The goal of this U01 is to characterize and understand the variability in the expressed transcriptome of human excitable cells. There are two predominant types of excitable cell in the human body, neurons and muscle cells, including cardiac cells. Many human CNS diseases result from modulation of the electrical responsiveness of neurons while cardiac arrhythmias account for most of heart associated deaths. However, at the level of individual cells there is considerable heterogeneity in function, response, and dysfunction. Here, we present preliminary data showing large-scale single cell variability that is difficult to explain as simple molecular noise. We hypothesize that there is a many-to-one relationship between transcriptome states and a cell's phenotype. In this relationship the functional molecular ratios of the RNA are determined by the cell systems'stoichiometric constraints, which underdetermine the transcriptome state. Because a broad set of multi-genic combinations support a particular phenotype, changes in the transcriptome state do not necessarily lead to changes in the phenotype potentially explaining cellular heterogeneity in phenotype response to variant conditions such as the application of therapeutic molecules. To test this hypothesis we propose to investigate the extent of single cell variation for the whole transcriptome for excitable cells that are in their natural environment using a novel mRNA capture methodology (TIVA-tag), and on a subset of the transcriptome, the mRNAs encoding the therapeutically important and manipulable G protein-coupled receptor (GPRC) pathways. The use of functional genomics techniques developed in the Eberwine and Kim labs (TIPeR) will permit an assessment of the biological role of multigenic transcriptome variation. These studies are truly interdisciplinary involving the collaboration of two clinicians (Drs. Grady, Neurosurgeon and Kuhn, Cardiologist), two genomicists (Drs. Eberwine and Kim) one of whom is a computational scientist (Dr. Kim), a neuro/cardio- pharmacologist (Dr. Bartfai) and a biophotonics expert (Dr. Sul).!
The goal of this proposal is to generate a compendium of single cells sequencing data from live human excitable cells that are in contact with endogenous neighboring cells. These sequencing data will be analyzed for variability in gene expression and the biological function of this variability assessed using a novel in vivo functional genomics methodology.
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