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Circular RNA expression profile in human primary multiple intracranial aneurysms

ABSTRACT: Primary multiple intracranial aneurysms (MIA) is a vascular disease that often leads to fatal vascular rupture and subarachnoid hemorrhage. However, little is known about the epigenetic regulation of MIA. Circular RNAs (circRNAs) serve important roles in cardiovascular diseases; however, they have received little research attention regarding their association with MIA. The present study initially aimed to explore novel mechanisms of MIA through circRNA expression profiles. Comprehensive circRNA expression profiles were detected by RNA sequencing (RNA-Seq) in human peripheral blood mononuclear cells. The RNA-Seq results were validated by reverse transcription-quantitative PCR. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses suggested the functions of these circRNAs. Among the 3,328 differentially expressed circRNAs between the MIA and matched groups, 60 exhibited marked expression changes (|log2 fold change|≥2; P<0.05). Among the 60 circRNAs that exhibited significant changes, 20 were upregulated, while the other 40 were downregulated. The circRNAs hsa_circ_0135895, hsa_circ_0000682 and hsa_circ_0000690 could regulate protein tyrosine kinase 2, protein kinase Cβ and integrin subunit αL, respectively. To the best of our knowledge, the present study was the first to perform circRNA sequencing analysis of MIA. Furthermore, the results specifically predicted the regulatory role of circRNAs in MIA pathogenesis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE159631 | GEO | 2020/10/20

REPOSITORIES: GEO

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Project description:In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17-188 fold relative to nucleated tissues, and 14-26 fold relative to samples digested with RNAseR to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched ~13X in platelets relative to nucleated tissues, and identify 3162 genes significantly enriched for circRNAs including some where all RNAs appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in megakaryocytes, and that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost on aveage over 90% of their progenitor mRNAs, and that translation in platelets occurrs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artefacts. A single rRNA depleted total RNA sample was sequenced. This together with 25 publicly available rRNA depleted total RNA samples (including 3 from platelets) were analysed using PTESFinder v 1 (http://sourceforge.net/projects/ptesfinder-v1/) to identify back-splice junctions, characteristic of circRNA transcripts. The contribution of circRNA producing exons was analysed on a gene by gene basis as follows: All circRNA transcripts identified in any sample were first pooled to define exons which can contribute to circRNA generation using custom scripts (available on request). For each sample, expression estimates (RPKMI) across all circRNA producing exons were computed for each locus using the total size of exons (in bp) and the read counts mapping to them. Similarly, total size and exonic read counts for exons for which no circRNA were detected in any sample were used to compute expression estimates (RPKME) for non-circRNA producing exons for each locus. Abundance ratios (RPKMI/RPKME and RPKMI/RPKMI+RPKME) were calculated and compared between Platelets and human tissues using Wilcoxon signed-rank test. Please note that the '25sample_info_accn_no.txt' contains the accession numbers and tissue/cell type information for 25 samples analyzed together.

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Circular RNA expression profile in human primary multiple intracranial aneurysms

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