Regulatory pathway analysis by high-throughput in situ hybridization

Area of Science:

• Developmental Biology
• Genomics
• Bioinformatics

Background:

• Automated in situ hybridization generates comprehensive gene expression atlases.
• These atlases serve as digital expression maps for understanding genetic interactions and signaling pathways.

Purpose of the Study:

• To construct a gene expression atlas of the midgestation mouse embryo.
• To identify novel components of developmental signaling cascades using cluster analysis.

Main Methods:

• Generated an atlas of ~1,000 spatial gene expression patterns in mouse embryos.
• Annotated patterns using a controlled vocabulary (>90 anatomical features).
• Performed hierarchical clustering on annotations to group similar expression patterns.

Main Results:

• Clustering yielded 12 distinct groups of expression patterns, suggesting co-regulation.
• Focused on a Pax6-containing group; 17/82 genes altered in Pax6-deficient embryos.
• Identified 12 novel potential Pax6 target genes using electromobility shift assays.

Conclusions:

• Cluster analysis of annotated gene expression patterns is a novel approach for identifying signaling cascade components.
• This method successfully identified novel Pax6 targets, highlighting its utility in developmental gene regulation studies.