Evidence mapPaperPMID 41944730Full record

ArticleeLife2026

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci.

Yuzhen Liu, Christopher D McGann, Conor P Herlihy, Mary Krebs, Thomas A Perkins, Rose Fields, Conor K Camplisson, David Z Nwizugbo, Qiaoyi Lin, Nicolas J Longhi and 7 more

Abstract read
In one paragraph

Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Yuzhen Liu *Department of Genome Sciences, University of Washington, Seattle, United States.
Christopher D McGann *Department of Genome Sciences, University of Washington, Seattle, United States.
Conor P Herlihy *Department of Genome Sciences, University of Washington, Seattle, United States.ORCID https://orcid.org/0000-0001-9818-4204
Mary KrebsDepartment of Genome Sciences, University of Washington, Seattle, United States.
Thomas A PerkinsDepartment of Genome Sciences, University of Washington, Seattle, United States.
Rose FieldsDepartment of Genome Sciences, University of Washington, Seattle, United States.
Conor K CamplissonDepartment of Genome Sciences, University of Washington, Seattle, United States.
David Z NwizugboDepartment of Genome Sciences, University of Washington, Seattle, United States.
Qiaoyi LinDepartment of Genome Sciences, University of Washington, Seattle, United States.
Nicolas J LonghiDepartment of Genome Sciences, University of Washington, Seattle, United States.
Chris HsuDepartment of Genome Sciences, University of Washington, Seattle, United States.
Shayan C AvanessianDepartment of Genome Sciences, University of Washington, Seattle, United States.
Ashley F TsueDepartment of Pharmacology, University of Washington, Seattle, United States.
Evan E KaniaDepartment of Pharmacology, University of Washington, Seattle, United States.
David M ShechnerDepartment of Pharmacology, University of Washington, Seattle, United States.
Brian J BeliveauDepartment of Genome Sciences, University of Washington, Seattle, United States.ORCID https://orcid.org/0000-0003-1314-3118
Devin K SchweppeDepartment of Genome Sciences, University of Washington, Seattle, United States.ORCID https://orcid.org/0000-0002-3241-6276

Funding

Pharmacological Sciences SupplementT32GM007750 · NIGMS · UNIVERSITY OF WASHINGTON · PI ATKINS, WILLIAM M · 1985 to 2023
$12.6M
Probing the dynamics of chromosome organization in single cellsR35GM137916 · NIGMS · UNIVERSITY OF WASHINGTON · PI Brian Joseph Beliveau · 2020 to 2026
$2.9M
Technology for evaluating drug-binding responses to small-molecule perturbationR35GM150919 · NIGMS · UNIVERSITY OF WASHINGTON · PI Devin Karl Schweppe · 2023 to 2026
$1.6M
American Heart Association AHA 902616National Heart Lung and Blood Institute T32HL007093NIGMS NIH HHS R35GM137916NIGMS NIH HHS R35 GM150919NIGMS NIH HHS R35GM150919NIH HHS 1R01GM138799-01NIH HHS 1R01HL160825-01NIH HHS T32GM007750
6 · The paper itself

Abstract

The accuracy of crucial nuclear processes such as transcription, replication, and repair depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed 'DNA O-MAP', which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with label-free or sample multiplexed quantitative proteomics, targeted chemical perturbations, and next-generation sequencing to quantify DNA-proximal proteins and DNA-DNA interactions at specific genomic loci in human and murine cells. Furthermore, we establish that DNA O-MAP is applicable to both repetitive and unique genomic loci of varying sizes, from kilobase

Indexed as

DNAGenetic LociAnimalsChromatinHumansMiceOligonucleotide ProbesProteomicsChromatinDNAOligonucleotide Probeschromatinchromosomescomputational biologygene expressionhumanmouseproteomicsproximity labelingsystems biology

Identifiers

PMID41944730
PMCPMC13056364

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.