Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy
Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy
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DOI：
10.1016/j.ymeth.2009.09.001
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发表时间：
2010-02-01
期刊：
影响因子：
4.8
通讯作者：
Mitra, Partha P.
中科院分区：
文献类型：
--
作者：
Bohland, Jason W.;Bokil, Hemant;Mitra, Partha P.
空间基因表达谱提供了探索大脑结构组织的新方法。通过艾伦脑图谱中 C57BL/6J 小鼠大脑的基因组规模图谱，可以对这些模式进行计算分析。在这里，我们描述了用于探索基于实验观察一致性（N = 2）的一组 3041 个基因的基因表达模式的空间结构的方法。对通过聚合细胞分辨率图像数据获得的每个基因的平滑、共同配准的 3D 表达体积进行分析。在降维和降噪之后，体素根据基因集表达的相似性进行聚类。我们展示了不同数量的簇（K）的小鼠大脑的分区结果，并将这些分区与不同粒度级别的经典定义的解剖参考图集进行定量比较，揭示了高度的对应性。这些观察结果表明，基因表达的空间定位为将分子水平的知识与有关大脑组织的更高级别的信息联系起来提供了巨大的希望。 (C) 2009 Elsevier Inc. 保留所有权利。
Spatial gene expression profiles provide a novel means of exploring the structural organization of the brain. Computational analysis of these patterns is made possible by genome-scale mapping of the C57BL/6J mouse brain in the Allen Brain Atlas. Here we describe methodology used to explore the spatial structure of gene expression patterns across a set of 3041 genes chosen on the basis of consistency across experimental observations (N = 2). The analysis was performed on smoothed, co-registered 3D expression volumes for each gene obtained by aggregating cellular resolution image data. Following dimensionality and noise reduction, voxels were clustered according to similarity of expression across the gene set. We illustrate the resulting parcellations of the mouse brain for different numbers of clusters (K) and quantitatively compare these parcellations with a classically-defined anatomical reference atlas at different levels of granularity, revealing a high degree of correspondence. These observations suggest that spatial localization of gene expression offers substantial promise in connecting knowledge at the molecular level with higher-level information about brain organization. (C) 2009 Elsevier Inc. All rights reserved.