Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits. From RNA Integrity to Network Topology

M. A. O'Brien, B. N. Costin, M. F. Miles

Research output: Chapter in Book/Report/Conference proceedingChapter

11 Scopus citations

Abstract

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, potentially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be "it's the network... stupid," the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology.

Original languageEnglish (US)
Title of host publicationInternational Review of Neurobiology
PublisherAcademic Press Inc.
Pages91-133
Number of pages43
DOIs
StatePublished - 2012

Publication series

NameInternational Review of Neurobiology
Volume104
ISSN (Print)0074-7742

Bibliographical note

Funding Information:
Work supported by NIAAA Grants: R01AA014717, U01AA016667, P20AA017828 (M. F. M.); 1F31AA021035-01 (M. A. O.); and 1F31AA020141-01 (B. N. C.).

Keywords

  • Complex traits
  • Gene networks
  • Genomics
  • Microarrays

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