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Comprehensive analysis of circRNA expression profiles in humans by RAISE

Circular RNAs (circRNAs) are pervasively expressed circles of non-coding RNAs. Even though many circRNAs have been reported in humans, their expression patterns and functions remain poorly understood. In this study, we employed a pipeline named RAISE to detect circRNAs in RNA-seq data. RAISE can ful...

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Autores principales: Li, Lin, Zheng, Yong-Chang, Kayani, Masood Ur Rehman, Xu, Wen, Wang, Guan-Qun, Sun, Pei, Ao, Ning, Zhang, Li-Na, Gu, Zhao-Qi, Wu, Liang-Cai, Zhao, Hai-Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673025/
https://www.ncbi.nlm.nih.gov/pubmed/29039477
http://dx.doi.org/10.3892/ijo.2017.4162
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author Li, Lin
Zheng, Yong-Chang
Kayani, Masood Ur Rehman
Xu, Wen
Wang, Guan-Qun
Sun, Pei
Ao, Ning
Zhang, Li-Na
Gu, Zhao-Qi
Wu, Liang-Cai
Zhao, Hai-Tao
author_facet Li, Lin
Zheng, Yong-Chang
Kayani, Masood Ur Rehman
Xu, Wen
Wang, Guan-Qun
Sun, Pei
Ao, Ning
Zhang, Li-Na
Gu, Zhao-Qi
Wu, Liang-Cai
Zhao, Hai-Tao
author_sort Li, Lin
collection PubMed
description Circular RNAs (circRNAs) are pervasively expressed circles of non-coding RNAs. Even though many circRNAs have been reported in humans, their expression patterns and functions remain poorly understood. In this study, we employed a pipeline named RAISE to detect circRNAs in RNA-seq data. RAISE can fully characterize circRNA structure and abundance. We evaluated inter-individual variations in circRNA expression in humans by applying this pipeline to numerous non-poly(A)-selected RNA-seq data. We identified 59,128 circRNA candidates in 61 human liver samples, with almost no overlap in the circRNA of the recruited samples. Approximately 89% of the circRNAs were detected in one or two samples. In comparison, 10% of the linear mRNAs and non-coding RNAs were detected in each sample. We estimated the variation in other tissues, especially the circRNA high-abundance tissues, in advance. Only 0.5% of the 50,631 brain circRNA candidates were shared among the 30 recruited brain samples, which is similar to the proportion in liver. Moreover, we found inter- and intra-individual diversity in circRNAs expression in the granulocyte RNA-seq data from seven individuals sampled 3 times at one-month intervals. Our findings suggest that careful consideration of inter-individual diversity is required when extensively identifying human circRNAs or proposing their use as potential biomarkers and therapeutic targets in disease.
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spelling pubmed-56730252017-11-16 Comprehensive analysis of circRNA expression profiles in humans by RAISE Li, Lin Zheng, Yong-Chang Kayani, Masood Ur Rehman Xu, Wen Wang, Guan-Qun Sun, Pei Ao, Ning Zhang, Li-Na Gu, Zhao-Qi Wu, Liang-Cai Zhao, Hai-Tao Int J Oncol Articles Circular RNAs (circRNAs) are pervasively expressed circles of non-coding RNAs. Even though many circRNAs have been reported in humans, their expression patterns and functions remain poorly understood. In this study, we employed a pipeline named RAISE to detect circRNAs in RNA-seq data. RAISE can fully characterize circRNA structure and abundance. We evaluated inter-individual variations in circRNA expression in humans by applying this pipeline to numerous non-poly(A)-selected RNA-seq data. We identified 59,128 circRNA candidates in 61 human liver samples, with almost no overlap in the circRNA of the recruited samples. Approximately 89% of the circRNAs were detected in one or two samples. In comparison, 10% of the linear mRNAs and non-coding RNAs were detected in each sample. We estimated the variation in other tissues, especially the circRNA high-abundance tissues, in advance. Only 0.5% of the 50,631 brain circRNA candidates were shared among the 30 recruited brain samples, which is similar to the proportion in liver. Moreover, we found inter- and intra-individual diversity in circRNAs expression in the granulocyte RNA-seq data from seven individuals sampled 3 times at one-month intervals. Our findings suggest that careful consideration of inter-individual diversity is required when extensively identifying human circRNAs or proposing their use as potential biomarkers and therapeutic targets in disease. D.A. Spandidos 2017-10-16 /pmc/articles/PMC5673025/ /pubmed/29039477 http://dx.doi.org/10.3892/ijo.2017.4162 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Li, Lin
Zheng, Yong-Chang
Kayani, Masood Ur Rehman
Xu, Wen
Wang, Guan-Qun
Sun, Pei
Ao, Ning
Zhang, Li-Na
Gu, Zhao-Qi
Wu, Liang-Cai
Zhao, Hai-Tao
Comprehensive analysis of circRNA expression profiles in humans by RAISE
title Comprehensive analysis of circRNA expression profiles in humans by RAISE
title_full Comprehensive analysis of circRNA expression profiles in humans by RAISE
title_fullStr Comprehensive analysis of circRNA expression profiles in humans by RAISE
title_full_unstemmed Comprehensive analysis of circRNA expression profiles in humans by RAISE
title_short Comprehensive analysis of circRNA expression profiles in humans by RAISE
title_sort comprehensive analysis of circrna expression profiles in humans by raise
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673025/
https://www.ncbi.nlm.nih.gov/pubmed/29039477
http://dx.doi.org/10.3892/ijo.2017.4162
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