Dataset Information

Dog and mouse: toward a balanced view of the mammalian olfactory system.

ABSTRACT: Although the most intensively studied mammalian olfactory system is that of the mouse, in which olfactory chemical cues of one kind or another are detected in four different nasal areas [the main olfactory epithelium (MOE), the septal organ (SO), Grüneberg's ganglion, and the sensory epithelium of the vomeronasal organ (VNO)], the extraordinarily sensitive olfactory system of the dog is also an important model that is increasingly used, for example in genomic studies of species evolution. Here we describe the topography and extent of the main olfactory and vomeronasal sensory epithelia of the dog, and we report finding no structures equivalent to the Grüneberg ganglion and SO of the mouse. Since we examined adults, newborns, and fetuses we conclude that these latter structures are absent in dogs, possibly as the result of regression or involution. The absence of a vomeronasal component based on VR2 receptors suggests that the VNO may be undergoing a similar involutionary process.

SUBMITTER: Barrios AW

PROVIDER: S-EPMC4174761 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Dog and mouse: toward a balanced view of the mammalian olfactory system.

Barrios Arthur W AW Sánchez-Quinteiro Pablo P Salazar Ignacio I

Frontiers in neuroanatomy 20140925

Although the most intensively studied mammalian olfactory system is that of the mouse, in which olfactory chemical cues of one kind or another are detected in four different nasal areas [the main olfactory epithelium (MOE), the septal organ (SO), Grüneberg's ganglion, and the sensory epithelium of the vomeronasal organ (VNO)], the extraordinarily sensitive olfactory system of the dog is also an important model that is increasingly used, for example in genomic studies of species evolution. Here w ...[more]

PMID: 25309347

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Project description:Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone.

Project description:The uptake, transmission and processing of sensory olfactory information is modulated by inhibitory and excitatory receptors in the olfactory system. Previous studies have focused on the function of individual receptors in distinct brain areas, but the receptor architecture of the whole system remains unclear. Here, we analyzed the receptor profiles of the whole olfactory system of adult male mice. We examined the distribution patterns of glutamatergic (AMPA, kainate, mGlu2/3, and NMDA), GABAergic (GABAA, GABAA(BZ), and GABAB), dopaminergic (D1/5) and noradrenergic (α1 and α2) neurotransmitter receptors by quantitative in vitro receptor autoradiography combined with an analysis of the cyto- and myelo-architecture. We observed that each subarea of the olfactory system is characterized by individual densities of distinct neurotransmitter receptor types, leading to a region- and layer-specific receptor profile. Thereby, the investigated receptors in the respective areas and strata showed a heterogeneous expression. Generally, we detected high densities of mGlu2/3Rs, GABAA(BZ)Rs and GABABRs. Noradrenergic receptors revealed a highly heterogenic distribution, while the dopaminergic receptor D1/5 displayed low concentrations, except in the olfactory tubercle and the dorsal endopiriform nucleus. The similarities and dissimilarities of the area-specific multireceptor profiles were analyzed by a hierarchical cluster analysis. A three-cluster solution was found that divided the areas into the (1) olfactory relay stations (main and accessory olfactory bulb), (2) the olfactory cortex (anterior olfactory cortex, dorsal peduncular cortex, taenia tecta, piriform cortex, endopiriform nucleus, entorhinal cortex, orbitofrontal cortex) and the (3) olfactory tubercle, constituting its own cluster. The multimodal receptor-architectonic analysis of each component of the olfactory system provides new insights into its neurochemical organization and future possibilities for pharmaceutic targeting.

Dataset Information

Dog and mouse: toward a balanced view of the mammalian olfactory system.

Publications

Dog and mouse: toward a balanced view of the mammalian olfactory system.

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