Evidence map›Paper›PMID 36833174›Full record

ArticleGenes2023

Investigation of UTR Variants by Computational Approaches Reveal Their Functional Significance in

Hania Shah, Khushbukhat Khan, Yasmin Badshah, Naeem Mahmood Ashraf, Maria Shabbir, Janeen H Trembley, Tayyaba Afsar, Ali Abusharha, Suhail Razak

Open access · goldAbstract read
In one paragraph

Article in Genes, 2023. 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
0.9field-weighted citation impact, top 26% 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. Article
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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

9 authors at 4 institutions in 3 countries.

Hania ShahDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 45860, Pakistan.
Khushbukhat KhanDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 45860, Pakistan.
Yasmin BadshahDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 45860, Pakistan.
Naeem Mahmood AshrafSchool of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan.
Maria ShabbirDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 45860, Pakistan.ORCID 0000-0002-5685-3059
Janeen H TrembleyMinneapolis VA Health Care System Research Service, Minneapolis, MN 55417, USA.ORCID 0000-0003-3597-2611
Tayyaba AfsarDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.
Ali AbusharhaDepartment of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.
Suhail RazakDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.
National University of Sciences and Technology · PKKing Saud University · SAUniversity of Minnesota · USUniversity of the Punjab · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single nucleotide polymorphisms (SNPs) are associated with many diseases including neurological disorders, heart diseases, diabetes, and different types of cancers. In the context of cancer, the variations within non-coding regions, including UTRs, have gained utmost importance. In gene expression, translational regulation is as important as transcriptional regulation for the normal functioning of cells; modification in normal functions can be associated with the pathophysiology of many diseases. UTR-localized SNPs in the PRKCI gene were evaluated using the PolymiRTS, miRNASNP, and MicroSNIper for association with miRNAs. Furthermore, the SNPs were subjected to analysis using GTEx, RNAfold, and PROMO. The genetic intolerance to functional variation was checked through GeneCards. Out of 713 SNPs, a total of thirty-one UTR SNPs (three in 3' UTR region and twenty-nine in 5' UTR region) were marked as ≤2b by RegulomeDB. The associations of 23 SNPs with miRNAs were found. Two SNPs, rs140672226 and rs2650220, were significantly linked with expression in the stomach and esophagus mucosa. The 3' UTR SNPs rs1447651774 and rs115170199 and the 5' UTR region variants rs778557075, rs968409340, and 750297755 were predicted to destabilize the mRNA structure with substantial change in free energy (∆G). Seventeen variants were predicted to have linkage disequilibrium with various diseases. The SNP rs542458816 in 5' UTR was predicted to put maximum influence on transcription factor binding sites. Gene damage index(GDI) and loss of function (o:e) ratio values for PRKCI suggested that the gene is not tolerant to loss of function variants. Our results highlight the effects of 3' and 5' UTR SNP on miRNA, transcription and translation of PRKCI. These analyses suggest that these SNPs can have substantial functional importance in the PRKCI gene. Future experimental validation could provide further basis for the diagnosis and therapeutics of various diseases.

Indexed as

MicroRNAsNeoplasmsProtein Kinase C3' Untranslated Regions5' Untranslated RegionsGene Expression RegulationHumansPolymorphism, Single NucleotideProtein Kinase C-lambda3' Untranslated Regions5' Untranslated RegionsMicroRNAsProtein Kinase CProtein Kinase C-lambda3′ UTR5′ UTRmiRNAnon-coding regionPRKCISNP

Identifiers

PMID36833174
PMCPMC9956319
OpenAlexW4317425679

What Socratic 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 Socratic graph.