Functional Genomic Architecture of Predisposition to Voluntary Exercise in Mice: Expression QTL in the Brain

Kelly, Scott A.; Nehrenberg, Derrick L.; Hua, Kunjie; Garland, Theodore; Pomp, Daniel

doi:10.1534/genetics.112.140509

Cited by 32 publications

(39 citation statements)

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“…We also present evidence that some of these gene polymorphisms may have some translational effects, although care must be taken not to overstress these results. This approach is obviously costly in terms of the number of individuals required for the eQTL analysis and to date has to our knowledge been used only to identify QTG for startle-induced locomotion behavior (among other ecological phenotypes) in Drosophila (Ayroles et al 2009), exercise behavior in mice (Kelly et al 2012), and tameness in rats (Heyne et al 2014), but has enormous potential. Here we use this technique to identify gene variants affecting anxiety for the first time in chickens.…”

Section: Discussionmentioning

confidence: 99%

Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior

et al. 2015

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The identification of genetic variants responsible for behavioral variation is an enduring goal in biology, with wide-scale ramifications, ranging from medical research to evolutionary theory on personality syndromes. Here, we use for the first time a largescale genetical genomics analysis in the brains of chickens to identify genes affecting anxiety as measured by an open field test. We combine quantitative trait locus (QTL) analysis in 572 individuals and expression QTL (eQTL) analysis in 129 individuals from an advanced intercross between domestic chickens and Red Junglefowl. We identify 10 putative quantitative trait genes affecting anxiety behavior. These genes were tested for an association in the mouse Heterogeneous Stock anxiety (open field) data set and human GWAS data sets for bipolar disorder, major depressive disorder, and schizophrenia. Although comparisons between species are complex, associations were observed for four of the candidate genes in mice and three of the candidate genes in humans. Using a multimodel approach we have therefore identified a number of putative quantitative trait genes affecting anxiety behavior, principally in chickens but also with some potentially translational effects as well. This study demonstrates that chickens are an excellent model organism for the genetic dissection of behavior.

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Section: Discussionmentioning

confidence: 99%

Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior

et al. 2015

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“…For example, the position-dependent strategy could be combined with mRNA expression profiles to identify candidate genes associated with a trait as reported by Kelly et al [41]. The combination strategy was also used by Liu et al [49] to identify genes that confer resistance to Marek's disease among resistant and susceptible chickens, and by Schwerin et al [70] to identify functional candidate genes associated with mastitis in dairy cattle.…”

Section: The Candidate Gene Approachmentioning

confidence: 99%

Complicated Relationships: A Review of Biological Interaction Networks and Pathways in Animal Science

Karisa

Moore

Plastow

2013

Springer Science Reviews

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The availability of high-throughput genomic technologies has resulted in the identification of millions of DNA polymorphisms, candidate genes and metabolites associated with several economically important traits in livestock production. However, despite the increase in DNA markers and candidate genes associated with these productivity traits, only a small proportion of phenotypic variation in these traits can be explained. This missing heritability creates a need to address the other levels of regulation of gene expression such as the levels occurring post-translation including metabolites. There is also need to use biological network analysis to understand the complex relationships and interactions among genes, metabolites, and markers in shaping the traits of economic importance in livestock production. At the moment, biological network analysis is still in its infancy in animal science; however, it has a great potential to create a holistic view of the underlying biological mechanisms associated with the variation in important traits in livestock production. The goal is to describe some of the approaches used to identify novel DNA variants associated with economically important traits in livestock and address biological interaction network reconstruction, analysis, and application in research in animal science.

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“…Such Musunuru et al 2010). A few eQTL studies have also recently been carried out to identify candidate genes for behavioral QTL (Hitzemann et al 2004;De Jong et al 2011;Saba et al 2011;Kelly et al 2012).Here, we studied two lines of rats (Rattus norvegicus) that, starting from one wild population, have been selected for increased tameness and increased aggression toward humans, respectively. These experimental populations derive from the work of Dmitry K. Belyaev who, along with his famous related work in foxes (Belyaev 1979;Trut 1999), initiated the rat lines to study the evolution and underlying biological mechanisms of tameness as a crucial first step in animal domestication (Diamond 1999;Trut 1999;Wiener and Wilkinson 2011).…”

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confidence: 99%

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confidence: 99%

“…This approach has been successfully applied to quantitative traits in different species, e.g., yeast (Perlstein et al 2007), rats (Hubner et al 2005;Heinig et al 2010), mice (Mehrabian et al 2005;Schadt et al 2005), and humans (Moffatt et al 2007;Musunuru et al 2010). A few eQTL studies have also recently been carried out to identify candidate genes for behavioral QTL (Hitzemann et al 2004;De Jong et al 2011;Saba et al 2011;Kelly et al 2012).…”

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Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

Heyne

Lautenschlaeger²,

Nelson

et al. 2014

Preprint

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Interindividual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F 2 intercross of two outbred lines of rats selected for tame and aggressive behavior toward humans for .64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F 2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F 2 animals, we identify the genes Gltscr2, Lgi4, Zfp40, and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals. B EHAVIORAL differences among members of a species are in part due to genetic variation. The identification of the genes and variants that influence behavior remains challenging. In human genome-wide association studies of psychiatric and cognitive traits, the identified loci typically explain only a small fraction of the heritability, i.e., the additive genetic contribution to the trait (Watanabe et al. 2007;Hovatta and Barlow 2008;Deary et al. 2009;Otowa et al. 2009;Calboli et al. 2010;Terracciano et al. 2010;Flint and Munafo 2013;Rietveld et al. 2013;Sokolowska and Hovatta 2013). In experimental crosses in model species, especially between inbred lines, the identified loci (termed quantitative trait loci, QTL), often explain much more of the heritability (Lynch and Walsh 1998). However, in this design the spatial resolution is limited-the QTL are wide and contain many, sometimes hundreds of genes. With the exception of a handful of identified genes with quantitative effects on behavioral traits (Yalcin et al. 2004;Watanabe et al. 2007;McGrath et al. 2009;Bendesky et al. 2012;Goodson et al. 2012), gene identification is particularly difficult for behavioral QTL that often have modest effect sizes (Flint 2003;Willis-Owen and Flint 2006;Wright et al. 2006;Hovatta and Barlow 2008).The causal variants within a QTL can alter the protein sequence encoded by a gene or affect gene expression. Such Musunuru et al. 2010). A few eQTL studies have also recently been carried out to identify candidate genes for behavioral QTL (Hitzemann et al. 2004;De Jong et al. 2011;Saba et al. 2011;Kelly et al. 2012).Here, we studied two lines of rats (Rattus norvegicus) that, starting from one wild population, have been selected for increased tameness and increased aggression toward humans, respectively. These experimental...

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Functional Genomic Architecture of Predisposition to Voluntary Exercise in Mice: Expression QTL in the Brain

Cited by 32 publications

References 71 publications

Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior

Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior

Complicated Relationships: A Review of Biological Interaction Networks and Pathways in Animal Science

Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

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