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Review
. 2021 Mar 19:12:665233.
doi: 10.3389/fgene.2021.665233. eCollection 2021.

Advances in the Identification of Circular RNAs and Research Into circRNAs in Human Diseases

Shihu Jiao  1   2 , Song Wu  3 , Shan Huang  4 , Mingyang Liu  5 , Bo Gao  6
Affiliations
Review

Advances in the Identification of Circular RNAs and Research Into circRNAs in Human Diseases

Shihu Jiao et al. Front Genet. .

Abstract

Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs (ncRNAs) with a closed-loop structure that are mainly produced by variable processing of precursor mRNAs (pre-mRNAs). They are widely present in all eukaryotes and are very stable. Currently, circRNA studies have become a hotspot in RNA research. It has been reported that circRNAs constitute a significant proportion of transcript expression, and some are significantly more abundantly expressed than other transcripts. CircRNAs have regulatory roles in gene expression and critical biological functions in the development of organisms, such as acting as microRNA sponges or as endogenous RNAs and biomarkers. As such, they may have useful functions in the diagnosis and treatment of diseases. CircRNAs have been found to play an important role in the development of several diseases, including atherosclerosis, neurological disorders, diabetes, and cancer. In this paper, we review the status of circRNA research, describe circRNA-related databases and the identification of circRNAs, discuss the role of circRNAs in human diseases such as colon cancer, atherosclerosis, and gastric cancer, and identify remaining research questions related to circRNAs.

Keywords: circRNAs; circRNAs identification; database; diseases; machine learning.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Formation of circRNAs by (a) exon skipping, (b) direct back-splicing, (c) formation by RNA-binding proteins (RBPs), and (d) circular intron RNA cyclization.
FIGURE 2
FIGURE 2
Methodology for predicting circRNAs based on machine learning methods.
See this image and copyright information in PMC

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