Biology

InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data

X. Liu, H. Chen, et al.

Discover InPACT, the groundbreaking computational method that accurately characterizes intronic polyadenylation (IPA) from RNA-seq data, revealed by our talented team of researchers including Xiaochuan Liu, Hao Chen, Zekun Li, and others. This innovative approach uncovers numerous unannotated IPA transcripts, highlights temporally coordinated IPA events during monocyte activation, and identifies context-specific IPA isoforms in fetal bone marrow single-cell RNA-seq data.

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Abstract

Intronic polyadenylation (IPA), a form of alternative polyadenylation, plays a role in various biological processes and diseases. This paper introduces InPACT, a computational method to accurately characterize IPA from RNA-seq data. InPACT identifies numerous unannotated IPA transcripts, many of which are translated. It outperforms existing methods and reveals temporally coordinated IPA events during monocyte activation and context-specific IPA isoforms in fetal bone marrow single-cell RNA-seq data.

Publisher

Nature Communications

Published On

Mar 22, 2024

Authors

Xiaochuan Liu, Hao Chen, Zekun Li, Xiaoxiao Yang, Wen Jin, Yuting Wang, Jian Zheng, Long Li, Chenghao Xuan, Jiapei Yuan, Yang Yang

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