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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Bioinformatics
Volume 15 - 2024 |
doi: 10.3389/fpls.2024.1437118
Dynamics of alternative polyadenylation in single root cells of Arabidopsis thaliana
Provisionally accepted- 1 Soochow University, Suzhou, Jiangsu Province, China
- 2 China Nuclear Power Operation Technology Corporation, Wuhan, Hubei Province, China
Single-cell RNA-seq (scRNA-seq) technologies have been widely used to reveal the diversity and complexity of cells, and pioneering studies on scRNA-seq in plants began to emerge since 2019. However, existing studies on plants utilized scRNA-seq focused only on the gene expression regulation, and there is still a lack of research with single-cell resolution on the transcript-isoform level. As an essential post-transcriptional mechanism for regulating gene expression, alternative polyadenylation (APA) generates diverse mRNA isoforms with distinct 3′ ends through the selective use of different polyadenylation sites in a gene. APA plays important roles in regulating multiple developmental processes in plants, such as flowering time and stress response. In this study, we comprehensively compiled a single-cell APA atlas from five scRNA-seq studies, covering over 150,000 cells spanning four major tissue branches, twelve cell types, and three developmental stages. High-confidence poly(A) sites in single root cells were identified and quantified. Moreover, three kinds of APA markers were identified for exploring APA dynamics in single cells, including differentially expressed poly(A) sites based on APA site expression, APA markers based on APA usages, and APA switching genes based on 3′ UTR (untranslated region) length change. By integrating both the APA information and the gene expression profile, cell type annotations of single root cells were refined. This study reveals that APA provides an additional layer of information for determining cell identity and provides a landscape of APA dynamics during Arabidopsis root development.
Keywords: alternative polyadenylation, single-cell RNA-seq, root development, RNA processing, Bioinformatics & Computational Biology
Received: 23 May 2024; Accepted: 02 Sep 2024.
Copyright: © 2024 Bi, Sheng, Liu and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaohui Wu, Soochow University, Suzhou, 215000, Jiangsu Province, China
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