Differential expression of cell adhesion molecules in neuronal populations is one of the many mechanisms promoting the formation of functional neural circuits in the developing nervous system. The IgLON family consists of five cell surface immunoglobulin proteins that have been associated with various developmental disorders, such as autism spectrum disorder, schizophrenia, and major depressive disorder. However, there is still limited and fragmented information about their patterns of expression in certain regions of the developing nervous system and how their expression contributes to their function. Utilizing an in situ hybridization approach, we have analyzed the spatiotemporal expression of all IgLON family members in the developing mouse brain, spinal cord, eye, olfactory epithelium, and vomeronasal organ. At one prenatal (E16) and two postnatal (P0 and P15) ages, we show that each IgLON displays distinct expression patterns in the olfactory system, cerebral cortex, midbrain, cerebellum, spinal cord, and eye, indicating that they likely contribute to the wiring of specific neuronal circuitry. These analyses will inform future functional studies aimed at identifying additional roles for these proteins in nervous system development.
Glomeruli are neuropil rich regions of the main or accessory olfactory bulbs where the axons of olfactory or vomeronasal neurons and dendrites of mitral/tufted cells form synaptic connections. In the main olfactory system olfactory sensory neurons (OSNs) expressing the same receptor innervate one or two glomeruli. However, in the accessory olfactory system, vomeronasal sensory neurons (VSNs) expressing the same receptor can innervate up to 30 different glomeruli in the accessory olfactory bulb (AOB). Genetic mutation disrupting genes with a role in defining the identity/diversity of olfactory and vomeronasal neurons can alter the number and size of glomeruli. Interestingly, two cell surface molecules, Kirrel2 and Kirrel3, have been indicated as playing a critical role in the organization of axons into glomeruli in the AOB. Being able to quantify differences in glomeruli features, such as number, size or immunoreactivity for specific markers, is an important experimental approach to validate the role of specific genes in controlling neuronal connectivity and circuit formation in either control or mutant animals. Since the manual recognition and quantification of glomeruli on digital images is a challenging and time-consuming task, we generated a program in Python able to identify glomeruli in digital images and quantify their properties, such as size, number, and pixel intensity. Validation of our program indicates that our script is a fast and suitable tool for high throughput quantification of glomerular features of mouse lines with different genetic makeup.
Glomeruli are neuropil rich regions of the main or accessory olfactory bulbs where the axons of olfactory or vomeronasal neurons and dendrites of mitral/tufted cells form synaptic connections. In the main olfactory system olfactory sensory neurons (OSNs) expressing the same receptor innervate one or two glomeruli. However, in the accessory olfactory system, vomeronasal sensory neurons (VSNs) expressing the same receptor can innervate up to 30 different glomeruli in the accessory olfactory bulb (AOB). Genetic mutation disrupting genes with a role in defining the identity/diversity of olfactory and vomeronasal neurons can alter number and size of glomeruli. Interestingly, two cell surface molecules, Kirrel2 and Kirrel3, have been indicated to play a critical role in the organization of axons into glomeruli in the AOB. Being able to quantify differences in glomeruli features such as number, size or immunoreactivity for specific markers is an important experimental approach to validate the role of specific genes in controlling neuronal connectivity and circuit formation in control or mutant animals. Since the manual recognition and quantification of glomeruli on digital images is a challenging and time-consuming task, we generated a program in Python able to identify glomeruli in digital images and quantify their properties, such as size, number, and pixel intensity. Validation of our program indicates that our script is a fast and suitable tool for high throughput quantification of glomerular features of mouse lines with different genetic makeup.
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