mRNA细胞起源的大规模估计:提高转录组分析的产量
Large-scale estimates of cellular origins of mRNAs: enhancing the yield of transcriptome analyses.
作者信息
Sibille Etienne, Arango Victoria, Joeyen-Waldorf Jennifer, Wang Yingjie, Leman Samuel, Surget Alexandre, Belzung Catherine, Mann J John, Lewis David A
机构信息
Department of Psychiatry, University of Pittsburgh, PA 15213, USA.
出版信息
J Neurosci Methods. 2008 Jan 30;167(2):198-206. doi: 10.1016/j.jneumeth.2007.08.009. Epub 2007 Aug 21.
Gene expression profiling holds great promise for identifying molecular pathologies of central nervous system disorders. However, the analysis of brain tissue poses unique analytical challenges, as typical microarray signals represent averaged transcript levels across neuronal and glial cell populations. Here we have generated ratios of gene transcript levels between gray and adjacent white matter samples to estimate the relative cellular origins of expression. We show that incorporating these ratios into transcriptome analysis (i) provides new analytical perspectives, (ii) increases the potential for biological insight obtained from postmortem transcriptome studies, (iii) expands knowledge about glial and neuronal cellular programs and (iv) facilitates the generation of cell-type specific hypotheses. This approach represents a robust and cost-effective "add-on" to transcriptome analyses of the mammalian brain. As this approach can be applied post hoc, we provide tables of ratios for analysis of existing mouse and human brain datasets.
基因表达谱分析在识别中枢神经系统疾病的分子病理学方面具有巨大潜力。然而,脑组织分析带来了独特的分析挑战,因为典型的微阵列信号代表了神经元和神经胶质细胞群体中平均转录水平。在这里,我们生成了灰质和相邻白质样本之间基因转录水平的比率,以估计表达的相对细胞来源。我们表明,将这些比率纳入转录组分析中:(i)提供了新的分析视角;(ii)增加了从死后转录组研究中获得生物学见解的潜力;(iii)扩展了关于神经胶质细胞和神经元细胞程序的知识;(iv)促进了细胞类型特异性假设的产生。这种方法是对哺乳动物脑转录组分析的一种强大且经济高效的“附加”方法。由于这种方法可以事后应用,我们提供了比率表,用于分析现有的小鼠和人类脑数据集。