Experimental and Computational Workflow for RNA Sequencing in Mycobacterium tuberculosis : From Total RNA to Differentially Expressed Genes.
Methods in molecular biology (Clifton, N.J.)(2021)
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.
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Key words
Differential gene expression calculation,FASTQ alignment,Gene expression quantification,Illumina sequencing,RNA sequencing,Sequencing data processing,Sequencing library preparation,rRNA depletion
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