capstone Presentation Junguk Hur05-26-2006 7
Previous Studies - Expression
http://www.fao.org/DOCREP/003/X6884E/x6884e03.htm
High-throughput DNA Microarray – mRNA expression
Overview
Background
Capstone Presentation Junguk Hur05-26-2006 8
Previous Studies - Expression
Literature : Gene Expression Microarray Stress
• Exploring the metabolic and genetic control of gene expression on a genomic scale, DeRisi JL, et al. (1997) Science
• Genomic expression programs in the response of yeast cells to environmental changes, Gasch AP, et al. (2000) Mol Biol Cell
• Global and specific translational regulation in the genomic response of Saccharomyces cerevisiae to a rapid transfer from a fermentable to a nonfermentable carbon source, Kuhn KM, et al. (2001) Mol Cell Biol
• Role of thioredoxin reductase in the Yap1p-dependent response to oxidative stress in Saccharomyces cerevisiae, Carmel-Harel O, et al. (2001) Mol Microbiol
• Transcriptional Remodeling in Response to Iron Deprivation in Saccharomyces cerevisiae, Shakoury-Elizeh M, et al. (2004). Mol Biol Cell
• Transcriptional response of steady-state yeast cultures to transient perturbations in carbon source, Ronen M and Botstein D (2005) Proc Natl Acad Sci
• About 900 publications
Overview
Background
Capstone Presentation Junguk Hur05-26-2006 9
Previous Studies – ChIP-Chip
Which genes are directly regulated by TFs?
Harbison et al. Nature 2004
Overview
Background
(Environment specific use of regulatory code)
Capstone Presentation Junguk Hur05-26-2006 10
Motivation and Goal
Limitation of Microarray data for understanding
regulatory system upon environmental change
Previous qualitative analysis of ChIP-Chip
Integration of heterogeneous data
ChIP-Chip (direct regulation) +
Microarray (direct/indirect regulation)
Quantitative analysis of TF binding
Better understanding of differential
responses of transcriptional regulatory
system via differential location analysis
Overview
Background
Capstone Presentation Junguk Hur05-26-2006 11
Location AnalysisGenome-wide Location Analysis : ChIP-on-Chip Exp.• In vivo assay based on
• ChIP (Chromatin Immuno-Precipitation)• High-throughput array experiment
Where and how strongly TF binds to
Overview
Background
Location Analysis
Capstone Presentation Junguk Hur05-26-2006 12
Differential Location Analysis
• Harbison et al. Nature 2004• Saccharomyces cerevisiae (budding yeast)• 204 TFs in 14 conditions (352 experiments)• Genome-wide location data (11,000 interactions)
Overview
Background
Location Analysis
Capstone Presentation Junguk Hur05-26-2006 13
ChIP-on-Chip 204 Yeast Transcription Factors (TFs)1
1 rich medium condition + 13 stress conditions 6540 genes & corresponding promoter sequences.
Microarray
Stress ConditionConcentratio
nTime point Array Ref.
H2O2 – oxidation 0.3 mM 20 mins cDNA 2
H2O2 – oxidation 0.32 mM 20 mins cDNA 3
H2O2 - oxidation 0.4 mM 20 mins oligo 4
SM (Sulfometuron methyl) – AA starvation
0.2 g/ml 15 mins cDNA 5
SM (Sulfometuron methyl) – AA starvation
0.2 g/ml 240 mins cDNA 5
Data Sets - IOverview
Background
Location Analysis
Capstone Presentation Junguk Hur05-26-2006 14
Data Sets - II
ChIP-on-Chip Data Preprocessing P-value and ratio data from Harbison et al. ‘NaN’ point removal Ratio value below 1 set to 1
Stress conditions 13 stress conditions 147 TF-cond pairs
Overview
Background
Location Analysis
Capstone Presentation Junguk Hur05-26-2006 15
Differential Binding Ratio
Rich medium Stress Condition
Increased binding in stress condition
Decreased binding in stress condition
How different the binding ratio btw different conditions???
Overview
Background
Location Analysis
Differential Binding
Capstone Presentation Junguk Hur05-26-2006 16
Differential Binding Measure
Ai, Bi: binding ratio of TF k to regulated region i
under stress and rich medium culture condition respectively
-1 Pik 1
Differential binding is represented as Pik by
using ChIP-chip binding ratio data between stress condition (A) and rich medium (B).
Overview
Background
Location Analysis
Differential Binding
Rich medium Stress Condition
PiK > 0 UP
PiK < 0 DOWN
Capstone Presentation Junguk Hur05-26-2006 17
All ChIP-Chip Binding Data
Normal distribution
Distribution of Pik - I
Ex) FHL1 YPD (Rich Medium) vs SM (Amino acid starvation)
High-confidence Binding Data (p0.001)
Skewed to negative direction
Overview
Background
Location Analysis
Differential Binding
Capstone Presentation Junguk Hur05-26-2006 18
HighUp vs HighDown
-10
10
30
50
70
90
110
130
-10 10 30 50 70 90 110 130
Num of Up regions
Num
of D
own r
egio
ns
Up vs Down
-30
0
30
60
90
120
150
180
210
-30 0 30 60 90 120 150 180 210
Num of Up regions
Num
of D
ow
n r
egio
ns
Distribution of Pik - II
• Number of UP/DOWN differentially bound regions (genes) for each TF-cond pair
• High-confidence data point only (p<0.001)
0.5 |Pik| 1
Overview
Background
Location Analysis
Differential Binding
-1 Pik 1
Capstone Presentation Junguk Hur05-26-2006 19
Chi-Square Test - I
* Chi-Square tests for Pik of 147 TF-condition pairs
to check their distributions (Normal or skewed)* R-package & Perl scripts* P<0.05 Skewed distribution
Normal Dist. (p=0.97)
All ChIP-Chip Binding Data
Skewed Dist. (p=0.00003)
High-confidence Binding Data (p0.001)
Overview
Background
Location Analysis
Differential Binding
Capstone Presentation Junguk Hur05-26-2006 20
Skewed DistributionChi-square test : p < 0.05105 TF-Cond pairs (out of 147) : 70%
Chi-Square Test - IIOverview
Background
Location Analysis
Differential Binding
Capstone Presentation Junguk Hur05-26-2006 21
Classification of TFs - I
Depending on patterns of the skewed
pattern , 105 TF-condition pairs have been
grouped into three categories.
UP : More than 2/3 are in ‘+’
direction
DOWN : More than 2/3 are in ‘–’
direction
BOTH : Similar proportions of ‘+’
and ’-’
Overview
Background
Location Analysis
Differential Binding
TF response classification
Capstone Presentation Junguk Hur05-26-2006 22
Classification of TFs - II
UP : YAP5_H2O2Hi BOTH : HPO4_Pi DOWN : SFP1_H2O2Lo
Overview
Background
Location Analysis
Differential Binding
TF response classification
Capstone Presentation Junguk Hur05-26-2006 23
Differential Location Analysis - Summary
Comparison of TF binding
between rich medium and stress cond.
Represented by PiK
Distribution of PiK
Normal and Skewed
Chi-Square Tests
70% TF-cond pairs differential
distribution
Classification of TF responses
UP, DOWN, and BOTH
Overview
Background
Location Analysis
Differential Binding
TF response classification
Capstone Presentation Junguk Hur05-26-2006 24
How differential binding?
1.1. Changes in the TF expressionChanges in the TF expression
2.2. Different TFBS signature for different Different TFBS signature for different
categorycategory
3.3. Interaction with other TFs expressionInteraction with other TFs expression
4.4. Modifications in TFs (protein level)Modifications in TFs (protein level)
5.5. Changes in physical structures Changes in physical structures
(epigenetic features) (epigenetic features)
6.6. Other unknown reasonsOther unknown reasons
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
1.1. Changes in the TF expressionChanges in the TF expression
Capstone Presentation Junguk Hur05-26-2006 25
Comparison with Microarray - I
ChIP-Chip vs
Microarray data
----------------------expression levels of
transcription factors (TFs).
----------------------H2O2 Low (oxidation)
----------------------TF-Cond pairs : 28Skewed : 23Normal : 5
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Capstone Presentation Junguk Hur05-26-2006 26
Comparison with Microarray - II
SM (Sulfometuron
methyl)Amino acid starvation
--------------------------ChIP-Chip
0.2 g/ml final2 hours
--------------------------Microarray0.2 g/ml 15
minutes5.0 g/ml 4 hours
--------------------------
TF-Cond pairs : 34Skewed : 21Normal : 13
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Capstone Presentation Junguk Hur05-26-2006 27
Comparison with Microarray - III
H2O2 Oxidation stress
SM (Sulfometuron methyl) Amino acid starvation
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Capstone Presentation Junguk Hur05-26-2006 28
Comparison with Microarray - IV
50~60% of differentially binding TFs have NO significant
expression change
Changes of gene regulation (differential binding) cannot be
fully revealed by Microarray
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Capstone Presentation Junguk Hur05-26-2006 29
How differential binding?
1.1. Changes in the TF expressionChanges in the TF expression
2.2. Different TFBS signature for different Different TFBS signature for different
categorycategory
3.3. Interaction with other TFs expressionInteraction with other TFs expression
4.4. Modifications in TFs (protein level)Modifications in TFs (protein level)
5.5. Changes in physical structures Changes in physical structures
(epigenetic features) (epigenetic features)
6.6. Other unknown reasonsOther unknown reasons
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Capstone Presentation Junguk Hur05-26-2006 30
Conclusion
Categorization of Transcription
Factors (TFs) depending on the
responses to stress
No significant expression changes in
about 50% of the tested TFs in response
to environmental changes.
Importance of integrating differential
binding of TFs with gene expression to
get the bigger picture
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Conclusion / Future Work
Capstone Presentation Junguk Hur05-26-2006 31
Future Work
Investigating the biological mechanism of
the differentially binding of TFs
1. Target gene of expression level
2. Post-translational modification
3. Protein-protein interaction
Comprehensive differential analysis
Integration
Diff. Expression
Diff. Location
Diff. Protein-Protein Int. (open)
Diff. Proteomics (open)
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
TF-TF Corr.
Conclusion / Future Work
Capstone Presentation Junguk Hur05-26-2006 32
References
1. Harbison, C.T., et al., Transcriptional regulatory code of a eukaryotic genome. Nature, 2004. 431(7004): p. 99-104. .
2. Shapira, M., E. Segal, and D. Botstein, Disruption of yeast forkhead-associated cell cycle transcription by oxidative stress. Mol Biol Cell, 2004. 15(12): p. 5659-69.
3. Gasch, A.P., et al., Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell, 2000. 11(12): p. 4241-57.
4. Causton, H.C., et al., Remodeling of yeast genome expression in response to environmental changes. Mol Biol Cell, 2001. 12(2): p. 323-37.
5. Jia, M.H., et al., Global expression profiling of yeast treated with an inhibitor of amino acid biosynthesis, sulfometuron methyl. Physiol Genomics, 2000. 3(2): p. 83-92.
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
TF-TF Corr.
Conclusion / Future Work
Capstone Presentation Junguk Hur05-26-2006 33
Acknowledgements
Dr. Haixu Tang
Dr. Sun Kim
Dr. Mehmet Dalkilic
Dr. Predrag Radivojac
Seung-hee Bae
Sourav Roy
Capstone class 2006
School of informatics
Center for Genomics and Bioinformatics
Dr. Zhixiong Xue at DuPont
My Family
Capstone Presentation Junguk Hur05-26-2006 34
Capstone Presentation Junguk Hur05-26-2006 35
Capstone Presentation Junguk Hur05-26-2006 36
Capstone Presentation Junguk Hur05-26-2006 37
How differential binding?
1.1. Changes in the TF expressionChanges in the TF expression
2.2. Different TFBS signature for different Different TFBS signature for different
categorycategory
3.3. Interaction with other TFs expressionInteraction with other TFs expression
4.4. Modifications in TFs (protein level)Modifications in TFs (protein level)
5.5. Changes in physical structures Changes in physical structures
(epigenetic features) (epigenetic features)
6.6. Other unknown reasonsOther unknown reasons
2.2. Different TFBS signature for different Different TFBS signature for different
categorycategory
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
Capstone Presentation Junguk Hur05-26-2006 38
Different TFBS signatures?
Category “BOTH” has Category “BOTH” has
similarsimilar numbers of numbers of
Up-differentially Up-differentially
bound and Down-bound and Down-
differentially bound differentially bound
regions.regions.
Is there any difference Is there any difference
between these between these
TFBSs in different TFBSs in different
groups?groups?
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
Capstone Presentation Junguk Hur05-26-2006 39
Different TFBS signatures?
Step1. Collect putative TFBS A. Frankel’s motifs
(102TFs) B. Gary Stormo’s “Patser”
Step2. Create profiles from collected TFBS seqs
Step3. Profile comparison A. “MatCompare”
program by Michale Zhang
BOTH
Up seqs Down seqs
TFBSs TFBSs
Profile Profile
Step3
Step2
Step1
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
Capstone Presentation Junguk Hur05-26-2006 40
Different TFBS signatures?High-Threshold
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
Capstone Presentation Junguk Hur05-26-2006 41
Different TFBS signatures?Low-Threshold
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
Capstone Presentation Junguk Hur05-26-2006 42
How differential binding?
1.1. Changes in the TF expressionChanges in the TF expression
2.2. Different TFBS signature for different Different TFBS signature for different
categorycategory
3.3. Association with other TFsAssociation with other TFs
4.4. Modifications in TFs (protein level)Modifications in TFs (protein level)
5.5. Changes in physical structures Changes in physical structures
(epigenetic features) (epigenetic features)
6.6. Other unknown reasonsOther unknown reasons
3.3. Association with other TFsAssociation with other TFs
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
TF-TF Corr.
Capstone Presentation Junguk Hur05-26-2006 43
TF-TF Correlation
TF
TF
Overview
Background
Location Analysis
Differential Binding
TF Response Classification
Comp. with Microarray
Diff. Binding Motif Anal.
TF-TF Corr.