Evidence map›Paper›PMID 41509405›Full record

ArticlebioRxiv : the preprint server for biology2026

Multiplexed measurements of protein-protein interactions and protein abundance across cellular conditions using Prod&PQ-seq.

Tianyao Xu, Jingyao Wang, Yoonju Shin, Yuwei Cao, Lingzhi Zhang, Eduardo Modolo, Tamar Dishon, Jeremy Fisher, Matthew Norton, Christopher J Fry and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

15 authors.

Tianyao XuDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-2934-7679
Jingyao WangDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0009-0004-5458-1100
Yoonju ShinDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0009-0001-8191-5071
Yuwei CaoDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0009-0000-4119-4399
Lingzhi ZhangDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0009-0002-1259-9244
Eduardo ModoloDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0009-0006-7698-6680
Tamar DishonDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-4912-4659
Jeremy FisherCell Signaling Technology, Danvers, MA 01923, USA.ORCID 0000-0002-7296-586X
Matthew NortonCell Signaling Technology, Danvers, MA 01923, USA.ORCID 0009-0001-5727-9976
Christopher J FryCell Signaling Technology, Danvers, MA 01923, USA.ORCID 0009-0007-2429-5383
Yossi FarjounFulcrum Genomics LLC., 240 Elm Street, 2nd Floor Somerville, MA, 02144, USA.ORCID 0000-0002-7002-2868
Eric MendenhallHudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA.ORCID 0000-0002-7395-6295
Sven HeinzDepartment of Medicine, Division of Endocrinology & Metabolism, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-4665-1007
Christopher BennerDepartment of Medicine, Division of Endocrinology & Metabolism, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0000-0002-4618-0719
Alon GorenDepartment of Medicine, University of California, San Diego, La Jolla, California 92093, USA.ORCID 0000-0001-5669-9357

Funding

The Cancer Cell Map Initiative v2.0U54CA274502 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Emma Lundberg · 2022 to 2026
$14.2M
Using Networks to Seed Hierarchical Whole-cell Models of CancerU54CA209891 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KROGAN, NEVAN J · 2017 to 2021
$10.9M
UC San Diego Genetics Training ProgramT32GM145427 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BRUCE A HAMILTON · 2022 to 2026
$2.6M
Multiscale genomic decryption of regulatory DNAR35GM149520 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Christopher W Benner · 2024 to 2026
$1.2M
Illumina NovaSeq 6000 Sequencing SystemS10OD026929 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JEPSEN, KRISTEN LYNN · 2019 to 2019
$600k
Development of a novel method to chart genomic localization of protein complexes in vivoR21HG010078 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GOREN, ALON · 2018 to 2019
$432k
NCI NIH HHS U54 CA209891NCI NIH HHS U54 CA274502NHGRI NIH HHS R21 HG010078NIGMS NIH HHS R35 GM149520NIGMS NIH HHS T32 GM145427NIH HHS S10 OD026929
6 · The paper itself

Abstract

Methods to profile protein-protein interactions (PPIs) have limited scalability and can only study a handful of conditions and/or targets. Here, we introduce Prod&PQ-seq, a framework for multiplexed detection and quantification of PPIs and proteins. Our framework uses cross-linked cells, antibody-oligonucleotide conjugates (ab-oligos), and captures PPIs by the DNA-caliper, a specialized oligonucleotide for bidirectional priming of proximal ab-oligos. We benchmarked Prod&PQ-seq using recombinant complexes, titrations and cell mixture experiments and show that our framework is quantitative, reproducible, sensitive and specific. Applying Prod&PQ-seq to study Polycomb Repressive Complex 2 (PRC2) shows that EZH2 inhibition and expression of the oncohistone H3.3K27M weakens both PRC2-H3K27me3 interactions and PPIs within PRC2. Further, H3.1K27M and H3.3K27M variants lead to distinct PPI profiles such as the intensity of H3K27ac-K27M or H3K27ac-EED. Together, Prod&PQ-seq enables detection of changes in PPI composition and intensity and protein quantification across biological conditions, small molecule inhibition and genetic perturbations.

Identifiers

PMID41509405
PMCPMC12776425

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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.