PLoS ONE：转录组断层技术可对脑部疾病的基因表达进行三维成像

近日，来自日本一个研究小组开发出了一种新型技术，可以对大脑结构中的基因表达样式进行三维成像，这种技术俗称为转录组断层技术，其结合了组织切片的微阵列技术，可以都对脑部基因表达的密度和位置进行精确图谱成像，相比当前的绘图成像技术，这种新型技术具有较高的分辨率，相关研究成果发表于国际杂志PLoS ONE上。

为了产生最新的数据资料，研究者将6个小鼠大脑切割分为许多5微米的部分，并且将每一部分分为3个解剖平面，研究者将这些样品进行收集并且使用微阵列技术将其分为1毫米厚度的组织碎片，随后，研究者用36，000个RNA探针对61个组织碎片进行处理并且重建数据以产生贯穿整个小鼠大脑的基因表达3D图谱。

这种转录组断层技术是一种半自动基础，相比当前手动方法更为有效和快速，这种技术可以被用于进行任何类型生化分子的组织分布图谱的绘制，比如蛋白质、脂质、糖类以及microRNAs在组织中的分布图谱的绘制等。

研究者Okamura-Oho和其同事通过比较以前方法所获得的数据和现在所获得的数据，更加确定了这项新型技术，同时研究者也分析了亨廷顿疾病基因表达的样式，亨廷顿疾病是一种神经变性疾病，主要表现为基底神经节神经元的死亡，紧接着会引发患者大脑皮层细胞的死亡。

研究分析揭示了亨廷丁在大脑区域中处于高表达的水平，这样就会严重影响患者的状况，比如基底神经节，但是在亨廷丁较低水平的区域，影响就相对小些，比如在中脑和小脑区域。研究者表示，相比MRI，这种新技术可以使得表达图谱分辨率高达20倍以上，高分辨率的基因表达图谱就能够更加详细地揭示疾病相关的异常情况。

转录组断层扫描数据组可以被上传至Waxholm空间，这样就方便研究者们进行资源数据共享以及疾病研究相关的分析。

doi:10.1371/journal.pone.0045373
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Transcriptome Tomography for Brain Analysis in the Web-Accessible Anatomical Space

Okamura-Oho Y, Shimokawa K, Takemoto S, Hirakiyama A, Nakamura S, et al.

Increased information on the encoded mammalian genome is expected to facilitate an integrated understanding of complex anatomical structure and function based on the knowledge of gene products. Determination of gene expression-anatomy associations is crucial for this understanding. To elicit the association in the three-dimensional (3D) space, we introduce a novel technique for comprehensive mapping of endogenous gene expression into a web-accessible standard space: Transcriptome Tomography. The technique is based on conjugation of sequential tissue-block sectioning, all fractions of which are used for molecular measurements of gene expression densities, and the block- face imaging, which are used for 3D reconstruction of the fractions. To generate a 3D map, tissues are serially sectioned in each of three orthogonal planes and the expression density data are mapped using a tomographic technique. This rapid and unbiased mapping technique using a relatively small number of original data points allows researchers to create their own expression maps in the broad anatomical context of the space. In the first instance we generated a dataset of 36,000 maps, reconstructed from data of 61 fractions measured with microarray, covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/inde​x.html) in one month. After computational estimation of the mapping accuracy we validated the dataset against existing data with respect to the expression location and density. To demonstrate the relevance of the framework, we showed disease related expression of Huntington’s disease gene and Bdnf. Our tomographic approach is applicable to analysis of any biological molecules derived from frozen tissues, organs and whole embryos, and the maps are spatially isotropic and well suited to the analysis in the standard space (e.g. Waxholm Space for brain-atlas databases). This will facilitate research creating and using open-standards for a molecular-based understanding of complex structures; and will contribute to new insights into a broad range of biological and medical questions.