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.
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Chen, L.S. (2012). Using eQTLs to Reconstruct Gene Regulatory Networks. In: Rifkin, S. (eds) Quantitative Trait Loci (QTL). Methods in Molecular Biology, vol 871. Humana Press. https://doi.org/10.1007/978-1-61779-785-9_9
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DOI: https://doi.org/10.1007/978-1-61779-785-9_9
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