Functional coding variation in recombinant inbred mouse lines reveals multiple serotonin transporter-associated phenotypes.

Document Type

Article

Publication Date

2009

Keywords

Animals, Behavior-Animal, Computational-Biology, Dopamine, Iron, Mesencephalon, Mice-Inbred-Strains, Phenotype, Polymorphism-Genetic, Serotonin, Serotonin-Plasma-Membrane-Transport-Proteins

First Page

2047

Last Page

2052

JAX Source

Proc Natl Acad Sci U S A 2009 Feb; 106(6):2047-52.

Abstract

The human serotonin (5-hydroxytryptamine, 5-HT) transporter (hSERT, SLC6A4) figures prominently in the etiology and treatment of many prevalent neurobehavioral disorders including anxiety, alcoholism, depression, autism, and obsessive-compulsive disorder (OCD). Here, we use naturally occurring polymorphisms in recombinant inbred (RI) lines to identify multiple phenotypes associated with altered SERT function. The widely used mouse strain C57BL/6J, harbors a SERT haplotype defined by 2 nonsynonymous coding variants [Gly-39 and Lys-152 (GK)]. At these positions, many other mouse lines, including DBA/2J, encode, respectively, Glu-39 and Arg-152 (ER haplotype), amino acids found also in hSERT. Ex vivo synaptosomal 5-HT transport studies revealed reduced uptake associated with the GK variant, a finding confirmed by in vitro heterologous expression studies. Experimental and in silico approaches using RI lines (C57BL/6J x DBA/2J = BXD) identify multiple anatomical, biochemical, and behavioral phenotypes specifically impacted by GK/ER variation. Among our findings are several traits associated with alcohol consumption and multiple traits associated with dopamine signaling. Further bioinformatic analysis of BXD phenotypes, combined with biochemical evaluation of SERT knockout mice, nominates SERT-dependent 5-HT signaling as a major determinant of midbrain iron homeostasis that, in turn, dictates iron-regulated DA phenotypes. Our studies provide an example of the power of coordinated in vitro, in vivo, and in silico approaches using mouse RI lines to elucidate and quantify the system-level impact of gene variation.

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