GMMID: genetically modified mice information database.

Area of Science:

• Genetics and Bioinformatics
• Mouse Models in Research
• Database Development

Background:

• Genetically engineered mouse models (GEMMs) are essential for understanding gene function and disease.
• Current databases lack detailed biological descriptions of allele compositions and associated human diseases.
• This limits the utility of GEMMs as models for human diseases and hinders cross-disciplinary research.

Purpose of the Study:

• To develop a comprehensive and user-friendly database for genetically modified mice information.
• To address the limitations of existing databases by integrating detailed genetic and disease-related data.
• To facilitate efficient access to complex genetic information for researchers across various disciplines.

Main Methods:

• Developed a Python-based algorithm to annotate allele compositions.
• Integrated data from multiple sources including NCBI, MGI, OMIM, IMPC, and Jax lab.
• Created the Genetically Modified Mice Information Database (GMMID) with a focus on user-friendliness.

Main Results:

• GMMID provides comprehensive genetic information for over 70,055 alleles and 65,520 allele compositions.
• The database includes information on approximately 4,000 associated human diseases.
• Offers biologically meaningful descriptions of alleles and allele combinations, with spatiotemporal visualization of anatomical tissues.

Conclusions:

• GMMID enhances the accessibility and interpretability of complex genetic data for GEMMs.
• The database serves as a valuable, efficient resource for cross-disciplinary researchers studying gene function and human diseases.
• GMMID significantly improves upon existing resources by integrating diverse data types and providing clear biological context.