Wang Xiaowei, Seed Brian
Department of Molecular Biology, Massachusetts General Hospital, 50 Blossom Street, Boston, MA 02114, USA.
Nucleic Acids Res. 2003 Dec 15;31(24):e154. doi: 10.1093/nar/gng154.
Although gene expression profiling by microarray analysis is a useful tool for assessing global levels of transcriptional activity, variability associated with the data sets usually requires that observed differences be validated by some other method, such as real-time quantitative polymerase chain reaction (real-time PCR). However, non-specific amplification of non-target genes is frequently observed in the latter, confounding the analysis in approximately 40% of real-time PCR attempts when primer-specific labels are not used. Here we present an experimentally validated algorithm for the identification of transcript-specific PCR primers on a genomic scale that can be applied to real-time PCR with sequence-independent detection methods. An online database, PrimerBank, has been created for researchers to retrieve primer information for their genes of interest. PrimerBank currently contains 147 404 primers encompassing most known human and mouse genes. The primer design algorithm has been tested by conventional and real-time PCR for a subset of 112 primer pairs with a success rate of 98.2%.
虽然通过微阵列分析进行基因表达谱分析是评估转录活性整体水平的有用工具,但与数据集相关的变异性通常要求通过其他方法(如实时定量聚合酶链反应(实时PCR))来验证观察到的差异。然而,在后一种方法中经常观察到非靶基因的非特异性扩增,当不使用引物特异性标签时,在大约40%的实时PCR实验中会干扰分析。在这里,我们提出了一种经过实验验证的算法,用于在基因组规模上鉴定转录本特异性PCR引物,该算法可应用于采用序列无关检测方法的实时PCR。已经创建了一个在线数据库PrimerBank,供研究人员检索他们感兴趣基因的引物信息。PrimerBank目前包含147404条引物,涵盖了大多数已知的人类和小鼠基因。引物设计算法已通过常规PCR和实时PCR对112对引物子集进行了测试,成功率为98.2%。