A gene expression resource generated by genome-wide lacZ profiling in the mouse

Area of Science:

• Genomics and Bioinformatics
• Developmental Biology
• Molecular Genetics

Background:

• Understanding gene expression profiles is crucial for discerning normal gene function and roles in disease.
• International efforts are underway to characterize reporter-tagged knockout mouse lines for large-scale gene expression analysis.

Purpose of the Study:

• To establish an open-access adult mouse expression resource detailing the expression profiles of 424 genes.
• To analyze gene expression patterns in up to 47 organs, tissues, and substructures using a lacZ reporter gene.
• To investigate the relationship between gene expression complexity and the viability of homozygous null animals.

Main Methods:

• Utilized a lacZ reporter gene to assess the expression profile of 424 genes in adult mice.
• Examined gene expression across up to 47 distinct anatomical structures.
• Validated the generated expression data against the Bgee database, a composite of RNA-based expression datasets.

Main Results:

• Identified specific and informative expression patterns for the assessed genes, with common expression in the testis and brain, and restricted expression in white adipose tissue and mammary gland.
• Observed that over half of the genes exhibited absent or localized expression patterns (0-10 positive structures).
• Found a correlation between expression complexity and viability, where genes expressed in 21 or more structures were more likely to result in reduced viability by postnatal day 14.
• Reported 1207 novel observations of gene expression in anatomical structures not previously documented in Bgee.

Conclusions:

• The developed mouse expression resource provides a valuable, open-access dataset with high specificity, validated against existing databases.
• The findings highlight a link between the complexity of a gene's expression profile and the viability of its homozygous null mutants.
• This resource offers significant potential for corroborating genotype-phenotype associations, identifying disease gene candidates, and advancing our understanding of gene function.