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Profiling and bioinformatics analyses reveal differential expression of circular RNA in tongue cancer revealed by high-throughput sequencing

ABSTRACT: Circular RNAs (circRNA) are special non-coding RNAs. They are widely present, but with unknown functions. Recent studies have shown that many endogenous circRNAs have sponge function to absorb microRNAs. They can regulate target gene mRNA expression and play important roles in many biological processes. However, expression profile and function of circRNAs in human TSCC haven’t been reported. High-throughput sequencing was performed to identify and annotate from three TSCC tissues and adjacent tissues. A separate set (n=20) of human TSCCs and corresponding adjacent tissues were subjected to RT-PCR for validation of circular RNAs expression profile. GO functional analysis, KEGG pathway analysis, and circRNA–microRNA network analysis were also performed to predict the function of circRNA in TSCC.A total of 12,156 circRNAs were identified and annotated, most of the circRNAs were novel (n=6,231) and exonic (62.09%). Statistical analysis revealed 322 differentially expressed (DE) circRNAs. RT-PCR results showed that circRNA expression in TSCC was higher than that in adjacent tissues. GO functional analysis, KEGG pathway analysis, and circRNA–microRNA network analysis all showed that circRNAs correlated with tumor development and progression to a certain extent. The present study is the first to systematically characterize and annotate circRNA expression in TSCC, the majority were novel circRNAs. Some host genes of the DE circRNAs were involved in tumor signaling pathway and had complicated correlations with tumor-relevant microRNAs, indicating that circRNAs might be promoted development and progression of TSCC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE118750 | GEO | 2018/12/31

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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Profiling and bioinformatics analyses reveal differential expression of circular RNA in tongue cancer revealed by high-throughput sequencing

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