Cancer-associated dynamics and potential regulators of intronic polyadenylation revealed by IPAFinder using standard RNA-seq data
- Zhaozhao Zhao1,
- Qiushi Xu1,
- Ran Wei1,
- Weixu Wang1,
- Dong Ding1,
- Yu Yang1,
- Jun Yao1,
- Liye Zhang2,
- Yue-Qing Hu3,
- Gang Wei1 and
- Ting Ni1
- 1State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai 200438, P.R. China;
- 2School of Life Science and Technology, ShanghaiTech University, Shanghai 200438, P.R. China;
- 3State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200438, P.R. China
Abstract
Intronic polyadenylation (IpA) usually leads to changes in the coding region of an mRNA, and its implication in diseases has been recognized, although at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2. Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m6A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.271627.120.
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Freely available online through the Genome Research Open Access option.
- Received September 23, 2020.
- Accepted August 31, 2021.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
