Evidence map›Paper›PMID 42642513›Full record

ArticleNature genetics2026

Improved spike-in normalization clarifies the relationship between active histone modifications and transcription.

Lauren Patel, Yuwei Cao, Tianyao Xu, Eduardo Modolo, Tamar Dishon, Lingzhi Zhang, Eric Mendenhall, Sven Heinz, Itamar Simon, Christopher Benner and 1 more

Abstract read
In one paragraph

Article in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Lauren PatelDepartment of Bioengineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0003-3495-5887
Yuwei CaoDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0009-0000-4119-4399
Tianyao XuDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-2934-7679
Eduardo ModoloDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA.
Tamar DishonDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA.
Lingzhi ZhangDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA.
Eric MendenhallHudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
Sven HeinzDepartment of Medicine, Division of Endocrinology and Metabolism, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-4665-1007
Itamar SimonDepartment of Microbiology and Molecular Genetics, Institute of Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University, Jerusalem, Israel.ORCID http://orcid.org/0000-0002-8517-1903
Christopher BennerDepartment of Medicine, Division of Endocrinology and Metabolism, University of California, San Diego, La Jolla, CA, USA. cbenner@health.ucsd.edu.ORCID http://orcid.org/0000-0002-4618-0719
Alon GorenDepartment of Medicine, Division of Genomics and Precision Medicine, University of California, San Diego, La Jolla, CA, USA. agoren@ucsd.edu.ORCID http://orcid.org/0000-0001-5669-9357

Funding

Novel SETD5-based Molecular Mechanisms and Therapeutic Tools to Understand and Revert Neuronal Dysfunction Associated with Intellectual disability and AutismR01MH127077 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Alon Goren, Alysson R. Muotri · 2022 to 2026
$3.9M
UC San Diego Genetics Training ProgramT32GM145427 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BRUCE A HAMILTON · 2022 to 2026
$2.6M
How transcription disrupts genome 3D organizationR01GM129523 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HEINZ, SVEN W · 2020 to 2023
$1.3M
Multiscale genomic decryption of regulatory DNAR35GM149520 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Christopher W Benner · 2024 to 2026
$1.2M
National Science Foundation (NSF) 2003358NIGMS NIH HHS R01 GM129523NIGMS NIH HHS R35 GM149520NIGMS NIH HHS T32 GM145427NIMH NIH HHS R01 MH127077U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01MH127077
6 · The paper itself

Abstract

Spike-in normalization enables quantitative analysis of chromatin immunoprecipitation sequencing (ChIP-seq) signal. Here we introduce a robust dual spike-in normalization approach for ChIP-seq (ChIP-wrangler), optimize parameters and verify its accuracy in quantifying changes in ChIP-seq signal and detecting technical artifacts. We use ChIP-wrangler to revisit recent claims that active histone marks depend on transcription. We show that acute depletion of RNA polymerase II (RNAPII) has a modest impact on H3K27ac levels, with only 6% of peaks significantly changing after RNAPII depletion, indicating that histone acetylation maintenance is not entirely dependent on ongoing transcription. Promoters and enhancers are differentially affected, with 82% of decreasing acetylation peaks located at promoter-distal elements with enhancer-related motifs. ChIP-wrangler provides increased rigor and 'guardrails' for successful spike-in normalization and, as applied here, refines the understanding of crosstalk between RNAPII activity and transcription-associated histone marks.

Indexed as

Chromatin Immunoprecipitation SequencingHistone CodeHistonesTranscription, GeneticAcetylationAnimalsChromatin ImmunoprecipitationEnhancer Elements, GeneticHumansPromoter Regions, GeneticRNA Polymerase IIHistonesRNA Polymerase II

Identifiers

PMID42642513
PMCPMC13647998

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.