Evidence map›Paper›PMID 35991697›Full record

ArticleVirusdisease2022

Identification of novel lncRNA by reanalysis of RNA-seq data in Zika Virus Infected hiNPCs.

Amouda Venkatesan, Aishwarya Barik, Dahrii Paul, Mathavan Muthaiyan, Rajesh Das

Open access · greenAbstract read
In one paragraph

Article in Virusdisease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. LncRNAJournal of virology · 2025
    Article
  2. Review
  3. 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

5 authors at 1 institution in 1 country.

Amouda VenkatesanDepartment of Bioinformatics, Pondicherry University, Puducherry, 605014 India.ORCID 0000-0002-9586-1887
Aishwarya BarikDepartment of Bioinformatics, Pondicherry University, Puducherry, 605014 India.
Dahrii PaulDepartment of Bioinformatics, Pondicherry University, Puducherry, 605014 India.
Mathavan MuthaiyanDepartment of Bioinformatics, Pondicherry University, Puducherry, 605014 India.
Rajesh DasDepartment of Bioinformatics, Pondicherry University, Puducherry, 605014 India.
Pondicherry University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Zika Virus (ZIKV) infection is a serious, public health concern with no vaccines or antiviral treatments. This study aims to identify the differentially expressed long non-coding RNAs (lncRNAs) in ZIKV infected human-induced neuroprogenitor cells (hiNPCs). Though lncRNA is well-known for its role in gene regulation, its role in ZIKV infection remains unclear. Thus, taking advantage of publicly available transcriptome data, BioProject PRJNA551246 was analysed. Performed the gene ontology and pathway analysis of differentially expressed lncRNAs were functionally interpreted based on the neighbouring protein-coding genes (100 kb upstream and downstream of each lncRNAs). The study revealed 19 novels and 237 differentially expressed lncRNAs in ZIKV infected hiNPCs. They are found to be significantly enriched in type I interferon signalling pathway, negative regulation of viral genome replication, defense response to the virus, pathways involved in Influenza A and Herpes simplex infection, tumor necrosis factor signalling pathway, and apoptosis. In ZIKV, associated microcephaly type I interferon act as potential modulating factors. Type-I interferon inhibits ZIKV replication in many human cell types. The results support future studies on understanding the structure and function of the novel lncRNAs and experimental approaches to determine the role of the lncRNAs in ZIKV induced infection. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-022-00771-1.

Indexed as

And microcephalyApoptosisLong non-coding RNAsTranscriptomeZika Virus

Identifiers

PMID35991697
PMCPMC9381673
OpenAlexW4283742294

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.