Scalable inference of transcriptional kinetic parameters from MS2 time series data.

ABSTRACT:

Motivation

The MS2-MCP (MS2 coat protein) live imaging system allows for visualization of transcription dynamics through the introduction of hairpin stem-loop sequences into a gene. A fluorescent signal at the site of nascent transcription in the nucleus quantifies mRNA production. Computational modelling can be used to infer the promoter states along with the kinetic parameters governing transcription, such as promoter switching frequency and polymerase loading rate. However, modelling of the fluorescent trace presents a challenge due its persistence; the observed fluorescence at a given time point depends on both current and previous promoter states. A compound state Hidden Markov Model (cpHMM) was recently introduced to allow inference of promoter activity from MS2-MCP data. How

SUBMITTER: Bowles JR 

PROVIDER: S-EPMC8796374 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature