Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model

Nucleic Acids Res. 2015 Jan;43(1):153-61. doi: 10.1093/nar/gku1272. Epub 2014 Dec 3.

Abstract

Changes in transcription factor levels, epigenetic status, splicing kinetics and mRNA degradation can each contribute to changes in the mRNA dynamics of a gene. We present a novel method to identify which of these processes is changed in cells in response to external signals or as a result of a diseased state. The method employs a mathematical model, for which the kinetics of gene regulation, splicing, elongation and mRNA degradation were estimated from experimental data of transcriptional dynamics. The time-dependent dynamics of several species of adipose differentiation-related protein (ADRP) mRNA were measured in response to ligand activation of the transcription factor peroxisome proliferator-activated receptor δ (PPARδ). We validated the method by monitoring the mRNA dynamics upon gene activation in the presence of a splicing inhibitor. Our mathematical model correctly identifies splicing as the inhibitor target, despite the noise in the data.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Cell Line, Tumor
  • Humans
  • Membrane Proteins / genetics
  • Models, Genetic*
  • Perilipin-2
  • RNA Splicing
  • RNA Stability
  • RNA, Messenger / metabolism
  • Transcription, Genetic*

Substances

  • Membrane Proteins
  • PLIN2 protein, human
  • Perilipin-2
  • RNA, Messenger