Detection of regulator genes and eQTLs in gene networks

Lingfei Wang, Tom Michoel*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract / Description of output

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in noncoding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are “expression quantitative trait loci” or eQTLs, for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins, and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, as well as to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and software to identify eQTLs and their associated genes, to reconstruct coexpression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.

Original languageEnglish
Title of host publicationSystems Biology in Animal Production and Health, Vol. 1
PublisherSpringer International Publishing
Pages1-23
Number of pages23
ISBN (Electronic)9783319433356
ISBN (Print)9783319433332
DOIs
Publication statusPublished - 1 Jan 2016

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