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Structured elements drive circular RNA translation and expand the human proteome, part3

ABSTRACT: The human genome encodes tens of thousands circular RNAs (circRNAs) whose levels correlate with many disease states. While studies have focused on the non-coding functions of circRNAs, emerging evidence suggests that a handful of circRNAs encode proteins. Translation canonically starts by recognition of mRNA 5â€™cap and scanning to the start codon; how circRNA translation initiates remains unclear. Here, we developed a high-throughput screen to systematically identify and quantify RNA sequences that can direct circRNA translation. We identify and validate over 17,000 circRNA internal ribosome entry sites (IRES) and reveal that 18S rRNA complementarity and a structured RNA element on the IRES are important for facilitating circRNA cap-independent translation. With genomic and peptidomic analyses of the IRES, we identified nearly 1,000 putative endogenous protein-coding circRNAs and hundreds of translational units encoded by these circRNAs. We further characterized circFGFR1p, a protein encoded by circFGFR1, functions as a negative regulator of FGFR1 to suppress cell growth under stress conditions. The circRNA proteome may be important links among circRNA, biological control, and disease.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Leukocyte, Lung, Epithelial Cell, Bone, Bone Marrow

DISEASE(S): Bone Osteosarcoma,Chronic Myeloid Leukemia,Non-small Cell Lung Carcinoma

SUBMITTER: Janos Demeter

LAB HEAD: Peter K. Jackson

PROVIDER: PXD025233 | Pride | 2021-08-25

REPOSITORIES: Pride

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			Action	DRS
	200110_MS058_H358_KEAP1-4_Frac1_Slot1-46_1_2574.d.7z	Other
	200110_MS058_H358_KEAP1-4_Frac1_Slot1-46_1_2574.d_20201018_Byonic_1_.mgf	Mgf
	200110_MS058_H358_KEAP1-4_Frac1_Slot1-46_1_2574.d_20201018_Byonic_1_.mzid.gz	Mzid
	200110_MS058_H358_KEAP1-4_Frac1_Slot1-46_1_2574.d_20201018_Byonic_1_.xlsx	Xlsx
	200110_MS058_H358_KEAP1-4_Frac2_Slot1-47_1_2575.d.7z	Other

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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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Structured elements drive circular RNA translation and expand the human proteome, part3

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