Deconvolution of expression for nascent RNA-sequencing data (DENR) highlights pre-RNA isoform diversity in human cells.
Bioinformatics
; 37(24): 4727-4736, 2021 12 11.
Article
em En
| MEDLINE
| ID: mdl-34382072
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 AND IMPLEMENTATION 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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
RNA
/
Isoformas de RNA
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article