title: Using eQTLs to reconstruct gene regulatory networks.
abstract: In recent years, a new type of experiment has emerged. It involves genetic crosses and simultaneous measurements of the genome-wide gene expression and genotype information of the offspring. In this chapter, I discuss how to reconstruct gene regulatory networks from this type of data. Subheading 1 provides an overview of the topic. In Subheading 2, I review previous methods of constructing gene networks from expression data alone and point out the difficulties of inferring causal relationships from observational studies. I also introduce the concept of Mendelian randomization of genotypes during a genetic cross. Based on this concept, several methods have been proposed that utilize the genetically randomized genotype information (expression quantitative trait loci information) to infer gene regulatory relationships. Subheading 3 describes the development and details of these methods. I also discuss the pros and cons of each. Subheading 4 addresses a major challenge of inferring gene regulation: how to adequately consider the existence of hidden variables, and points out that further research is still needed.
authors.affiliation: Department of Health Studies, The University of Chicago, Chicago, IL, USA. lchen@health.bsd.uchicago.edu
authors.forename: Lin S
authors.initials: LS
authors.lastname: Chen
mesh_terms: D053263:Gene Regulatory Networks / Q000235:genetics*; D040641:Quantitative Trait Loci / Q000235:genetics*