Evidence map›Paper›PMID 36281987›Full record

ReviewBiochemical Society transactions2022

Single-cell transcriptomics in planaria: new tools allow new insights into cellular and evolutionary features.

Helena García-Castro, Jordi Solana

Open access · hybridAbstract readReview
In one paragraph

Review in Biochemical Society transactions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

2 authors at 1 institution in 1 country.

Helena García-CastroDepartment of Biological and Medical Sciences, Oxford Brookes University, Oxford, U.K.ORCID 0000-0001-9106-3557
Jordi SolanaDepartment of Biological and Medical Sciences, Oxford Brookes University, Oxford, U.K.ORCID 0000-0002-6770-3929
Oxford Brookes University · GB

Funding

Biotechnology and Biological Sciences Research Council BB/V014447/1Medical Research Council MR/S007849/1Medical Research Council MR/W017539/1
6 · The paper itself

Abstract

Single-cell transcriptomics has revolutionised biology allowing the quantification of gene expression in individual cells. Since each single cell contains cell type specific mRNAs, these techniques enable the classification of cell identities. Therefore, single cell methods have been used to explore the repertoire of cell types (the single cell atlas) of different organisms, including freshwater planarians. Nowadays, planarians are one of the most prominent animal models in single cell biology. They have been studied at the single cell level for over a decade using most of the available single cell methodological approaches. These include plate-based methods, such as qPCR, nanodroplet methods and in situ barcoding methods. Because of these studies, we now have a very good picture of planarian cell types and their differentiation trajectories. Planarian regenerative properties and other characteristics, such as their developmental plasticity and their capacity to reproduce asexually, ensure that another decade of single cell biology in planarians is yet to come. Here, we review these characteristics, the new biological insights that have been obtained by single-cell transcriptomics and outline the perspectives for the future.

Indexed as

PlanariansPluripotent Stem CellsAnimalsCell DifferentiationRegenerationRNA, MessengerTranscriptomeRNA, Messengerplanarianregenerationsingle-cell transcriptomicsstem cells

Identifiers

PMID36281987
PMCPMC9704525
OpenAlexW4307201160

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.