# Single-Cell RNA Sequencing Outperforms Single-Nucleus RNA Sequencing in Analyzing Pancreatic Cell Diversity and Gene Expression in Goats

## TL;DR

This study found that single-cell RNA sequencing provides better insights into pancreatic cell diversity and gene expression in goats compared to single-nucleus RNA sequencing.

## Contribution

The study directly compares scRNA-seq and snRNA-seq for pancreatic cell analysis in goats, highlighting scRNA-seq's superior performance.

## Key findings

- scRNA-seq identified more pancreatic cell types, including stellate, immune, and delta cells.
- Genes related to digestive enzymes showed higher expression in scRNA-seq compared to snRNA-seq.
- snRNA-seq uniquely identified pancreatic stem cells, while scRNA-seq provided broader cell diversity.

## Abstract

The objective of this study was to determine whether single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq) was more effective for studying the goat pancreas. Pancreas tissues from three healthy 10-day-old female Xiangdong black goats were processed into single-cell and single-nucleus suspensions. These suspensions were then used to compare cellular composition and gene expression levels following library construction and sequencing. Both scRNA-seq and snRNA-seq were eligible for primary analysis but produced different cell identification profiles in pancreatic tissue. Both methods successfully annotated pancreatic acinar cells, ductal cells, alpha cells, beta cells, and endothelial cells. However, pancreatic stellate cells, immune cells, and delta cells were uniquely annotated by scRNA-seq, while pancreatic stem cells were uniquely identified by snRNA-seq. Furthermore, the genes related to digestive enzymes showed a higher expression in scRNA-seq than in snRNA-seq. In the present study, scRNA-seq detected a great diversity of pancreatic cell types and was more effective in profiling key genes than snRNA-seq, demonstrating that scRNA-seq was better suited for studying the goat pancreas. However, the choice between scRNA-seq and snRNA-seq should consider the sample compatibility, technical differences, and experimental objectives.