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Updated: Jul 19, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
Published on: February 7, 2019
Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities
Michael F Berger1, Anthony A Philippakis, Aaron M Qureshi
1Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Researchers developed a universal DNA microarray to map transcription factor (TF) binding sites. This method comprehensively identifies TF DNA sequence preferences, advancing gene regulation studies.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences.
- Characterizing the DNA binding specificities of TFs is crucial for understanding gene regulation but remains incomplete for most TFs.
Purpose of the Study:
- To develop a universally applicable DNA microarray design for comprehensive TF binding specificity determination.
- To enable high-throughput interrogation of TF binding preferences at unprecedented resolution.
Main Methods:
- Designed a maximally compact, synthetic DNA sequence for universal microarrays representing all possible k-mers.
- Constructed all 10-base pair (bp) k-mer microarrays by converting single-stranded to double-stranded DNA arrays.
- Determined binding specificities for five TFs from diverse species and structural classes using these microarrays.
Main Results:
- Successfully created universal all k-mer microarrays for comprehensive TF binding analysis.
- Comprehensively mapped the binding specificities of five TFs across a range of affinities.
- Enabled the interrogation of nucleotide interdependencies within TF binding sites.
Conclusions:
- The developed universal microarray platform provides a powerful tool for high-throughput TF binding site discovery.
- This method offers unbiased coverage, allowing for detailed analysis of TF sequence preferences and interdependencies.
- Advances the understanding of gene regulation by providing comprehensive TF binding data.
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