A Computational Pipeline To Infer Alternative Poly-Adenylation From 3′ Sequencing Data

Authors

Hari Krishna Yalamanchili
Nathan D Elrod
Madeline K Jensen
Ping Ji
Ai Lin
Eric J Wagner
Zhandong Liu

Publication Date

1-1-2021

Journal

Methods in Enzymology

DOI

10.1016/bs.mie.2021.04.001

PMID

34183121

PMCID

PMC10866047

PubMedCentral® Posted Date

2-14-2024

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes

Keywords

3' Untranslated Regions, Poly A, Polyadenylation, RNA, Messenger, Sequence Analysis, RNA

Abstract

An increasing number of investigations have established alternative polyadenylation (APA) as a key mechanism of gene regulation through altering the length of 3' untranslated region (UTR) and generating distinct mRNA termini. Further, appreciation for the significance of APA in disease contexts propelled the development of several 3' sequencing techniques. While these RNA sequencing technologies have advanced APA analysis, the intrinsic limitation of 3' read coverage and lack of appropriate computational tools constrain precise mapping and quantification of polyadenylation sites. Notably, Poly(A)-ClickSeq (PAC-seq) overcomes limiting factors such as poly(A) enrichment and 3' linker ligation steps using click-chemistry. Here we provide an updated PolyA-miner protocol, a computational approach to analyze PAC-seq or other 3'-Seq datasets. As a key practical constraint, we also provide a detailed account on the impact of sequencing depth on the number of detected polyadenylation sites and APA changes. This protocol is also updated to handle unique molecular identifiers used to address PCR duplication potentially observed in PAC-seq.