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Updated: May 30, 2026
11:35
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
Published on: August 21, 2016
In silico searching for disease-associated functional DNA variants
Rao Sethumadhavan1, C George Priya Doss, R Rajasekaran
1School of BioSciences and Technology, Vellore Institute of Technology, 632014, Vellore, Tamil Nadu, India. rsethumadhavan@vit.ac.in
Methods in Molecular Biology (Clifton, N.J.)
|July 23, 2011
Summary
Computational methods can identify functional DNA variants linked to disease, reducing experimental screening. Tools like SIFT, PolyPhen, and PupaSuite prioritize high-risk variants for drug discovery and biomarker development.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Experimental identification of functional DNA variants is challenging due to numerous neutral variants.
- Large-scale genotyping studies generate vast amounts of DNA variant data.
- Computational biology offers a powerful approach to sift through this data.
Purpose of the Study:
- To outline in silico methods for predicting disease-associated functional DNA variants.
- To reduce the number of DNA variants that require experimental screening for disease association.
- To identify variants most likely to alter gene function for further investigation.
Main Methods:
- Discusses computational methods including Sorting Intolerant from Tolerant (SIFT) and Polymorphism Phenotyping (PolyPhen).
- Highlights PupaSuite for predicting phenotypic effects on protein structure and function.
- Explains mapping deleterious variants to 3D protein structures and analyzing solvent accessibility and secondary structure.
Main Results:
- In silico tools effectively prioritize high-risk DNA variants.
- Predicts the phenotypic impact of variants on protein structure and function.
- Enables detailed molecular-level investigation of disease-causing mutations.
Conclusions:
- Computational methods are crucial for efficient identification of functional DNA variants.
- These approaches facilitate the discovery of new drug targets and biomarkers.
- Bioinformatics tools provide a practical framework for DNA variant analysis in disease research.
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