Evidence map›Paper›PMID 24563719›Full record

ReviewCommunicative & integrative biology2013

Unexpected functions of lncRNAs in gene regulation.

Siwen Wang, Elizabeth J Tran

Open access · goldAbstract readReview
In one paragraph

Review in Communicative & integrative biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Endothelial long non-coding RNAs regulated by oxidized LDL.Molecular and cellular biochemistry · 2017
    Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Non-coding RNAs and lipid metabolism.International journal of molecular sciences · 2014
    Review
  13. 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

2 authors at 2 institutions in 1 country.

Siwen WangDepartment of Biochemistry; Purdue University; West Lafayette, IN USA.
Elizabeth J TranDepartment of Biochemistry; Purdue University; West Lafayette, IN USA ; Purdue University Center for Cancer Research; Purdue University; West Lafayette, IN USA.
Center for Cancer Research · USPurdue University West Lafayette · US

Funding

The Role of DEAD-box Proteins in Gene ExpressionR01GM097332 · NIGMS · PURDUE UNIVERSITY · PI TRAN, ELIZABETH J · 2011 to 2025
$4.1M
NIGMS NIH HHS R01 GM097332
6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are a group of molecules that function in gene regulation in yeast, plants and mammals. The precise mechanisms of action for lncRNAs, however, remain largely unclear. The GAL gene cluster has been used as a model system to study the function of these molecules in Saccharomyces cerevisiae, with a historical focus on lncRNA-dependent repression. Strikingly, in characterizing the role of the RNA helicase Dbp2, we discovered that the GAL lncRNAs could also promote transcriptional activation of the targeted GAL protein-coding genes. Interestingly, these lncRNAs help determine how quickly the GAL genes can be induced in response to galactose, without altering final steady-state transcript levels. This unexpected finding suggests that one role for lncRNAs is to promote the timing of gene expression. Herein, we discuss our discoveries in the context of current models of lncRNA functions in eukaryotes, with a key emphasis on future challenges for genomic research.

Indexed as

gene expressiongeneticshelicasekineticslong non-coding RNAsS. cerevisiaetranscriptionyeast

Identifiers

PMID24563719
PMCPMC3917965
OpenAlexW2016740169

What OpenQuestion holds

Textmetadata
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.