Evidence map›Paper›PMID 28465541›Full record

ArticleScientific reports2017

Transcriptional landscape of epithelial and immune cell populations revealed through FACS-seq of healthy human skin.

Richard S Ahn, Keyon Taravati, Kevin Lai, Kristina M Lee, Joanne Nititham, Rashmi Gupta, David S Chang, Sarah T Arron, Michael Rosenblum, Wilson Liao

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Layilin Anchors Regulatory T Cells in Skin.Journal of immunology (Baltimore, Md. : 1950) · 2021
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Richard S AhnDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States. richard.ahn@ucsf.edu.ORCID http://orcid.org/0000-0002-9698-2752
Keyon TaravatiDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Kevin LaiDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Kristina M LeeDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Joanne NitithamDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Rashmi GuptaDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
David S ChangDepartment of Plastic Surgery, California Pacific Medical Center, San Francisco, CA, United States.
Sarah T ArronDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Michael RosenblumDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.
Wilson LiaoDepartment of Dermatology, University of California, San Francisco, San Francisco, CA, United States.

Funding

UCSF Dermatology Training GrantT32AR007175 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Wilson Liao, Michael David Rosenblum · 1986 to 2026
$6.1M
MHC and KIR Region Genomics in PsoriasisU01AI119125 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIAO, WILSON · 2015 to 2019
$3.5M
Functional Manipulation of Memory Regulatory T cells in SkinDP2AR068130 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSENBLUM, MICHAEL DAVID · 2014 to 2014
$2.4M
Identification of Causal Variants in PsoriasisR01AR065174 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIAO, WILSON · 2013 to 2016
$1.8M
Mechanisms of immune regulation in the skinK08AR062064 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSENBLUM, MICHAEL DAVID · 2012 to 2016
$670k
Elucidating the Fundamental Biology of Memory Regulatory T cells in SkinR21AR066821 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ROSENBLUM, MICHAEL DAVID · 2014 to 2015
$381k
NIAID NIH HHS U01 AI119125NIAMS NIH HHS DP2 AR068130NIAMS NIH HHS K08 AR062064NIAMS NIH HHS L30 AR068704NIAMS NIH HHS R01 AR065174NIAMS NIH HHS R21 AR066821NIAMS NIH HHS T32 AR007175
6 · The paper itself

Abstract

Human skin consists of multiple cell types, including epithelial, immune, and stromal cells. Transcriptomic analyses have previously been performed from bulk skin samples or from epithelial and immune cells expanded in cell culture. However, transcriptomic analysis of bulk skin tends to drown out expression signals from relatively rare cells while cell culture methods may significantly alter cellular phenotypes and gene expression profiles. To identify distinct transcriptomic profiles of multiple cell populations without substantially altering cell phenotypes, we employed a fluorescence activated cell sorting method to isolate keratinocytes, dendritic cells, CD4+ T effector cells, and CD8+ T effector cells from healthy skin samples, followed by RNA-seq of each cell population. Principal components analysis revealed distinct clustering of cell types across samples, while differential expression and coexpression network analyses revealed transcriptional profiles of individual cell populations distinct from bulk skin, most strikingly in the least abundant CD8+ T effector population. Our work provides a high resolution view of cutaneous cellular gene expression and suggests that transcriptomic profiling of bulk skin may inadequately capture the contribution of less abundant cell types.

Indexed as

AdultCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesDendritic CellsFemaleFlow CytometryGene Expression ProfilingHumansKeratinocytesMaleMiddle AgedSequence Analysis, RNASkinTranscriptome

Identifiers

PMID28465541
PMCPMC5430950

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.