Dataset Information

Fcirc: A comprehensive pipeline for the exploration of fusion linear and circular RNAs.

ABSTRACT: BACKGROUND:In cancer cells, fusion genes can produce linear and chimeric fusion-circular RNAs (f-circRNAs), which are functional in gene expression regulation and implicated in malignant transformation, cancer progression, and therapeutic resistance. For specific cancers, proteins encoded by fusion transcripts have been identified as innovative therapeutic targets (e.g., EML4-ALK). Even though RNA sequencing (RNA-Seq) technologies combined with existing bioinformatics approaches have enabled researchers to systematically identify fusion transcripts, specifically detecting f-circRNAs in cells remains challenging owing to their general sparsity and low abundance in cancer cells but also owing to imperfect computational methods. RESULTS:We developed the Python-based workflow "Fcirc" to identify fusion linear and f-circRNAs from RNA-Seq data with high specificity. We applied Fcirc to 3 different types of RNA-Seq data scenarios: (i) actual synthetic spike-in RNA-Seq data, (ii) simulated RNA-Seq data, and (iii) actual cancer cell-derived RNA-Seq data. Fcirc showed significant advantages over existing methods regarding both detection accuracy (i.e., precision, recall, F-measure) and computing performance (i.e., lower runtimes). CONCLUSION:Fcirc is a powerful and comprehensive Python-based pipeline to identify linear and circular RNA transcripts from known fusion events in RNA-Seq datasets with higher accuracy and shorter computing times compared with previously published algorithms. Fcirc empowers the research community to study the biology of fusion RNAs in cancer more effectively.

SUBMITTER: Cai Z

PROVIDER: S-EPMC7259471 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Fcirc: A comprehensive pipeline for the exploration of fusion linear and circular RNAs.

Cai Zhaoqing Z Xue Hongzhang H Xu Yue Y Köhler Jens J Cheng Xiaojie X Dai Yao Y Zheng Jie J Wang Haiyun H

GigaScience 20200601 6

<h4>Background</h4>In cancer cells, fusion genes can produce linear and chimeric fusion-circular RNAs (f-circRNAs), which are functional in gene expression regulation and implicated in malignant transformation, cancer progression, and therapeutic resistance. For specific cancers, proteins encoded by fusion transcripts have been identified as innovative therapeutic targets (e.g., EML4-ALK). Even though RNA sequencing (RNA-Seq) technologies combined with existing bioinformatics approaches have ena ...[more]

PMID: 32470133

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Project description:BackgroundNon-co-linear (NCL) transcripts consist of exonic sequences that are topologically inconsistent with the reference genome in an intragenic fashion (circular or intragenic trans-spliced RNAs) or in an intergenic fashion (fusion or intergenic trans-spliced RNAs). On the basis of RNA-seq data, numerous NCL event detectors have been developed and detected thousands of NCL events in diverse species. However, there are great discrepancies in the identification results among detectors, indicating a considerable proportion of false positives in the detected NCL events. Although several helpful guidelines for evaluating the performance of NCL event detectors have been provided, a systematic guideline for measurement of NCL events identified by existing tools has not been available.ResultsWe develop a software, NCLcomparator, for systematically post-screening the intragenic or intergenic NCL events identified by various NCL detectors. NCLcomparator first examine whether the input NCL events are potentially false positives derived from ambiguous alignments (i.e., the NCL events have an alternative co-linear explanation or multiple matches against the reference genome). To evaluate the reliability of the identified NCL events, we define the NCL score (NCLscore) based on the variation in the number of supporting NCL junction reads identified by the tools examined. Of the input NCL events, we show that the ambiguous alignment-derived events have relatively lower NCLscore values than the other events, indicating that an NCL event with a higher NCLscore has a higher level of reliability. To help selecting highly expressed NCL events, NCLcomparator also provides a series of useful measurements such as the expression levels of the detected NCL events and their corresponding host genes and the junction usage of the co-linear splice junctions at both NCL donor and acceptor sites.ConclusionNCLcomparator provides useful guidelines, with the input of identified NCL events from various detectors and the corresponding paired-end RNA-seq data only, to help users selecting potentially high-confidence NCL events for further functional investigation. The software thus helps to facilitate future studies into NCL events, shedding light on the fundamental biology of this important but understudied class of transcripts. NCLcomparator is freely accessible at https://github.com/TreesLab/NCLcomparator .

Project description:RNA in milk exosomes can be absorbed in the mammalian intestinal tract and function in gene expression regulations. Our previous work demonstrated that porcine milk exosomes (PME) contain large amounts of miRNAs and mRNAs. Increasing evidence suggests that long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) are of particular interest, given their key role in diverse biological processes of animals. However, the expression profiles and the potential functions of lncRNAs and circRNAs in PME are still unknown. In the present study, we isolated PME by ultracentrifugation and performed a comprehensive analysis of lncRNA and circRNA in PME by using RNA sequencing. As a result, 2,466 novel lncRNAs, 809 annotated lncRNAs, and 61 circRNAs were identified in PME. The lncRNAs shared similar characteristics with other mammals in terms of length, exon number, and open reading frames. However, lncRNAs showed a higher level compared with mRNAs. Eight lncRNAs and five circRNAs in PME were selected for PCR identification. A functional enrichment analysis on the target genes of lncRNAs indicated that these genes were involved in cellular macromolecule metabolic, RNA metabolic, and immune processes. The circRNAs host genes were enriched in nucleic acid binding and adherence junction. We also evaluated the potential interaction targets between miRNAs and PME lncRNAs or circRNAs, and the results showed that the PME lncRNAs and the circRNAs have a high density of miRNA target sites. The top 20 highly expressed lncRNAs were found to interact with the proliferation-related miRNAs, and the circRNAs potentially targeted many miRNAs that are associated with the intestinal barrier. This study is the first to provide a resource for lncRNA and circRNA research of porcine milk. Moreover, the potential interaction between lncRNA/circRNA and miRNA is revealed. The present study expands our knowledge of non-coding RNAs in milk, and additional research is necessary to confirm their exactly physiological functions.

Dataset Information

Fcirc: A comprehensive pipeline for the exploration of fusion linear and circular RNAs.

Publications

Fcirc: A comprehensive pipeline for the exploration of fusion linear and circular RNAs.

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