Abstract
Circular RNAs (circRNAs) are a vast class of covalently closed, noncoding RNAs expressed in specific tissues and developmental stages. The molecular, cellular, and pathophysiologic roles of circRNAs are not fully known, but their impact on gene expression programs is beginning to emerge, as circRNAs often associate with RNA-binding proteins and nucleic acids. With rising interest in identifying circRNAs associated with disease processes, it has become particularly important to identify circRNAs in RNA sequencing (RNA-seq) datasets, either generated by the investigator or reported in the literature. Here, we present a methodology to identify and analyze circRNAs in RNA-seq datasets, including those archived in repositories. We elaborate on the unique features of circRNAs that require specialized attention in RNA-seq datasets, the software packages designed for circRNA identification, the ongoing efforts to reconstruct the body of circRNAs starting from unique circularizing junctions, and the interacting factors that can be proposed from putative circRNA body sequences. We discuss the advantages and limitations of the current approaches for high-throughput circRNA analysis from RNA-sequencing datasets and identify areas that would benefit from the development of superior bioinformatic tools.
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This work was supported in full by the National Institute on Aging Intramural Research Program, National Institutes of Health.
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Cochran, K.R., Gorospe, M., De, S. (2022). Bioinformatic Analysis of CircRNA from RNA-seq Datasets. In: Cortassa, S., Aon, M.A. (eds) Computational Systems Biology in Medicine and Biotechnology. Methods in Molecular Biology, vol 2399. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1831-8_2
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DOI: https://doi.org/10.1007/978-1-0716-1831-8_2
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