# Multimodal Exploration Offers Novel Insights into the Transcriptomic and Epigenomic Landscape of the Human Submandibular Glands

## TL;DR

This study explores the molecular and regulatory landscape of human submandibular glands using transcriptomic and epigenomic data, offering new insights into their biology and potential for therapeutic research.

## Contribution

The study provides a comprehensive, multi-modal analysis of human SMG biology, identifying novel gene and regulatory networks.

## Key findings

- An SMG-enriched gene expression signature was identified, including 289 protein-coding and 75 lncRNA genes.
- Epigenomic analysis revealed genome-wide enhancers and super-enhancers linked to SMG biology.
- Comparative analysis showed evolutionary conserved gene and regulatory networks in salivary glands.

## Abstract

The submandibular glands (SMGs), along with the parotid and sublingual glands, generate the majority of saliva and play critical roles in maintaining oral and systemic health. Despite their physiological importance, long-term therapeutic options for salivary gland dysfunction remain limited, highlighting the need for a deeper molecular understanding of SMG biology, particularly in humans. To address this knowledge gap, we have performed transcriptomic- and epigenomic-based analyses and molecular characterization of the human SMG. Our integrated analysis of multiorgan RNA-sequencing datasets has identified an SMG-enriched gene expression signature comprising 289 protein-coding and 75 long non-coding RNA (lncRNA) genes that include both known regulators of salivary gland function and several novel candidates ripe for future exploration. To complement these transcriptomic studies, we have generated chromatin immunoprecipitation sequencing (ChIP-seq) datasets of key histone modifications on human SMGs. Our epigenomic analyses have allowed us to identify genome-wide enhancers and super-enhancers that are likely to drive genes and regulatory pathways that are important in human SMG biology. Finally, comparative analysis with mouse and human SMG and other tissue datasets reveals evolutionary conserved gene and regulatory networks, underscoring fundamental mechanisms of salivary gland biology. Collectively, this study offers a valuable knowledge-based resource that can facilitate targeted research on salivary gland dysfunction in human patients.