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Integrated Chip-Seq and RNA-Seq Data Analysis Coupled with Bioinformatics Approaches to Investigate Regulatory Landscape of Transcription Modulators in Breast Cancer Cells

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Molecular Toxicology Protocols

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2102))

Abstract

The objective of this chapter is to describe step-by-step bioinformatics and functional genomics solutions for analyzing ChIP-Seq and RNA-Seq data for understanding the regulatory mechanisms of chromatin modifiers and transcription factors that can drive pathogenesis of chronic complex human diseases, such as cancer. Here we have used two transcription regulatory proteins: nuclear respiratory factor 1 (NRF1) and inhibitor of differentiation protein 3 (ID3) for ChIP-Seq and RNA-Seq data as examples for discussing the importance of selecting the appropriate computational analysis methods, software, and parameters for the processing of raw data as well as their integrative regulatory landscape analysis to obtain accurate and reliable results. Both ChIP-Seq and RNA-Seq analytic methodologies are used as instructional examples to identify NRF1 or ID3 binding to the promoters and enhancers in the genome and their effects on the activity as well as to discover target genes that can drive breast cancer.

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Authors and Affiliations

  1. Department of Environmental Health Sciences, Florida International University, Miami, FL, USA

    Jairo Ramos, Quentin Felty & Deodutta Roy

Authors
  1. Jairo Ramos
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  2. Quentin Felty
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  3. Deodutta Roy
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Corresponding author

Correspondence to Deodutta Roy .

Editor information

Editors and Affiliations

  1. Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA

    Phouthone Keohavong

  2. Department of Environmental Toxicology, The Institute of Environmental and Human Health (TIEHH), Texas Tech University, Lubbock, TX, USA

    Kamaleshwar P. Singh

  3. Department of Occupational and Environmental Health Sciences, School of Public Health West Virginia University, Morgantown, WV, USA

    Weimin Gao

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Ramos, J., Felty, Q., Roy, D. (2020). Integrated Chip-Seq and RNA-Seq Data Analysis Coupled with Bioinformatics Approaches to Investigate Regulatory Landscape of Transcription Modulators in Breast Cancer Cells. In: Keohavong, P., Singh, K., Gao, W. (eds) Molecular Toxicology Protocols. Methods in Molecular Biology, vol 2102. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0223-2_3

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  • DOI: https://doi.org/10.1007/978-1-0716-0223-2_3

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0222-5

  • Online ISBN: 978-1-0716-0223-2

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