DESCRIPTION (Provided by the applicant) Abstract: Here, I propose a unique strategy to bring genomics and proteomics into single cells by super- resolution microscopy. The basis for this new approach are the following: given the 10 nanometers resolution of a super-resolution microscope and a typical cell a size of (10um)3, individual cells contains effectively 109 super-resolution pixels or bits of information. Most eukaryotic cells have 104 genes and cellular abundances of 10-100 copies per transcript. Thus, under a super-resolution microscope, an individual cell has 1000 times more pixel volume or information capacities than is needed to encode all transcripts within that cell. Individual species of mRNA can be uniquely identified by labeling them each with a distinct combination of fluorophores by Fluorescence in situ hybridization (FISH). With at least 6 fluorophores available in super-resolution, 20,000 genes in our genome can be barcoded by as few as 6 probes, as 66=46656. These calculations suggest that by combining super-resolution microscopy and barcode labeling, single cells can be turned into informatics platforms denser than microarrays, and that molecular species in individual cells can be profiled in a massively parallel fashion. I propose to develop techniques to transcriptional profile mRNAs with single molecule sensitivity, generate a high-resolution physical map of chromosome, and map protein-DNA interactions, all within individual cells. To demonstrate the feasibility of these approaches, I will present preliminary data on resolving barcodes on mRNAs labeled by FISH with super- resolution microscopy and discuss its application to problems in transcriptional co-regulation and developmental processes in model systems. These approaches offer several distinct advantages: the detection method is high throughput and single molecule sensitive, requires only single cells as starting material, and the in situ labeling preserves the spatial context of molecules in cells as well as cellular contacts in tissues. By mapping regulatory networks within cells and signaling interactions among cells in tissues, we are open to a wide range of biological problems in development and neurobiology in which a individual cells embedded in tissues interact to generate patterns and determine cell fates. Single cell genomics and proteomics techniques proposed here have the broad impact from fundamental scientific problems in regulatory networks in developmental and neurobiology to medical applications in mapping out the molecular origin of diseases such as cancer and autism, and hold promise as the next generation diagnostic tools in clinical settings. Public Health Relevance: Single cell genomics and proteomics techniques proposed here have the potential to transform our understanding the molecular origin of diseases such as cancer and autism. By profiling the genome and proteome of single cells and exploring the spatial and signaling context in which they are embedded, these techniques hold promises for the next generation diagnostic tools in clinical settings.

Single cell genomics and proteomics techniques proposed here have the potential to transform our understanding the molecular origin of diseases such as cancer and autism. By profiling the genome and proteome of single cells and exploring the spatial and signaling context in which they are embedded, these techniques hold promises for the next generation diagnostic tools in clinical settings.