A high-resolution anatomical framework of the neonatal mouse brain for managing gene expression data
- Department of Neurology, UCLA School of Medicine, USA
This study aims to provide a high-resolution atlas and use it as an anatomical framework to localize the gene expression data for mouse brain on postnatal day 0 (P0). A color Nissl-stained volume with a resolution of 13.3 × 50 × 13.3 µ3 was constructed and co-registered to a standard anatomical space defined by an averaged geometry of C57BL∕6J P0 mouse brains. A 145 anatomical structures were delineated based on the histological images. Anatomical relationships of delineated structures were established based on the hierarchical relations defined in the atlas of adult mouse brain (MacKenzie-Graham et al., 2004) so the P0 atlas can be related to the database associated with the adult atlas. The co-registered multimodal atlas as well as the original anatomical delineations is available for download at http∕∕www.loni.ucla.edu∕Atlases∕
. The region-specific anatomical framework based on the neonatal atlas allows for the analysis of gene activity within a high-resolution anatomical space at an early developmental stage. We demonstrated the potential application of this framework by incorporating gene expression data generated using in situ hybridization to the atlas space. By normalizing the gene expression patterns revealed by different images, experimental results from separate studies can be compared and summarized in an anatomical context. Co-displaying multiple registered datasets in the atlas space allows for 3D reconstruction of the co-expression patterns of the different genes in the atlas space, hence providing better insight into the relationship between the differentiated distribution pattern of gene products and specific anatomical systems.
Keywords:
atlas, C57BL∕6J, in situ hybridization
Citation:
Erh-Fang Lee, Jyl Boline and Arthur W. Toga (2007). A high-resolution anatomical framework of the neonatal mouse brain for managing gene expression data. Front. neuroinform. 1:6. doi: 10.3389/neuro.11/006.2007
Received: 13 September 2007;
Paper pending published: 24 September 2007;
Accepted: 12 October 2007;
Published online: 2 November 2007.
Edited by:
Jan G. Bjaalie, International Neuroinformatics Coordination Facility, Karolinska Institutet, Sweden; University of Oslo, Norway
Reviewed by:
Trygve B. Leergaard, University of Oslo, Norway
Ilya Zaslavsky, Spatial Information Systems Laboratory, University of California San Diego, USA
Copyright:
© 2007 Lee, Boline, Toga. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
*Correspondence:
Arthur W. Toga, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive South, Suite 225, Los Angeles, CA 90095, USA. e-mail: arthur.toga@loni.ucla.edu