Evidence map›Paper›PMID 42282592›Full record

ArticlebioRxiv : the preprint server for biology2026

The molecular asynchrony of single cells.

Boshi Fu, Robert Tan, Zhenkun Cao, Xiuzhen Bai, Dongsheng Bai, Jinghui Song, Chenxu Zhu

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

7 authors.

Boshi FuNew York Genome Center, New York, NY, USA.
Robert TanNew York Genome Center, New York, NY, USA.
Zhenkun CaoNew York Genome Center, New York, NY, USA.
Xiuzhen BaiNew York Genome Center, New York, NY, USA.
Dongsheng BaiNew York Genome Center, New York, NY, USA.
Jinghui SongMemorial Sloan Kettering Cancer Center, New York, NY, USA.
Chenxu ZhuNew York Genome Center, New York, NY, USA.ORCID 0000-0003-4216-6562

Funding

Center for Integrated Cellular Analysis - Valeria A. Sanchez EstradaRM1HG011014 · NHGRI · NEW YORK GENOME CENTER · PI LANDAU, DAN, SATIJA, RAHUL · 2020 to 2025
$22.1M
Studying the Regulatory Dynamics with Single-cell MultiomicsDP2GM154011 · NIGMS · NEW YORK GENOME CENTER · PI Chenxu Zhu · 2023 to 2026
$2.7M
Single-cell Joint Profiling of Single- and Double-Stranded DNA Breaks with TranscriptomeR61CA309705 · NCI · NEW YORK GENOME CENTER · PI Chenxu Zhu · 2026 to 2026
$271k
NCI NIH HHS R61 CA309705NHGRI NIH HHS RM1 HG011014NIGMS NIH HHS DP2 GM154011
6 · The paper itself

Abstract

Integrating single-cell transcriptomic and epigenomic data provides a robust framework for investigating gene regulation mechanisms. Existing analyses typically treat these modalities as synchronized features that can be translated in a static manner; however, the temporal delays that underpin cellular kinetics are intrinsic to dynamic biological systems. To address this limitation, we propose utilizing the "molecular asynchrony" within regulatory hierarchies to determine the thermodynamic properties of individual cells. Here, we present SeqTag, a single-cell multiomics sequencing method that simultaneously profiles the transcriptome, chromatin accessibility, and histone modifications, supported by an analytical framework to identify asynchronous states across regulatory layers for characterization of single-cell kinetics. By measuring the epigenetic priming potential and remodeling rates during adult mouse oligodendrogenesis, we delineated a sequential program for bivalency resolution as maturing cells traverse Waddington's landscape. This process becomes increasingly decoupled with age, a change linked to a drift in progenitor cell-fate probabilities. By identifying entropy-driving regulatory elements, we characterized the aging-related decline in cell identity across various cell types and proposed a dynamic model linking static genetic variants to the risk of late-onset diseases. In summary, our integrated approach established a unified framework for employing multimodal single-cell genomics to model the kinetics of complex cellular processes.

Identifiers

PMID42282592
PMCPMC13251968

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.