Evidence map›Paper›PMID 36614000›Full record

ArticleInternational journal of molecular sciences2022

The Enrichment of Specific Hair Follicle-Associated Cell Populations in Plucked Hairs Offers an Opportunity to Study Gene Expression Underlying Hair Traits.

Rakan Naboulsi, Jakub Cieślak, Denis Headon, Ahmad Jouni, Juan J Negro, Göran Andersson, Gabriella Lindgren

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

7 authors at 4 institutions in 5 countries.

Rakan NaboulsiDepartment of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.ORCID 0000-0002-3610-4341
Jakub CieślakDepartment of Genetics and Animal Breeding, Poznan University of Life Sciences, 60-637 Poznań, Poland.
Denis HeadonThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK.
Ahmad JouniDepartment of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.
Juan J NegroDepartment of Evolutionary Ecology, Doñana Biological Station, CSIC, 41092 Seville, Spain.ORCID 0000-0002-8697-5647
Göran AnderssonDepartment of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.ORCID 0000-0001-5131-3144
Gabriella LindgrenDepartment of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.ORCID 0000-0001-6046-9669
Swedish University of Agricultural Sciences · SEEstación Biológica de Doñana · ESRoslin Institute · GBUniversity of Life Sciences in Poznań · PL

Funding

The Swedish Research Council (VR) 2016-04361 and 2020-03375
6 · The paper itself

Abstract

Gene expression differences can assist in characterizing important underlying genetic mechanisms between different phenotypic traits. However, when population-dense tissues are studied, the signals from scarce populations are diluted. Therefore, appropriately choosing a sample collection method that enriches a particular type of effector cells might yield more specific results. To address this issue, we performed a polyA-selected RNA-seq experiment of domestic horse (

Indexed as

HairHair FollicleAnimalsEpidermisGene ExpressionHorsesKeratinocytesMiceequinefolliclehairRNA-seqskin

Identifiers

PMID36614000
PMCPMC9820680
OpenAlexW4313328156

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.