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A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions
Anna K Miller1, Anlu Chen2, Jacquelaine Bartlett3
1Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106.
G3 (Bethesda, Md.)
|October 7, 2020
Summary
Mouse chromosome substitution strains reveal that gene interactions (epistasis) significantly influence complex traits, impacting blood cell counts and gene expression. These interactions are crucial for a complete understanding of genetic architecture.
Area of Science:
- Genetics
- Systems Biology
- Quantitative Genetics
Background:
- The relative contributions of additive and non-additive (epistatic) genetic effects to complex traits remain poorly understood.
- Genome-wide association studies often overlook gene-gene interactions due to statistical power limitations.
- Mouse chromosome substitution strains (CSSs) offer a valuable model for detecting epistasis due to reduced allelic variation.
Purpose of the Study:
- To utilize CSSs to identify and map both additive and epistatic quantitative trait loci (QTL) controlling hematologic, metabolism, and hepatic gene expression traits.
- To compare the variance explained by additive versus epistatic effects in complex traits.
- To assess the detectability of epistatic single nucleotide polymorphisms (SNPs) in traditional association analyses.
Main Methods:
- Employed a CSS-based backcross strategy using A/J-derived chromosomes 4 and 6 on a C57BL/6J background.
- Analyzed segregation of variants to identify additive and epistatic QTL.
- Quantified trait variation attributed to identified QTL for various hematologic, metabolic, and hepatic gene expression traits.
Main Results:
- Identified additive QTL for 768 hepatic gene expression traits and epistatic QTL pairs for 519 genes.
- Detected additive QTL for fat pad weight, platelets, and granulocyte percentage.
- Found epistatic QTL pairs controlling lymphocyte percentage and red cell distribution width, explaining variance comparable to additive QTL.
- Observed that significant epistatic SNPs were missed by single-locus association analyses.
Conclusions:
- Epistatic interactions play a substantial role in the genetic architecture of complex traits, comparable to additive effects.
- The study underscores the necessity of incorporating epistasis into genetic association studies for a comprehensive understanding.
- Mouse chromosome substitution strains are effective for dissecting complex genetic interactions and mapping epistatic loci.
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