Evidence map›Paper›PMID 41386983›Full record

ArticleGenome research2026

Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations.

Yuwei Cao, Lauren Patel, Lauren Alcoser, Eric Mendenhall, Christopher Benner, Sven Heinz, Alon Goren

Abstract read
In one paragraph

Article in Genome research, 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

7 authors.

Yuwei CaoDepartment of Medicine, Division of Genomics & Precision Medicine, University of California San Diego, La Jolla, California 92093, USA.ORCID 0009-0000-4119-4399
Lauren PatelDepartment of Medicine, Division of Genomics & Precision Medicine, University of California San Diego, La Jolla, California 92093, USA.ORCID 0000-0003-3495-5887
Lauren AlcoserAgilent Technologies, Santa Clara, California 95051, USA.
Eric MendenhallHudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA.ORCID 0000-0002-7395-6295
Christopher BennerDepartment of Medicine, Division of Endocrinology & Metabolism, University of California San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-4618-0719
Sven HeinzDepartment of Medicine, Division of Endocrinology & Metabolism, University of California San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-4665-1007
Alon GorenDepartment of Medicine, Division of Genomics & Precision Medicine, University of California San Diego, La Jolla, California 92093, USA; agoren@ucsd.edu.ORCID 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
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
NIGMS NIH HHS R01 GM129523NIGMS NIH HHS R35 GM149520NIMH NIH HHS R01 MH127077
6 · The paper itself

Abstract

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map nonhistone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol, named spa-ChIP-seq, which enables scalable processing of eight to 96 ChIP-seq samples from cross-linked cells to a sequencing-ready library in approximately 3 days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates a comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and cross-linking conditions, buffer compositions, and the ratio of antibody to cell number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody-to-cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

Indexed as

ChromatinChromatin ImmunoprecipitationChromatin Immunoprecipitation SequencingHigh-Throughput Nucleotide SequencingHumansChromatin

Identifiers

PMID41386983
PMCPMC12758389

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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.