Hi-TOM: a platform for high-throughput tracking of mutations induced by CRISPR/Cas systems

被引:309
作者
Liu, Qing [1 ]
Wang, Chun [1 ]
Jiao, Xiaozhen [1 ]
Zhang, Huawei [2 ]
Song, Lili [3 ]
Li, Yanxin [3 ]
Gao, Caixia [2 ]
Wang, Kejian [1 ]
机构
[1] Chinese Acad Agr Sci, China Natl Rice Res Inst, State Key Lab Rice Biol, Hangzhou 310006, Zhejiang, Peoples R China
[2] Chinese Acad Sci, Inst Genet & Dev Biol, State Key Lab Plant Cell & Chromosome Engn, Beijing 100101, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Med, Shanghai Childrens Med Ctr, Pediat Translat Med Inst, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金;
关键词
CRISPR; Cas; genome editing; mutation identification; Hi-TOM; GENOME; GENERATION;
D O I
10.1007/s11427-018-9402-9
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The CRISPR/Cas system has been extensively applied to make precise genetic modifications in various organisms. Despite its importance and widespread use, large-scale mutation screening remains time-consuming, labour-intensive and costly. Here, we developed Hi-TOM (available at https://doi.org/www.hi-tom.net/hi-tom/), an online tool to track the mutations with precise percentage for multiple samples and multiple target sites. We also described a corresponding next-generation sequencing (NGS) library construction strategy by fixing the bridge sequences and barcoding primers. Analysis of the samples from rice, hexaploid wheat and human cells reveals that the Hi-TOM tool has high reliability and sensitivity in tracking various mutations, especially complex chimeric mutations frequently induced by genome editing. Hi-TOM does not require special design of barcode primers, cumbersome parameter configuration or additional data analysis. Thus, the streamlined NGS library construction and comprehensive result output make Hi-TOM particularly suitable for high-throughput identification of all types of mutations induced by CRISPR/Cas systems.
引用
收藏
页码:1 / 7
页数:7
相关论文
共 21 条
[1]   A high-throughput screening strategy for detecting CRISPR-Cas9 induced mutations using next-generation sequencing [J].
Bell, Charles C. ;
Magor, Graham W. ;
Gillinder, Kevin R. ;
Perkins, Andrew C. .
BMC GENOMICS, 2014, 15
[2]   BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment [J].
Boel, Annekatrien ;
Steyaert, Woutert ;
De Rocker, Nina ;
Menten, Bjorn ;
Callewaert, Bert ;
De Paepe, Anne ;
Coucke, Paul ;
Willaert, Andy .
SCIENTIFIC REPORTS, 2016, 6
[3]   Easy quantitative assessment of genome editing by sequence trace decomposition [J].
Brinkman, Eva K. ;
Chen, Tao ;
Amendola, Mario ;
van Steensel, Bas .
NUCLEIC ACIDS RESEARCH, 2014, 42 (22)
[4]   CRISPR/Cas9-mediated base-editing system efficiently generates gain-of-function mutations in Arabidopsis [J].
Chen, Yiyu ;
Wang, Zhiping ;
Ni, Hanwen ;
Xu, Yong ;
Chen, Qijun ;
Jiang, Linjian .
SCIENCE CHINA-LIFE SCIENCES, 2017, 60 (05) :520-523
[5]   Coming of age: ten years of next-generation sequencing technologies [J].
Goodwin, Sara ;
McPherson, John D. ;
McCombie, W. Richard .
NATURE REVIEWS GENETICS, 2016, 17 (06) :333-351
[6]   Genome editing assessment using CRISPR Genome Analyzer (CRISPR-GA) [J].
Gueell, Marc ;
Yang, Luhan ;
Church, George M. .
BIOINFORMATICS, 2014, 30 (20) :2968-2970
[7]   Anything impossible with CRISPR/Cas9? [J].
Jiao, Renjie ;
Gao, Caixia .
SCIENCE CHINA-LIFE SCIENCES, 2017, 60 (05) :445-446
[8]   Fast and accurate short read alignment with Burrows-Wheeler transform [J].
Li, Heng ;
Durbin, Richard .
BIOINFORMATICS, 2009, 25 (14) :1754-1760
[9]   CrispRVariants charts the mutation spectrum of genome engineering experiments [J].
Lindsay, Helen ;
Burger, Alexa ;
Biyong, Berthin ;
Felker, Anastasia ;
Hess, Christopher ;
Zaugg, Jonas ;
Chiavacci, Elena ;
Anders, Carolin ;
Jinek, Martin ;
Mosimann, Christian ;
Robinson, Mark D. .
NATURE BIOTECHNOLOGY, 2016, 34 (07) :701-+
[10]   APPLICATIONS OF NEXT-GENERATION SEQUENCING Sequencing technologies - the next generation [J].
Metzker, Michael L. .
NATURE REVIEWS GENETICS, 2010, 11 (01) :31-46