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Expression profiling of circular RNAs in human islet samples

ABSTRACT: Expression profiling of circular RNAs in human islet samples

PROVIDER: PRJNA414628 | ENA |

REPOSITORIES: ENA

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Expression profiling of circular RNAs in human islet samples

Project description:There is already strong evidence indicating that different types of non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs, are key players in the regulation of β-cell functions and in the development of diabetes. However, the role of the newly discovered class of circular RNAs remains to be elucidated. We therefore analysed circular RNA expression in human islet samples.

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Microarray Profiling of Circular RNAs in Human Papillary Thyroid Carcinoma

Project description:Background: Non-coding circular RNAs (circRNAs) have displayed dysregulated expression in several human cancers. Here, we profiled the circRNA expression of papillary thyroid carcinoma (PTC) tumors to improve our understanding of PTC pathogenesis as well as to identify potential circRNA biomarkers for PTC.

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An improved method for identifying biological circular RNAs

Project description:Purpose: We are using the illumina sequencing to compare the false positive and true positive circular RNA findings to confine the method to detect the true circular RNAs Methods: The testis whole transcriptome profiling was generated from 4-week mouse testis using illumina Nextseq, duplicated. The sequence reads that passed quality filters were analyzed at the transcript isoform level with TopHat followed by Cufflinks. Results: our data suggest that circular RNAs identified based on junction sequences in the RNA-seq reads, especially those from Illumina Hiseq sequencing, mostly result from template-switching events during reverse transcription by MMLV-derived reverse transcriptases. It is critical to employ reverse transcriptases lacking terminal transferase activity (e.g., MonsterScript) to construct sequencing library or perform RT-PCR for identification and quantification of true circular RNAs. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. The wild type mouse testis RNAs were constructed NGS library by two different enzyme, then parallel sequenced in illumina Nextseq

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