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目的 :建立发掘未知单核苷酸多态性 (singlenucleotidepolymorphisms,SNPs)和已知SNPs分型的技术平台。方法 :运用PCR产物双向大规模测序的方法发掘未知SNPs;运用基于聚合酶链反应 -限制性片段长度多态性 (poly merasechainreaction restrictionendonucleasedigestion ,PCR RFLP)、TaqMan技术对已知SNPs进行分型。结果 :建立了基于PCR产物双向大规模测序发掘未知SNP的技术平台 ,并以此在 2 7个个体的 6 9个乙型肝炎候选易感基因区域检测到 5 92个SNPs,核苷酸变异度为 (4 .5 1± 1.2 4 )× 10 - 4;建成基于PCR RFLP和TaqMan的SNP分型技术平台 ,这两种方法与直接测序法比较 ,PCR RFLP的检出率达到 10 0 % ,错误率几乎为 0 ,并且操作简单 ,成本低廉 ;TaqMan分型技术的检出率也可达到 10 0 % ,与测序结果的一致性达到 10 0 % ,并且过程简单、易于操作 ,结果直观 ,易于判断 ,也能快速得到结果。结论 :基于PCR产物双向大规模测序发掘未知SNPs的技术平台成熟可靠 ,适于准确、大规模地发掘未知SNPs;PCR RFLP技术和TaqMan分型技术均适用于今后大规模正常人群和疾病人群的SNPs分型 ,为进行关联分析以确定疾病相关的SNPs奠定了坚实的技术基础。
OBJECTIVE: To establish a technology platform for discovering single nucleotide polymorphisms (SNPs) and known SNPs. Methods: Undetected SNPs were screened by two-way large-scale sequencing of PCR products. Knp SNPs were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR RFLP) and TaqMan technique. Results: A technology platform based on bidirectional large-scale sequencing of PCR products to discover unknown SNPs was established. Based on this, 5 92 SNPs were detected in 69 susceptibility genes of hepatitis B candidates in 27 individuals. The nucleotide variation (4 .5 ± 1.2 4) × 10 - 4. A SNP typing platform based on PCR RFLP and TaqMan was established. Compared with direct sequencing, the detection rate of PCR RFLP was 100% The rate is almost 0, and the operation is simple and the cost is low; the detection rate of TaqMan typing technology can reach 10% and the consistency with the sequencing result reaches 10%, and the process is simple and easy to operate, the result is intuitive and easy to judge , But also get results quickly. Conclusion: The technology platform based on bidirectional large-scale sequencing of PCR products to discover unknown SNPs is mature and reliable and suitable for accurate and large-scale exploration of unknown SNPs. Both PCR RFLP and TaqMan typing are suitable for SNPs in large-scale normal population and disease-free population Typing has laid a solid technical foundation for the association analysis to identify disease-related SNPs.