A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions That Regulate Complex Traits.

摘要: The genetic contribution of additive versus non-additive (epistatic) effects in the regulation complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, part because lack statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate approach epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both epistatic loci that regulate a range hematologic- metabolism-related traits, as well hepatic gene expression. Quantitative trait (QTLs) were identified using CSS-based backcross strategy involving segregation variants on A/J-derived substituted chromosomes 4 6 otherwise C57BL/6J background. In liver transcriptomes offspring from this cross, mapped QTLs regulating expression 768 genes, QTL pairs 519 genes. Similarly, fat pad weight, platelets, percentage granulocytes blood, controlling lymphocytes blood red cell distribution width. variance attributed was approximately equal QTLs; however, SNPs accounted largest variances undetected our single locus analyses. These findings highlight need account studies, more broadly demonstrate importance identifying interactions understand complete architecture traits.