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Updated: May 14, 2026
11:25
Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
Published on: February 11, 2019
PRISM offers a comprehensive genomic approach to transcription factor function prediction
Aaron M Wenger1, Shoa L Clarke, Harendra Guturu
1Department of Computer Science, Stanford University, Stanford, California 94305, USA.
Genome Research
|February 6, 2013
Summary
We developed PRISM, a computational framework to predict transcription factor (TF) functions. This approach identifies TF binding sites and links them to gene functions, revealing novel TF roles.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- The human genome has 1500-2000 transcription factors (TFs), but their functions are largely unknown.
- ChIP-seq reveals TF binding but is costly and limited in scope.
- Discovering novel TF functions typically relies on expression perturbation and genetic screens.
Purpose of the Study:
- To develop a comprehensive computational framework for predicting transcription factor function.
- To identify novel transcription factor roles and regulatory elements.
Main Methods:
- Curated 332 TF binding motifs and predicted 3.3 million conserved binding sites.
- Integrated binding site predictions with 2.4 million gene function facts.
- Developed a statistical framework (PRISM) to find motif-gene function enrichments.
Main Results:
- PRISM predicted 2543 TF functions across diverse contexts with a 16% false discovery rate.
- Predictions showed significant enrichment for validated TF roles.
- 67% of tested binding sites acted as enhancers in relevant cellular contexts.
Conclusions:
- PRISM offers a scalable computational approach for predicting transcription factor functions.
- The framework successfully identifies novel TF roles and regulatory elements.
- Predicted TF binding sites are functionally validated as enhancers.
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