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

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

Author information

1
Center for Molecular Systems Biology, University of Turin, 10043, Orbassano, Turin, Italy.
2
Dept. of Computer Science, University of Turin, 10149, Turin, Italy.
3
Dept. of Biological and Clinical Sciences, University of Turin, 10043, Orbassano, Turin, Italy.
4
Center for Molecular Systems Biology, University of Turin, 10043, Orbassano, Turin, Italy. michele.debortoli@unito.it.
5
Dept. of Biological and Clinical Sciences, University of Turin, 10043, Orbassano, Turin, Italy. michele.debortoli@unito.it.

Abstract

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.

PMID:
28819152
PMCID:
PMC5561104
DOI:
10.1038/s41598-017-08754-9
[Indexed for MEDLINE]
Free PMC Article

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