Tool Development and Computational Analysis of Chromatin with Applications to Renin Cell Biology
Smith, Jason, Biochemistry and Molecular Genetics - School of Medicine, University of Virginia
Sheffield, Nathan, MD-PBHS Public Health Sciences Admin, University of Virginia
An ultimate goal of biology is the understanding, at a fundamental level, of the function of the cell. What factors shape cell identity and function and how does an organism or individual cell control the timing, development, and activity of its genome? A cell’s identity can change over time, based on genetic and epigenetic signals, its spatial context in an organism, or due to internal or external stimuli. Genomics and epigenomics seek to uncover these signals by measuring molecular profiles of RNA [1–4], DNA [5–8], protein [9, 10], epigenetic modifications [11–13], or chromatin accessibility and conformation [14–18]. Open chromatin and gene expression assays with their corresponding computational tools enable the deconvolution of complex samples, the identification of rare or novel cell types and regulatory elements, and of the interactions between DNA and chromatin-interacting proteins [19–24]. We sought to evaluate the status of the computational infrastructure to enable these sorts of analyses, address unmet needs in the field, and apply this knowledge and expertise to investigate questions of development in a rare kidney cell (renin or juxtaglomerular cells) that is integral for maintaining homeostasis. To fulfill this goal, we evaluated current methods for open chromatin analysis, developed computational pipelines to analyze bulk ATAC-seq, nascent RNA-seq, and applied an integrated analysis of scATAC-seq and scRNA-seq to uncover the regions and factors driving the differentiation of renin cells in developing mouse kidneys. This work led to the novel finding of the importance of the MEF2 family of transcription factors being primary drivers of renin cell differentiation.
PHD (Doctor of Philosophy)
chromatin, ATAC-seq, nascent RNA-seq, scATAC-seq, scRNA-seq, renin, bioinformatics, computational biology, molecular biology
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