Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune...

Area of Science:

• Immunology
• Computational Biology
• Genomics

Background:

• High-throughput gene expression data are crucial for understanding cellular dynamics.
• Publicly available datasets offer potential for studying gene regulatory relationships.
• Study-specific biases and batch effects hinder the integration and analysis of such data.

Purpose of the Study:

• To present Immuno-Navigator, a batch-corrected gene expression and coexpression database for mouse immune cells.
• To improve the consistency of inferred gene correlations by removing batch effects.
• To provide tools for generating hypotheses about biological networks and candidate regulators.

Main Methods:

• Systematic removal of batch effects from gene expression data for 24 mouse immune cell types.
• Creation of a gene coexpression database.
• Development of integrated analysis tools for hypothesis generation.

Main Results:

• Batch effect removal significantly improved the consistency between inferred correlations and prior knowledge.
• Widespread cell type-specific correlations of gene expression were observed.
• Immuno-Navigator successfully predicted known regulators in regulatory T cells (Treg cells).
• Integrin beta 8 (Itgb8) expression was associated with Treg-specific epigenetic remodeling in Foxp3-positive T cells.

Conclusions:

• Immuno-Navigator facilitates the exploration of gene regulatory networks in specific immune cell types.
• Gene regulation within Treg cells may be partially independent of Foxp3 expression.
• The database aids in identifying novel candidate regulators and understanding immune cell biology.