Unknown,Transcriptomics,Genomics,Proteomics

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An improved method for identifying biological circular RNAs

ABSTRACT: 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

ORGANISM(S): Mus musculus

SUBMITTER: Wei Yan

PROVIDER: E-GEOD-83992 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The pervasive expression of circular RNA from protein coding loci is a recently discovered feature of many eukaryotic gene expression programs. Computational methods to discover and quantify circular RNA are essential to the study of the mechanisms of circular RNA biogenesis and potential functional roles they may play. In this paper, we present a new statistical algorithm that increases the sensitivity and specificity of circular RNA detection.by discovering and quantifying circular and linear RNA splicing events at both annotated exon boundaries and in un-annotated regions of the genome Unlike previous approaches which rely on heuristics like read count and homology between exons predicted to be circularized to determine confidence in prediction of circular RNA expression, our algorithm is a statistical approach. We have used this algorithm to discover general induction of circular RNAs in many tissues during human fetal development. We find that some regions of the brain show marked enrichment for genes where circular RNA is the dominant isoform. Beyond this global trend, specific circular RNAs are tissue specifically induced during fetal development, including a circular isoform of NCX1 in the developing fetal heart that, by 20 weeks, is more highly expressed than the linear isoform as well as beta-actin. In addition, while the vast majority of circular RNA production occurs at canonical U2 (major spliceosome) splice sites, we find the first examples of developmentally induced circular RNAs processed by the U12 (minor) spliceosome, and an enriched propensity of U12 donors to splice into circular RNA at un-annotated, rather than annotated, exons. Together, our algorithm and its results suggest a potentially significant role for circular RNA in human development. 35 human fetal samples from 6 tissues (3 - 7 replicates per tissue) collected between 10 and 20 weeks gestational time were sequenced using Illumina TruSeq Stranded Total RNA with Ribo-Zero Gold sample prep kit.

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An improved method for identifying biological circular RNAs

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