Identification of genes under dynamic post-transcriptional regulation from time-series epigenomic data

Epigenomics. 2019 May;11(6):619-638. doi: 10.2217/epi-2018-0084. Epub 2019 May 2.


Aim: Prediction of genes under dynamic post-transcriptional regulation from epigenomic data. Materials & methods: We used time-series profiles of chromatin immunoprecipitation-seq data of histone modifications from differentiation of mesenchymal progenitor cells toward adipocytes and osteoblasts to predict gene expression levels at five time points in both lineages and estimated the deviation of those predictions from the RNA-seq measured expression levels using linear regression. Results & conclusion: The genes with biggest changes in their estimated stability across the time series are enriched for noncoding RNAs and lineage-specific biological processes. Clustering mRNAs according to their stability dynamics allows identification of post-transcriptionally coregulated mRNAs and their shared regulators through sequence enrichment analysis. We identify miR-204 as an early induced adipogenic microRNA targeting Akr1c14 and Il1rl1.

Keywords: ChIP-seq; RNA-seq; adipocyte; chromatin; differentiation; epigenomics; linear regression; microRNA; osteoblast; post-transcriptional regulation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipocytes / metabolism
  • Aldehyde Reductase / genetics
  • Animals
  • Cell Differentiation / genetics
  • Cell Line
  • Cell Lineage / genetics
  • Chromatin Immunoprecipitation
  • Cluster Analysis
  • Epigenomics
  • Gene Expression Regulation*
  • Interleukin-1 Receptor-Like 1 Protein / genetics
  • Linear Models
  • Mice
  • MicroRNAs / genetics
  • MicroRNAs / metabolism
  • MicroRNAs / physiology
  • Osteoblasts / metabolism
  • RNA Processing, Post-Transcriptional*


  • Il1rl1 protein, mouse
  • Interleukin-1 Receptor-Like 1 Protein
  • MIRN204 microRNA, mouse
  • MicroRNAs
  • Aldehyde Reductase
  • aldo-keto reductase family 1, member C14 protein, mouse