Dataset Information

Structure and degradation of circular RNAs regulate PKR activation in innate immunity

ABSTRACT: CircRNAs produced from back-splicing of exons of pre-mRNAs are widely expressed, but current understanding of their functions is limited. These RNAs are stable in general and are thought to have unique structural conformations distinct from their linear RNA cognates. Here we uncover that endogenous circRNAs tend to form 16-26 bp RNA duplexes and act as inhibitors of dsRNA-activated protein kinase (PKR) related to innate immunity. Upon poly(I:C) stimulation or viral infection, circRNAs are globally degraded by RNase L, a process required for PKR activation in early cellular innate immune responses. Augmented PKR phosphorylation and circRNA reduction are found in peripheral blood mononuclear cells (PBMCs) derived from patients of autoimmune disease systemic lupus erythematosus (SLE). Importantly, over-expression of the dsRNA-containing circRNA in PBMCs or T cells derived from SLE can alleviate the aberrant PKR activation cascade, thus providing a connection between circRNAs and SLE.

SUBMITTER: Li,Yang

PROVIDER: OEX001577 | NODE |

REPOSITORIES: NODE

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Structure and Degradation of Circular RNAs Regulate PKR Activation in Innate Immunity.

Liu Chu-Xiao CX Li Xiang X Nan Fang F Jiang Shan S Gao Xiang X Guo Si-Kun SK Xue Wei W Cui Yange Y Dong Kaige K Ding Huihua H Qu Bo B Zhou Zhaocai Z Shen Nan N Yang Li L Chen Ling-Ling LL

Cell 20190425 4

Circular RNAs (circRNAs) produced from back-splicing of exons of pre-mRNAs are widely expressed, but current understanding of their functions is limited. These RNAs are stable in general and are thought to have unique structural conformations distinct from their linear RNA cognates. Here, we show that endogenous circRNAs tend to form 16-26 bp imperfect RNA duplexes and act as inhibitors of double-stranded RNA (dsRNA)-activated protein kinase (PKR) related to innate immunity. Upon poly(I:C) stimu ...[more]

PMID: 31031002

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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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