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Updated: Jul 15, 2026
05:53
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Identification of polymorphic antioxidant response elements in the human genome
Xuting Wang1, Daniel J Tomso, Brian N Chorley
1Environmental Genomics Section, Laboratory of Molecular Genetics, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709, USA.
Human Molecular Genetics
|April 6, 2007
Summary
This study introduces a computational system to identify functional single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBSs). The system predicts how these SNPs impact gene expression and disease susceptibility, aiding in identifying at-risk individuals.
Area of Science:
- Genomics
- Computational Biology
- Molecular Genetics
Background:
- Single nucleotide polymorphisms (SNPs) within transcription factor binding sites (TFBSs) can alter transcription factor binding, leading to variations in gene expression, phenotypes, and susceptibility to environmental factors.
- Identifying functional SNPs in TFBSs is crucial for understanding gene regulation and disease mechanisms.
Purpose of the Study:
- To develop and validate an integrated computational system for discovering functional SNPs in human TFBSs.
- To predict the impact of these SNPs on target gene expression and their potential role in disease susceptibility.
Main Methods:
- Construction of a position weight matrix (PWM) from known TFBSs.
- Prediction of TFBSs in SNP sequences and mapping to gene upstream regions.
- Assessment of evolutionary conservation using phylogenetic footprinting.
- Prioritization of candidate SNPs using microarray expression data.
- Analysis of SNP genotype association with gene expression phenotypes.
Main Results:
- The system successfully identified functional polymorphisms in the antioxidant response element (ARE), a key regulatory sequence for antioxidant and detoxification genes.
- Demonstrated the utility of the computational approach in identifying polymorphic AREs with functional evidence.
- Highlighted the potential of the system for validating genomic variations and identifying individuals at higher risk.
Conclusions:
- The developed computational system is effective for discovering functional SNPs in TFBSs and predicting their effects on gene expression.
- The findings underscore the importance of TFBS variations in modulating cellular responses and disease susceptibility.
- The system provides a valuable tool for experimental validation and personalized risk assessment.
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