The self-renewal and differentiation of stem cells is controlled by signals derived from the microenvironment or “niche”. The paired hematopoietic organs of the Drosophila genetic model organism are a well-characterized system in which the regulation of stem cell behaviour within a niche can be genetically dissected. We will use this system to understand how stem cell self-renewal and differentiation can be influenced by signals from stromal cells in the niche, and integrated with hormonal and endocrine signals. Research using in vitro cultured stem cell lines demonstrates that stem cell differentiation is accompanied by alterations in the chromatin architecture, with stem cells exhibiting unique patterns of histone post-translational modifications (so-called “epigenetic marks”). In vitro tissue culture systems, however, do not allow the influence of signals from the niche on the establishment and propagation of these patterns of epigenetic modifications to be dissected. The extraordinary genetic amenability of Drosophila provides a system in which targeted ablation or over-expression of signalling mediators allows experimental manipulation of signals from the niche to the stem cell populations to investigate effects on epigenetic landscapes.
We have developed experimental strategies to isolate sufficient quantities of chromatin from these cell populations. In this project we will purify chromatin of stem cell populations from in vivo stem cell niches and use this for whole genome profiling by chromatin immunoprecipitation-coupled sequencing (ChIP-seq). This cell-specific chromatin will then be used to probe unique signatures of stem versus differentiated chromatin.
The project will make extensive use of molecular biology techniques such as chromatin immunoprecipitation and handling of ChIP DNA for sequencing library preparation. It will also provide expertise in basic Drosophila genetics and husbandry. A key element of the project, however, will be analysis of high-throughput sequencing data. This includes mapping of sequence reads to the Drosophila genome, ChIP peak, and integrating ChIP-seq data sets to discriminate unique epigenetic fingerprints of each cell type.