Evidence map›Paper›PMID 42149448›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Isolation of Mouse Hair Matrix Keratinocytes for Multi-omics Analysis.

Guodong Chen, Elena Rozhkova, Andrey A Sharov

Abstract read
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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Guodong ChenSchool of Life Sciences, Central South University, Changsha, China.ORCID https://orcid.org/0000-0001-9399-9252
Elena RozhkovaDepartment of Dermatology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.ORCID https://orcid.org/0000-0002-5793-845X
Andrey A SharovDepartment of Dermatology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA. drsharov@bu.edu.ORCID https://orcid.org/0000-0002-7240-304X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The isolation and molecular characterization of distinct cell populations from heterogeneous tissues are essential for investigating cell-type-specific functions and regulatory mechanisms, particularly within complex organs such as the skin. Here, we present a comprehensive workflow for isolating hair matrix cells from postnatal mouse skin using fluorescence-activated cell sorting (FACS) for gene expression and high-resolution chromatin profiling. The protocol begins with enzymatic dissociation of the skin to obtain a single-cell suspension, followed by immunolabeling with cell surface markers to enable precise FACS-based enrichment of the desired cell populations. A low-input CUT&Tag assay is then used to map histone posttranslational modifications, transcription factor binding sites, and DNA modifications. Importantly, this cell isolation strategy is compatible with a range of integrative multi-omics approaches including RNA sequencing (RNA-seq), assay for transposase-accessible chromatin using sequencing (ATAC-seq), whole-genome bisulfite sequencing (WGBS), and high-throughput chromosome conformation capture (Hi-C) using input material as low as ~100,000 cells per assay. Together, this methodology allows comprehensive, cell-type resolved analysis of the transcriptional and epigenetic landscapes in hair matrix keratinocytes in postnatal skin.

Indexed as

Cell SeparationHair FollicleKeratinocytesAnimalsChromatinEpigenesis, GeneticFlow CytometryGene Expression ProfilingMiceMultiomicsChromatinChromatin profilingCUT&TagEpidermal keratinocytesEpigeneticsFluorescence-activated cell sorting (FACS)Hair matrix cellsMouse skin cell isolationMulti-omics

Identifiers

PMID42149448

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.