International Journal of Molecular SciencesMolecular BiologyPeer-reviewed journal article
Dysregulation of circular RNAs in myotonic dystrophy type 1
Christine VoellenkleiD, Alessandra PerfettiiD, Matteo CarraraiD, Paola Fuschi, Laura Valentina RennaiD, Marialucia Longo, Simona Baghai SainiD, Rosanna CardaniiD, Rea Valaperta, Gabriella SilvestriiD, Ivano LegniniiD, Irene BozzoniiD, Denis FurlingiD, Carlo GaetanoiD, Germana FalconeiD, Giovanni MeolaiD, Fabio MartelliiD
Abstract
Circular RNAs (circRNAs) constitute a recently re-discovered class of non-coding RNAs functioning as sponge for miRNAs and proteins, affecting RNA splicing and regulating transcription. CircRNAs are generated by \"back-splicing\", linking covalently 3- and 5-ends of exons. Thus, circRNA levels might be deregulated in conditions associated to altered RNA-splicing. Indeed, increasing evidence indicates their role in human diseases. Specifically, myotonic dystrophy type 1 (DM1) is a multisystemic disorder caused by expanded CTG-repeats in the DMPK gene, resulting in abnormal mRNA-splicing. In this investigation, circRNAs expressed in DM1 skeletal muscles were identified by analyzing RNA-sequencing data-sets followed by qPCR validation. In muscle biopsies, out of 9 tested, 4 transcripts showed an increased circular fraction: CDYL, HIPK3, RTN4_03 and ZNF609. The circular fraction values correlated positively with skeletal muscle strength and Receiver-Operating-Characteristics curves showed that these four circRNAs allow to distinguish DM1 patients from controls. The identified circRNAs were also detectable in peripheral-blood-mononuclear-cells (PBMCs) and plasma of DM1 patients, but they were not regulated significantly, indicating a tissue-selectivity of the identified modulations. Finally, increased circular fractions of RTN4_03 and ZNF609 were also observed in differentiated myogenic cell lines derived from DM1 patients.\n\nIn conclusion, this proof-of-principle study identified circRNA dysregulation in DM1 patients.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 44
- FWCI
- 2.23
- Field percentile
- top 11%
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