Literature DB >> 34183130

TRENDseq-A highly multiplexed high throughput RNA 3' end sequencing for mapping alternative polyadenylation.

Anton Ogorodnikov1, Sven Danckwardt2.   

Abstract

Alternative polyadenylation (APA) is a widespread and highly dynamic mechanism of gene regulation. It affects more than 70% of all genes, resulting in transcript isoforms with distinct 3' end termini. APA thereby considerably expands the diversity of the transcriptome 3' end (TREND). This leads to mRNA isoforms with profoundly different physiological effects, by affecting protein output, production of distinct protein isoforms, or modulating protein localization. APA is globally regulated in various conditions, including developmental and adaptive programs. Since perturbations of APA can disrupt biological processes, ultimately resulting in most devastating disorders, querying the APA landscape is crucial to decipher underlying mechanisms, resulting consequences and potential diagnostic and therapeutic implications. Here we provide a detailed step-by-step protocol for TRENDseq, a method for transcriptome-wide high-throughput sequencing of polyadenylated RNA 3' ends in a highly multiplexed fashion. TRENDseq exploits linear amplification of the starting material to improve sensitivity while significantly reducing the amount of input material. It thereby represents a powerful tool to study APA in numerous experimental set-ups and/or limited human samples in a highly multiplexed and reproducible manner.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alternative polyadenylation (APA); Cleavage and polyadenylation; RNA processing; Transcriptome diversity

Year:  2021        PMID: 34183130     DOI: 10.1016/bs.mie.2021.03.022

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  2 in total

Review 1.  The Bidirectional Link Between RNA Cleavage and Polyadenylation and Genome Stability: Recent Insights From a Systematic Screen.

Authors:  Stefano Spada; Brian Luke; Sven Danckwardt
Journal:  Front Genet       Date:  2022-04-28       Impact factor: 4.772

2.  APAview: A web-based platform for alternative polyadenylation analyses in hematological cancers.

Authors:  Xi Hu; Jialin Song; Jacqueline Chyr; Jinping Wan; Xiaoyan Wang; Jianqiang Du; Junbo Duan; Huqin Zhang; Xiaobo Zhou; Xiaoming Wu
Journal:  Front Genet       Date:  2022-08-12       Impact factor: 4.772

  2 in total

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