Coronary heart diseases (CHD) are the leading cause of mortality and morbidity in the United States. A well-developed coronary collateral circulation ameliorates the consequences of CHD, reducing the incidence of sudden death and infarct sizes following coronary occlusion. Stimulation of coronary collateral growth (CCG) is also an alternative therapeutic approach for patients with intractable angina pectoris. The importance of CCG is undisputable, but the process and mechanism underlying the CCG is unclear. We developed a mouse model of CCG by repetitive ischemia (RI) in adults, and the CCG was validated with contrast echo to measure the coronary blood flow 3D images of micro-CT to quantitate the CCG. In this study, we use single cell-RNA sequencing (scRNA-Seq) to analyze the molecular signaling of CCG at different time points during the RI process. We digested the hearts from RI days 5, 10, and 17 and control (naïve) mice, harvested non-cardiomyocytes, performed scRNA-Seq with 10x Genomics and sequenced with Next-Seq 500 (Illumina).The fastq files are converted to a gene count matrix using kallisto|bustools with refdata-gex-mm10-2020-A employed as the reference mouse genome. The Kallisto bustools output is then converted in R to files compatible for uploading to Cellenics, an open-source platform for single-cell RNA-Seq analysis. Dimensionality reduction is done with Principal Components Analysis (PCA) with 30 principal components. We will use UMAP to visualize cell clusters. Cellenics uses scType to annotate the cell populations automatically when building clusters of cell populations. Our preliminary data show dynamic kinetics of non-cardiomyocytes induced by RI over the timeline of CCG and different cell populations of non-cardiomyocytes and EC expression profiling varied in response to RI throughout CCG. We will validate the critical signaling in CCG and explore the potential targets to induce CCG.
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