# AVATAR: highly parallel analysis of variation in transcription factors and their DNA binding sites

> **NIH NIH R21** · BRIGHAM AND WOMEN'S HOSPITAL · 2020 · $268,500

## Abstract

Abstract
The interactions between transcription factors (TFs) and their DNA binding sites are central to
gene regulatory networks. Genetic variation in TFs or their DNA binding sites can contribute to
differences in traits among individuals. However, the role of interactions among such genetic
variants remains poorly understood.
Existing high-throughput technologies for assaying the DNA binding activities of TFs (or TF
variants) are “1-by-many” approaches, in which a given protein is assayed for its binding to a
large library of different DNA sequences, or alternatively assay a large library of protein variants
for activity from a given DNA sequence. A major hurdle in characterization of TF coding variants
and DNA noncoding variants is the lack of a high-throughput “many-by-many” technology that
would enable testing of a large collection of TF coding variants for binding to a library of different
DNA binding site sequences; such DNA binding site sequences could represent either a large
collection of substitutions in a TF's DNA binding site motif, or alternatively putative cis-regulatory
variants.
The primary goal of this project is to develop novel technology, termed All-Variant Analysis of
Transcription factor Affinity and Recognition (AVATAR), for highly parallel analysis of a library of
TF coding variants for interaction with a library of variants in their DNA binding sites. We will
prioritize human TFs that are associated with diseases and for which disease-associated
mutations or naturally occurring polymorphisms predicted to have damaged DNA binding
activity have been identified. Such technology would permit: more extensive experimental
testing of putatively damaging TF coding variants whose precise effects on DNA binding activity
are not currently predictable (unpublished results); an improved understanding of specificity-
determining residues and TF-DNA `recognition rules' for various TF classes; and identification of
potential genetic interactions between TF coding variants and noncoding variants in TF binding
sites (TFBSs).
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## Key facts

- **NIH application ID:** 9937791
- **Project number:** 5R21HG010200-03
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** MARTHA L BULYK
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $268,500
- **Award type:** 5
- **Project period:** 2018-08-20 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9937791

## Citation

> US National Institutes of Health, RePORTER application 9937791, AVATAR: highly parallel analysis of variation in transcription factors and their DNA binding sites (5R21HG010200-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9937791. Licensed CC0.

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