Academic journal article Genetics

High-Resolution Genetic Mapping of Complex Traits from a Combined Analysis of F^sub 2^ and Advanced Intercross Mice

Academic journal article Genetics

High-Resolution Genetic Mapping of Complex Traits from a Combined Analysis of F^sub 2^ and Advanced Intercross Mice

Article excerpt

ANXIETY disorders are among the most prevalent psychiatric disorders in the world; in the United States, they affect the lives of ~18% of the adult population (Demyttenaere et al. 2004; Kessler et al. 2005a,b). Many of these debilitating illnesses can be characterized by exagger- ations of normal and adaptive emotional response to fearful or stressful events (Mahan and Ressler 2012). Twin and family studies support a genetic basis for anxiety disorders, but attempts to identify the underlying genetic substrates have been disappointing-to date, genome-wide associa- tion studies (GWAS) have not reliably replicated candi- date genes associated with anxiety disorders (Hettema et al. 2011). As a result, we have little knowledge of the specific genes that underlie these disorders. Genetic loci relevant to these disorders may be difficult to map via GWAS be- cause anxiety disorders are only modestly heritable and, like many psychiatric conditions, are expected to be highly polygenic-that is, modulated by a large number of genetic factors with individually small effects (Sullivan et al. 2012). Therefore, genetic contributions to anxiety are likely to be difficult to distinguish from correlations that occur by chance alone (Flint 2011; Parker and Palmer 2011; Flint and Eskin 2012).

While the full spectrum of any human psychiatric dis- order can never be fully recapitulated in a single mouse model, there is substantial behavioral, genetic, and neuro- anatomical conservation between humans and mice. When broken down into individual components, many of the symp- toms of anxiety disorders can be modeled in mice. Thus, translational mouse models can provide a powerful strategy for understanding the genetic and biological underpinnings of the acquisition of fear, as well as the etiologic processes related to anxiety (Kalueff et al. 2007; Flint and Shifman 2008; Hovatta and Barlow 2008). Animal models provide similarly strong models for comorbidity of traits, like evidence for a shared genetic substrate in anxiety and fear. For example, selective breeding paradigms in mice and rats have shown that selection of anxiety-like behavior also selects for differences in fear and vice versa (Ponder et al. 2007a; López-Aumatell et al. 2009).

Reverse genetic approaches using genetically modified mice have been important for testing hypotheses about specific genes relevant to fear and anxiety, but they have tended to focus on the "usual suspects" underlying anxiety disorders. Alternatively, forward genetic approaches in mice have been developed to measure phenotypes and identify the underly- ing sources of standing genetic variability in these pheno- types without prior hypotheses. However, forward genetic approaches have been less successful at identifying relevant genes. This may be because forward genetic studies in mice have traditionally used recombinant inbred (RI) lines, back- crosses (BC), or F^sub 2^ intercrosses to identify quantitative trait loci (QTL)-in these experimental crosses, we can have high statistical power to detect genetic loci, but poor mapping resolution due to limited recombination (Cheng et al. 2010; Flint 2011; Parker and Palmer 2011).

To better pinpoint candidate genes and genetic loci that might influence anxiety, we mapped QTL in a combined F^sub 2^ intercross and an F34 advanced intercross line (AIL). An AIL is created by successive generations of pseudorandom mat- ing after the F^sub 2^ generation. Each additional generation leads to the accumulation of new recombinations, which allows for more precise mapping due to a breakdown in linkage disequilibrium. We show that our analysis not only yields strong support for several QTL in anxiety-related pheno- types, but also highlights a narrower set of candidate genes than previous studies of these phenotypes.

AILs have been employed in several previous studies to successfully map QTL for complex traits in mice, including locomotor activity (Cheng et al. …

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