Genome-Wide Epistatic Interaction Analysis Reveals Complex Genetic Determinants of Circadian Behavior in Mice

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Abstract
Genetic heterogeneity underlies many phenotypic variations observed in circadian rhythmicity. Continuous distributions in measures of circadian behavior observed among multiple inbred strains of mice suggest that the inherent contributions to variability are polygenic in nature. To identify genetic loci that underlie this complex behavior, we have carried out a genome-wide complex trait analysis in 196 (C57BL/6J X BALB/cJ)F2 hybrid mice. We have characterized variation in this panel of F2 mice among five circadian phenotypes: free-running circadian period, phase angle of entrainment, amplitude of the circadian rhythm, circadian activity level, and dissociation of rhythmicity. Our genetic analyses of these phenotypes have led to the identification of 14 loci having significant effects on this behavior, including significant main effect loci that contribute to three of these phenotypic measures: period, phase, and amplitude. We describe an additional locus detection method, genome-wide genetic interaction analysis, developed to identify locus pairs that may interact epistatically to significantly affect phenotype. Using this analysis, we identified two additional pairs of loci that have significant effects on dissociation and activity level; we also detected interaction effects in loci contributing to differences of period, phase, and amplitude. Although single gene mutations can affect circadian rhythms, the analysis of interstrain variants demonstrates that significant genetic complexity underlies this behavior. Importantly, most of the loci that we have detected by these methods map to locations that differ from the nine known clock genes, indicating the presence of additional clock-relevant genes in the mammalian circadian system. These data demonstrate the analytical value of both genome-wide complex trait and epistatic interaction analyses in further understanding complex phenotypes, and point to promising approaches for genetic analysis of such phenotypes in other mammals, including humans.