Evidence map›Paper›PMID 41386229›Full record

ArticleCell genomics2026

Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.

Andrew Liao, Zehao Zhang, Andras Sziraki, Abdulraouf Abdulraouf, Abid Rehman, Zihan Xu, Ziyu Lu, Weirong Jiang, Alia Arya, Jasper Lee and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell genomics, 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Andrew LiaoLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The Tri-Institutional MD-PhD Program, New York, NY, USA.
Zehao ZhangLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The David Rockefeller Graduate Program in Bioscience, the Rockefeller University, New York, NY, USA.
Andras SzirakiLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The David Rockefeller Graduate Program in Bioscience, the Rockefeller University, New York, NY, USA.
Abdulraouf AbdulraoufLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The Tri-Institutional MD-PhD Program, New York, NY, USA.
Abid RehmanLaboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA.
Zihan XuLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The David Rockefeller Graduate Program in Bioscience, the Rockefeller University, New York, NY, USA.
Ziyu LuLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA; The David Rockefeller Graduate Program in Bioscience, the Rockefeller University, New York, NY, USA.
Weirong JiangLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA.
Alia AryaLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA.
Jasper LeeLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA.
Manolis MaragkakisLaboratory of Genetics and Genomics, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA.
Wei ZhouLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA. Electronic address: wzhou@rockefeller.edu.
Junyue CaoLaboratory of Single-Cell Genomics and Population Dynamics, the Rockefeller University, New York, NY, USA. Electronic address: jcao@rockefeller.edu.

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
RNA dynamics and co-translational decay in aging and aging-related diseaseZIAAG000696 · NIA · NATIONAL INSTITUTE ON AGING · PI MARAGKAKIS, MANOLIS · 2020 to 2025
$14.0M
Weill Cornell/Rockefeller/Sloan Kettering MST ProgramT32GM152349 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI KATHARINE C HSU · 2024 to 2026
$6.6M
Development of novel genomic approaches for profiling cellular temporal-spatial dynamics of neurogenesis in Aging and Alzheimer's diseaseR01AG076932 · NIA · ROCKEFELLER UNIVERSITY · PI Junyue Cao · 2022 to 2026
$4.0M
Single cell dynamics on a whole organism scaleDP2HG012522 · NHGRI · ROCKEFELLER UNIVERSITY · PI CAO, JUNYUE · 2021 to 2024
$2.5M
Single Cell Long Read Sequencing of the Aging Mouse BrainZIAAG000493 · NIA · NATIONAL INSTITUTE ON AGING · PI MARAGKAKIS, MANOLIS · 2022 to 2024
$2.5M
Intramural NIH HHS ZIA AG000493Intramural NIH HHS ZIA AG000696NHGRI NIH HHS DP2 HG012522NHGRI NIH HHS RM1 HG011014NIA NIH HHS R01 AG076932NIGMS NIH HHS T32 GM152349
6 · The paper itself

Abstract

Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.

Indexed as

Cell NucleusSequence Analysis, RNASingle-Cell AnalysisAgingAnimalsBrainGene Expression ProfilingIn Situ Hybridization, FluorescenceMiceMice, Inbred C57BLOligodendrogliaTranscriptomebrain agingcell type targetedcombinatorial indexingexon dynamicshybridization chain reactionisoform switchingoligodendrocytessingle-cell RNA sequencingsplicingtranscriptome dynamics

Identifiers

PMID41386229
PMCPMC12985360

What OpenQuestion holds

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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.