Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Detection of circRNA in Drosophila Fly heads and S2 cells using RNA-seq with or without RNaseR tretment

ABSTRACT: We determined circRNA abundance in fly Heads and S2 cells by generating and analyzing high-throughput RNA-sequencing libraries prepared from rRNA-depleted RNA. In order to determine whether the observed sequencing reads are due to bona fide circRNAs, we pre-treated the RNA with RNAse-R before the rRNA-depletion procedure. Indeed, most of the identified circRNAs were more enriched in comparison to the canonical mRNA isoforms following the RNAse-R treatment. We compare circRNA levels in wt (Canton S) flies with flies carrying the C4 ("slow polymerase") mutation. 4 samples of Drosophila Canton S and 4 samples of flies carrying the C4 ("slow polymerase") mutation. For each sample, one library was prepared from RNA after RNaseR treatment and the second from RNA with without treatment (mock). RNA library from one Canton Sample was used for stranded libray preprepation.

ORGANISM(S): Drosophila melanogaster

SUBMITTER: Sebastian Kadener

PROVIDER: E-GEOD-55872 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

circRNA biogenesis competes with pre-mRNA splicing.

Ashwal-Fluss Reut R Meyer Markus M Pamudurti Nagarjuna Reddy NR Ivanov Andranik A Bartok Osnat O Hanan Mor M Evantal Naveh N Memczak Sebastian S Rajewsky Nikolaus N Kadener Sebastian S

Molecular cell 20140918 1

Circular RNAs (circRNAs) are widely expressed noncoding RNAs. However, their biogenesis and possible functions are poorly understood. Here, by studying circRNAs that we identified in neuronal tissues, we provide evidence that animal circRNAs are generated cotranscriptionally and that their production rate is mainly determined by intronic sequences. We demonstrate that circularization and splicing compete against each other. These mechanisms are tissue specific and conserved in animals. Interesti ...[more]

PMID: 25242144

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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.

Dataset Information

Detection of circRNA in Drosophila Fly heads and S2 cells using RNA-seq with or without RNaseR tretment

Publications

circRNA biogenesis competes with pre-mRNA splicing.

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