Gamma-protocadherins regulate the functional integrity of hypothalamic feeding circuitry in mice.

The hypothalamic neuronal circuits that modulate energy homeostasis become mature and functional during early postnatal life. However, the molecular mechanism underlying this developmental process remains largely unknown. Here we use a mouse genetic approach to investigate the role of gamma-protocadherins (Pcdh-gammas) in hypothalamic neuronal circuits. First, we show that rat insulin promoter (RIP)-Cre conditional knockout mice lacking Pcdh-gammas in a broad subset of hypothalamic neurons are obese and hyperphagic. Second, specific deletion of Pcdh-gammas in anorexigenic proopiomelanocortin (POMC) expressing neurons also leads to obesity. Using cell lineage tracing, we show that POMC and RIP-Cre expressing neurons do not overlap but interact with each other in the hypothalamus. Moreover, excitatory synaptic inputs are reduced in Pcdh-gamma deficient POMC neurons. Genetic evidence from both knockout models shows that Pcdh-gammas can regulate POMC neuronal function autonomously and non-autonomously through cell-cell interaction. Taken together, our data demonstrate that Pcdh-gammas regulate the formation and functional integrity of hypothalamic feeding circuitry in mice.

Genomewide association analysis in diverse inbred mice: power and population structure.

The discovery of quantitative trait loci (QTL) in model organisms has relied heavily on the ability to perform controlled breeding to generate genotypic and phenotypic diversity. Recently, we and others have demonstrated the use of an existing set of diverse inbred mice (referred to here as the mouse diversity panel, MDP) as a QTL mapping population. The use of the MDP population has many advantages relative to traditional F(2) mapping populations, including increased phenotypic diversity, a higher recombination frequency, and the ability to collect genotype and phenotype data in community databases. However, these methods are complicated by population structure inherent in the MDP and the lack of an analytical framework to assess statistical power. To address these issues, we measured gene expression levels in hypothalamus across the MDP. We then mapped these phenotypes as quantitative traits with our association algorithm, resulting in a large set of expression QTL (eQTL). We utilized these eQTL, and specifically cis-eQTL, to develop a novel nonparametric method for association analysis in structured populations like the MDP. These eQTL data confirmed that the MDP is a suitable mapping population for QTL discovery and that eQTL results can serve as a gold standard for relative measures of statistical power.