Integrating multi-omics data to investigate pseudogene expression in Mycolicibacterium smegmatis

Large-scale -omics data now allows for investigating genome-wide functional elements. Using RNA-Seq data, we tested the expression of 134 pseudogenes which do not show duplicated protein coding genes in the M. smegmatis genome. We observe significant expression and translation of 28 pseudogenes. Further examination using RNA-Seq reads suggested the sequencing errors in many pseudogenes. These include some of the functionally relevant genes such as recN and manB. We propose that the analysis of transcriptional and translational landscape using multi-dimensional -omics data could shed light on the current annotations of the bacterial pseudogenes.