Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and
Daniel E Miller1, Zubin H Patel2, Xiaoming Lu3
1Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital.
This study presents a strategy to functionally analyze non-coding genetic variants, which are often linked to diseases. The approach uses computational and experimental methods to identify how these variants affect gene expression by altering transcription factor binding.
Area of Science:
- Genetics
- Molecular Biology
- Bioinformatics
Background:
- Population and family studies identify genetic variants associated with diseases and traits.
- Most identified variants are non-coding, potentially affecting gene expression regulation.
- Understanding non-coding variant function is crucial for disease mechanism elucidation.
Purpose of the Study:
- To describe a general strategic approach for prioritizing and screening non-coding genetic variants for function.
- To enable the study of non-coding variants impacting gene expression and disease risk.
Main Methods:
- Computational prioritization using functional genomic databases.
- Experimental screening via transcription factor (TF) binding assays (EMSA, DAPA).
- Utilizing synthetic DNA oligonucleotides (oligos) with disease-relevant cell nuclear lysates.
Main Results:
- Demonstrated a method to assess differential TF binding to risk and non-risk alleles.
- EMSA analyzes TF-DNA complex formation using non-denaturing electrophoresis.
- DAPA elutes bound factors for analysis via mass spectrometry or Western blot.
Conclusions:
- The described approach provides a framework for functional analysis of non-coding genetic variants.
- This strategy can be applied to any disease or trait associated with non-coding variants.
- Facilitates understanding of gene expression mechanisms influenced by genetic variation.
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