Transcriptome dataset of Bacillus subtilis 168 cultivated in LB medium

Useful as a prolific secretor of enzymes in biotechnology, <i>Bacillus subtilis</i> is also an important microbial chassis for metabolic engineering applications where the goal is to over-produce a particular metabolite through carefully choreographed modulation of gene expression. But, the bedrock of metabolic engineering remains a thorough understanding of cell metabolism under differing stress and nutritional conditions, which provides the necessary inputs for formulating ideas on how modulation of gene expression could direct metabolic flux towards the target compound. To do this, transcriptome analysis has become an enabling tool for understanding differential gene expression in cells. In this work, the experimentally obtained RNA-seq transcriptome of <i>Bacillus subtilis</i> 168 grown in LB medium (Array Express accession number E-GEOD-74926) was analyzed by an in-house MATLAB software for determining the relative expression levels of all genes in the organism at the global level. Specifically, the dataset is a culmination of analyzing 0.4 million reads in the transcriptome analysis, where each read that aligned to a particular gene sequence of <i>B. subtilis</i> 168 was counted. Aggregating over all reads across the entire genome, the transcriptomic picture that emerges portrait a set of highly expressed genes comprising <i>dnaA, gyrB, dnaN, recF, gyrA, guaB, dacA, yaaC, pdxS, </i>and <i>sleL</i>. Overall, RNA-seq transcriptomics provides useful fundamental information on gene expression under varied conditions, which constitutes the basis on which hypothesis could be formulated to help direct flux to particular nodes and metabolites in metabolic engineering applications. Being a biotechnology workhorse, the current transcriptome dataset of <i>B. subtilis</i> 168 in rich LB medium should serve as a useful resource for researchers in both fundamental and applied biology fields. <br><br>