摘要
目的:为我国高通量测序标准数据库的建设提供参考。方法:总结分析国内外高通量测序产品及数据库建设现状,剖析当前我国高通量测序标准数据库建设中亟待解决的问题。结果与结论:高通量测序是精准医疗重要的组成部分,国内外已批准多个高通量测序产品用于癌症等的临床诊治。但是,高通量测序能否在精准医疗中发挥更好的作用,还取决于是否有标准数据库用于准确地指导测序数据解读。随着高通量测序技术的发展,海量基因测序数据不断产生,如何建立中国人群基因变异解读标准数据库,用于评估和指导相关检测机构对致病基因的解读具有重大的现实意义。目前急需引入新的数据库建设及数据解读机制,为我国高通量测序行业的标准化健康发展及科学监管提供依据和保障。
Objective:To provide suggestions for the construction of high-throughput sequencing standard database in China.Methods:The current status of high-throughput sequencing products and database construction at home and abroad were summarized and analyzed.The urgent problems needed to be solved in the construction of high-throughput sequencing standard database in China were analyzed.Results and Conclusion:Since highthroughput sequencing is an important part of precision medicine,many high-throughput sequencing products have been approved for clinical diagnosis and treatment of tumors at home and abroad.However,whether highthroughput sequencing can play a better role in precision medicine depends on whether there is a standard database to accurately guide the sequencing data interpretation.With the development of high-throughput sequencing technology,massive gene sequencing data are continuously generated.It is of great practical significance to establish a standard database for the interpretation of gene variations of Chinese population,which can be used to evaluate and guide the interpretation of pathogenic genes by relevant detection institutions.At present,it is urgent to introduce a new database construction and data interpretation mechanism in order to provide basis and guarantee for the healthy development and scientific regulation of high-throughput sequencing industry in China.
作者
杨振
张孝明
黄杰
胡泽斌
李丽莉
孙彬裕
李颖
Yang Zhen;Zhang Xiaoming;Huang Jie;Hu Zebin;Li Lili;Sun Binyu;Li Ying(National Institutes for Food and Drug Control,Beijing 100050,China)
出处
《中国药事》
CAS
2019年第9期1051-1057,共7页
Chinese Pharmaceutical Affairs
关键词
高通量测序
标准数据库
数据库建设
数据解读
区块链
科学监管
high-throughput sequencing
standard database
database construction
data interpretation
block chains
scientific regulation