# HIGH-THROUGHPUT FUNCTIONAL INTERROGATION OF MAMMALIAN ACTIVATION DOMAINS

> **NIH NIH K99** · WASHINGTON UNIVERSITY · 2020 · $99,998

## Abstract

Project Summary Abstract
Transcription factors (TFs) control gene expression by binding to DNA and either
activating or repressing target gene expression. While our understanding of how TFs
bind DNA has grown rapidly, our understanding of how TFs activate transcription once
they are bound has not kept pace. As a result, when we identify a mutation in a patient
in a TF, if this mutation is in the DNA binding domain, we can sometimes predict if it will
disrupt function; if the mutation is in the activation domain, we have no ability to predict
its effects.
To address this gap, I propose to study the amino acid composition of acidic activation
domains using high-throughput assays and modern computational analyses. I have
recently developed a high-throughput assay for measuring thousands of designed
activation domain mutants in yeast. Here, I propose to develop a similar method in
mammalian cell culture. In Aim 1, I propose an in-depth study of a few activation
domains as a model for how genetic variation impacts TF function. In Aim 2, I propose a
broad survey of human transcription factors to search for new activation domains. In the
independent phase of this grant (R00), I propose 2 more aims to investigate the
mechanisms how TFs activate target genes. In Aim 3, I will functional classify different
type of activation domains and search for common features of each time. In Aim 4, I will
link activation domains to cofactors and look for the features that predict activation.]
This proposal will create a new layer of annotation for the human genome: all regions
that are sufficient to serve as activation domains, create a new genome-scale method
and deliver computational models for predicting activation domains from amino acid
sequence. This award will support training in mammalian experimental systems and
advanced machine learning analysis. Together these aims will support the long term
goal of reading the regulatory genome by predicting gene expression from DNA
sequence.

## Key facts

- **NIH application ID:** 9856466
- **Project number:** 5K99GM131022-02
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Max Valentin Staller
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $99,998
- **Award type:** 5
- **Project period:** 2019-02-01 → 2021-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9856466

## Citation

> US National Institutes of Health, RePORTER application 9856466, HIGH-THROUGHPUT FUNCTIONAL INTERROGATION OF MAMMALIAN ACTIVATION DOMAINS (5K99GM131022-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9856466. Licensed CC0.

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