Singh Ram P, Liu Dahai, Chaudhari Abhijit, Cherry Simon R, Leahy Richard M, Smith Desmond J
Department of Molecular and Medical Pharmacology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
J Mol Histol. 2004 May;35(4):397-402. doi: 10.1023/b:hijo.0000039878.01844.c6.
Voxelation is a new approach for genome scale acquisition of brain gene expression patterns. The method employs high-throughput analysis of spatially registered voxels (cubes) to create multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. The spatial resolution of voxelation depends on voxel size, with smaller voxels giving higher resolution. An important question is the applicability of different transcript profiling tools for the various levels of resolution that can be employed. Here, we describe the use of three methods to analyze voxel transcript abundance: real-time PCR, microarray analysis and linear amplification coupled with microarrays. We show statistically significant concordance between real-time PCR and microarray analysis for the myelin basic protein gene in human brain specimens at differing levels of spatial resolution. In addition, we also demonstrate the feasibility of using linear amplification coupled with microarray analysis to create voxelation maps from the mouse brain at high resolution, 1 microl. These data indicate the suitability of a number of transcript profiling tools for various levels of spatial resolution in voxelation.
体素化是一种用于在基因组规模上获取大脑基因表达模式的新方法。该方法采用对空间配准的体素(立方体)进行高通量分析,以创建大脑基因表达的多个体积图像,类似于从生物医学成像系统获得的图像。体素化的空间分辨率取决于体素大小,体素越小分辨率越高。一个重要的问题是不同转录谱分析工具对于可采用的各种分辨率水平的适用性。在这里,我们描述了三种分析体素转录本丰度的方法的使用:实时PCR、微阵列分析以及与微阵列相结合的线性扩增。我们展示了在不同空间分辨率水平的人脑标本中,髓鞘碱性蛋白基因的实时PCR和微阵列分析之间具有统计学上显著的一致性。此外,我们还证明了使用与微阵列分析相结合的线性扩增在小鼠大脑中以1微米的高分辨率创建体素化图谱的可行性。这些数据表明许多转录谱分析工具适用于体素化中的各种空间分辨率水平。