Tarasov Kirill V, Brugh Sheryl A, Tarasova Yelena S, Boheler Kenneth R
The Laboratory of Cardiovascular Science, The National Institute on Aging, NIH, Baltimore, MD, USA.
Methods Mol Biol. 2007;366:41-59. doi: 10.1007/978-1-59745-030-0_3.
Serial analysis of gene expression (SAGE), a functional genomics technique, can be used for global profiling of gene transcripts. It relies on the preparation and sequencing of cDNA concatemers, but it does not require prior knowledge of the genes to be assayed (as with microarrays). Once analyzed, SAGE data provide both a qualitative and quantitative assessment of potentially every transcript present in a particular cell or tissue type. In this chapter, we describe the fundamental principles of SAGE, describe a complete protocol for the generation of SAGE libraries, and show how it has been employed to generate the first SAGE reference data set of the mouse myocardium. Following the protocols described here, investigators should be able to generate unique mouse heart SAGE libraries, which can be directly compared with our reference library. This permits the identification of transcripts that are differentially expressed as a function of time, age, genetic background or transgenic state, among other factors. SAGE is thus a powerful technique that permits a comprehensive analysis of changes in mRNA abundance. The results provide a snapshot of altered patterns of gene expression in response to any genetic or environmental stimulus that can be used to generate new biological hypotheses or test existing paradigms.
基因表达序列分析（SAGE）是一种功能基因组学技术，可用于对基因转录本进行全局分析。它依赖于cDNA串联体的制备和测序，但不需要像微阵列那样预先了解待检测的基因。一旦进行分析，SAGE数据就能对特定细胞或组织类型中可能存在的每个转录本提供定性和定量评估。在本章中，我们描述了SAGE的基本原理，介绍了生成SAGE文库的完整方案，并展示了如何利用它来生成小鼠心肌的首个SAGE参考数据集。按照此处所述的方案，研究人员应该能够生成独特的小鼠心脏SAGE文库，并可直接与我们的参考文库进行比较。这有助于识别那些因时间、年龄、遗传背景或转基因状态等因素而差异表达的转录本。因此，SAGE是一种强大的技术，能够对mRNA丰度的变化进行全面分析。其结果提供了响应任何遗传或环境刺激而改变的基因表达模式的快照，可用于产生新的生物学假设或检验现有范式。
