Targeted capture and massively parallel sequencing of 12 human exomes.
Targeted capture and massively parallel sequencing of 12 human exomes.
复制标题
作者：
全基因组关联研究表明，常见的基因变异仅能解释常见疾病遗传风险的一小部分，这就提出了一个问题：罕见变异是否在未解释的遗传率中占很大比例。虽然DNA测序成本已大幅下降，但与在大型队列中全基因组范围内常规鉴定罕见和新型变异所需的成本相比，仍然相去甚远。因此，我们试图开发针对所有蛋白质编码区域（“外显子组”）进行靶向测序的第二代方法，以降低成本，同时增加发现高外显率变异的机会。在此，我们报告了对12个人的外显子组进行靶向捕获和大规模平行测序的情况。其中包括代表三个群体的8个国际人类基因组单体型图（HapMap）个体，以及4个患有罕见显性遗传病弗里曼 - 谢尔登综合征（FSS）的无亲缘关系个体。我们展示了在超过3亿个碱基对（Mb）的编码序列中对罕见和常见变异进行灵敏且特异的鉴定。以FSS作为概念验证，我们表明通过对少数无亲缘关系的患病个体进行外显子组测序，可以确定单基因疾病的候选基因。通过更大的样本量以及根据预测的功能影响对非同义变异进行适当加权，这一策略可能可扩展到遗传学更复杂的疾病。
Genome-wide association studies suggest that common genetic variants explain only a small fraction of heritable risk for common diseases, raising the question of whether rare variants account for a significant fraction of unexplained heritability. While DNA sequencing costs have fallen dramatically, they remain far from what is necessary for rare and novel variants to be routinely identified at a genome-wide scale in large cohorts. We have therefore sought to develop second-generation methods for targeted sequencing of all protein-coding regions (`exomes'), to reduce costs while enriching for discovery of highly penetrant variants. Here we report on the targeted capture and massively parallel sequencing of the exomes of twelve humans. These include eight HapMap individuals representing three populations, and four unrelated individuals with a rare dominantly inherited disorder, Freeman-Sheldon syndrome (FSS). We demonstrate the sensitive and specific identification of rare and common variants in over 300 megabases (Mb) of coding sequence. Using FSS as a proof-of-concept, we show that candidate genes for monogenic disorders can be identified by exome sequencing of a small number of unrelated, affected individuals. This strategy may be extendable to diseases with more complex genetics through larger sample sizes and appropriate weighting of nonsynonymous variants by predicted functional impact.
登录
查看更多内容
DOI：
10.1073/pnas.0812824106
发表时间：
2009-03-10
影响因子：
11.1
作者：
Kryukov, Gregory V.;Shpunt, Alexander;Sunyaev, Shamil R.
通讯作者：
Sunyaev, Shamil R.
影响因子：
30.8
作者：
Toydemir, RM;Rutherford, A;Bamshad, MJ
通讯作者：
Bamshad, MJ
影响因子：
4.5
作者：
Ng, Pauline C.;Levy, Samuel;Huang, Jiaqi;Stockwell, Timothy B.;Walenz, Brian P.;Li, Kelvin;Axelrod, Nelson;Busam, Dana A.;Strausberg, Robert L.;Venter, J. Craig
通讯作者：
Venter, J. Craig
影响因子：
7
作者：
Li, Heng;Ruan, Jue;Durbin, Richard
通讯作者：
Durbin, Richard
影响因子：
30.8
作者：
Campbell, Peter J.;Stephens, Philip J.;Pleasance, Erin D.;O'Meara, Sarah;Li, Heng;Santarius, Thomas;Stebbings, Lucy A.;Leroy, Catherine;Edkins, Sarah;Hardy, Claire;Teague, Jon W.;Menzies, Andrew;Goodhead, Ian;Turner, Daniel J.;Clee, Christopher M.;Quail, Michael A.;Cox, Antony;Brown, Clive;Durbin, Richard;Hurles, Matthew E.;Edwards, Paul A. W.;Bignell, Graham R.;Stratton, Michael R.;Futreal, P. Andrew
通讯作者：
Futreal, P. Andrew