This application is intended for the (06) "Enabling Technologies" challenge area and (06- HG-102*) "Technologies for obtaining genomic, proteomic, and metabolomic data from individual viable cells in complex tissue" challenge topic. The specialized microenvironment surrounding stem cells or cancer cells is thought to be a major regulator of critical functions such as stem cell quiescence, self-renewal, proliferation and differentiation, as well as cancer progression. The amount of speculation implicating microenvironments in these processes currently exceeds the ability to generate supporting experimental data. This is, in part, due to the nature of micro-environments: they must be studied in vivo as in vitro recreations have not been convincing;the roles of individual cell types are often unclear;and there is a lack of techniques to systematically evaluate micro-environmental regulatory pathways in an unbiased manner. One means of evaluating cellular responses is to monitor changes in gene expression. We have established new methods that increase sensitivity and species-selectivity of TaqMan-based probes when combined with a PCR-based pre-amplification protocol. This allows homologous transcripts from two closely-related species to be distinguished, even when the mRNA from one species is up to 100,000,000-fold higher than in the other species. Thus, allows the quantification of gene expression in as few as 1-10 cells of a specified type (e.g., muscle stem cells) as they reside in cellular heterogeneous in vivo microenvironments in a distinct species. Similarly, this Q-PCR- based approach can be used to quantify the total contribution of a stem cell population to a specific tissue, allowing repopulating assays to be efficiently completed on solid organs. Finally, the utility of this approach to prospectively isolate satellite cells from skeletal muscle at the single cell level is explored. While these advances in Q-PCR will have a large impact on the study up to 200 genes per sample, the current techniques are not scalable to genome wide discovery. Several alternative approaches to scale up species-specific gene quantification are explored. While specific studies are proposed here, we believe that this powerful approach is broadly applicable to the study of a wide variety of biological processes such as tissue regeneration and cancer. While our primary rational for creating this technology is to identify the molecular mechanisms of regulating skeletal muscle stem cells, this technique has broad applicability to study the reciprocal interactions between stem cells and their niche as well as malignant cells within the supporting stroma. CHOP contributes substantially to the local economy. In 2008, CHOP's operations created and supported over 16,882 jobs in the region, and CHOP's total economic impact was over $2.01 billion. Moreover, through a combination of private donations, NIH funding, and allocations from its hospital operations, CHOP receives more total research support than any other children's hospital in the United States -- $180 million in fiscal year 2007-2008. The direct funding in this proposal will create or retain 4 full-time staff positions in academic research plus 2 trainee/work study positions for undergraduate students at the University of Pennsylvania. In addition, $390,000 in indirect costs will directly enable an additional 4 CHOP staff members to retain their employment. Furthermore, approximately, over 95% of the material and supplies will be purchased from American, biotechnology companies. Approximately 50% of the supply budget will go to Applied Biosystems in Foster City, CA where it will create an estimated 1.3 jobs. Thus, this award will create or maintain approximately 11.3 U.S. jobs. The specialized microenvironments surround stem cells or cancer cells and are thought to be major regulators of cell behavior. We present here a technique to quantify expression of up to 100 genes in 1-10 cells residing in intact tissue in an animal. This powerful approach is broadly applicable to the study of a wide variety of biological processes. Specifically, we propose that these techniques can distinguish gene expression patterns in a selected cell type in gross tissue samples and allow the recognition of regulatory pathways and metabolic processes that are fundamental to stem cell and cancer cell behaviors.