Integrated Analysis of Anatomical Gene Expression Maps and Co-Expression Networks Using a Database, ViBrism

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Event Abstract Back to Event Integrated Analysis of Anatomical Gene Expression Maps and Co-Expression Networks Using a Database, ViBrism Yuko Okamura-Oho1*, Kazuro Shimokawa2, Satoko Takemoto3, Gang Song4, James Gee4 and Hideo Yokota3 1 BReNt-Brain Research Network and Advanced Science Institute, RIKEN, Japan 2 Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Japan 3 Bio-research Infrastructure Construction Team, Advanced Science Institute, RIKEN , Japan 4 Penn Image Computing and Science Laboratory, University of Pennsylvania, United States Detection of gene expression-anatomy association in biological structure is crucial for understanding its function based on the molecular and genetic/genomic information. Particularly in the mammalian brain where there are estimated 25,000 genes expressed, systematic and comprehensive quantification of the expression densities in the whole three-dimensional (3D) anatomical context is critical. The combinatorial number of randomly selected genes is more than the cell number in the brain, which assumes that non-random combinatorial gene expression underlies the formation of a wide variety of functional brain regions composed of multiple cells. To determine the association systematically, we have introduced a novel framework, Transcriptome Tomography, for spatially integrating comprehensive endogenous gene expression within an isotropic anatomical context. Using this rapid and unbiased 3D mapping technique, in the first instance, we have generated a dataset of 36,000 maps covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/index.html ) and validated them against existing data with respect to the expression location and density (paper submitted). Here, we used an informatics approach to identify the combinatorial gene expression as a broad co-expression network. The gene network links covering the whole brain followed an inverse-power law and were rich in functional interaction and gene ontology terms. Developmentally conserved co-expression modules underlie the network structure. To demonstrate the relevance of the finding, we mined Huntington's disease gene (Htt) and found a novel disease-related co-expression network containing genes potentially co-functioning with Htt in neural differentiation and modulating the disease specific differential vulnerability in brain regions. The maps are spatially isotropic and well suited to analysis in the standard space for brain-atlas databases, e.g. Waxholm Space (PLoS Comput Biol 2011, 7[2]: e1001065) as shown in the related poster by J. Boline et., al. Our time and cost effective framework will facilitate research creating and using open-resources for a molecular-based understanding of complex structures. A part of this work was conducted within the Waxholm Space Task Force of the International Neuroinformatics Coordinating Facility (INCF) Program on Digital Brain Atlasing. We thank the program members, particularly, R. Baldock, I. Zaslavsky, L.Ibanez and J. Boline. Keywords: digital atlasing, Gene Expression, Network analysis, mammalian brain development, computational neuroscience Conference: 5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012. Presentation Type: Poster Topic: Neuroinformatics Citation: Okamura-Oho Y, Shimokawa K, Takemoto S, Song G, Gee J and Yokota H (2014). Integrated Analysis of Anatomical Gene Expression Maps and Co-Expression Networks Using a Database, ViBrism. Front. Neuroinform. Conference Abstract: 5th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2014.08.00079 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: 21 Mar 2013; Published Online: 27 Feb 2014. * Correspondence: Dr. Yuko Okamura-Oho, BReNt-Brain Research Network and Advanced Science Institute, RIKEN, Zushi-shi, Japan, yoho-tky@umin.ac.jp 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 Yuko Okamura-Oho Kazuro Shimokawa Satoko Takemoto Gang Song James Gee Hideo Yokota Google Yuko Okamura-Oho Kazuro Shimokawa Satoko Takemoto Gang Song James Gee Hideo Yokota Google Scholar Yuko Okamura-Oho Kazuro Shimokawa Satoko Takemoto Gang Song James Gee Hideo Yokota PubMed Yuko Okamura-Oho Kazuro Shimokawa Satoko Takemoto Gang Song James Gee Hideo Yokota Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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