Bayesian analysis dissects kinetic modulation during non-stationary gene expression.

ABSTRACT: Labelling of nascent stem loops with fluorescent proteins has fostered the visualization of transcription in living cells. Quantitative analysis of recorded fluorescence traces can shed light on kinetic transcription parameters and regulatory mechanisms. However, existing methods typically focus on steady state dynamics. Here, we combine a stochastic process transcription model with a hierarchical Bayesian method to infer global as well locally shared parameters for groups of cells and recover unobserved quantities such as initiation times and polymerase loading of the gene. We apply our approach to the cyclic response of the yeast CUP1 locus to heavy metal stress. Within the previously described slow cycle of transcriptional activity on the scale of minutes, we discover fast time-m

SUBMITTER: Wildner C 

PROVIDER: S-EPMC10370195 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature