Genome-wide association of multiple complex traits in outbred mice by ultra-low-coverage sequencing

Area of Science:

• Genetics
• Genomics
• Mammalian Biology

Background:

• Genetic analysis of complex traits in rodents faces challenges with mapping populations and reference panels.
• Developing gene-level mapping resolution is crucial for understanding trait heritability.

Purpose of the Study:

• To overcome bottlenecks in rodent genetic analysis by combining low-coverage sequencing with haplotype imputation.
• To achieve gene-level mapping resolution for quantitative trait loci (QTLs) in outbred mice.

Main Methods:

• Utilized low-coverage (0.15×) whole-genome sequencing for 1,887 commercially available outbred mice.
• Developed and applied a novel imputation method to reconstruct the ancestral haplotype space.
• Performed genome-wide association studies (GWAS) to map QTLs for 92 phenotypes.

Main Results:

• Successfully mapped 156 unique QTLs across 92 phenotypes with a 5% false discovery rate.
• Achieved gene-level mapping resolution at approximately 20% of the identified QTLs.
• Identified specific genes (e.g., Unc13c, Pgc1a, Adarb2, Bmp2, Il15, Id2, Prkca) associated with various traits including sleep quality, activity, and immune response.

Conclusions:

• Low-coverage sequencing combined with haplotype imputation is effective for genetic analysis in highly recombinant outbred populations.
• This approach extends the utility of GWAS in species previously limited by the need for specialized genotyping arrays.
• Findings provide insights into the genetic architecture of complex traits in mammals and facilitate future research.