Bayesian inference of polymerase dynamics over the exclusion process.
Massimo CavallaroYuexuan WangDaniel HebenstreitRitabrata DuttaPublished in: Royal Society open science (2023)
Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e. the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, while avoiding the explicit inversion of the system's dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.
Keyphrases
- gene expression
- single cell
- transcription factor
- copy number
- air pollution
- computed tomography
- dna methylation
- contrast enhanced
- structural basis
- circulating tumor
- genome wide
- molecular dynamics
- single molecule
- molecular dynamics simulations
- healthcare
- molecularly imprinted
- high resolution
- mass spectrometry
- dual energy
- solid phase extraction