Evidence map›Paper›PMID 41025978›Full record

ReviewThe Biochemical journal2025

Functional analysis and transcriptional profiling of non-coding RNAs in yeast.

Tanda Qi, Daniela Delneri, Soukaina Timouma

Abstract readReview
In one paragraph

Review in The Biochemical journal, 2025. 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

3 authors.

Tanda QiManchester Institute of Biotechnology, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-2097-246X
Daniela DelneriManchester Institute of Biotechnology, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-8070-411X
Soukaina TimoumaManchester Institute of Biotechnology, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-0178-4228

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced transcriptomic technology has identified a great number of non-coding RNAs (ncRNAs) that are pervasively transcribed in the yeast genome. ncRNAs can be classified into short ncRNAs (<200 nt) and long ncRNAs (lncRNAs; >200 nt). Those transcripts are strictly regulated through transcription and degradation mechanisms to maintain proper cellular homeostasis and prevent aberrant expression. It has been revealed that ncRNAs can play roles in various regulatory processes, particularly in transcriptional regulation. While short ncRNAs are well characterised, the function of lncRNAs remains poorly understood. Both functional and transcriptional profiling have been applied to fill the gap in the lncRNA functions landscape. It has been proven by functional profiling that these long transcripts can serve important cellular roles in gene regulation, RNA metabolism, sexual differentiation and telomeric overhang homeostasis. In addition, transcriptional profiling allowed the characterisation of ncRNAs involved in the cell cycle, colony subpopulation dynamics, virulence and regulatory networks. In this review, we introduce the classification, the cellular fate, the evolution and conservation, the mechanisms of action, and the profiling of yeast ncRNAs.

Indexed as

Gene Expression ProfilingGene Expression Regulation, FungalRNA, FungalRNA, Long NoncodingRNA, UntranslatedSaccharomyces cerevisiaeTranscription, GeneticRNA, FungalRNA, Long NoncodingRNA, Untranslatedfunctional genomicsnon-coding RNASaccharomyces cerevisiaetranscriptionyeast

Identifiers

PMID41025978
PMCPMC12599242

What OpenQuestion holds

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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.