Circular RNAs (circRNAs), an abundant class of noncoding RNAs in higher eukaryotes, are generated from pre-mRNAs by circularization of adjacent exons. Using a set of 15 circRNAs, we demonstrated their cell-type-specific expression and circular versus linear processing in mammalian cells. Northern blot analysis combined with RNase H cleavage conclusively proved a circular configuration for two examples, LPAR1 and HIPK3. To address the circularization mechanism, we analyzed the sequence requirements using minigenes derived from natural circRNAs. Both canonical splice sites are required for circularization, although they vary in flexibility and potential use of cryptic sites. Surprisingly, we found that no specific circRNA exon sequence is necessary and that potential flanking intron structures can modulate circularization efficiency. In combination with splice inhibitor assays, our results argue that the canonical spliceosomal machinery functions in circRNA biogenesis, constituting an alternative splicing mode.
Circular RNAs (circRNAs) are a novel class of noncoding RNAs present in all eukaryotic cells investigated so far and generated by a special mode of alternative splicing of pre-mRNAs. Thereby, single exons, or multiple adjacent and spliced exons, are released in a circular form. CircRNAs are cell-type specifically expressed, are unusually stable, and can be found in various body fluids such as blood and saliva. Here we analysed circRNAs and the corresponding linear splice isoforms from human platelets, where circRNAs are particularly abundant, compared with other hematopoietic cell types. In addition, we isolated extracellular vesicles from purified and in vitro activated human platelets, using density-gradient centrifugation, followed by RNA-seq analysis for circRNA detection. We could demonstrate that circRNAs are packaged and released within both types of vesicles (microvesicles and exosomes) derived from platelets. Interestingly, we observed a selective release of circRNAs into the vesicles, suggesting a specific sorting mechanism. In sum, circRNAs represent yet another class of extracellular RNAs that circulate in the body and may be involved in signalling pathways. Since platelets are essential for central physiological processes such as haemostasis, wound healing, inflammation and cancer metastasis, these findings should greatly extend the potential of circRNAs as prognostic and diagnostic biomarkers.
Circular RNAs (circRNAs) constitute a new class of noncoding RNAs in higher eukaryotes generated from pre-mRNAs by alternative splicing. Here we investigated in mammalian cells the association of circRNAs with proteins. Using glycerol gradient centrifugation, we characterized in cell lysates circRNA-protein complexes (circRNPs) of distinct sizes. By polysome-gradient fractionation we found no evidence for efficient translation of a set of abundant circRNAs in HeLa cells. To identify circRNPs with a specific protein component, we focused on IMP3 (IGF2BP3, insulin-like growth factor 2 binding protein 3), a known tumor marker and RNA-binding protein. Combining RNA-seq analysis of IMP3-co-immunoprecipitated RNA and filtering for circular-junction reads identified a set of IMP3-associated circRNAs, which were validated and characterized. In sum, our data suggest that specific circRNP families exist defined by a common protein component. In addition, this provides a general approach to identify circRNPs with a given protein component.
How multidomain RNA-binding proteins recognize their specific target sequences, based on a combinatorial code, represents a fundamental unsolved question and has not been studied systematically so far. Here we focus on a prototypical multidomain RNA-binding protein, IMP3 (also called IGF2BP3), which contains six RNA-binding domains (RBDs): four KH and two RRM domains. We establish an integrative systematic strategy, combining single-domain-resolved SELEX-seq, motif-spacing analyses, in vivo iCLIP, functional validation assays, and structural biology. This approach identifies the RNA-binding specificity and RNP topology of IMP3, involving all six RBDs and a cluster of up to five distinct and appropriately spaced CA-rich and GGC-core RNA elements, covering a >100 nucleotide-long target RNA region. Our generally applicable approach explains both specificity and flexibility of IMP3-RNA recognition, allows the prediction of IMP3 targets, and provides a paradigm for the function of multivalent interactions with multidomain RNA-binding proteins in gene regulation.
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