Genetic and systems level analysis of Drosophila sticky/citron kinase and dFmr1 mutants reveals common regulation of genetic networks.

backgroundIn Drosophila, the genes sticky and dFmr1 have both been shown to regulate cytoskeletal dynamics and chromatin structure. These genes also genetically interact with Argonaute family microRNA regulators. Furthermore, in mammalian systems, both genes have been implicated in neuronal development. Given these genetic and functional similarities, we tested Drosophila sticky and dFmr1 for a genetic interaction and measured whole genome expression in both mutants to assess similarities in gene regulation.

resultsWe found that sticky mutations can dominantly suppress a dFmr1 gain-of-function phenotype in the developing eye, while phenotypes produced by RNAi knock-down of sticky were enhanced by dFmr1 RNAi and a dFmr1 loss-of-function mutation. We also identified a large number of transcripts that were misexpressed in both mutants suggesting that sticky and dFmr1 gene products similarly regulate gene expression. By integrating gene expression data with a protein-protein interaction network, we found that mutations in sticky and dFmr1 resulted in misexpression of common gene networks, and consequently predicted additional specific phenotypes previously not known to be associated with either gene. Further phenotypic analyses validated these predictions.

conclusionThese findings establish a functional link between two previously unrelated genes. Microarray analysis indicates that sticky and dFmr1 are both required for regulation of many developmental genes in a variety of cell types. The diversity of transcripts regulated by these two genes suggests a clear cause of the pleiotropy that sticky and dFmr1 mutants display and provides many novel, testable hypotheses about the functions of these genes. As both of these genes are implicated in the development and function of the mammalian brain, these results have relevance to human health as well as to understanding more general biological processes.