Abstract P225: The Reninness Score: Integrative Analysis Of Multi-omic Data To Define Renin Cell Identity.

Abstract

Renin cell (RC) descendants regain the endocrine renin phenotype to overcome homeostatic threats, a process known as recruitment. The determinants that control the identity, fate, and recruitment of RCs are not well understood. We aim to 1) define the chromatin pattern that determines RC identity; and 2) develop a computational tool to score samples by similarity to that pattern. We compared open chromatin regions (ATAC-seq) between non-renin-expressing (n = 184) and renin-expressing samples (n = 19) from three different sources and stimulation states: 1) primary RCs in basal state (WT); 2) primary RCs chronically stimulated to produce renin (recruited); and 3) constitutively renin-expressing tumoral cells. Differential analyses between the three types of RCs and the non-RCs revealed 1,525 unique open chromatin regions shared in at least two RC groups, including regions associated with RC-specific genes: Ren1 and Akr1b7. Increased accessibility regions in RC groups are enriched in renin-related GO terms ( e.g., cAMP and Notch signaling pathway). The bZip family ( e.g. , Atf3, p < 10 -2147 ) was the most enriched motifs in tumoral cells, and MEF2 family ( e.g. , MEF2a, p < 10 -91 ) in primary cells. Co-enriched motifs (e.g., MEIS1, p < 10 -10 ; NR4A2, p < 10 -9 ) in Ren1 and Akr1b7 regions suggest a group of TFs govern their co-expression. In addition, we identified unique open chromatin regions and enriched motifs ( e.g., E2F4, p < 10 -9 ; SP2, p < 10 -7 ) in recruited RCs, suggesting associated TFs involved in the recruitment.Next, we used a machine-learning approach to calculate a "reninness" score by training a genomic region model with renin and non-renin ATAC-seq data. We identified a cluster of regions (n = 112,992) around the trained renin label, which included 89% (21,820 of 24,612) of the increased accessibility regions from the differential analyses. We calculated the reninness score based on the distance between the trained label embeddings and predicted samples using the trained model. Homogeneous WT RCs had the highest score, followed by renin-expressing tumoral and primary cells. Non-RCs had the lowest score. In conclusion, we identified the chromatin configurations defining the identity and recruitment of RCs and developed a computational score to quantify it.