Evidence map›Paper›PMID 38935964›Full record

ArticleJMIR bioinformatics and biotechnology2022

Differential Expression of Long Noncoding RNAs in Murine Myoblasts After Short Hairpin RNA-Mediated Dysferlin Silencing In Vitro: Microarray Profiling.

Richa Singhal, Rachel Lukose, Gwenyth Carr, Afsoon Moktar, Ana Lucia Gonzales-Urday, Eric C Rouchka, Bathri N Vajravelu

Abstract read
In one paragraph

Article in JMIR bioinformatics and biotechnology, 2022. 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. Review
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

7 authors.

Richa Singhal *Department of Biochemistry and Molecular Genetics, KY IDeA Networks of Biomedical Research Excellence Bioinformatics Core, University of Louisville, Louisville, KY, United States.ORCID https://orcid.org/0000-0002-8559-8798
Rachel Lukose *Department of Physician Assistant Studies, Massachusetts College of Pharmacy and Health Sciences, Boston, MA, United States.ORCID https://orcid.org/0000-0002-9609-929X
Gwenyth CarrDepartment of Medical and Molecular Biology, School of Arts and Sciences, Massachusetts College of Pharmacy and Health Sciences, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8622-4432
Afsoon MoktarDepartment of Physician Assistant Studies, Massachusetts College of Pharmacy and Health Sciences, Boston, MA, United States.ORCID https://orcid.org/0000-0003-1883-6706
Ana Lucia Gonzales-UrdayDepartment of Pharmaceutical Sciences, Massachusetts College of Pharmacy and Health Sciences, Boston, MA, United States.ORCID https://orcid.org/0000-0002-8822-5321
Eric C RouchkaDepartment of Biochemistry and Molecular Genetics, KY IDeA Networks of Biomedical Research Excellence Bioinformatics Core, University of Louisville, Louisville, KY, United States.ORCID https://orcid.org/0000-0003-3487-6572
Bathri N VajraveluDepartment of Physician Assistant Studies, Massachusetts College of Pharmacy and Health Sciences, Boston, MA, United States.ORCID https://orcid.org/0000-0002-1558-2651

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong noncoding RNAs (lncRNAs) are noncoding RNA transcripts greater than 200 nucleotides in length and are known to play a role in regulating the transcription of genes involved in vital cellular functions. We hypothesized the disease process in dysferlinopathy is linked to an aberrant expression of lncRNAs and messenger RNAs (mRNAs).

objectiveIn this study, we compared the lncRNA and mRNA expression profiles between wild-type and dysferlin-deficient murine myoblasts (C2C12 cells).

methodsLncRNA and mRNA expression profiling were performed using a microarray. Several lncRNAs with differential expression were validated using quantitative real-time polymerase chain reaction. Gene Ontology (GO) analysis was performed to understand the functional role of the differentially expressed mRNAs. Further bioinformatics analysis was used to explore the potential function, lncRNA-mRNA correlation, and potential targets of the differentially expressed lncRNAs.

resultsWe found 3195 lncRNAs and 1966 mRNAs that were differentially expressed. The chromosomal distribution of the differentially expressed lncRNAs and mRNAs was unequal, with chromosome 2 having the highest number of lncRNAs and chromosome 7 having the highest number of mRNAs that were differentially expressed. Pathway analysis of the differentially expressed genes indicated the involvement of several signaling pathways including PI3K-Akt, Hippo, and pathways regulating the pluripotency of stem cells. The differentially expressed genes were also enriched for the GO terms, developmental process and muscle system process. Network analysis identified 8 statistically significant (P<.05) network objects from the upregulated lncRNAs and 3 statistically significant network objects from the downregulated lncRNAs.

conclusionsOur results thus far imply that dysferlinopathy is associated with an aberrant expression of multiple lncRNAs, many of which may have a specific function in the disease process. GO terms and network analysis suggest a muscle-specific role for these lncRNAs. To elucidate the specific roles of these abnormally expressed noncoding RNAs, further studies engineering their expression are required.

Indexed as

abnormal expressionbioinformaticsdysferlinopathygene ontologyLGMD-2Blimb-girdle muscular dystrophy 2BlncRNAlong noncoding RNAsmessenger RNAmRNAmuscular dystrophynoncoding RNAprotein expressionqRT-PCRquantitative real-time polymerase chain reactiontranscription

Identifiers

PMID38935964
PMCPMC11135227

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