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Li XC, Tang ZD, Peng L, Li YY, Qian FC, Zhao JM, Ding LW, Du XJ, Li M, Zhang J, Bai XF, Zhu J, Feng CC, Wang QY, Pan J, Li CQ. Integrative Epigenomic Analysis of Transcriptional Regulation of Human CircRNAs. Front Genet 2021; 11:590672. [PMID: 33569079 PMCID: PMC7868561 DOI: 10.3389/fgene.2020.590672] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 12/02/2020] [Indexed: 12/25/2022] Open
Abstract
Circular RNAs (circRNAs) are evolutionarily conserved and abundant non-coding RNAs whose functions and regulatory mechanisms remain largely unknown. Here, we identify and characterize an epigenomically distinct group of circRNAs (TAH-circRNAs), which are transcribed to a higher level than their host genes. By integrative analysis of cistromic and transcriptomic data, we find that compared with other circRNAs, TAH-circRNAs are expressed more abundantly and have more transcription factors (TFs) binding sites and lower DNA methylation levels. Concordantly, TAH-circRNAs are enriched in open and active chromatin regions. Importantly, ChIA-PET results showed that 23–52% of transcription start sites (TSSs) of TAH-circRNAs have direct interactions with cis-regulatory regions, strongly suggesting their independent transcriptional regulation from host genes. In addition, we characterize molecular features of super-enhancer-driven circRNAs in cancer biology. Together, this study comprehensively analyzes epigenomic characteristics of circRNAs and identifies a distinct group of TAH-circRNAs that are independently transcribed via enhancers and super-enhancers by TFs. These findings substantially advance our understanding of the regulatory mechanism of circRNAs and may have important implications for future investigations of this class of non-coding RNAs.
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Affiliation(s)
- Xue-Cang Li
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Zhi-Dong Tang
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Li Peng
- Guangdong Province Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yan-Yu Li
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Feng-Cui Qian
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Jian-Mei Zhao
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Ling-Wen Ding
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Xiao-Juan Du
- The 942 Hospital of Joint Logistic Support Force of PLA, Yinchuan, China
| | - Meng Li
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Jian Zhang
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Xue-Feng Bai
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Jiang Zhu
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Chen-Chen Feng
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Qiu-Yu Wang
- School of Medical Informatics, Harbin Medical University, Daqing, China
| | - Jian Pan
- Department of Hematology and Oncology, Children's Hospital of Soochow University, Suzhou, China
| | - Chun-Quan Li
- School of Medical Informatics, Harbin Medical University, Daqing, China
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