基因组的“读-改-写”技术

doi:10.12211/2096-8280.2020-013

合成生物学 ›› 2020, Vol. 1 ›› Issue (5): 503-515.DOI: 10.12211/2096-8280.2020-013

基因组的“读-改-写”技术

王会¹^,²(), 戴俊彪¹^,², 罗周卿²

^1.深圳大学生命与海洋科学学院，广东深圳 518055
^2.中国科学院深圳先进技术研究院，深圳合成生物学创新研究院，合成基因组学研究中心，广东省合成基因组学重点实验室，深圳合成基因组学重点实验室，广东深圳 518055

收稿日期:2020-02-29 修回日期:2020-04-19 出版日期:2020-10-31 发布日期:2020-12-03
通讯作者: 戴俊彪,罗周卿
作者简介:作者简介:王会(1993—)，女，硕士研究生，主要研究方向为合成生物学。E-mail：15225377578@163.com
戴俊彪（1974—），男，博士，研究员，主要研究方向为合成生物学。E-mail：junbiao.dai@siat.ac.cn
罗周卿（1990—），男，博士，副研究员，主要研究方向为合成生物学。E-mail：zq.luo@siat.ac.cn
基金资助:
国家重点研发计划“合成生物学”重点专项(2018YFA0900100);国家自然科学基金(31725002);深圳合成基因组学重点实验室项目(ZDSYS201802061806209);广东省合成基因组学重点实验室(2019B030301006);深圳市科技计划(KQTD20180413181837372)

Reading, editing, and writing techniques for genome research

WANG Hui¹^,²(), DAI Junbiao¹^,², LUO Zhouqing²

^1.College of Life Sciences and Oceanography，Shenzhen University，Shenzhen 518055，Guangdong，China
^2.Guangdong Provincial Key Laboratory of Synthetic Genomics，Shenzhen Key Laboratory of Synthetic Genomics，Center for Synthetic Genomics，Shenzhen Institute of Synthetic Biology，Shenzhen Institutes of Advanced Technology，Chinese Academy of Sciences，Shenzhen 518055，Guangdong，China

Received:2020-02-29 Revised:2020-04-19 Online:2020-10-31 Published:2020-12-03
Contact: DAI Junbiao, LUO Zhouqing

摘要/Abstract

摘要：

基因组是生命系统的指令中枢，对基因组的研究是生命科学的核心内容，基因组研究相关技术的开发是深化对基因组序列和功能认识的重要推动力量。通过基因组测序获取基因组全序列，通过人工诱变、定点编辑研究基因组局部序列的功能与调控，通过对基因组的从头设计与化学再造实现对生命性状的定制，是基因组研究的三个不同层面。从一代测序到三代测序，基因组“读”技术极大地降低了成本和难度，提升了速度和精准度，引领着复杂基因组、大型基因组从草图走向完成图时代。通过人工诱变、定点编辑等技术可以改变野生型基因组的局部序列，研究基因组序列的功能与调控。从人工诱变到定点编辑，从ZFN到CRISPR，基因组“改”技术在效率、适用对象和简便性上有了显著的提高，为“基因型-表型”研究提供了有力工具，精准编辑、高通量编辑逐步走向应用。通过对基因组的从头设计与化学再造，书写人工基因组，可以获得对基因组全局的系统认识，实现对生命性状的定制。从病毒基因组合成、细菌基因组合成到酵母基因组合成，再到国际基因组写计划，基因组“写”技术在适用对象上不断拓展，人工设计、化学再造正成为复杂生物学问题研究和已有性状优化、新性状引入的一把利器。本文主要综述了基因组测序（读）、基因组编辑（改）和基因组合成（写）技术的发展历程、各自的特征、目前的研究进展及在基因组研究方面的一些应用，并对近期相关技术的可能突破点进行了总结和展望。“读-改-写”技术互为支撑，推动基因组研究在致知和致用领域两面开花。

关键词: 合成生物学, 功能基因组, 基因组测序, 基因组编辑, 合成基因组学

Abstract:

Genome carries the entire genetic information of life. Genome-related researches are ultimate fundamentals for life sciences. Technological development in genomic researches has deepened our understanding of genomes and their function. Obtaining genome sequences through sequencing, studying their function and regulation through editing and creating customer designed genomes through synthesis are three important aspects of genome research. From the first-generation sequencing to the third-generation sequencing, the "reading" technology has greatly reduced the cost and difficulty, while improved the speed, enabling the production of complete genomic information for complex and large genomes. From random mutagenesis to site-specific genome editing and, from ZFN to CRISPR, the genome "editing" technology has improved significantly in efficiency, applicability, and simplicity, providing a wealth of materials to dissect "genotype-phenotype" relationship. Accurate editing and high-throughput editing are moving towards applications in various areas. From viral genome, bacterial genome to yeast genome, and ultimately to human genome, synthetic genomics has moved from simple organisms to many complex organisms. Precise, fast and low-cost synthesis technologies are important for the development of synthetic genomics. This article reviews the histories, features, present status, and applications of technologies for genome sequencing (reading), genome editing (editing) and genome synthesizing (writing). The potential breakthrough of these technologies in the near future is also summarized and prospected. The ability to read, edit and write a genome has been and will continue to advance not only our understanding but also better utilization of living systems.

Key words: synthetic biology, functional genomics, genome sequencing, genome editing, synthetic genomics

中图分类号:

王会, 戴俊彪, 罗周卿. 基因组的“读-改-写”技术[J]. 合成生物学, 2020, 1(5): 503-515.

WANG Hui, DAI Junbiao, LUO Zhouqing. Reading, editing, and writing techniques for genome research[J]. Synthetic Biology Journal, 2020, 1(5): 503-515.

图/表 7

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物种	基因组大小/Mb	编码区占比/%	非编码区占比/%	参考数据库
Homo sapiens	3107	2.8	97.2	UCSC Genome Browser (hg18)
Drosophila melanogaster	168.7	18.3	81.7	FlyBase
Saccharomyces cerevisiae	12.2	72.9	27.1	Saccharomyces Genome Database
Escherichia coli K12	4.6	88	12	EcoCyc

物种	基因组大小/Mb	编码区占比/%	非编码区占比/%	参考数据库
Homo sapiens	3107	2.8	97.2	UCSC Genome Browser (hg18)
Drosophila melanogaster	168.7	18.3	81.7	FlyBase
Saccharomyces cerevisiae	12.2	72.9	27.1	Saccharomyces Genome Database
Escherichia coli K12	4.6	88	12	EcoCyc

测序技术	应用	读长	优点	缺点
一代测序	早期简单基因组测序；日常PCR产物、质粒等的测序	约1000 bp	读长较长，准确度高（99.999%）	成本高，通量低
二代测序	目前大部分基因组、转录组的测序	200～500 bp	成本低，通量高，准确度大于99.94%	读长短
三代测序（SMRT sequencing）	复杂基因组、全长转录组等的测序	10～100 kb	读长长，准确度高，可直接检测DNA或者RNA上的修饰	测序成本高，每个SMRT cell的数据产出有限（约10 Gb），文库准备需要大量的起始材料，目前读长还比较有限（约80 kb）
三代测序（nanopore sequencing）	复杂基因组的测序，结构变异的鉴定等	kb～Mb	超长读长，经济高效，可直接检测DNA或者RNA上的修饰	错误率高，对于多碱基重复存在系统误差，文库准备需要大量的起始材料

测序技术	应用	读长	优点	缺点
一代测序	早期简单基因组测序；日常PCR产物、质粒等的测序	约1000 bp	读长较长，准确度高（99.999%）	成本高，通量低
二代测序	目前大部分基因组、转录组的测序	200～500 bp	成本低，通量高，准确度大于99.94%	读长短
三代测序（SMRT sequencing）	复杂基因组、全长转录组等的测序	10～100 kb	读长长，准确度高，可直接检测DNA或者RNA上的修饰	测序成本高，每个SMRT cell的数据产出有限（约10 Gb），文库准备需要大量的起始材料，目前读长还比较有限（约80 kb）
三代测序（nanopore sequencing）	复杂基因组的测序，结构变异的鉴定等	kb～Mb	超长读长，经济高效，可直接检测DNA或者RNA上的修饰	错误率高，对于多碱基重复存在系统误差，文库准备需要大量的起始材料

种类	大小（氨基酸数）	PAM	来源及特色	参考文献
SpCas9	1368	NGG	Streptococcus pyogenes，应用广泛	[10,11]
SaCas9	1053	NNGRRT	Staphylococcus aureus 体积小，单个AAV载体即可承载SaCas9和对应的guide RNA	[34]
NmeCas9	1082	NNNNGATT	Neisseria meningitidis 识别的PAM位点较长，切割活性较SpCas9低，但特异性较好	[35]
CjCas9	984	NNNNACAC 和 NNNNRYAC	Campylobacter jejuni 迄今为止发现的最小的Cas9蛋白，单个AAV载体即可承载CjCas9和对应的guide RNA	[36]
SpCas9-NG	1368	NGH	理性设计的SpCas9突变体，具有与SpCas9类似的特异性	[37]
xCas9	1368	NG，GAA和GTA	用噬菌体辅助的连续进化技术对SpCas9改造而来，相比SpCas9有更好的特异性	[38]

基因组的“读-改-写”技术

Reading, editing, and writing techniques for genome research

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Cas蛋白	蛋白大小（氨基酸数）	导向分子大小（核苷酸数）	靶标核酸的主要类型	靶标序列限制	活性控制	精确性	应用领域
Cas9	约1000～1600	约105 （sgRNA）	dsDNA	含有PAM序列（对SpCas9而言，为NGG），PAM位点近端产生平末端	由RuvC和HNH结构域负责靶DNA的切割，结合并切割靶向DNA	可容忍DNA链上的单个错配	基因组编辑、基因表达调控、成像等
Cas12	约1300	约42～44 （crRNA）	dsDNA	含有PAM序列（对Cas12a而言，为TTTV），在PAM位点远端产生5' 突出末端	由RuvC和Nuc结构域负责靶DNA的切割，结合并切割靶向DNA	可有效区分双链DNA上一个碱基的差异	基因组编辑和基于双链DNA的分子诊断等
Cas13	约1400	约64 （crRNA）	ssRNA	RNA结构影响其活性，不同来源的Cas13蛋白对PFS序列的要求不同，但都相对较弱	由两个HEPN结构域负责靶RNA的切割；在体外及细菌体内，Cas13a识别并切割靶向序列后即转入酶促“激活”状态，结合并切割其他的ssRNA	很难区分一个碱基的差异	RNA敲低和基于RNA的分子诊断等
Cas14	约400～700	约140 （sgRNA）	ssDNA	对单链DNA没有限制，双链DNA必须含有PAM序列（对Cas14a而言，为TTTR）	由RuvC结构域负责靶DNA的切割，识别并切割靶向序列后即转入酶促“激活”状态，这时它将结合并切割其他的 ssDNA	可有效区分单链DNA上一个碱基的差异	基于单链DNA的分子诊断等

物种	基因组大小	基因数目	合成时间
Poliovirus	7.7 kb	10	2002年
PhiX174	5.4 kb	11	2003年
Mycoplasma genitalium	580 kb	525	2008年
Mycoplasma mycoides	1.2 Mb	985	2010年
Escherichia coli	3.97 Mb	3730	2019年
Saccharomyces cerevisiae	1.25 Mb	5770	2011年
Homo sapiens	3.3 Gb	约21 000	2016年

SCRaMbLE对象	对后续合成菌株的应用所具有的价值	参考文献
synⅨR（环形）	对SCRaMbLE系统的首次实验验证，证实了SCRaMbLE系统可以高效地产生删除、倒换和重复等基因组结构变异	[83]
synⅤ	利用纳米孔测序技术解析重排基因组，证实了SCRaMbLE所造成的基因组重排可用于外源代谢途径特异的底盘细胞改良	[84]
含有loxPsym 位点的质粒	建立光控的Cre重组酶活性控制系统（L-SCRaMbLE），实现对其活性更加精准的控制	[85]
synⅤ	利用与门电路精准控制Cre重组酶的活性以及利用多次SCRaMbLE实现带有合成染色体的异源二倍体菌株中的外源代谢途径的产量提升	[86]
synⅡ	通过对loxPsym等位点的设计改造建立SCRaMbLE-in技术，实现外源代谢途径的优化和底盘细胞的适配	[87]
synⅫ，synⅢ等	基于loxP与loxPsym位点的正交性建立ReSCuES基因组重排报告系统，实现重排菌株的高效筛选、耐受性进化和机制解析	[88]
synⅤ，synⅩ	表征了带有合成染色体的种内杂交菌株或种间杂交菌株的SCRaMbLE行为，为利用合成染色体优化工业菌株性状奠定基础	[89]
synⅤ（环形）	环形染色体SCRaMbLE可以产生非合成染色体的数目变化，非整倍体菌株可用于提高prodeoxyviolacein的产量	[90]
β-胡萝卜素途径	利用SCRaMbLE原理设计了基于结构变异的DNA文库体外构建方法，可用于外源代谢途径的体外优化	[91]
synⅤ	将自动化样品制备、超快速LC-MS方法和条形码纳米孔测序相结合，解决了重排菌株代谢性能快速表征的技术障碍	[92]

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