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首页> 外文期刊>Nucleic acids research >RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples
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RNA expression microarrays (REMs), a high-throughput method to measure differences in gene expression in diverse biological samples

机译:RNA表达微阵列(REM),一种高通量方法,可测量多种生物样品中基因表达的差异

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We have developed RNA expression microarrays (REMs), in which each spot on a glass support is composed of a population of cDNAs synthesized from a cell or tissue sample. We used simultaneous hybridization with test and reference (housekeeping) genes to calculate an expression ratio based on normalization with the endogenous reference gene. A test REM containing artificial mixtures of liver cDNA and dilutions of the bacterial LysA gene cDNA demonstrated the feasibility of detecting transcripts at a sensitivity of four copies of LysA mRNA per liver cell equivalent. Furthermore, LysA cDNA detection varied linearly across a standard curve that matched the sensitivity of quantitative real-time PCR. In REMs with real samples, we detected organ-specific expression of albumin, Hnf-4 and Igfbp-1, in a set of mouse organ cDNA populations and c-Myc expression in tumor samples in paired tumorormal tissue cDNA samples. REMs extend the use of classic microarrays in that a single REM can contain cDNAs from hundreds to thousands of cell or tissue samples each representing a specific physiological or pathophysiological state. REMs will extend the analysis of valuable samples by providing a common broad based platform for their analysis and will promote research aimed at defining gene functions, by broadening our understanding of their expression patterns in health and disease.
机译:我们已经开发了RNA表达微阵列(REM),其中玻璃支持物上的每个斑点都由从细胞或组织样品合成的cDNA种群组成。我们使用与测试和参考(管家)基因的同时杂交来基于内源参考基因的标准化来计算表达率。包含肝脏cDNA人工混合物和细菌LysA基因cDNA稀释液的测试REM证明了以每肝细胞当量4个LysA mRNA的敏感性检测转录本的可行性。此外,LysA cDNA的检测在标准曲线上线性变化,与定量实时PCR的灵敏度相匹配。在具有真实样品的REM中,我们在一组小鼠器官cDNA群体中检测了白蛋白,Hnf-4和Igfbp-1的器官特异性表达,并在配对的肿瘤/正常组织cDNA样品中的肿瘤样品中检测到c-Myc表达。 REM扩展了经典微阵列的使用,因为单个REM可以包含成百上千的细胞或组织样本的cDNA,每个样本都代表一种特定的生理或病理生理状态。 REM将通过提供一个通用的基础平台来扩展有价值的样品的分析范围,并通过扩大我们对它们在健康和疾病中的表达方式的理解,来促进旨在定义基因功能的研究。

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