High-Resolution Transcriptomic Landscape of the Human Submandibular Gland

Area of Science:

• Genomics
• Cell Biology
• Human Physiology

Background:

• Human salivary glands are crucial for physiology but lack comprehensive molecular characterization at single-cell resolution.
• Difficulties in obtaining normal human tissues hinder detailed analysis.

Purpose of the Study:

• To perform an in-depth molecular analysis of adult human submandibular gland (SMG) samples.
• To characterize heterogeneous cell populations using single-cell RNA sequencing (scRNA-seq).

Main Methods:

• Bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) on human SMG samples.
• Bioinformatic analyses including deconvolution, CellChat for interactome prediction, and trajectory inference.

Main Results:

• Identified diverse epithelial and nonepithelial cell clusters in the SMG, recapitulated by bulk RNA data deconvolution.
• Revealed transcriptomic heterogeneity within ductal and acinar cells, identifying human-specific mucoacinar cells and ionocytes.
• Mapped cell-cell communication networks and inferred differentiation pathways within the adult SMG.

Conclusions:

• The study provides a high-resolution molecular atlas of the human SMG.
• Offers insights into the complex cellular composition, communication, and differentiation processes.
• Serves as a valuable resource for understanding SMG biology and pathophysiology.