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What is the Best Way to Find the Binding Site for a Transcription Factor?

What is the Best Way to Find the Binding Site for a Transcription Factor? Dennis Shasha, Courant Institute, New York University With Philip Benfey and Ken Birnbaum Biology Department, New York University. AAAA. Transcriptional Networks. Induction. Specificity Modularity. AAAA. AAAA.

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What is the Best Way to Find the Binding Site for a Transcription Factor?

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  1. What is the Best Way to Find the Binding Site for a Transcription Factor? Dennis Shasha, Courant Institute, New York University With Philip Benfey and Ken Birnbaum Biology Department, New York University.

  2. AAAA Transcriptional Networks Induction • Specificity • Modularity AAAA AAAA e.g. cis-element AAAA AAAA Repression AAAA AAAA AAAA AAAA Time 1 Time 2 Time 3

  3. Genomic and Expression Data Cis-regulatory regions of expressed genes Expres-sion Level Time

  4. Clusters of Co-Expressed Genes Expres-sion level Time a a a a a a a a a Over-represented motifs

  5. Low Correlation Transcription Factor Expression Level Time Time Dowstream Genes

  6. Modularity early specification module later expression module From: Arnone & Davidson, Development, 1997

  7. Transcription Factor X Expres-sion Time NAAAAAA.. ..TTTTTTN

  8. Transcription Factor X Expres-sion Expression levels of genes with ACA?GTC in their promoters Time Gene Cis - regulatory region ACA?GTC A

  9. Transcription Factor X Expres-sion Expression levels of genes with ACA?GTC in their promoters Time Gene Cis - regulatory region ACA?GTC A ACA?GTC B

  10. Transcription Factor X Expres-sion Expression levels of genes with ACA?GTC in their promoters Time Gene Cis - regulatory region ACA?GTC A ACA?GTC B ACA?GTC C

  11. Composite expression of ACAGTC at Time 5 = 8 Transcription Factor X Expres-sion Expression levels of genes with ACA?GTC in their promoters Time Gene Cis - Expression regulatory Level Example: Time 5 region ACA?GTC A 2 ACA?GTC B 4 ACA?GTC C 2

  12. Composite expression of ACAGTC at Time 5 = 8 Transcription Factor X Composite expression of genes with ACA?GTC in promoter Expres-sion Time Expression levels of genes with ACA?GTC in their promoters Gene Cis - Expression regulatory Level Example: Time 5 region ACA?GTC A 2 ACA?GTC B 4 ACA?GTC C 2

  13. AND A B C Cooperative Binding Model TFs Binding Sites TF Expression Cell Type A Cell Type B Cell Type C Z Z Expression Level Z

  14. AND Cell Type A Cell Type B Cell Type C Z Z A B C Z A B C Z X X Z Z Cooperative Binding Model TFs Binding Sites TF Expression Expression Level Target Gene Expression Expression Level

  15. AND A B C A B C Z Z Z Cooperative Binding Model TFs Binding Sites TF Expression Cell Type A Cell Type B Cell Type C Z Z Expression Level Z Z Target Gene Expression X X Z Z X X Expression Level

  16. AND A B C A B C Z Z Z Cooperative Binding Model TFs Binding Sites TF Expression Cell Type A Cell Type B Cell Type C Z Z Expression Level Z Z Target Gene Expression X X Z Z X X Expression Level

  17. Cooperative Binding Model TFs OR Binding Sites

  18. Independent Binding Model: well handled by Bussemaker et al.

  19. Assumptions: • TF RNA Expression = TF protein (protein movement) • TFs are active where they are expressed (co-factors) • Binding sites are within 2 kb of initiation site

  20. Testing the Method • Yeast • Fully sequenced genome • Genome-wide mRNA expression profiles 300 knockout lines from Rosetta (Hughes et al. 2000) 2 datasets on yeast progressing through the cell cycle (Spellman et al. 1998; Cho et al. 1998)

  21. Results for STE12 *From SCPD (Zhang, Cold Spring Harbor)

  22. Results for STE12 *From SCPD (Zhang, Cold Spring Harbor)

  23. Results for STE12 *From SCPD (Zhang, Cold Spring Harbor)

  24. Overall Results

  25. Conclusions • Technique: correlate transcription factor expression with cis-element expression. Can capture information that would be missed by gene expression correlation. • Can handle cooperative (AND) and independent (OR) cases. Does less well for complex circuits. • Future effort: manipulate promoters to eliminate false positives. (Information theory + experiments)

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