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06:41
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
Published on: August 20, 2019
In silico regulatory analysis for exploring human disease progression.
Dustin T Holloway1, Mark Kon, Charles DeLisi
1Molecular Biology Cell Biology and Biochemistry Department, Boston University, 5 Cummington Street, Boston, USA.
Biology Direct
|June 20, 2008
Summary
Bioinformatics methods identified new targets for 152 human transcription factors (TFs). Predictions for WT1 (Wilms
Area of Science:
- Bioinformatics
- Genomics
- Molecular Biology
Background:
- Understanding transcription factor (TF) networks is crucial in human genomics, particularly for disease-related TFs.
- Identifying TF targets aids in comprehending gene regulation and disease mechanisms.
Purpose of the Study:
- To identify novel targets for 152 human transcriptional regulators using computational classification methods.
- To leverage sequence composition, conservation, and overrepresentation for target prediction.
Main Methods:
- Applied classification methods to predict TF targets using existing data.
- Utilized sequence composition, conservation, and overrepresentation as features.
- Developed an enrichment score to filter and validate predictions.
Main Results:
- Predicted 9333 new TF-target interactions for 152 TFs, significantly enriching for true targets.
- Case studies on OCT4 and WT1 demonstrated biological relevance of predictions.
- Identified potential WT1 targets in chromosomal regions linked to Wilms' tumor, suggesting roles in tumor progression.
Conclusions:
- Developed a robust method for identifying human TF targets based on sequence features.
- Proposed novel targets for WT1, with implications for understanding Wilms' tumor pathogenesis.
- Highlighted the potential role of chromosomal rearrangements in WT1 target regions in tumor development.
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