Reconstruction of the mouse brain regions from the spatial gene expression data

Abstract

Event Abstract Back to Event Reconstruction of the mouse brain regions from the spatial gene expression data Alexey Tsvetkov1* 1 Russian Scientific Centre, Kurchatov Institute, Nano-, Bio-, Info-, Cognitive (NBIC) Center Understanding the structural basis of nervous system still remains one of the primary challenges in neuroscience. New perspectives for the studies of brain anatomy are emerging with the availability of large-scale spatial gene expression data. Exploration of these data promises to deliver new insights into the understanding of relations between genes and brain structure. We performed an analysis of the gene expression for more than 4000 genes in the mouse brain with the spatial resolution of 200 micrometers. These data are freely available from the Allen Brain Atlas [1] project. After data filtering and scaling, distance matrices between all brain voxels (volumetric pixels) were calculated for a number of common distance measures. We also proposed and utilized a novel distance measure based on the locality of gene expression. Then the brain volume was hierarchically clustered with a variety of techniques [2]. In order to verify the resulting brain parcellations we compared them by means of a quantitative measure to the histologically-defined anatomical reference atlas and found significant overlap between automatically derived spatial clusters and anatomical structures. We also compared brain regions by the number of genes expressed. Here the number of simultaneously activated genes was considered to be proportional to the amount of accumulated evolutionary changes. This allows us to identify dentate gyrus and adjoining hippocampal regions as the structures with the richest expression and, hence, less conservative in the evolutionary sense. Other regions of the cerebral cortex show intermediate levels of expression variability while other brain structures have accumulated fewer changes in the process of evolution, with olfactory bulbs and cerebellum being most conservative. This work was supported by Russian FTP "Scientific and scientific-pedagogical personnel". [1] Ng L., Bernard A., Lau C. et. al., "An anatomic gene expression atlas of the adult mouse brain" (2009) Nature Neuroscience, 12 (3): 356-362. [2] Xu R. and Wunsch D., "Survey of clustering algorithms" (2005) IEEE Transactions on Neural Networks, 16 (3): 645-678. Keywords: General neuroinformatics Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: General neuroinformatics Citation: Tsvetkov A (2011). Reconstruction of the mouse brain regions from the spatial gene expression data. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00043 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Alexey Tsvetkov, Russian Scientific Centre, Kurchatov Institute, Nano-, Bio-, Info-, Cognitive (NBIC) Center, Moscow, alexis.tsvetkov@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Alexey Tsvetkov Google Alexey Tsvetkov Google Scholar Alexey Tsvetkov PubMed Alexey Tsvetkov Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.