Accepted for/Published in: JMIR Bioinformatics and Biotechnology
Date Submitted: Aug 27, 2021
Open Peer Review Period: Aug 26, 2021 - Oct 21, 2021
Date Accepted: May 10, 2022
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Long non-coding RNAs are differentially expressed in dysferlinopathy
ABSTRACT
Background:
Long non-coding RNAs (lncRNAs) are non-coding 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 mRNAs.
Objective:
In this study, we compared the lncRNA and mRNA expression profiles between the normal and dysferlin deficient murine myoblasts (C2C12 cells).
Methods:
LncRNA and mRNA expression profiling were performed using a microarray. Several lncRNAs with differential expression were validated using quantitative real time polymerase chain reaction (qRT-PCR). Gene Ontology 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.
Results:
We found 3195 lncRNAs and 1966 mRNAs that are differentially expressed. The chromosomal distribution of the differentially expressed lncRNAs and mRNAs was unequal, with the 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, FoxO, Wnt, cAMP and Hippo. The differentially expressed genes were also enriched for the GO terms, developmental process and muscle system process. Network analysis identified 8 statistically significant (p<0.05) network objects from the upregulated lncRNAs and 3 statistically significant network objects from the downregulated lncRNAs.
Conclusions:
Our 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 non-coding RNAs, further studies engineering their expression are required.
Citation
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Copyright
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