Nishida Nao, Tanabe Tetsuya, Hashido Kento, Hirayasu Kouyuki, Takasu Miwa, Suyama Akira, Tokunaga Katsushi
Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Anal Biochem. 2005 Nov 15;346(2):281-8. doi: 10.1016/j.ab.2005.08.007. Epub 2005 Aug 31.
As a consequence of Human Genome Project and single nucleotide polymorphism (SNP) discovery projects, several millions of SNPs, which include possible susceptibility SNPs for multifactorial diseases, have been revealed. Accordingly, there has been a strong drive to perform the investigation with all candidate SNPs for a certain disease without decreasing the number of analyzed SNPs. We developed DigiTag assay, which uses well-designed oligonucleotides called DNA coded numbers (DCNs) in multiplex SNP genotype analysis. During the analysis, the information of a genotype is converted to one of the DCNs in a one to one manner using oligonucleotide ligation assay (encoding). After the encoding reaction, only the DCNs regions and not the SNP specific regions are amplified using the universal primers and then SNP genotype is read out using DNA capillary arrays. DigiTag assay was found to be successful in SNP genotyping, giving a high success rate (24 of 27 SNPs) for randomly chosen SNPs. Moreover, this assay has the potential to analyze almost all kinds of the target SNPs by applying mismatch-induced probes and redesigned primer pairs at a low-cost.
由于人类基因组计划和单核苷酸多态性(SNP)发现计划,现已揭示出数百万个SNP,其中包括多因素疾病的可能易感SNP。因此,人们强烈希望对某一疾病的所有候选SNP进行研究,同时又不减少分析的SNP数量。我们开发了数字标签分析方法,该方法在多重SNP基因型分析中使用精心设计的称为DNA编码数字(DCN)的寡核苷酸。在分析过程中,使用寡核苷酸连接分析(编码)将基因型信息一对一地转换为DCN之一。编码反应后,仅使用通用引物扩增DCN区域而非SNP特异性区域,然后使用DNA毛细管阵列读出SNP基因型。结果发现数字标签分析方法在SNP基因分型中很成功,对随机选择的SNP有很高的成功率(27个SNP中有24个)。此外,该分析方法有潜力通过应用错配诱导探针和重新设计的引物对,以低成本分析几乎所有类型的目标SNP。