Abstract Body: 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 cell type specific and 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. We did not find a unique set of TFs specific to the Recruited group, indicating that renin recruitment may not be regulated by a recruitment-specific factor family, but could instead be driven by post-translational modification, differential co-factors, or epigenetic modifications.
Next, we used a machine-learning approach to calculate a "reninness" score by training a genomic region model with renin and non-renin bulkATAC-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 regions with increased accessibility from the differential analyses. We calculated the reninness score based on the distance between the trained label and the predicted bulkATA sample embeddings using the trained model. Homogeneous WT RCs had the highest score, followed by renin-expressing tumoral and primary cells. Non-RCs had the lowest scores. We also adapted bulkATAC region-embedding models to pseudo-bulk ATAC- and scATAC-seq data. The observed reninness scores show that the model can also capture differences in renin recruitment potential.
In conclusion, we identified the chromatin configurations defining the identity and recruitment of RCs and developed a computational score to quantify it.