Single genes and complex phenotypes

Low, Malcolm J.; Kelly, MJ; Rubinstein, Marcelo; Grandy, David K.

doi:10.1038/sj.mp.4000455

Cited by 6 publications

(2 citation statements)

References 5 publications

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“…Incipient congenic mice were used in the current studies, which provides the advantage of greater genetic homogeneity with regard to almost all loci except Drd2. This drastically reduces the possibility of obtaining a difference between knockout and wild-type mice that could be due to a gene closely linked to Drd2, and therefore systematically varying between the +/+ and -/-genotypes, as was observed in a study of rotarod ataxia in second-generation, F2 (129/Sv,C57BL/6J), D 2 +/+ and D 2 -/-mice 42,48 . However, a more complete evaluation of the role of D 2 receptors in ethanol reward and sensitivity would require studying the knockout on several genetic backgrounds.…”

Section: Discussionmentioning

confidence: 99%

Alcohol preference and sensitivity are markedly reduced in mice lacking dopamine D2 receptors

et al. 1998

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Although dopaminergic transmission has been strongly implicated in alcohol self-administration, the involvement of specific dopamine receptor subtypes has not been well established. We studied the ethanol preference and sensitivity of D2-receptor-deficient mice to directly evaluate whether dopamine D2 receptors contribute to alcohol (ethanol) consumption. We report a marked aversion to ethanol in these mice, relative to the high preference and consumption exhibited by wild-type littermates. Sensitivity to ethanol-induced locomotor impairment was also reduced in these mutant mice, although they showed a normal locomotor depressant response to the dopamine D1 antagonist SCH-23390. These data demonstrate that dopamine signaling via D2 receptors is an essential component of the molecular pathway determining ethanol self-administration and sensitivity.

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Section: Discussionmentioning

confidence: 99%

Alcohol preference and sensitivity are markedly reduced in mice lacking dopamine D2 receptors

et al. 1998

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“…These issues have been well discussed. Examples of the complications which can arise, and recommendations for controlling genetic background and other effects, appear in the literature (Crusio 1996;Gerlai 1996;Lathe 1996;Banbury Conference 1997;Kelly et al 1998;Low et al 1998;Phillips et al 1999;Gingrich & Hen 2000).…”

Section: Phillips Et Almentioning

confidence: 99%

Harnessing the mouse to unravel the genetics of human disease

Phillips

Belknap

Hitzemann

et al. 2002

Genes Brain and Behavior

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Complex traits, i.e. those with multiple genetic and environmental determinants, represent the greatest challenge for genetic analysis, largely due to the difficulty of isolating the effects of any one gene amid the noise of other genetic and environmental influences. Methods exist for detecting and mapping the Quantitative Trait Loci (QTLs) that influence complex traits. However, once mapped, gene identification commonly involves reduction of focus to single candidate genes or isolated chromosomal regions. To reach the next level in unraveling the genetics of human disease will require moving beyond the focus on one gene at a time, to explorations of pleiotropism, epistasis and environment-dependency of genetic effects. Genetic interactions and unique environmental features must be as carefully scrutinized as are single gene effects. No one genetic approach is likely to possess all the necessary features for comprehensive analysis of a complex disease. Rather, the entire arsenal of behavioral genomic and other approaches will be needed, such as random mutagenesis, QTL analyses, transgenic and knockout models, viral mediated gene transfer, pharmacological analyses, gene expression assays, antisense approaches and importantly, revitalization of classical genetic methods. In our view, classical breeding designs are currently underutilized, and will shorten the distance to the target of understanding the complex genetic and environmental interactions associated with disease. We assert that unique combinations of classical approaches with current behavioral and molecular genomic approaches will more rapidly advance the field.

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