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

ABSTRACT: 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.

SUBMITTER: Liu X

PROVIDER: S-EPMC10960005 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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

Liu Xiaochuan X Chen Hao H Li Zekun Z Yang Xiaoxiao X Jin Wen W Wang Yuting Y Zheng Jian J Li Long L Xuan Chenghao C Yuan Jiapei J Yang Yang Y

Nature communications 20240322 1

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 previous ...[more]

PMID: 38519498

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Project description:Herpesviruses employ extensive bidirectional transcription of overlapping genes to overcome length constraints on their gene product repertoire. As a consequence, many lytic transcripts cannot be measured individually by reverse transcription-quantitative PCR (RT-qPCR) or conventional RNA sequencing (RNA-seq) analysis. A. G. Bruce, S. Barcy, T. DiMaio, E. Gan, et al. (Pathogens 6:11, 2017, https://doi.org/10.3390/pathogens6010011) have proposed an approximation method using unique coding sequences (UCDS) to estimate lytic gene abundance from Kaposi's sarcoma-associated herpesvirus (KSHV) RNA-seq data. Although UCDS has been widely employed, its accuracy, to our knowledge, has never been rigorously validated for any herpesvirus. In this study, we use cap analysis of gene expression sequencing (CAGE-seq) as a gold-standard to determine the accuracy of UCDS for estimating Epstein-Barr virus (EBV) lytic gene expression levels from RNA-seq data. We also introduce the Unique TranScript (UTS) method, which, like UCDS, estimates transcript abundance from changes in mean RNA-seq read depth. UTS is distinguished by its use of empirically determined 5' and 3' transcript ends rather than coding sequence annotations. Compared to conventional read assignment, both UCDS and UTS improved the accuracy of quantitation of overlapping genes, with UTS giving the most-accurate results. The UTS method discards fewer reads and may be advantageous for experiments with less sequencing depth. UTS is compatible with any aligner and, unlike isoform-aware alignment methods, can be implemented on a laptop computer. Our findings demonstrate that the accuracy achieved by complex and expensive techniques such as CAGE-seq can be approximated using conventional short-read RNA-seq data when read assignment methods address transcript overlap. Although our study focuses on EBV transcription, the UTS method should be applicable across all herpesviruses as well as to other genomes with extensively overlapping transcriptomes. IMPORTANCE Many viruses employ extensively overlapping transcript structures. This complexity makes it difficult to quantify gene expression by using conventional methods, including RNA-seq. Although high-throughput techniques that overcome these limitations exist, they are complex, expensive, and scarce in the herpesvirus literature relative to short-read RNA-seq. Here, using Epstein-Barr virus (EBV) as a model, we demonstrate that conventional RNA-seq analysis methods fail to accurately quantify the abundances of many overlapping transcripts. We further show that the previously described Unique CoDing Sequence (UCDS) method and our Unique TranScript (UTS) method greatly improve the accuracy of EBV lytic gene measurements obtained from RNA-seq data. The UTS method has the advantages of discarding fewer reads and being implementable on a laptop computer. Although this study focuses on EBV, the UCDS and UTS methods should be applicable across herpesviruses and for other viruses that make extensive use of overlapping transcription.

Dataset Information

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

Publications

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

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