MouseFM

MouseFM performs fine-mapping of genotype–phenotype associations by integrating whole-genome sequencing–based genotypes from 37 inbred mouse strains (>74 million variant sites) with user-provided phenotypes to identify candidate variants and genes.

Key Features:

• Comprehensive Genomic Data Integration: Uses whole-genome sequencing–based genotype data from 37 inbred mouse strains covering over 74 million variant sites for variant-level queries.
• Phenotype-Driven Fine-Mapping: Compares user-provided phenotypes across strains to identify variants compatible with observed phenotypic differences and to generate candidate gene lists.
• Variant Annotation and Filtering: Allows filtering of variants based on molecular consequence and predicted impact to prioritize candidate variants and genes.
• eQTL Fine-Mapping Application: Applied to expression datasets across 20 inbred strains, including neutrophils and CD4+ T cells, fine-mapping approximately 10,000 genes per dataset and identifying candidate variants and haplotypes associated with reported eQTLs.
• Case Studies: Identified a single moderate- or high-impact variant in the Tyr gene for albinism; identified 12 candidate genes (three linked to skull-shaping abnormalities) for interfrontal bone formation; and identified a moderate-impact variant in Abcc6 for dystrophic cardiac calcification.

Scientific Applications:

• Candidate variant and gene identification: Mapping genotype–phenotype relationships in inbred mouse strains to generate hypotheses for functional validation.
• Expression QTL mapping: Fine-mapping eQTLs in immune cell expression datasets such as neutrophils and CD4+ T cells.
• Trait-specific genetic studies: Investigating genetic bases of traits including albinism, interfrontal bone formation, and dystrophic cardiac calcification.
• Functional genomics and disease modeling: Prioritizing variants and genes for downstream experimental validation in developmental biology and disease research.

Methodology:

Integrates whole-genome sequencing genotype data from 37 inbred strains and performs phenotype-driven fine-mapping by querying genotypes compatible with strain phenotypes, filtering variants by molecular consequence and impact, and applying the same approach to expression datasets from 20 strains to fine-map ~10,000 genes per dataset and identify candidate variants and haplotypes associated with reported eQTLs.