Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification

ABSTRACT RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely cent...

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Autor principal:	Taylor Reiter
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	prokaryote software transcriptomics Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/772217c05ce743bd83fea033122e0091
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spelling	oai:doaj.org-article:772217c05ce743bd83fea033122e00912021-12-02T19:36:37ZCaught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification10.1128/mSystems.01256-202379-5077https://doaj.org/article/772217c05ce743bd83fea033122e00912021-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.01256-20https://doaj.org/toc/2379-5077ABSTRACT RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely centered around the human transcriptome. While eukaryotic and prokaryotic transcriptomes are similar, key differences in transcribed units limit the transfer of wet-lab and computational tools between the two domains. The article by M. Chung, R. S. Adkins, J. S. A. Mattick, K. R. Bradwell, et al. (mSystems 6:e00917-20, 2021, https://doi.org/10.1128/mSystems.00917-20), demonstrates that integrating prokaryote-specific strategies into existing RNA-seq analyses improves read quantification. Unlike in eukaryotes, polycistronic transcripts derived from operons lead to sequencing reads that span multiple neighboring genes. Chung et al. introduce FADU, a software tool that performs a correction for such reads and thereby improves read quantification and biological interpretation of prokaryotic RNA sequencing.Taylor ReiterAmerican Society for MicrobiologyarticleprokaryotesoftwaretranscriptomicsMicrobiologyQR1-502ENmSystems, Vol 6, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	prokaryote software transcriptomics Microbiology QR1-502
spellingShingle	prokaryote software transcriptomics Microbiology QR1-502 Taylor Reiter Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
description	ABSTRACT RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely centered around the human transcriptome. While eukaryotic and prokaryotic transcriptomes are similar, key differences in transcribed units limit the transfer of wet-lab and computational tools between the two domains. The article by M. Chung, R. S. Adkins, J. S. A. Mattick, K. R. Bradwell, et al. (mSystems 6:e00917-20, 2021, https://doi.org/10.1128/mSystems.00917-20), demonstrates that integrating prokaryote-specific strategies into existing RNA-seq analyses improves read quantification. Unlike in eukaryotes, polycistronic transcripts derived from operons lead to sequencing reads that span multiple neighboring genes. Chung et al. introduce FADU, a software tool that performs a correction for such reads and thereby improves read quantification and biological interpretation of prokaryotic RNA sequencing.
format	article
author	Taylor Reiter
author_facet	Taylor Reiter
author_sort	Taylor Reiter
title	Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
title_short	Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
title_full	Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
title_fullStr	Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
title_full_unstemmed	Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification
title_sort	caught between two genes: accounting for operonic gene structure improves prokaryotic rna sequencing quantification
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/772217c05ce743bd83fea033122e0091
work_keys_str_mv	AT taylorreiter caughtbetweentwogenesaccountingforoperonicgenestructureimprovesprokaryoticrnasequencingquantification
_version_	1718376388088561664

Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification

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