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Luminal subtype-specific circRNAs in breast cancer cells by a novel tool for external data analysis.

ABSTRACT: Circular RNAs are molecules present in all eukaryotes that are generated from a large number of genes by a particular processing of transcripts. We have exploited poly(A-) RNA-Seq data generated in our lab in MCF-7 breast cancer cells to define a compilation of exonic circRNAs more comprehensive than previously existing lists. Development of novel computational algorithms allowed us to quantitatively evaluate expression of these circRNA also in publicly available data. We report here novel findings with important implications both for circRNA biogenesis and as specific markers for breast cancer. We observed and confirmed by ChIP analysis that exons involved in circularization events display significantly higher levels of the histone post-transcriptional modification H3K36me3 than non-circularizing exons. This suggests a clear link with a published alternative splicing mechanism in the circRNA biogenesis mechanism. We also found that circRNAs contain an unexpectedly elevated number of Ago binding sites, revamping the hypothesis of circRNAs acting as miRNA sponges in some cases. Finally, we report that a subset of MCF-7 circRNAs are specific to tumor versus normal tissue, while others can differentiate the Luminal tumor subtype, thus suggesting that circRNAs can be exploited as novel biomarkers and drug targets for breast cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE101410 | GEO | 2018/02/15

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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Luminal subtype-specific circRNAs in breast cancer cells by a novel tool for external data analysis.

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