BCB Research Seminar: Huaming Sun, 'Unraveling the transcript properties related to mRNA stability in M. smegmatis using machine learning'

Abstract:  

As a highly successful pathogen, M. tuberculosis is able to infect, survive and proliferate within the harsh microenvironments of its human host with the help of mRNA degradation regulation. However, the mechanisms underlying the regulation of mRNA degradation in mycobacteria remain poorly understood. To address this, we developed a computational pipeline using RNAseq and machine learning to identify the mRNA features associated with mRNA degradation in M. smegmatis. Our results demonstrate that multiple types of features contributing to differentiate the degradation rate, rather than a single dominant feature. We also found that the features associated with degradation are different for leadered and leaderless mRNAs, as well as for mRNAs in normal and stress condition. These findings suggest that mRNA degradation in mycobacteria is regulated through complex mechanisms.