InPACT : a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data
© 2024. The Author(s)..
Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
Nature communications - 15(2024), 1 vom: 22. März, Seite 2583 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Xiaochuan [VerfasserIn] |
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| Anmerkungen: |
Date Completed 25.03.2024 Date Revised 25.03.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1038/s41467-024-46875-8 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data | ||
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| 700 | 1 | |a Li, Zekun |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Xiaoxiao |e verfasserin |4 aut | |
| 700 | 1 | |a Jin, Wen |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yuting |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Jian |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Long |e verfasserin |4 aut | |
| 700 | 1 | |a Xuan, Chenghao |e verfasserin |4 aut | |
| 700 | 1 | |a Yuan, Jiapei |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Yang |e verfasserin |4 aut | |
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