Dissecting the genomic activity of a transcriptional regulator by the integrative analysis of omics data

Sci Rep. 2017 Aug 17;7(1):8564. doi: 10.1038/s41598-017-08754-9.


In the study of genomic regulation, strategies to integrate the data produced by Next Generation Sequencing (NGS)-based technologies in a meaningful ensemble are eagerly awaited and must continuously evolve. Here, we describe an integrative strategy for the analysis of data generated by chromatin immunoprecipitation followed by NGS which combines algorithms for data overlap, normalization and epigenetic state analysis. The performance of our strategy is illustrated by presenting the analysis of data relative to the transcriptional regulator Estrogen Receptor alpha (ERα) in MCF-7 breast cancer cells and of Glucocorticoid Receptor (GR) in A549 lung cancer cells. We went through the definition of reference cistromes for different experimental contexts, the integration of data relative to co-regulators and the overlay of chromatin states as defined by epigenetic marks in MCF-7 cells. With our strategy, we identified novel features of estrogen-independent ERα activity, including FoxM1 interaction, eRNAs transcription and a peculiar ontology of connected genes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • A549 Cells
  • Chromatin Immunoprecipitation / methods*
  • Estrogen Receptor alpha / genetics
  • Estrogen Receptor alpha / metabolism
  • Forkhead Box Protein M1 / genetics
  • Forkhead Box Protein M1 / metabolism
  • Gene Expression Regulation, Neoplastic*
  • Genomics / methods*
  • Genomics / statistics & numerical data
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • MCF-7 Cells
  • Neoplasms / genetics
  • Neoplasms / metabolism
  • Neoplasms / pathology
  • Receptors, Glucocorticoid / genetics
  • Receptors, Glucocorticoid / metabolism


  • Estrogen Receptor alpha
  • Forkhead Box Protein M1
  • Receptors, Glucocorticoid
  • estrogen receptor alpha, human