Mills J C, Roth K A, Cagan R L, Gordon J I
Department of Molecular Biology and Pharmacology, Washington University School of Medicine, St Louis, Missouri 63110, USA.
Nat Cell Biol. 2001 Aug;3(8):E175-8. doi: 10.1038/35087108.
For the cell biologist, identifying changes in gene expression using DNA microarrays is just the start of a long journey from tissue to cell. We discuss how chip users can first filter noise (false-positives) from daunting microarray datasets. Combining laser capture microdissection with real-time polymerase chain reaction and reverse transcription is a helpful follow-up step that allows expression of selected genes to be quantified using sensitive new in situ hybridization and immunohistochemical methods based on tyramide signal amplification.
对于细胞生物学家而言,利用DNA微阵列识别基因表达的变化仅仅是从组织到细胞漫长研究历程的开端。我们将探讨芯片使用者如何首先从海量的微阵列数据集中过滤噪声(假阳性)。将激光捕获显微切割技术与实时聚合酶链反应及逆转录相结合是一个有用的后续步骤,它能通过基于酪胺信号放大的灵敏新原位杂交和免疫组化方法对选定基因的表达进行定量分析。