Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways

Most heritable traits, including disease susceptibility, are affected by interactions between multiple genes. However, we understand little about how genes interact because very few possible genetic interactions have been explored experimentally. We have used RNA interference in Caenorhabditis elegans to systematically test approximately 65,000 pairs of genes for their ability to interact genetically. We identify approximately 350 genetic interactions between genes functioning in signaling pathways that are mutated in human diseases, including components of the EGF/Ras, Notch and Wnt pathways. Most notably, we identify a class of highly connected 'hub' genes: inactivation of these genes can enhance the phenotypic consequences of mutation of many different genes. These hub genes all encode chromatin regulators, and their activity as genetic hubs seems to be conserved across animals. We propose that these genes function as general buffers of genetic variation and that these hub genes may act as modifier genes in multiple, mechanistically unrelated genetic diseases in humans.     

Population dynamics of Schistosoma mansoni in mice repeatedly exposed to infection

Studies of host resistance to parasite infection are usually based on experimental designs involving a primary infection and subsequent challenge exposure, resistance being recorded as the percentage reduction in parasite establishment in challenged hosts when compared with that in uninfected animals. Few studies have focused on the dynamic nature of helminth establishment and mortality (and their presumed dependency on the rate of current exposure and past experiences of infection) in hosts repeatedly exposed to low levels of infection. Here, we report the results of population studies on the dynamics of resistance to Schistosoma mansoni infection (a helminth parasite) in mice repeatedly exposed to cercarial invasion. Parasite burdens created by different levels and durations of exposure to infection reflect a dynamic interplay between rates of helminth establishment and mortality. Depending on the intensity of exposure, changes in worm load with duration of host infection vary from monotonic growth to a stable average parasite burden to convex curves in which the average load attains a maximum value before decaying in old animals. These trends are similar to observed patterns of S. mansoni infection in human communities.     

A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans

The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets.