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Discovery of novel circular RNAs through integration of short- and long-read RNA sequencing

ABSTRACT: Circular RNAs (circRNAs) have been reported to be associated in crucial hallmarks of tumorigenesis. The lack of open ends gives rise to their high stability, making them clinically significant as potential non-invasive as biomarkers for cancer diagnosis and prognosis. Select circRNAs contain open reading frames and impact tumorigenesis through encoded small peptides, though computational challenges remain in accurately profiling circular open reading frames. Currently circRNA sequencing projects rely heavily on detecting circRNA backsplice junctions, without accurate transcript reconstruction to differentiate circular isoforms that share backsplice junctions but contain different intermediate exons. We adopted a long-read RNA sequencing strategy that enriches for full-length circRNAs to generate an accurate reference to integrate with matched short-read sequencing samples of colorectal cancer cell lines and patient trio tissues. We further validated circRNAs detected in long-read sequencing with high-confidence support from short reads. We present CHRIS, an open-source bioinformatic workflow that maximizes the detection of novel circRNAs missed in existing tools. In addition, we performed an integrative proteogenomic analysis and discovered thousands of novel peptides encoded by circRNAs that previously eluded short-read based methods, published in an online database PepCircDB. Our unique findings revealed numerous novel circRNAs, non-canonical isoforms of known circRNAs, circRNAs altered in cancer metastasis, and candidates that encode small peptides. Overall, this research will improve existing computational methods for circRNA detection and provide valuable resources for future research of circRNAs in tumor biology.

ORGANISM(S): Homo sapiens

PROVIDER: GSE250483 | GEO | 2025/11/12

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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Discovery of novel circular RNAs through integration of short- and long-read RNA sequencing

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