Host factor prioritization for pan-viral genetic perturbation screens using random intercept models and network propagation

by Simon Dirmeier, Christopher D ächert, Martijn van Hemert, Ali Tas, Natacha S. Ogando, Frank van Kuppeveld, Ralf Bartenschlager, Lars Kaderali, Marco Binder, Niko Beerenwinkel Genetic perturbation screens using RNA interference (RNAi) have been conducted successfully to identify host factors that are essential for the life cycle of bacteria or viruses. So far, most published studies identified host factors primarily for single pathogens. Furthermore, often only a small subset of genes, e.g., genes encoding kinases, have been targeted. Identification of host factors on a pan-pathogen level, i.e., genes that are crucial for the replication of a diverse group of pathogens has received relatively little attention, despite the fact that such common host factors would b e highly relevant, for instance, for devising broad-spectrum anti-pathogenic drugs. Here, we present a novel two-stage procedure for the identification of host factors involved in the replication of different viruses using a combination of random effects models and Markov random walks on a functiona l interaction network. We first infer candidate genes by jointly analyzing multiple perturbations screens while at the same time adjusting for high variance inherent in these screens. Subsequently the inferred estimates are spread across a network of functional interactions thereby allowing for the analysis of missing genes in the biological studies, smoothing the effect sizes of previously found host factors, and co...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research