Evidence map›Paper›PMID 40777328›Full record

ArticlebioRxiv : the preprint server for biology2025

An automated ATAC-seq method reveals sequence determinants of transcription factor dose response in the open chromatin.

Betty B Liu, Masaru Shimasawa, Sidney Vermeulen, Samuel H Kim, Nika Iremadze, Doron Lipson, Zohar Shipony, William J Greenleaf

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Betty B LiuDepartment of Bioengineering, Stanford University, Stanford, CA, US.ORCID 0000-0003-1655-7164
Masaru ShimasawaDepartment of Biology, Stanford University, Stanford, CA, US.ORCID 0000-0003-4656-7638
Sidney VermeulenDepartment of Genetics, Stanford University, Stanford, CA, US.
Samuel H KimCancer Biology Program, Stanford University, Stanford, CA, US.ORCID 0000-0001-8353-6190
Nika IremadzeUltima Genomics, Fremont, CA, US.ORCID 0000-0002-4977-204X
Doron LipsonUltima Genomics, Fremont, CA, US.
Zohar ShiponyUltima Genomics, Fremont, CA, US.
William J GreenleafDepartment of Genetics, Stanford University, Stanford, CA, US.ORCID 0000-0003-1409-3095

Funding

Stanford Center for Connecting DNA Variants to Function and PhenotypeUM1HG011972 · NHGRI · STANFORD UNIVERSITY · PI JESSE M ENGREITZ, THOMAS QUERTERMOUS · 2021 to 2026
$10.5M
Spatial multiomic mapping of gene function with CRISPRoffUM1HG012660 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Luke Gilbert · 2022 to 2026
$8.2M
Combinatorial Cell State EngineeringDP1HG013599 · NHGRI · STANFORD UNIVERSITY · PI William James Greenleaf · 2023 to 2026
$5.4M
Defining and perturbing gene regulatory dynamics in the developing human brainR01NS128028 · NINDS · STANFORD UNIVERSITY · PI William James Greenleaf · 2023 to 2026
$2.4M
Defining and perturbing gene regulatory dynamics in the developing human heart to understand mechanisms of congenital heart defectsR01HL171611 · NHLBI · STANFORD UNIVERSITY · PI William James Greenleaf · 2024 to 2026
$2.1M
NHGRI NIH HHS DP1 HG013599NHGRI NIH HHS UM1 HG011972NHGRI NIH HHS UM1 HG012660NHLBI NIH HHS R01 HL171611NINDS NIH HHS R01 NS128028
6 · The paper itself

Abstract

Transcription factor (TF) dosage is a critical determinant of cellular identity. However, the quantitative relationship between TF dosage and its regulation of chromatin accessibility and gene expression remains poorly understood. To address this, we developed RoboATAC, a scalable, automated ATAC-seq platform for high-throughput accessibility profiling. We then systematically profiled genome-wide chromatin accessibility and gene expression changes induced by graded overexpression of 22 TFs in HEK293T cells (246 total samples), observing dose-dependent changes in accessibility and aggregate TF footprints. Modeling accessibility as a function of sequence and chromatin states revealed that DNA sequence alone accurately predicts dosage sensitivity at elements that become accessible, with low-affinity motifs requiring higher TF levels to induce accessibility. Interpretable deep learning models revealed contributions of motif orientation, spacing, and flanking bases to accessibility, both recapitulating known motifs and nominating novel dosage-sensitive motif arrangements. Nucleosome positioning analysis uncovered two distinct, TF identity dependent patterns by which accessibility is established by changing nucleosome position and occupancy.

Identifiers

PMID40777328
PMCPMC12330524

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.