基因表达系列分析(SAGE)

１９９５年Ｖｅｌｃｕｌｅｓｃｕ等提出了基因表达系列分析（ＳｅｒｉａｌＡｎａｌｙｓｉｓｏｆＧｅｎｅＥｘｐｒｅｓ－ｓｉｏｎ,ＳＡＧＥ）技术,能同时对上千个转录物进行研究。１．ＳＡＧＥ的原理和实验路线。１．１ＳＡＧＥ的原理ＳＡＧＥ的主要依据有两个。第一,一...     

USAGE: a web-based approach towards the analysis of SAGE data. Serial Analysis of Gene Expression

MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should reside on a central server and be accessed via the internet. Since such an application was not available we developed the USAGE package. RESULTS: USAGE is a web-based application that comprises an integrated set of tools, which offers many functions for analysing and comparing SAGE data. Additionally, USAGE includes a statistical method for the planning of new SAGE experiments. USAGE is available in a multi-user environment giving users the option of sharing data. USAGE is interfaced to a relational database to store data and analysis results. The USAGE query editor allows the composition of queries for searching this database. Several database functions have been included which enable the selection and combination of data. USAGE provides the biologist increased functionality and flexibility for analysing SAGE data. AVAILABILITY: USAGE is freely accessible for academic institutions at http://www.cmbi.kun.nl/usage/. The source code of USAGE is freely available for academic institutions on request from the first author.     

A systematic screen for genes expressed in definitive endoderm by Serial Analysis of Gene Expression (SAGE)

Background  

The embryonic definitive endoderm (DE) gives rise to organs of the gastrointestinal and respiratory tract including the liver, pancreas and epithelia of the lung and colon. Understanding how DE progenitor cells generate these tissues is critical to understanding the cause of visceral organ disorders and cancers, and will ultimately lead to novel therapies including tissue and organ regeneration. However, investigation into the molecular mechanisms of DE differentiation has been hindered by the lack of early DE-specific markers.     

Enhanced concatemer cloning-a modification to the SAGE (Serial Analysis of Gene Expression) technique.

The Serial Analysis of Gene Expression (SAGE) method, described in 1995 by Velculescu et al ., represents a powerful means to compare gene expression between two mRNA populations. An improvement to SAGE that removes contaminating linker molecules, which compromise the efficiency of the method, has been developed. This modification utilises biotinylated PCR primers, which generate biotinylated linkers at an early stage in the SAGE protocol, thus allowing removal of the unwanted linkers by binding to streptavidin-coated magnetic beads at a later stage. The application of this modification resulted in the rapid generation of high ditag yields and clones with large average insert sizes.     

基因表达系列分析法(SAGE)的改进及其在植物功能基因组研究中的应用

基因表达系列分析方法(SAGE)是一种新的基因表达分析方法,与基因芯片技术一样具有高通量的特点,可测定特定组织的基因表达水平,在全基因组水平上同时定量检测数万个基因表达模式;可在未知目的基因的前提下,分析来自一个细胞的全部转录本信息;对已知或未知基因表达进行定性和定量分析.目前,虽然在疾病、发育、细胞凋亡、药物筛选等多个领域已有利用SAGE方法进行的研究,但该方法在植物功能基因组研究中的应用相对较少.本文主要综述了该方法在RNA用量、PCR循环次数、SAGE效能和可靠性、标签长度和未知标签分析等方面的改进及其在植物中构建SAGE文库、筛选新基因、基因表达图谱分析等方面的应用,从而为其在植物功能基因组研究中的进一步应用提供理论参考.     

基因表达的连续分析技术

基因表达的连续分析技术是一种能对某一细胞群或特定的微解剖结构基因表达做全面分析的技术。本文就基因表达的连续分析技术的原理、方法进行综述。     

Substantially enhanced cloning efficiency of SAGE (Serial Analysis of Gene Expression) by adding a heating step to the original protocol.

The efficiency of the original SAGE (Serial Analysis of Gene Expression) protocol was limited by a small average size of cloned concatemers. We describe a modification of the technique that overcomes this problem. Ligation of ditags yields concatemers of various sizes. Small concatemers may aggregate and migrate with large ones during gel electrophoresis. A heating step introduced before gel electrophoresis breaks such contaminating aggregates. This modification yields cloned concatemers with an average size of 67 tags as compared to 22 tags by the original protocol. It enhances the length of cloned concatemers substantially and reduces the costs of SAGE.     

Serial Analysis of Gene Expression (SAGE) of<Emphasis Type="Italic"> Magnaporthe grisea</Emphasis>: genes involved in appressorium formation

Treatment with cyclic AMP (cAMP) induces appressorium formation in the phytopathogenic fungus Magnaporthe grisea, the causative agent of rice blast disease. In a search for the M. grisea genes responsible for appressorium formation and host invasion, SAGE (Serial Analysis of Gene Expression) was carried out using mRNA isolated from fungal conidia germinating in the presence and absence of cAMP. From cAMP-treated conidia 5087 tags including 2889 unique tags were isolated, whereas untreated conidia yielded 2342 unique tags out of total of 3938. cAMP treatment resulted in up- and down-regulation of genes corresponding to 57 and 53 unique tags, respectively. Upon consultation of EST/cDNA databases, 22 tags with higher representation in cAMP-treated conidia were annotated with putative gene names. Furthermore, 28 tags corresponding to cAMP-induced genes could be annotated with the help of the recently published genome sequence of M. grisea. cAMP-induced genes identified by SAGE included many genes that have not been described so far, as well as a number of genes known to be involved in pathogenicity, e.g. MPG1, MAS1 and MAC1. RT-PCR of 13 randomly selected genes confirmed the SAGE results, verifying the fidelity of the SAGE data.Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by E. Cerdá-Olmedo     

A feature selection approach for identification of signature genes from SAGE data

Background  

One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements.     

基因表达的系列分析方法研究进展

基因表达的系列分析（SAGE）是探讨组织或器官在不同条件下基因表达丰度以及差异表达的一种有效方法。本文介绍了SAGE方法的详细机理并且对SAGE方法学的改进进行了综述。     

基因表达系列分析技术的新进展

作为新近建立的研究基因表达的有效工具 ,基因表达系列分析 (SAGE)技术能同时对大量的转录物进行定性和定量分析。它不仅可以显示低丰度的转录物 ,提供基因组表达的完整信息 ,而且可以通过不同状态下基因表达图谱的比较 ,深入了解基因表达的时空性和有序性 ,从而寻找和发现新基因。本文介绍了SAGE的工作原理和方法 ,并着重对其最新的应用与研究进展进行了综述。     

基因表达系列分析(SAGE)的研究进展

基因表达系列分析方法（SAGE）是一种新的基因表达分析方法,它可同时分析数千种转录子的表达情况.SAGE不仅可以定量分析已知基因,还可分析未知的基因表达情况.SAGE为从分子水平阐明疾病的发病机制找到有效的治疗靶位和诊断标志创造了条件.     

强大的广谱基因表达分析技术——基因表达系列分析法

基因表达系列分析(serial analysis of gene expression,SAGE)是一项强大的数字化分析基因组整体表达模式的技术。它的诞生为定量、全局性地分析特定细胞内的基因表达情况提供了可能。本文介绍了SAGE技术的基本原理、最新进展和应用。