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Updated: Jun 8, 2026
Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets
Published on: July 18, 2019
EuroDia: a beta-cell gene expression resource
Robin Liechti1, Gábor Csárdi, Sven Bergmann
1Vital-IT, SIB Swiss Institute of Bioinformatics, Genopode Building, CH-1015 Lausanne, Switzerland.
Abstract:
Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.
Insights
The EuroDia database and GEDAI system offer a unique resource for studying type 2 diabetes mellitus (T2DM) by analyzing pancreatic beta-cell gene expression. This platform aids researchers in identifying key genes and pathways involved in T2DM development.
Area of Science:
- Biomedical Informatics
- Genomics
- Endocrinology
Background:
- Type 2 diabetes mellitus (T2DM) affects millions globally, with pancreatic beta-cell dysfunction being a critical factor.
- Understanding T2DM pathophysiology requires detailed analysis of beta-cell gene expression under various conditions.
Purpose of the Study:
- To establish a centralized database (EuroDia) of pancreatic beta-cell gene expression data from human, mouse, and rat models.
- To develop an integrated analysis system (GEDAI) for quality control, differential gene expression, and pathway analysis.
Main Methods:
- Creation of the EuroDia database, collecting gene expression measurements from multiple organisms.
- Development of the Gene Expression Data Analysis Interface (GEDAI) with quality control procedures.
- Integration of R/Bioconductor tools for analyzing gene expression data and combining experiments across platforms.
Main Results:
- GEDAI provides a web interface for users to design custom analysis pipelines for gene expression data.
- The system identifies differentially expressed genes and pathways, facilitating T2DM research.
- Raw and normalized data are downloadable, supporting reproducibility and further investigation.
Conclusions:
- The EuroDia database and GEDAI system offer a valuable, flexible resource for T2DM research.
- This integrated platform supports the analysis of complex gene expression datasets across different organisms and experimental platforms.
- GEDAI is currently utilized for various laboratory projects, demonstrating its utility in handling diverse gene expression data.
