Suppr超能文献

利用代表性差异分析结合微阵列杂交技术检测原发性肿瘤组织中差异表达的基因。

Detection of differentially expressed genes in primary tumor tissues using representational differences analysis coupled to microarray hybridization.

作者信息

Welford S M, Gregg J, Chen E, Garrison D, Sorensen P H, Denny C T, Nelson S F

机构信息

Molecular Biology Institute and the Departments of Pathology, Pediatrics and 4Biological Chemistry, UCLA Medical Center, Los Angeles, CA 90095, USA.

出版信息

Nucleic Acids Res. 1998 Jun 15;26(12):3059-65. doi: 10.1093/nar/26.12.3059.

Abstract

The identification of differential gene expressionbetween cells is a frequent goal in modern biological research. Here we demonstrate the coupling of representational difference analysis (RDA) of cDNA with microarray analysis of the output for high throughput screening. Two primary Ewing's sarcoma tissue samples with different biological behavior in vivo were compared by RDA: one which was metastatic and progressed rapidly; the other localized and successfully treated. A modified RDA protocol that minimizes the necessary starting material was employed. After a reduced number of subtractive rounds, the output of RDA was shotgun cloned into a plasmid vector. Inserts from individual colonies from the subtracted library were amplified with vector-specific primers and arrayed at high density on glass slides. The arrays were then hybridized with differentially fluorescently labeled starting amplicons from the two tissues and fluorescent signals were measured at each DNA spot. We show that the relative amounts of fluorescent signal correlate well with the abundance of fragments in the RDA amplicon and in the starting mRNA. In our system, we analyzed 192 products and 173 (90%) were appropriately detected as being >2-fold differentially expressed. Fifty unique, differentially expressed clones were identified. Therefore, the use of RDA essentially provides an enriched library of differentially expressed genes, while analysis of this library with microarrays allows rapid and reproducible screening of thousands of DNA molecules simultaneously. The coupling of these two techniques in this system resulted in a large pool of differentially expressed genes.

摘要

细胞间差异基因表达的鉴定是现代生物学研究中一个常见的目标。在此,我们展示了cDNA的代表性差异分析(RDA)与高通量筛选输出的微阵列分析的结合。通过RDA比较了两种在体内具有不同生物学行为的原发性尤因肉瘤组织样本:一种具有转移性且进展迅速;另一种为局限性且治疗成功。采用了一种改良的RDA方案,该方案将所需起始材料减至最少。经过减少次数的消减轮次后,将RDA的输出产物进行鸟枪法克隆到质粒载体中。用载体特异性引物扩增来自消减文库的各个菌落的插入片段,并将其高密度排列在载玻片上。然后将阵列与来自两种组织的差异荧光标记的起始扩增子杂交,并在每个DNA斑点处测量荧光信号。我们表明,荧光信号的相对量与RDA扩增子和起始mRNA中片段的丰度密切相关。在我们的系统中,我们分析了192个产物,其中173个(90%)被正确检测为差异表达>2倍。鉴定出了50个独特的差异表达克隆。因此,RDA的使用本质上提供了一个差异表达基因的富集文库,而用微阵列分析这个文库则允许同时快速且可重复地筛选数千个DNA分子。这两种技术在该系统中的结合产生了大量差异表达基因。

相似文献

2
Representational difference analysis of cDNA.互补DNA的代表性差异分析
Methods Mol Med. 2004;94:49-66. doi: 10.1385/1-59259-679-7:49.

引用本文的文献

3
Powerful quantifiers for cancer transcriptomics.用于癌症转录组学的强大定量方法。
World J Clin Oncol. 2020 Sep 24;11(9):679-704. doi: 10.5306/wjco.v11.i9.679.

本文引用的文献

5
Gene expression profiles in normal and cancer cells.正常细胞和癌细胞中的基因表达谱。
Science. 1997 May 23;276(5316):1268-72. doi: 10.1126/science.276.5316.1268.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验