Evidence map›Paper›PMID 31906285›Full record

ReviewInternational journal of molecular sciences2020

A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs.

Enrico Alessio, Raphael Severino Bonadio, Lisa Buson, Francesco Chemello, Stefano Cagnin

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Decoding the Epigenome of Breast Cancer.International journal of molecular sciences · 2025
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  11. Artificial miRNAs and target-mimics as potential tools for crop improvement.Physiology and molecular biology of plants : an international journal of functional plant biology · 2025
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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

5 authors.

Enrico AlessioDepartment of Biology, University of Padova, 35131 Padova, Italy.
Raphael Severino BonadioDepartment of Biology, University of Padova, 35131 Padova, Italy.
Lisa BusonDepartment of Biology, University of Padova, 35131 Padova, Italy.
Francesco ChemelloDepartment of Biology, University of Padova, 35131 Padova, Italy.
Stefano CagninDepartment of Biology, University of Padova, 35131 Padova, Italy.

Funding

Agenzia Nazionale di Valutazione del Sistema Universitario e della Ricerca (ANVUR) FFABR- 2017Associazione Italiana per la Ricerca sul Cancro IG2015-ID17773Bando Grandi Attrezzature 2015 University of Padova Prot. 5086Fondazione Cariplo 2016-1006Fondazione Cassa di Risparmio di Padova e Rovigo FIBRE-GEXPMinistero della Salute GR-2011-02346845Università degli Studi di Padova CPDA139317
6 · The paper itself

Abstract

In late 2012 it was evidenced that most of the human genome is transcribed but only a small percentage of the transcripts are translated. This observation supported the importance of non-coding RNAs and it was confirmed in several organisms. The most abundant non-translated transcripts are long non-coding RNAs (lncRNAs). In contrast to protein-coding RNAs, they show a more cell-specific expression. To understand the function of lncRNAs, it is fundamental to investigate in which cells they are preferentially expressed and to detect their subcellular localization. Recent improvements of techniques that localize single RNA molecules in tissues like single-cell RNA sequencing and fluorescence amplification methods have given a considerable boost in the knowledge of the lncRNA functions. In recent years, single-cell transcription variability was associated with non-coding RNA expression, revealing this class of RNAs as important transcripts in the cell lineage specification. The purpose of this review is to collect updated information about lncRNA classification and new findings on their function derived from single-cell analysis. We also retained useful for all researchers to describe the methods available for single-cell analysis and the databases collecting single-cell and lncRNA data. Tables are included to schematize, describe, and compare exposed concepts.

Indexed as

Cell LineageDatabases, GeneticGene Expression RegulationHumansMicroRNAsNeoplasmsRNA, Long NoncodingRNA, RibosomalRNA SplicingSingle-Cell AnalysisMicroRNAsRNA, Long NoncodingRNA, RibosomallncRNA databaselncRNAslong non-coding RNAsnon-coding RNAssingle-cellsingle-cell databasesingle-cell expressionsingle-cell sequencing

Identifiers

PMID31906285
PMCPMC6982300

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.