Sunday, May 18, 2025
5/18/2025
The reninness score: integrative analysis of multi-omic data to define renin cell identity - ABSTRACT Renin cells are crucial for survival. They are well-known for their function in blood pressure regulation, fluid- electrolyte homeostasis, kidney development, and tissue morphogenesis. In the fetal kidney, renin cells are progenitors for multiple cell types that retain epigenetic memory of the renin phenotype in adults. When homeostatic threats arise, the descendants of renin progenitor cells can transform to re-express the renin phenotype to restore homeostasis. But the mechanisms of this process, known as recruitment, have yet to be discovered. Furthermore, the regulatory networks that control the identity, fate, and recruitment of renin- expressing cells are unknown. This work comprehensively explores the open chromatin landscape of renin- expressing cells, defines the regulatory factors and transcription factor networks that determine renin cell identity and govern the recruitment process, and develops a novel computational method to score reninness based on epigenetic signals. The rarity of renin cells and the complexity of this phenotype-switching process presents a challenge of distinguishing renin-expressing cells from other kidney cells. This work will address this challenge by integrating ATAC-seq data and RNA-seq data from renin-expressing cells and a wide variety of other cell types. This proposal offers an extensive perspective of the epigenetic landscape of renin-expressing cells and regulatory element changes in the renin recruitment by performing analyses of differentially accessible genomic regions with computational approaches. In addition, it proposes a method to score samples along a spectrum of reninness with given ATAC-seq data. The outcome will aid in overcoming the challenge to identify the rare renin- expressing cells among other kidney cells. This proposal also uses computational approaches to define the transcription factor networks that governs renin recruitment which provides opportunities for follow-up research to verify and potentially fill the gap in understanding the cell-fate switching process mechanisms. Newly defining open chromatin regions and transcription factor networks will improve the scientific understanding of the epigenetic landscape of renin-expressing cells and the mechanisms controlling the identity, fate, and recruitment of renin cells. This proposal has the potential to uncover potential therapeutic targets for alternative treatment for kidney diseases, vascular diseases, and hypertension. The proposed novel computational method to score the reninness from ATAC-seq data will be useful in identifying renin cells in signal-cell data, measuring the level of response of kidney cells under homeostatic threats, predicting renin-related disease progression, and evaluating the effectiveness of treatment for the renin-related disease.
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