MacKenzie-Graham Allan, Lee Erh-Fang, Dinov Ivo D, Bota Mihail, Shattuck David W, Ruffins Seth, Yuan Heng, Konstantinidis Fotios, Pitiot Alain, Ding Yi, Hu Guogang, Jacobs Russell E, Toga Arthur W
Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, 710 Westwood Plaza, Room 4-238, Los Angeles, CA 90095-1769, USA.
J Anat. 2004 Feb;204(2):93-102. doi: 10.1111/j.1469-7580.2004.00264.x.
Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP.
通过繁殖或破坏正常遗传途径获得的小鼠品系被广泛用于模拟人类疾病。图谱通过提供一个比较标准,对于理解此类操作的影响具有极其重要的帮助。我们已经开发了成年C57BL/6J小鼠脑的数字图谱,作为一个全面的框架,用于存储和获取有关小鼠脑的各种类型信息。我们的实现使用了几种不同的成像技术:磁共振显微镜、块面成像、经典组织学和免疫组织化学。除了原始图像和注释图像外,它还包含数据库管理系统以及一组用于比较不同技术信息的工具。该框架通过建立小鼠脑的规范表示,并提供将独立数据插入与图谱相同空间的工具,使得不同动物、研究人员或实验室的结果能够轻松关联。这个工具将有助于管理关于哺乳动物脑的日益复杂和大量的信息。它提供了一个在解剖成像背景下包含遗传信息的框架,并有望为深入了解基因型和表型之间的关系产生新的见解。我们描述了一套工具,这些工具能够独立输入其他类型的数据、轻松检索信息并直接显示图像。因此,图谱成为管理关于小鼠脑的复杂遗传和表观遗传信息的框架。可通过http://www.loni.ucla.edu/MAP访问图谱及相关工具。