Recently, Bandyopadhyay et al. adapted this approach to reveal how cells cope

with DNA damage [ 44••]. They directly compared interactions maps recorded under normal or DNA-damage inducing conditions, a strategy similar to identifying gene expression changes using microarrays. Analyzing each dataset individually recovered mainly ‘housekeeping interactions’ find more between genes involved in chromatin biology (and previously observed in other datasets [ 36•• and 37••]). Focusing on the differences, on the other hand, specifically revealed known DNA repair pathways and pinpointed several new regulators of this well-characterized process. The technical challenges of constructing similar maps in higher organisms are formidable, for example, as the number of possible pairwise gene-combinations grow exponentially with genome size. Our own work has provided a first indication that metazoan interaction maps can be constructed from high-throughput,

combinatorial RNAi approaches [45] (Figure 3). To study the functional interdependencies of signaling pathways in Drosophila cells, we targeted 96 genes – each with two independent RNAi reagents – and generated all ca. 18 000 possible double-knockdown combinations. Recording three distinct quantitative phenotypes (cell growth, nuclear size and DNA content) allowed us to identify more than 600 instances where the double-RNAi phenotype learn more could not be predicted from single perturbations using a multiplicative model [ 46]. Many of these genetic interactions specifically affected only one of the assayed cellular characteristics, highlighting the context-dependence of functional connections ( Figure Baf-A1 nmr 3). Correlating these interaction profiles across different signaling pathways pinpointed Cka/Striatin3 as novel positive regulator of the Ras/MAPK cascade in fruitflies and in human cells [ 45]. The large number of pair-wise – let alone higher order – interactions currently limits

the scope of genetic interaction studies in metazoan cells and further technical innovations are clearly required to experimentally map interactions within mammalian-sized genomes. Future experiments in mammalian cells might, for example, take advantage of novel multiplexing strategies. For example, Muellner et al. molecularly barcoded a panel of 89 engineered isogenic cancer cell lines to survey over 6000 drug–gene interactions in a highly multiplexed format [ 47•] ( Figure 1c). The assay faithfully identified known as well as novel interactions, revealing, for example, that NOTCH1 activation can confer resistance to PI3K inhibitors. Similar multiplex approaches could be applied to the study of gene-gene interactions in the future, and might be expanded further, for example, through next-generation sequencing based quantification strategies [ 48].