The aim of this proposal is to understand how self-renewal is controlled in neural stem cell lineages and how defects in this process can lead to the formation of brain tumors in model organisms. The system we use are Drosophila neuroblasts, stem cell like progenitors in the developing fly brain that undergo repeated rounds of asymmetric cell division. During each division, protein determinants called Numb, Prospero and Brat are segregated into one of the daughter cells where they stop self-renewal and ultimately trigger neuronal differentiation. Mutations in those proteins or their segregation machinery lead to the formation of tumor neuroblasts, which proliferate indefinitely leading to the formation of a deadly brain tumor. The approach we take is to determine the transcriptional network that acts in neuroblasts to control self-renewal. We will use time-resolved transcriptional profiling to determine, how this network changes in the differentiating daughter cell and develop tools for medium-throughput functional analysis of the key network players. We will develop methodology for tissue-specific chromatin immunoprecipitation to determine, how the asymmetrically segregating determinants feed into this network. Using this data set, we will determine the pathological state of the network in the tumorigenic situation. We will determine, how wild type neural stem cells limit their proliferation capacity and how those control mechanisms are affected in the tumor situation. Ultimately, we will expand this analysis to other stem cell systems inside and outside the fly nervous system to determine how modifications of stem cell systems like transit amplifying pools or perpetual adult proliferation are reflected in network architecture.