Literature DB >> 34235667

Experimental and Computational Workflow for RNA Sequencing in Mycobacterium tuberculosis : From Total RNA to Differentially Expressed Genes.

Shuyi Ma1, Richard M Jones1, Natalie S Gleason1, Jessica Farrow-Johnson1, David R Sherman2.   

Abstract

RNA sequencing (RNAseq) in bacteria has become a transformative tool for many applications, including the identification of mechanisms that contribute to pathogenesis, environmental adaptation, and drug response. The kinds of analysis outputs achievable from RNA-seq depend heavily on several key technical parameters during the sample preparation, sequencing, and data processing steps. In this chapter, we will describe the process of preparing Mycobacterium tuberculosis samples into sequencing libraries, selecting the appropriate sequencing platform, and performing data processing compatible with gene expression quantification. We will also discuss how each parameter could affect outcomes. The protocols described below produce consistently high yields. This chapter should inform on the technical considerations that impact sequencing output and enable the reader to decide on the best parameters to implement based on their own experimental goals.

Entities:  

Keywords:  Differential gene expression calculation; FASTQ alignment; Gene expression quantification; Illumina sequencing; RNA sequencing; Sequencing data processing; Sequencing library preparation; rRNA depletion

Year:  2021        PMID: 34235667     DOI: 10.1007/978-1-0716-1460-0_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  19 in total

Review 1.  RNA sequencing: the teenage years.

Authors:  Rory Stark; Marta Grzelak; James Hadfield
Journal:  Nat Rev Genet       Date:  2019-07-24       Impact factor: 53.242

Review 2.  Orchestrating high-throughput genomic analysis with Bioconductor.

Authors:  Wolfgang Huber; Vincent J Carey; Robert Gentleman; Simon Anders; Marc Carlson; Benilton S Carvalho; Hector Corrada Bravo; Sean Davis; Laurent Gatto; Thomas Girke; Raphael Gottardo; Florian Hahne; Kasper D Hansen; Rafael A Irizarry; Michael Lawrence; Michael I Love; James MacDonald; Valerie Obenchain; Andrzej K Oleś; Hervé Pagès; Alejandro Reyes; Paul Shannon; Gordon K Smyth; Dan Tenenbaum; Levi Waldron; Martin Morgan
Journal:  Nat Methods       Date:  2015-02       Impact factor: 28.547

3.  Ligand binding and protein dynamics: a fluorescence depolarization study of aspartate transcarbamylase from Escherichia coli.

Authors:  C A Royer; P Tauc; G Hervé; J C Brochon
Journal:  Biochemistry       Date:  1987-10-06       Impact factor: 3.162

Review 4.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

Review 5.  Sequencing depth and coverage: key considerations in genomic analyses.

Authors:  David Sims; Ian Sudbery; Nicholas E Ilott; Andreas Heger; Chris P Ponting
Journal:  Nat Rev Genet       Date:  2014-02       Impact factor: 53.242

6.  How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

Authors:  Brian J Haas; Melissa Chin; Chad Nusbaum; Bruce W Birren; Jonathan Livny
Journal:  BMC Genomics       Date:  2012-12-27       Impact factor: 3.969

7.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Authors:  Michael I Love; Wolfgang Huber; Simon Anders
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

8.  The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update.

Authors:  Enis Afgan; Dannon Baker; Bérénice Batut; Marius van den Beek; Dave Bouvier; Martin Cech; John Chilton; Dave Clements; Nate Coraor; Björn A Grüning; Aysam Guerler; Jennifer Hillman-Jackson; Saskia Hiltemann; Vahid Jalili; Helena Rasche; Nicola Soranzo; Jeremy Goecks; James Taylor; Anton Nekrutenko; Daniel Blankenberg
Journal:  Nucleic Acids Res       Date:  2018-07-02       Impact factor: 16.971

Review 9.  Advanced Applications of RNA Sequencing and Challenges.

Authors:  Yixing Han; Shouguo Gao; Kathrin Muegge; Wei Zhang; Bing Zhou
Journal:  Bioinform Biol Insights       Date:  2015-11-15

Review 10.  A survey of best practices for RNA-seq data analysis.

Authors:  Ana Conesa; Pedro Madrigal; Sonia Tarazona; David Gomez-Cabrero; Alejandra Cervera; Andrew McPherson; Michał Wojciech Szcześniak; Daniel J Gaffney; Laura L Elo; Xuegong Zhang; Ali Mortazavi
Journal:  Genome Biol       Date:  2016-01-26       Impact factor: 13.583

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