外显子组测序技术述评  

A review on exome sequencing technique

作　　者：马秋月[1] 戴晓港[1] 李淑娴[1] 

机构地区：[1]南京林业大学林学院,林木遗传与生物技术省部共建教育部重点实验室,江苏南京210037

出　　处：《南京林业大学学报（自然科学版）》2016年第4期157-163,共7页Journal of Nanjing Forestry University：Natural Sciences Edition

基　　金：国家林业公益性行业科研重大项目(201304102);江苏省创新团队项目;江苏高校优势学科建设工程资助项目(PAPD);南京林业大学优博基金项目

摘　　要：外显子组测序主要包括3个步骤:目标序列的富集、DNA测序、生物信息学分析。笔者介绍了外显子组测序技术及其在遗传研究中的应用,分析了该技术的优势和不足,并对其应用前景进行了展望。与转录组和全基因组测序技术相比,外显子组测序在编码基因获取方面具有高效、准确、低成本的特点;与全基因组关联分析技术(Genome-wide association analysis,GWAS)相比,能有效检测基因组中编码基因的稀有变异,但还不能检测到基因组水平上较大的结构性变异以及内含子区域的信息。目前,外显子组测序技术在人类单基因控制的遗传疾病和多基因控制的复杂疾病的分子机理研究中,能准确找到孟德尔遗传疾病致病基因;在动植物上能成功检测到目标编码区的核苷酸变化。随着模式木本植物全基因组测序的完成,利用该技术可以加快对木本植物性别、林木抗逆性及生长等重要性状基因的定位,应用前景广阔。The exome sequencing mainly includes three steps： enriching the target region, DNA sequencing, bioinfor-matics analysis. The authors give a brief introduction on the exome sequencing technique and its application in genetic studies, discuss its advantages and disadvantages and propose its application prospect in future studies. Compared with the transcriptome and the whole genome sequencing techniques, it is more efficient, more time and labor saving in ac-quisition of large sequencing data of the encoding genes. Moreover, compared with Genome-wide association analysis （ GWAS） , it can effectively detect the rare variation in exonic DNA sequences. However, it can not detect the large structural variation and the information of introns in the genome level. At present, this technique can accurately find the Mendel disease-causing gene underlying both the single gene associated diseases and the multiple gene associated diseases in the molecular mechanism. It can also detect successfully the nucleotide variations in the target coding region in animal and plant genetic studies. With the completion of the pattern of woody plants genome sequencing, some important traits gene could be located by this technique, such as sex, plant resistance, growth etc. It will bring broad application prospects.

关 键 词：外显子组测序 序列捕获 高通量测序 遗传诊断 

分 类 号：Q78[生物学—分子生物学]