Gene expression analyses reveal molecular relationships among 20 regions of the human CNS
Gene expression analyses reveal molecular relationships among 20 regions of the human CNS
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DOI：
10.1007/s10048-006-0032-6
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发表时间：
2006-05-01
期刊：
影响因子：
2.2
通讯作者：
Zlotnik, A
中科院分区：
文献类型：
--
作者：
Roth, RB;Hevezi, P;Zlotnik, A
进行转录谱分析，以调查人类中枢神经系统（CNS）的20个解剖学上不同的网站的全球表达模式。还对45个非CNS组织进行了分析，以进行比较分析。使用主成分分析和层次聚类，我们能够表明，表达模式的20个CNS网站的轮廓是显着不同的所有非CNS组织，也彼此相似，表明一个潜在的共同表达签名。通过将我们的分析集中在CNS的20个位点上，我们能够表明，这20个位点可以被分离成在解剖结构上具有潜在相似性的离散组，并且在许多情况下，功能活性。这些发现表明，基因表达数据可以帮助在分子水平上定义CNS功能。我们已经确定了具有以下表达模式的基因子集：（1）跨CNS，表明稳态/管家功能;（2）通过我们的无监督学习分析确定的CNS功能相关位点的子集;（3）CNS内的单个位点，表明它们参与不同的位点特异性功能。通过对这些基因集进行网络分析，我们确定了许多在CNS特定位点上调的途径，其中一些先前在文献中描述过，验证了我们的数据集和方法。总之，我们已经产生了一个基因表达数据库，可以用来获得有价值的洞察到的分子表征的功能进行的不同网站的人中枢神经系统。
Transcriptional profiling was performed to survey the global expression patterns of 20 anatomically distinct sites of the human central nervous system (CNS). Forty-five non-CNS tissues were also profiled to allow for comparative analyses. Using principal component analysis and hierarchical clustering, we were able to show that the expression patterns of the 20 CNS sites profiled were significantly different from all non-CNS tissues and were also similar to one another, indicating an underlying common expression signature. By focusing our analyses on the 20 sites of the CNS, we were able to show that these 20 sites could be segregated into discrete groups with underlying similarities in anatomical structure and, in many cases, functional activity. These findings suggest that gene expression data can help define CNS function at the molecular level. We have identified subsets of genes with the following patterns of expression: (1) across the CNS, suggesting homeostatic/housekeeping function; (2) in subsets of functionally related sites of the CNS identified by our unsupervised learning analyses; and (3) in single sites within the CNS, indicating their participation in distinct site-specific functions. By performing network analyses on these gene sets, we identified many pathways that are upregulated in particular sites of the CNS, some of which were previously described in the literature, validating both our dataset and approach. In summary, we have generated a database of gene expression that can be used to gain valuable insight into the molecular characterization of functions carried out by different sites of the human CNS.