Evidence map›Paper›PMID 28495919›Full record

ArticleMolecular systems biology2017

Alternative TSSs are co-regulated in single cells in the mouse brain.

Kasper Karlsson, Peter Lönnerberg, Sten Linnarsson

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

17 citing papers in PubMed, 32 citations in OpenAlex.

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  12. Mobile genomics: tools and techniques for tackling transposons.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Review
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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 at 2 institutions in 2 countries.

Kasper KarlssonStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0003-0162-1354
Peter LönnerbergLaboratory for Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Sten LinnarssonLaboratory for Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden sten.linnarsson@ki.se.ORCID 0000-0002-3491-3444
Karolinska Institutet · SEStanford University · US

Funding

European Research Council 261063
6 · The paper itself

Abstract

Alternative transcription start sites (TSSs) have been extensively studied genome-wide for many cell types and have been shown to be important during development and to regulate transcript abundance between cell types. Likewise, single-cell gene expression has been extensively studied for many cell types. However, how single cells use TSSs has not yet been examined. In particular, it is unknown whether alternative TSSs are independently expressed, or whether they are co-activated or even mutually exclusive in single cells. Here, we use a previously published single-cell RNA-seq dataset, comprising thousands of cells, to study alternative TSS usage. We find that alternative TSS usage is a regulated process, and the correlation between two TSSs expressed in single cells of the same cell type is surprisingly high. Our findings indicate that TSSs generally are regulated by common factors rather than being independently regulated or stochastically expressed.

Indexed as

Transcription Initiation SiteAnimalsBase SequenceBrainCystatin CGene ExpressionMiceSingle-Cell AnalysisCst3 protein, mouseCystatin Calternative TSS usageneuronssingle‐cell RNA sequencingtranscriptionUMI

Identifiers

PMID28495919
PMCPMC5448164
OpenAlexW2613027773

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.