Exploring Variability in Reads from Next Generation RNA-Sequencing Data
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Next generation RNA-sequencing (RNA-seq) technologies have revolutionized the study of the transcriptome, allowing for estimation of RNA levels in a given population of cells or even in individual cells. The levels of mRNAs are most commonly examined as they are generally a good proxy for gene expression, an important variable in many studies. Much less commonly studied are the levels of tRNA. We investigated whether information about the levels of tRNA present in Escherichia coli provide useful information with regards to amino acid levels in the context of a larger metabolic characterization study. To this end, we found very little correlation but did observe several distinct patterns in tRNA read coverage that may suggest flaws in read mapping or sequencing techniques when dealing with this type of RNA. Further work should be pursued to determine whether these patterns are biologically relevant or simply an artifact of the current sequencing and processing techniques.