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A high-resolution association mapping panel for the dissection of complex traits in mice
Brian J Bennett1, Charles R Farber, Luz Orozco
1Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA.
Genome Research
|January 8, 2010
Summary
This study introduces a novel mouse association mapping strategy combining inbred and recombinant strains. This approach significantly improves mapping resolution for complex traits and gene expression quantitative trait loci (eQTLs).
Area of Science:
- Genetics
- Systems Biology
- Genomics
Background:
- Systems genetics utilizes genetic variants to understand complex disease networks.
- Mouse models are crucial, but traditional linkage analysis offers limited resolution.
- Mouse association analysis faces challenges with population structure and statistical power for small-effect quantitative trait loci (QTL).
Purpose of the Study:
- To develop a novel association mapping strategy in mice with enhanced resolution and power.
- To overcome limitations of traditional QTL mapping in mouse models.
- To facilitate systems-based approaches for complex traits and gene-environment interactions.
Main Methods:
- Combined classic inbred strains (for resolution) and recombinant inbred strains (for power).
- Employed a mixed-model algorithm to correct for population structure.
- Validated the approach by mapping cis-expression QTL and metabolic traits.
Main Results:
- Successfully mapped over 2500 cis-expression QTL with resolution an order of magnitude finer than traditional methods.
- Achieved fine mapping of metabolic traits, including plasma lipids.
- Developed the Hybrid Mouse Diversity Panel resource.
Conclusions:
- The novel association mapping strategy significantly enhances QTL mapping resolution and power in mice.
- The Hybrid Mouse Diversity Panel provides a valuable resource for integrating diverse datasets.
- This approach is highly beneficial for systems genetics, complex trait analysis, and gene-environment interaction studies.
