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It has long been thought that the mammalian visual system is organized into parallel pathways, with incoming visual signals being parsed in the retina based on feature (e.g. color, contrast and motion) and then transmitted to the brain in unmixed, feature-specific channels. To faithfully convey feature-specific information from retina to cortex, thalamic relay cells must receive inputs from only a small number of functionally similar retinal ganglion cells. However, recent studies challenged this by revealing substantial levels of retinal convergence onto relay cells. Here, we sought to identify mechanisms responsible for the assembly of such convergence. Using an unbiased transcriptomics approach and targeted mutant mice, we discovered a critical role for the synaptic adhesion molecule Leucine Rich Repeat Transmembrane Neuronal 1 (LRRTM1) in the emergence of retinothalamic convergence. Importantly, LRRTM1 mutant mice display impairment in visual behaviors, suggesting a functional role of retinothalamic convergence in vision.
Pubmed ID: 29424692 RIS Download
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An independent, nonprofit organization focused on mammalian genetics research to advance human health. Their mission is to discover the genetic basis for preventing, treating, and curing human disease, and to enable research for the global biomedical community. Jackson Laboratory breeds and manages colonies of mice as resources for other research institutions and laboratories, along with providing software and techniques. Jackson Lab also conducts genetic research and provides educational material for various educational levels.
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View all literature mentionsSoftware package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.
View all literature mentionsMus musculus with name STOCK Tg(Crh-cre)KN282Gsat/Mmucd from MMRRC.
View all literature mentionsStatistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.
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View all literature mentionsAn ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database. What can you do with it? * Semantic segmentation editor: order segmentations in tree hierarchies, whose template is exportable for reuse in other, comparable projects. * Model, visualize and export 3D. * Work from your laptop on your huge, remote image storage. * Work with an endless number of images, limited only by the hard drive capacity. Dozens of formats supported thanks to LOCI Bioformats and ImageJ. * Import stacks and even entire grids (montages) of images, automatically stitch them together and homogenize their histograms for best montaging quality. * Add layers conveniently. A layer represents, for example, one 50 nm section (for TEM) or a confocal section. Each layer has its own Z coordinate and thickness, and contains images, labels, areas, nodes of 3d skeletons, profiles... * Insert layer sets into layers: so your electron microscopy serial sections can live inside your optical microscopy sections. * Run any ImageJ plugin on any image. * Measure everything: areas, volumes, pixel intensities, etc. using both built-in data structures and segmentation types, and standard ImageJ ROIs. And with double dissectors! * Visualize RGB color channels changing the opacity of each on the fly, non-destructively. * Annotate images non-destructively with floating text labels, which you can rotate/scale on the fly and display in any color. * Montage/register/stitch/blend images manually with transparencies, semiautomatically, or fully automatically within and across sections, with translation, rigid, similarity and affine models with automatically extracted SIFT features. * Correct the lens distortion present in the images, like those generated in transmission electron microscopy. * Add alpha masks to images using ROIs, for example to split images in two or more parts, or to remove the borders of an image or collection of images. * Model neuronal arbors with 3D skeletons (with areas or radiuses), and synapses with connectors. * Undo all steps. And much more...
View all literature mentionsThis polyclonal targets Human LRRTM1 Affinity Purified Ab
View all literature mentionsThis polyclonal targets VGLUT 2
View all literature mentionsThis polyclonal targets Iba1
View all literature mentionsThis monoclonal targets actin
View all literature mentionsMus musculus with name B6;129S6-Gt(ROSA)26Sortm9(CAG-tdTomato)Hze/J from IMSR.
View all literature mentionsMus musculus with name B6;FVB-Nrn1tm1.2Ndiv/J from IMSR.
View all literature mentionsMus musculus with name STOCK Tg(Aldh1l1-EGFP)OFC789Gsat/Mmucd from MMRRC.
View all literature mentionsMus musculus with name B6J.129-Atoh7tm1Gla/Mmucd from MMRRC.
View all literature mentionsMus musculus with name B6;129S5-Lrrtm1tm1Lex/Mmucd from MMRRC.
View all literature mentionsMus musculus with name STOCK Tg(Crh-cre)KN282Gsat/Mmucd from MMRRC.
View all literature mentionsThis polyclonal targets mouse mGluR1a, 945-1127 aa (NM_016976)
View all literature mentionsThis polyclonal targets mouse mGluR1a, 945-1127 aa (NM_016976)
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