Related Experiment Videos
rVista for comparative sequence-based discovery of functional transcription factor binding sites
Gabriela G Loots1, Ivan Ovcharenko, Lior Pachter
1Genome Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA. ggloots@lbl.gov
Genome Research
|May 9, 2002
Summary
rVista identifies functional regulatory elements by combining transcription factor binding site clustering and sequence conservation. This tool significantly reduces false positives while accurately detecting experimentally verified sites.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- Identifying cis-regulatory elements is crucial for annotating vertebrate genomes.
- Computational tools are needed for high-throughput discovery of these elements.
Purpose of the Study:
- To develop and assess rVista, a computational tool for discovering cis-regulatory elements.
- To improve the accuracy of transcription factor binding site (TFBS) prediction.
Main Methods:
- rVista combines clustering of predicted TFBSs with interspecies sequence conservation analysis.
- Analyzed TFBS distribution in the human-cytokine gene cluster (Hs5q31) and its mouse ortholog.
- Focused on AP-1, NFAT, and GATA-3 binding sites.
Main Results:
- rVista significantly reduced predicted TFBSs by over 95% when using orthologous human-mouse data compared to human data alone.
- The tool identified 88% of experimentally verified binding sites in the analyzed region.
- Demonstrated high specificity and sensitivity in TFBS prediction.
Conclusions:
- rVista effectively identifies functional cis-regulatory elements by integrating TFBS clustering and conservation.
- The tool enhances the accuracy of genome annotation by minimizing false positive predictions.
- rVista is a valuable tool for high-throughput discovery of regulatory elements in higher vertebrates.