The YANA approach combining synthetic and chemical genetics with simple model systems can identify human disease gene networks for therapeutic target discovery.
Should not change SMA management; extends chemical genetic screening in zebrafish for therapeutic target discovery.
Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA) approach and test it with the X-linked spinal muscular atrophy (SMA) disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish) SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases.
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Wiley et al. (2014) studied X-linked spinal muscular atrophy. MLN4294 vs. Vehicle/Control was evaluated on Motor axon abnormalities in zebrafish embryos.
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