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Inferring transcription factor function through regulon-based expression analysis

Inferring transcription factor function through regulon-based expression analysis. Harmen Bussemaker Biological Sciences & C2B2 Columbia University. Hidden, protein-level TF activities. TF1. TF2. TF3. Regulatory Connectivities. Gene1. Gene2. Gene3. Measured mRNA abundances.

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Inferring transcription factor function through regulon-based expression analysis

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  1. Inferring transcription factor function through regulon-based expression analysis Harmen Bussemaker Biological Sciences & C2B2 Columbia University

  2. Hidden, protein-level TF activities TF1 TF2 TF3 Regulatory Connectivities Gene1 Gene2 Gene3 Measured mRNA abundances

  3. “T-profiler”(Lascaris, 2003; Boorsma, 2005) Quantify the difference in mean expression between a gene set and its complement:

  4. Score condition-specific differential activity of regulon using t-test

  5. Two types of yeast regulons: • Based on ChIP-chip data (Harbison, 2004) • Based on consensus motif matches (SCPD)Large number (~1000) of conditions

  6. Validation: • Overexpression/deletion of TF • Activator (Yap1p) and repressor (Rox1p)T-values consistent with expectation

  7. GFP-labeled Crz1p

  8. How good a proxy is mRNA level for TF activity? mRNA level is a good predictor of TF activity mRNA level is a poor predictor of TF activity

  9. [mRNA] vs. inferred TF activity correlation

  10. Detecting “co-modulation” of pairs of TFs Inferred TF activities are highly correlated The mRNA levels arepoorly correlated

  11. Better performance observed for all pairs of TFs

  12. Network of co-modulated TF pairs (r > 0.5)

  13. What do these TFs have in common?

  14. RED: Part of network / BOLD: Significant for both

  15. Dissecting the Environmental Stress Response

  16. Conclusion Regulon-based analysis of genomewide expression profiles using the unpaired t-test is a simple but effective tool for analyzing the condition-specific modulation of TF activity http://www.t-profiler.org http://bussemakerlab.org/T-base/

  17. ATACACAAAGACTCGTTACAAAAGCCG + ATACACAAAGACTCGTTACAAAAGCCG Genome PSAM Affinity Landscape Functional Predictor

  18. mRNA expression acgacgcagcagca tctactacgagcgata aaaaccacggcttat cccctcttcatcactca ggactatactacaac

  19. Nutrients Rapamycin Target of Rapamycin (TOR) Signaling Pathway Puf4p Puf3p Ribosomes Mitochondria Foat et al, PNAS, 2005

  20. bZIP910 GAMYB E2F1 ZNF42_5-13 ZNF42_1-4 NF-Y Discovering Regulators of Human B-cell Maturation

  21. Inferred TF Activity Time Course during GC Reaction

  22. Mina Fazlollahi Barrett Foat Pilar Gomez-Alcala Gabor Halasz Eunjee Lee Xiang-Jun Lu Ben Snyder Ron Tepper Luke Ward Sean Housmandi Wendy Olivas Kevin White Bas van Steensel Alexandre Morozov Andre Boorsma Frans Klis NIH, HFSP Acknowledgements

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