Evidence map›Paper›PMID 42816519›Full record

ArticleScientific data2026

A single-cell RNA-seq dataset characterizing cellular diversity in healthy equine skin.

Srinivas Akula, Birong Zhang, Miia Riihimäki, Sara Wernersson, Amanda Raine

Abstract readDataset
In one paragraph

Article in Scientific data, 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. Article
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

5 authors.

Srinivas Akula *Department of Animal Biosciences, Swedish University of Agricultural Sciences, Uppsala, Sweden. srinivas.akula@slu.se.ORCID http://orcid.org/0000-0001-6628-1640
Birong Zhang *Department of Medical Sciences, Uppsala University, Uppsala, Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Miia RiihimäkiDepartment of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.ORCID http://orcid.org/0000-0002-9766-1440
Sara WernerssonDepartment of Animal Biosciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Amanda RaineDepartment of Medical Sciences, Uppsala University, Uppsala, Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. amanda.raine@medsci.uu.se.

Funding

Svenska Forskningsrådet Formas 2023-01000Svenska Forskningsrådet Formas 2023-01377
6 · The paper itself

Abstract

The skin serves as the primary barrier tissue in horses and is frequently affected by immune-mediated dermatological conditions, most notably insect bite hypersensitivity (IBH). Yet, the cellular composition and transcriptional landscape of normal equine skin have never been characterized at single-cell resolution. Here, we present a single-cell RNA sequencing dataset of healthy equine skin comprising 85,574 high-quality transcriptomes from two horses, with one skin biopsy collected from each horse, divided into two portions for independent processing via manual or automated tissue dissociation. The dataset resolved 22 transcriptionally distinct cell populations, encompassing keratinocyte subpopulations that reflect discrete epidermal differentiation states, adnexal epithelial lineages, stromal and vascular compartments, and resident immune cell types. Cell-type identities are supported by marker gene expression, KEGG pathway enrichment analysis, and functional module scoring. This dataset constitutes the first single-cell transcriptomic reference of normal equine skin, enabling investigations into equine dermatological diseases, wound healing, immune responses and comparative skin biology.

Indexed as

SkinTranscriptomeAnimalsHorsesRNA-SeqSequence Analysis, RNASingle-Cell AnalysisSingle-Cell Gene Expression Analysis

Identifiers

PMID42816519
PMCPMC13627664

What OpenQuestion holds

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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.