Deconvolution of Expression for Nascent RNA sequencing data (DENR) highlights pre-RNA isoform diversity in human cells

Zhao, Yixin, Dukler, Noah, Barshad, Gilad, Toneyan, Shushan, Danko, Charles G, Siepel, Adam (August 2021) Deconvolution of Expression for Nascent RNA sequencing data (DENR) highlights pre-RNA isoform diversity in human cells. Bioinformatics. ISSN 1367-4803

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Abstract

MOTIVATION: Quantification of isoform abundance has been extensively studied at the mature-RNA level using RNA-seq but not at the level of precursor RNAs using nascent RNA sequencing. RESULTS: We address this problem with a new computational method called Deconvolution of Expression for Nascent RNA sequencing data (DENR), which models nascent RNA sequencing read counts as a mixture of user-provided isoforms. The baseline algorithm is enhanced by machine-learning predictions of active transcription start sites and an adjustment for the typical "shape profile" of read counts along a transcription unit. We show that DENR outperforms simple read-count-based methods for estimating gene and isoform abundances, and that transcription of multiple pre-RNA isoforms per gene is widespread, with frequent differences between cell types. In addition, we provide evidence that a majority of human isoform diversity derives from primary transcription rather than from post-transcriptional processes. AVAILABILITY: DENR and nascentRNASim are freely available at https://github.com/CshlSiepelLab/DENR (version v1.0.0) and https://github.com/CshlSiepelLab/nascentRNASim (version v0.3.0). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Item Type:	Paper
Subjects:	bioinformatics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics bioinformatics > computational biology
CSHL Authors:	Zhao, Yixin Dukler, Noah Siepel, Adam Toneyan, Shushan
Communities:	CSHL labs > Koo Lab CSHL labs > Siepel lab School of Biological Sciences > Publications
SWORD Depositor:	CSHL Elements
Depositing User:	CSHL Elements
Date:	11 August 2021
Date Deposited:	18 Aug 2021 13:35
Last Modified:	29 Feb 2024 18:18
PMCID:	PMC8665767
URI:	https://repository.cshl.edu/id/eprint/40327

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