Cellular and Molecular Life Sciences

, Volume 75, Issue 6, pp 1013–1025 | Cite as

Differential gene regulatory networks in development and disease

  • Arun J. Singh
  • Stephen A. Ramsey
  • Theresa M. Filtz
  • Chrissa Kioussi
Review

Abstract

Gene regulatory networks, in which differential expression of regulator genes induce differential expression of their target genes, underlie diverse biological processes such as embryonic development, organ formation and disease pathogenesis. An archetypical systems biology approach to mapping these networks involves the combined application of (1) high-throughput sequencing-based transcriptome profiling (RNA-seq) of biopsies under diverse network perturbations and (2) network inference based on gene–gene expression correlation analysis. The comparative analysis of such correlation networks across cell types or states, differential correlation network analysis, can identify specific molecular signatures and functional modules that underlie the state transition or have context-specific function. Here, we review the basic concepts of network biology and correlation network inference, and the prevailing methods for differential analysis of correlation networks. We discuss applications of gene expression network analysis in the context of embryonic development, cancer, and congenital diseases.

Keywords

Correlation Coexpression networks Systems biology Transcriptomics 

Notes

Acknowledgements

We apologize to our colleagues whose work could not be cited due to space limitations and our focused perspective. This work was supported by the College of Pharmacy, Oregon State University and by the National Science Foundation (award 1553728-DBI to S.A.R.).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Pharmaceutical Sciences, College of PharmacyOregon State UniversityCorvallisUSA
  2. 2.Department of Biomedical Sciences, College of Veterinary MedicineOregon State UniversityCorvallisUSA
  3. 3.School of Electrical Engineering and Computer Science, College of EngineeringOregon State UniversityCorvallisUSA

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