Coexpression and cosplicing network approaches for the study of mammalian brain transcriptomes

Ovidiu Dan Iancu, Alexandre Colville, Priscila Darakjian, Robert Hitzemann

Research output: Chapter in Book/Report/Conference proceedingChapter

11 Scopus citations


Next-generation sequencing experiments have demonstrated great potential for transcriptome profiling. While transcriptome sequencing greatly increases the level of biological detail, system-level analysis of these high-dimensional datasets is becoming essential. We illustrate gene network approaches to the analysis of transcriptional data, with particular focus on the advantage of RNA-Seq technology compared to microarray platforms. We introduce a novel methodology for constructing cosplicing networks, based on distance measures combined with matrix correlations. We find that the cosplicing network is distinct and complementary to the coexpression network, although it shares the scale-free properties. In the cosplicing network, we find a set of novel hubs that have unique characteristics distinguishing them from coexpression hubs: they are heavily represented in neurobiological functional pathways and have strong overlap with markers of neurons and neuroglia, long-coding lengths, and high number of both exons and annotated transcripts. We also find that gene networks are plastic in the face of genetic and environmental pressures.

Original languageEnglish (US)
Title of host publicationInternational Review of Neurobiology
PublisherAcademic Press Inc.
Number of pages21
StatePublished - 2014
Externally publishedYes

Publication series

NameInternational Review of Neurobiology
ISSN (Print)0074-7742


  • Coexpression
  • Cosplicing
  • Gene network
  • Network inference
  • Network topology
  • Systems biology

ASJC Scopus subject areas

  • Clinical Neurology
  • Cellular and Molecular Neuroscience


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