Dataset Information

Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq.

ABSTRACT: Although the functional role of circular RNA (circRNA) interaction with microRNAs and proteins has been studied extensively, circRNA interactions with the protein-coding mRNAs in intact cells remain largely unknown. Here, by employing AMT-mediated proximity ligation of RNA-RNA duplexes followed by circRNA enrichment and deep sequencing, we report a novel Cross-Linking Poly(A) Pulldown RNase R Sequencing (CLiPPR-seq) technology which identified hundreds of mRNA-interacting circRNAs in three different cell types, including βTC6, C2C12 and HeLa cells. Furthermore, CLiPP-seq without RNase R treatment was also performed to identify the mRNA expression in these cells. BLAST analysis of circRNAs in CLiPPR-seq sample with the mRNAs in CLiPP-seq samples determined their potential complementary sequences for circRNA-mRNA interaction. Pulldown of circRNAs and poly(A) RNAs confirmed the direct interaction of circRNAs with target mRNAs. Silencing of mRNA-interacting circRNAs led to the altered expression of target mRNAs in βTC6 cells, suggesting the role of direct interaction of circRNAs with mRNAs in gene expression regulation. CLiPPR-seq thus represents a novel method for illuminating the myriad of uncharacterized circRNA-mRNA hybrids that may regulate gene expression.

SUBMITTER: Singh S

PROVIDER: S-EPMC11014417 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

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Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq.

Singh Suman S Shyamal Sharmishtha S Das Arundhati A Panda Amaresh C AC

Nucleic acids research 20240401 6

Although the functional role of circular RNA (circRNA) interaction with microRNAs and proteins has been studied extensively, circRNA interactions with the protein-coding mRNAs in intact cells remain largely unknown. Here, by employing AMT-mediated proximity ligation of RNA-RNA duplexes followed by circRNA enrichment and deep sequencing, we report a novel Cross-Linking Poly(A) Pulldown RNase R Sequencing (CLiPPR-seq) technology which identified hundreds of mRNA-interacting circRNAs in three diffe ...[more]

PMID: 38324478

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Project description:Replicating circular RNAs are independent plant pathogens known as viroids, or act to modulate the pathogenesis of plant and animal viruses as their satellite RNAs. The rate of discovery of these subviral pathogens was low over the past 40 years because the classical approaches are technical demanding and time-consuming. We previously described an approach for homology-independent discovery of replicating circular RNAs by analysing the total small RNA populations from samples of diseased tissues with a computational program known as progressive filtering of overlapping small RNAs (PFOR). However, PFOR written in PERL language is extremely slow and is unable to discover those subviral pathogens that do not trigger in vivo accumulation of extensively overlapping small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating independent infection. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was 3 to 8 times faster than PFOR. A new computational program was further developed and incorporated into PFOR2 to allow the identification of circular RNAs by deep sequencing of long RNAs instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine and apple plants led to the discovery of Grapevine latent viroid (GLVd) and Apple hammerhead viroid-like RNA (AHVd-like RNA), respectively. GLVd was proposed as a new species in the genus Apscaviroid, because it contained the typical structural elements found in this group of viroids and initiated independent infection in grapevine seedlings. AHVd-like RNA encoded a biologically active hammerhead ribozyme in both polarities, and was not specifically associated with any of the viruses found in apple plants. We propose that these computational algorithms have the potential to discover novel circular RNAs in plants, invertebrates and vertebrates regardless of whether they replicate and/or induce the in vivo accumulation of small RNAs.

Project description:Abnormal expression of non-coding circular RNAs (circRNAs) have been reported in many types of tumors. circRNA have been suggested to be an ideal candidate biomarker for diagnostic and therapeutic implications in cancers. The aim of this study was to assess the circRNA expression profile of laryngeal squamous cell carcinomas (LSCC). The biopsy samples from patients with LSCC were obtained intra-operatively. The circRNA expression was performed using secondary sequencing. Among 10 patients with LSCC, 2 were well differentiated, 3 were moderately differentiated and 5 were adjunctive samples with normal and LSCC tissues. A total of 21,444 distinct circRNA candidates were detected. Among them, we defined the statistical criteria for selecting aberrant-expressed circRNA using a q-value of < 0.001 with a fold change of > 2.0 or < 0.5. A total of 29 circRNA were upregulated and 19 circRNA were downregulated significantly in the LSCC tissues. The intersection of these dysregulated circRNAs of normal-well differentiated set and normal-moderately differentiated set was then assessed to narrow the upregulated and downregulated circRNAs down to 18 and 5 respectively. Furthermore, an association of the circRNA-miRNA-mRNA was investigated, showing that 20 dysregulated circRNA successfully predicted an interaction with several cancer-related miRNAs. Finally, a further KEGG analysis showed that PPAR, Axon guidance, Wnt and Cell cycle signaling pathway were key putative pathways in the process of LSCC. hsa_circ:chr20:31876585-31,897,648 was found to be able to differentiate most of LSCC from the matching normal tissues. This observational study demonstrated dysregulation of circRNA in LSCC, which may have an impact on development of potential biomarkers in this disease. Validation of down-regulation of hsa_circ:chr20:31876585-31,897,648 in LSCC compared to each adjunctive tissue by Q-RT-PCR, indicating that hsa_circ:chr20:31876585-31,897,648 may be a novel promising tumor suppresser in LSCC.

Dataset Information

Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq.

Publications

Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq.

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