合成生物学 ›› 2023, Vol. 4 ›› Issue (1): 30-46.DOI: 10.12211/2096-8280.2022-055
杨毅1, 毛雨丰1, 杨春贺1,2, 王猛1, 廖小平1, 马红武1
收稿日期:
2022-10-03
修回日期:
2022-11-23
出版日期:
2023-02-28
发布日期:
2023-03-07
通讯作者:
马红武
作者简介:
杨毅(1986—),男,博士研究生。研究方向为生物信息学、合成生物学、代谢工程。基金资助:
Yi YANG1, Yufeng MAO1, Chunhe YANG1,2, Meng WANG1, Xiaoping LIAO1, Hongwu MA1
Received:
2022-10-03
Revised:
2022-11-23
Online:
2023-02-28
Published:
2023-03-07
Contact:
Hongwu MA
摘要:
以同源重组、CRISPR等为代表的遗传操作技术是合成生物学的重要支撑技术。高效准确的遗传操作依赖于可准确定位编辑位点和实现序列改造的编辑序列(如引物序列、同源臂序列、sgRNA序列等)。由于遗传改造目标与遗传操作技术丰富多变,加之近年来基于生物铸造厂(BioFoundry)的自动化遗传改造模式对高通量设计的需求日益增加,使得通过计算机辅助设计工具实现精准快速的编辑序列设计愈发重要。本文针对不同阶段实现不同目标的微生物遗传操作技术和相应的编辑序列辅助设计工具的发展进行了综述。按照不同编辑序列类型和遗传操作应用场景,将编辑序列设计工具划分为四种类型:引物设计工具、DNA组装的设计工具、sgRNA设计工具、基因组编辑的全流程设计工具,对各类编辑序列设计工具的应用及存在的问题进行了分析总结并对未来的研究方向进行了展望。编辑序列设计工具的发展将有助于实现合成生物学“设计—构建—测试—学习”(design-build-test-learn,DBTL)工作循环中上游的基因型“设计”与下游“构建”两个关键环节之间的无缝衔接。
中图分类号:
杨毅, 毛雨丰, 杨春贺, 王猛, 廖小平, 马红武. 面向微生物遗传操作的编辑序列设计工具的研究进展[J]. 合成生物学, 2023, 4(1): 30-46.
Yi YANG, Yufeng MAO, Chunhe YANG, Meng WANG, Xiaoping LIAO, Hongwu MA. Recent progress in computational tools for designing editing sequences used in microbial genetic manipulations[J]. Synthetic Biology Journal, 2023, 4(1): 30-46.
图1 遗传操作技术与编辑序列设计需求、工具的代表性进展(蓝色框代表遗传操作技术;绿色框代表编辑序列设计需求;棕色框代表编辑序列设计工具;棕色序号代表该编辑序列设计工具能够解决对应的编辑序列设计需求)
Fig. 1 Development of genetic manipulation technologies and corresponding editing sequences and tools for editing sequence design(Blue rectangle: Genetic manipulation technologies; Green rectangle: Editing sequence design requirements; Brown rectangle: Editing sequence design tools; Brown serial numbers indicates that the editing sequence design tools can address the corresponding editing sequence design requirements)
工具 | 基于Primer3 | 特异性检验 | 批量设计 | 功能特色 | 可用性 | URL |
---|---|---|---|---|---|---|
Primer3[ | — | 否 | 否 | 基础引物设计 | 在线/图形界面、离线/命令行 | https://bioinfo.ut.ee/primer3/ |
BatchPrimer3[ | 是 | 否 | 是 | 批量引物设计 | 在线/图形界面 | http://probes.pw.usda.gov/cgi-bin/batchprimer3/batchprimer3.cgi |
ConservedPrimer2.0[ | 是 | 是 | 是 | Sanger测序引物设计 | 在线/图形界面 | https://probes.pw.usda.gov/ConservedPrimers/index.html |
PrimerDesign-M[ | 否 | 是 | 是 | Sanger测序引物设计 | 在线/图形界面 | www.hiv.lanl.gov/content/sequence/PRIMER_DESIGN/primer_design.html |
Primer-BLAST[ | 是 | 是 | 否 | RT-PCR引物设计 | 在线/图形界面 | https://www.ncbi.nlm.nih.gov/tools/primer-blast/ |
PCR designer[ | 否 | 否 | 否 | SNP分析引物设计 | 在线/图形界面 | http://primer1.soton.ac.uk/primer.html |
PRIMEGENS-v2[ | 是 | 否 | 是 | 剪接变体引物设计 | 在线/图形界面、离线/命令行 | http://primegens.org/ |
PrimerSeq[ | 是 | 否 | 是 | 剪接变体引物设计 | 离线/图形界面 | https://primerseq.sourceforge.net/ |
MSP-HTPrimer[ | 是 | 否 | 是 | DNA甲基化分析引物设计 | 离线/命令行 | https://sourceforge.net/projects/msp-htprimer/ |
MPD[ | 否 | 是 | 是 | 多重PCR引物设计 | 离线/命令行 | https://wingolab-org.github.io/mpd-c/ |
Mutation Maker[ | 是 | 是 | 是 | 多重PCR引物设计、氨基酸突变引物设计 | 离线/命令行 | https://github.com/ra100/Mutation_Maker |
PerlPrimer[ | 否 | 否 | 是 | Sanger测序引物设计、RT-PCR引物设计、开放阅读框(ORF)搜索及相关引物设计 | 离线/图形界面 | https://perlprimer.sourceforge.net/ |
表1 不同功能的主流引物设计工具
Table 1 Major primer design tools with different functions
工具 | 基于Primer3 | 特异性检验 | 批量设计 | 功能特色 | 可用性 | URL |
---|---|---|---|---|---|---|
Primer3[ | — | 否 | 否 | 基础引物设计 | 在线/图形界面、离线/命令行 | https://bioinfo.ut.ee/primer3/ |
BatchPrimer3[ | 是 | 否 | 是 | 批量引物设计 | 在线/图形界面 | http://probes.pw.usda.gov/cgi-bin/batchprimer3/batchprimer3.cgi |
ConservedPrimer2.0[ | 是 | 是 | 是 | Sanger测序引物设计 | 在线/图形界面 | https://probes.pw.usda.gov/ConservedPrimers/index.html |
PrimerDesign-M[ | 否 | 是 | 是 | Sanger测序引物设计 | 在线/图形界面 | www.hiv.lanl.gov/content/sequence/PRIMER_DESIGN/primer_design.html |
Primer-BLAST[ | 是 | 是 | 否 | RT-PCR引物设计 | 在线/图形界面 | https://www.ncbi.nlm.nih.gov/tools/primer-blast/ |
PCR designer[ | 否 | 否 | 否 | SNP分析引物设计 | 在线/图形界面 | http://primer1.soton.ac.uk/primer.html |
PRIMEGENS-v2[ | 是 | 否 | 是 | 剪接变体引物设计 | 在线/图形界面、离线/命令行 | http://primegens.org/ |
PrimerSeq[ | 是 | 否 | 是 | 剪接变体引物设计 | 离线/图形界面 | https://primerseq.sourceforge.net/ |
MSP-HTPrimer[ | 是 | 否 | 是 | DNA甲基化分析引物设计 | 离线/命令行 | https://sourceforge.net/projects/msp-htprimer/ |
MPD[ | 否 | 是 | 是 | 多重PCR引物设计 | 离线/命令行 | https://wingolab-org.github.io/mpd-c/ |
Mutation Maker[ | 是 | 是 | 是 | 多重PCR引物设计、氨基酸突变引物设计 | 离线/命令行 | https://github.com/ra100/Mutation_Maker |
PerlPrimer[ | 否 | 否 | 是 | Sanger测序引物设计、RT-PCR引物设计、开放阅读框(ORF)搜索及相关引物设计 | 离线/图形界面 | https://perlprimer.sourceforge.net/ |
图2 Gibson 和Golden Gate DNA序列组装技术及相关编辑序列设计原理F—片段;P—引物;RE—限制性内切酶
Fig. 2 Gibson and Golden Gate assembly and corresponding principles for editing sequence designF—Fragement; P—Primer; RE—Restriction enzyme
工具 | 基于Primer3 | 支持的DNA片段组装技术 | 批量设计 | 可用性 | URL |
---|---|---|---|---|---|
J5[ | 是 | Golden Gate/Gibson/ CPEC/SLIC | 是 | 在线/图形界面 | https://j5.jbei.org/ |
Geneious | 否 | Gibson | 是 | 在线/图形界面 | https://www.geneious.com/ |
Raven[ | 否 | Gibson | 是 | 在线/图形界面 | http://ravencad.org/ |
MCDS[ | 否 | GoldenGate/Gibson/ SLIC/Gateway | 否 | 离线/命令行 | https://github.com/errisy/MCDS |
NEBbridge Golden Gate[ | 未知 | Golden Gate | 是 | 在线/图形界面 | https://goldengate.neb.com/ |
iBioCAD GGA[ | 未知 | Golden Gate | 是 | 在线/图形界面 | https://ibiocad.igb.illinois.edu/ |
PlasmidMaker[ | 是 | Golden Gate/Gibson | 是 | 在线/图形界面 | https://biofoundry.web.illinois.edu/ |
表2 面向DNA片段组装的代表性设计工具
Table 2 Representative design tools for DNA assembly
工具 | 基于Primer3 | 支持的DNA片段组装技术 | 批量设计 | 可用性 | URL |
---|---|---|---|---|---|
J5[ | 是 | Golden Gate/Gibson/ CPEC/SLIC | 是 | 在线/图形界面 | https://j5.jbei.org/ |
Geneious | 否 | Gibson | 是 | 在线/图形界面 | https://www.geneious.com/ |
Raven[ | 否 | Gibson | 是 | 在线/图形界面 | http://ravencad.org/ |
MCDS[ | 否 | GoldenGate/Gibson/ SLIC/Gateway | 否 | 离线/命令行 | https://github.com/errisy/MCDS |
NEBbridge Golden Gate[ | 未知 | Golden Gate | 是 | 在线/图形界面 | https://goldengate.neb.com/ |
iBioCAD GGA[ | 未知 | Golden Gate | 是 | 在线/图形界面 | https://ibiocad.igb.illinois.edu/ |
PlasmidMaker[ | 是 | Golden Gate/Gibson | 是 | 在线/图形界面 | https://biofoundry.web.illinois.edu/ |
工具 | 编辑效率预测方法 | 特异性预测方法 | PAM | 支持的改造类型 | URL |
---|---|---|---|---|---|
E-CRISP[ | 假设先验 | 假设先验 | NGG | 敲除、激活、抑制 | http://www.e-crisp.org/E-CRISP/index.html |
CRISPR-ERA[ | 假设先验 | 假设先验 | NGG | 敲除、激活、抑制 | http://CRISPR-ERA.stanford.edu |
EuPaGDT[ | 假设先验 | 假设先验 | NGG、TTTN、NGA等 | 敲除 | http://grna.ctegd.uga.edu/ |
CRISPOR[ | 假设先验/机器学习 | 假设先验 | NGG、TTTN、NGA等 | 敲除 | http://crispor.tefor.net/ |
CHOPCHOP[ | 假设先验/机器学习 | 假设先验 | NGG、TTTN、NGA等 | 敲除、敲入、激活、抑制 | http://chopchop.cbu.uib.no/ |
CRISPETa[ | 假设先验 | 数据库搜索 | NGG | 敲除 | http://crispeta.crg.eu |
CRISPR-P[ | 假设先验 | 假设先验 | NGG、NRG、TTN等 | 敲除 | http://crispr.hzau.edu.cn/CRISPR2/ |
CRISPRscan[ | 机器学习 | 假设先验 | NGG、TTTN、NGN等 | 敲除 | https://www.crisprscan.org |
WU-CRISPR[ | 机器学习 | 假设先验 | NGG | 敲除 | http://crisprdb.org/wu-crispr/ |
CRISTA[ | 机器学习 | 机器学习 | NGG | 敲除 | https://crista.tau.ac.il/ |
Elevation[ | 机器学习 | 机器学习 | NGG | 敲除 | https://crispr.ml/ |
表3 基于假设先验方法与基于学习方法的代表性sgRNA设计工具
Table 3 Representative hypothesis-driven and learning-based sgRNA design tools
工具 | 编辑效率预测方法 | 特异性预测方法 | PAM | 支持的改造类型 | URL |
---|---|---|---|---|---|
E-CRISP[ | 假设先验 | 假设先验 | NGG | 敲除、激活、抑制 | http://www.e-crisp.org/E-CRISP/index.html |
CRISPR-ERA[ | 假设先验 | 假设先验 | NGG | 敲除、激活、抑制 | http://CRISPR-ERA.stanford.edu |
EuPaGDT[ | 假设先验 | 假设先验 | NGG、TTTN、NGA等 | 敲除 | http://grna.ctegd.uga.edu/ |
CRISPOR[ | 假设先验/机器学习 | 假设先验 | NGG、TTTN、NGA等 | 敲除 | http://crispor.tefor.net/ |
CHOPCHOP[ | 假设先验/机器学习 | 假设先验 | NGG、TTTN、NGA等 | 敲除、敲入、激活、抑制 | http://chopchop.cbu.uib.no/ |
CRISPETa[ | 假设先验 | 数据库搜索 | NGG | 敲除 | http://crispeta.crg.eu |
CRISPR-P[ | 假设先验 | 假设先验 | NGG、NRG、TTN等 | 敲除 | http://crispr.hzau.edu.cn/CRISPR2/ |
CRISPRscan[ | 机器学习 | 假设先验 | NGG、TTTN、NGN等 | 敲除 | https://www.crisprscan.org |
WU-CRISPR[ | 机器学习 | 假设先验 | NGG | 敲除 | http://crisprdb.org/wu-crispr/ |
CRISTA[ | 机器学习 | 机器学习 | NGG | 敲除 | https://crista.tau.ac.il/ |
Elevation[ | 机器学习 | 机器学习 | NGG | 敲除 | https://crispr.ml/ |
图4 CRISPR/Cas系统介导的同源重组技术实现靶序列敲除相关编辑序列设计DF—敲除的片段;P—引物;UHAmin—游同源臂长度最小值;UHAmax—游同源臂长度最大值;ODRUHA—游同源臂上游引物的可选设计区域;DHAmin—游同源臂长度最小值;DHAmax—游同源臂长度最大值;ODRDHA—游同源臂下游引物的可选设计区域;R—gRNA(sgRNA边框线的绿色和蓝色的深度分别代表on-target效率和off-target风险);TP—证引物;UHA—游同源臂;DHA—游同源臂;USSmin—游间隔序列(上游验证引物的3'末端到上游同源臂5'末端的序列)的长度最小值;USSmax—游间隔序列的长度最大值;ODRUSS—游验证引物可选设计区域;DSSmin—游间隔序列(下游验证引物的3'末端到下游同源臂3'-末端的序列)的长度最小值;DSSmax—游间隔序列的长度最大值;ODRDSS—游验证引物可选设计区域
Fig. 4 Schematic diagram for CRISPR/Cas-based homologous recombination and its editing sequencesDF—Deleted fragment; P — Primer; UHAmin—Minimum length of upstream homology arm; UHAmax— Maximum length of upstream homology arm; ODRUHA—Optional design region of the upstream primer of the upstream homologous arm; DHAmin —Minimum length of downstream homology arm; DHAmax— Maximum length of downstream homology arm; ODRDHA— Optional design region of the downstream primer of downstream homologous arm; R—sgRNA (dark green and blue of the sgRNA border lines represent on-target efficiency and off-target risk, respectively); TP— Test primer; UHA— Upstream homologous arm; DHA— Downstream homologous arm; USSmin—Minimum length of upstream spacer sequence (sequence from the 3'-end of the upstream verification primer to the 5'-end of the upstream homology arm); USSmax— Maxmum length of upstream spacer sequence; ODRUSS— Optional design region of the upstream verification primer; DSSmin— Minimum length of downstream spacer sequence (sequence from the 3'-end of the downstream verification primer to the 3'-end of the downstream homology arm); DSSmax— Maxmum length of downstream spacer sequence; ODRDSS—Optional design region of the downstream verification primer
工具 | 编辑序列设计 | 遗传改造类型 | 是否高通量 | 可支持物种 | 可编辑位点 | web应用 |
---|---|---|---|---|---|---|
Yeastriction[ | 引物设计sgRNA设计 | 删除 | 否 | Saccharomyces cerevisiae(33个菌株) | 已被注释的基因 | http://yeastriction.tnw.tudelft.nl/#!/ |
GeneTargeter[ | 引物设计sgRNA设计 | 删除、表达弱化 | 是 | Plasmodium falciparum | 已被注释的基因 | http://genetargeter.mit.edu/ |
GEDpm-cg[ | 引物设计、同源臂设计 | 单点突变 | 是 | Corynebacterium glutamicum | 基因组任意区域 | https://gedpm-cg.biodesign.ac.cn/ |
AutoESD[ | 引物设计、同源臂设计 | 插入、删除、替换、单点突变 | 是 | 多种原核、真核微生物 | 基因组任意区域 | https://autoesd.biodesign.ac.cn/ |
表4 面向基因组编辑全流程的编辑序列设计工具
Table 4 Editing sequence design tools for the whole workflow of genome editing
工具 | 编辑序列设计 | 遗传改造类型 | 是否高通量 | 可支持物种 | 可编辑位点 | web应用 |
---|---|---|---|---|---|---|
Yeastriction[ | 引物设计sgRNA设计 | 删除 | 否 | Saccharomyces cerevisiae(33个菌株) | 已被注释的基因 | http://yeastriction.tnw.tudelft.nl/#!/ |
GeneTargeter[ | 引物设计sgRNA设计 | 删除、表达弱化 | 是 | Plasmodium falciparum | 已被注释的基因 | http://genetargeter.mit.edu/ |
GEDpm-cg[ | 引物设计、同源臂设计 | 单点突变 | 是 | Corynebacterium glutamicum | 基因组任意区域 | https://gedpm-cg.biodesign.ac.cn/ |
AutoESD[ | 引物设计、同源臂设计 | 插入、删除、替换、单点突变 | 是 | 多种原核、真核微生物 | 基因组任意区域 | https://autoesd.biodesign.ac.cn/ |
1 | COHEN S N, CHANG A C, BOYER H W, et al. Construction of biologically functional bacterial plasmids in vitro [J]. Proceedings of the National Academy of Sciences of the United States of America, 1973, 70(11): 3240-3244. |
2 | CHANG A C, COHEN S N. Genome construction between bacterial species in vitro: replication and expression of Staphylococcus plasmid genes in Escherichia coli [J]. Proceedings of the National Academy of Sciences of the United States of America, 1974, 71(4): 1030-1034. |
3 | KLECKNER N, ROTH J, BOTSTEIN D. Genetic engineering in vivo using translocatable drug-resistance elements: new methods in bacterial genetics[J]. Journal of Molecular Biology, 1977, 116(1): 125-159. |
4 | GIBSON D G, YOUNG L, CHUANG R Y, et al. Enzymatic assembly of DNA molecules up to several hundred kilobases[J]. Nature Methods, 2009, 6(5): 343-345. |
5 | ENGLER C, GRUETZNER R, KANDZIA R, et al. Golden gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes[J]. PLoS One, 2009, 4(5): e5553. |
6 | SCHERER S, DAVIS R W. Replacement of chromosome segments with altered DNA sequences constructed in vitro [J]. Proceedings of the National Academy of Sciences of the United States of America, 1979, 76(10): 4951-4955. |
7 | MURPHY K C. Use of bacteriophage lambda recombination functions to promote gene replacement in Escherichia coli [J]. Journal of Bacteriology, 1998, 180(8): 2063-2071. |
8 | JINEK M, CHYLINSKI K, FONFARA I, et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity[J]. Science, 2012, 337(6096): 816-821. |
9 | KOMOR A C, KIM Y B, PACKER M S, et al. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage[J]. Nature, 2016, 533(7603): 420-424. |
10 | ANZALONE A V, RANDOLPH P B, DAVIS J R, et al. Search-and-replace genome editing without double-strand breaks or donor DNA[J]. Nature, 2019, 576(7785): 149-157. |
11 | STORCH M, HAINES M C, BALDWIN G S. DNA-BOT: a low-cost, automated DNA assembly platform for synthetic biology[J]. Synthetic Biology, 2020, 5(1): ysaa010. |
12 | SI T, CHAO R, MIN Y H, et al. Automated multiplex genome-scale engineering in yeast[J]. Nature Communications, 2017, 8: 15187. |
13 | ENGHIAD B, XUE P, SINGH N, et al. PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction[J]. Nature Communications, 2022, 13: 2697. |
14 | YANG Y, MAO Y F, WANG R Y, et al. AutoESD: a web tool for automatic editing sequence design for genetic manipulation of microorganisms[J]. Nucleic Acids Research, 2022, 50(W1): W75-W82. |
15 | UNTERGASSER A, CUTCUTACHE I, KORESSAAR T, et al. Primer3—new capabilities and interfaces[J]. Nucleic Acids Research, 2012, 40(15): e115. |
16 | HILLSON N J, ROSENGARTEN R D, KEASLING J D. J5 DNA assembly design automation software[J]. ACS Synthetic Biology, 2012, 1(1): 14-21. |
17 | MONTAGUE T G, CRUZ J M, GAGNON J A, et al. CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing[J]. Nucleic Acids Research, 2014, 42(W1): W401-W407. |
18 | 唐婷, 付立豪, 郭二鹏, 等. 自动化合成生物技术与工程化设施平台[J]. 科学通报, 2021, 66(3): 300-309. |
TANG T, FU L H, GUO E P, et al. Automation in synthetic biology using biological foundries[J]. Chinese Science Bulletin, 2021, 66(3): 300-309. | |
19 | ARNOLD C. Cloud labs: Where robots do the research[J]. Nature, 2022, 606(7914): 612-613. |
20 | WANG Y, LIU Y, LIU J, et al. MACBETH: Multiplex automated Corynebacterium glutamicum base editing method[J]. Metabolic Engineering, 2018, 47: 200-210. |
21 | CÁRDENAS P, ESHERICK L Y, CHAMBONNIER G, et al. GeneTargeter: automated in silico design for genome editing in the malaria parasite, Plasmodium falciparum [J]. The CRISPR Journal, 2022, 5(1): 155-164. |
22 | KÄMPKE T, KIENINGER M, MECKLENBURG M. Efficient primer design algorithms[J]. Bioinformatics, 2001, 17(3): 214-225. |
23 | LINZ U, DELLING U, RÜBSAMEN-WAIGMANN H. Systematic studies on parameters influencing the performance of the polymerase chain reaction[J]. Journal of Clinical Chemistry and Clinical Biochemistry (Zeitschrift Fur Klinische Chemie Und Klinische Biochemie), 1990, 28(1): 5-13. |
24 | ABD-ELSALAM K A. Bioinformatic tools and guideline for PCR primer design[J]. African Journal of Biotechnology, 2003, 2(5): 91-95. |
25 | 张新宇, 高燕宁. PCR引物设计及软件使用技巧[J]. 生物信息学, 2004, 2(4): 15-18, 46. |
ZHANG X Y, GAO Y N. To design PCR primers with oligo 6 and primer premier 5[J]. Bioinformatiocs, 2004, 2(4): 15-18, 46. | |
26 | ROZEN S, SKALETSKY H. Primer3 on the WWW for general users and for biologist programmers[J]. Methods in Molecular Biology, 2000, 132: 365-386. |
27 | KORESSAAR T, REMM M. Enhancements and modifications of primer design program Primer3[J]. Bioinformatics, 2007, 23(10): 1289-1291. |
28 | YOU F M, HUO N X, GU Y Q, et al. BatchPrimer3: a high throughput web application for PCR and sequencing primer design[J]. BMC Bioinformatics, 2008, 9: 253. |
29 | ANDRESON R, REPPO E, KAPLINSKI L, et al. GENOMEMASKER package for designing unique genomic PCR primers[J]. BMC Bioinformatics, 2006, 7: 172. |
30 | BOUTROS R, STOKES N, BEKAERT M, et al. UniPrime2: a web service providing easier Universal Primer design[J]. Nucleic Acids Research, 2009, 37(): W209-W213. |
31 | SHEN Z Y, QU W B, WANG W, et al. MPprimer: a program for reliable multiplex PCR primer design[J]. BMC Bioinformatics, 2010, 11: 143. |
32 | ZIESEL A C, CHRENEK M A, WONG P W. MultiPriDe: automated batch development of quantitative real-time PCR primers[J]. Nucleic Acids Research, 2008, 36(9): 3095-3100. |
33 | VIJAYA SATYA R, KUMAR K, ZAVALJEVSKI N, et al. A high-throughput pipeline for the design of real-time PCR signatures[J]. BMC Bioinformatics, 2010, 11: 340. |
34 | ARVIDSSON S, KWASNIEWSKI M, RIAÑO-PACHÓN D M, et al. QuantPrime—a flexible tool for reliable high-throughput primer design for quantitative PCR[J]. BMC Bioinformatics, 2008, 9: 465. |
35 | YOU F M, HUO N X, GU Y Q, et al. ConservedPrimers 2.0: a high-throughput pipeline for comparative genome referenced intron-flanking PCR primer design and its application in wheat SNP discovery[J]. BMC Bioinformatics, 2009, 10: 331. |
36 | YOU F M, WANJUGI H, HUO N X, et al. RJPrimers: unique transposable element insertion junction discovery and PCR primer design for marker development[J]. Nucleic Acids Research, 2010, 38(): W313-W320. |
37 | SRIVASTAVA G P, HANUMAPPA M, KUSHWAHA G, et al. Homolog-specific PCR primer design for profiling splice variants[J]. Nucleic Acids Research, 2011, 39(10): e69. |
38 | TSAI M F, LIN Y J, CHENG Y C, et al. PrimerZ: streamlined primer design for promoters, exons and human SNPs[J]. Nucleic Acids Research, 2007, 35(): W63-W65. |
39 | PIRIYAPONGSA J, NGAMPHIW C, ASSAWAMAKIN A, et al. RExPrimer: an integrated primer designing tool increases PCR effectiveness by avoiding 3' SNP-in-primer and mis-priming from structural variation[J]. BMC Genomics, 2009, 10(): S4. |
40 | YOON H, LEITNER T. PrimerDesign-M: a multiple-alignment based multiple-primer design tool for walking across variable genomes[J]. Bioinformatics, 2015, 31(9): 1472-1474. |
41 | YE J, COULOURIS G, ZARETSKAYA I, et al. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction[J]. BMC Bioinformatics, 2012, 13: 134. |
42 | KE X Y, COLLINS A, YE S. PCR designer for restriction analysis of various types of sequence mutation[J]. Bioinformatics, 2002, 18(12): 1688-1689. |
43 | TOKHEIM C, PARK J W, XING Y. PrimerSeq: design and visualization of RT-PCR primers for alternative splicing using RNA-seq data[J]. Genomics, Proteomics & Bioinformatics, 2014, 12(2): 105-109. |
44 | PANDEY R V, PULVERER W, KALLMEYER R, et al. MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics[J]. Clinical Epigenetics, 2016, 8:101. |
45 | WINGO T S, KOTLAR A, CUTLER D J. MPD: multiplex primer design for next-generation targeted sequencing[J]. BMC Bioinformatics, 2017, 18(1):14. |
46 | HIRAGA K, MEJZLIK P, MARCISIN M, et al. Mutation maker, an open source oligo design platform for protein engineering[J]. ACS Synthetic Biology, 2021, 10(2): 357-370. |
47 | MARSHALL O J. PerlPrimer: cross-platform, graphical primer design for standard, bisulphite and real-time PCR[J]. Bioinformatics, 2004, 20(15): 2471-2472. |
48 | SANTALUCIA J. Physical principles and visual-OMP software for optimal PCR design[J]. Methods in Molecular Biology, 2007, 402: 3-34. |
49 | WANG K, LI H W, XU Y, et al. MFEprimer-3.0: Quality control for PCR primers[J]. Nucleic Acids Research, 2019, 47(W1): W610-W613. |
50 | KECHIN A, BOROBOVA V, BOYARSKIKH U, et al. NGS-PrimerPlex: High-throughput primer design for multiplex polymerase chain reactions[J]. PLoS Computational Biology, 2020, 16(12): e1008468. |
51 | RAIBAUD O, MOCK M, SCHWARTZ M. A technique for integrating any DNA fragment into the chromosome of Escherichia coli [J]. Gene, 1984, 29(1/2): 231-241. |
52 | KNIGHT T. Idempotent vector design for standard assembly of biobricks[R]. MIT Artificial Intelligence Laboratory, MIT Synthetic Biology Working Group, 2003. |
53 | ANDERSON J C, DUEBER J E, LEGUIA M, et al. BglBricks: a flexible standard for biological part assembly[J]. Frontiers in Medicine, 2010, 4(1): 1. |
54 | ENGLER C, KANDZIA R, MARILLONNET S. A one pot, one step, precision cloning method with high throughput capability[J]. PLoS One, 2008, 3(11): e3647. |
55 | HORTON R M, HUNT H D, HO S N, et al. Engineering hybrid genes without the use of restriction enzymes: gene splicing by overlap extension[J]. Gene, 1989, 77(1): 61-68. |
56 | QUAN J Y, TIAN J D. Circular polymerase extension cloning of complex gene libraries and pathways[J]. PLoS One, 2009, 4(7): e6441. |
57 | LI M Z, ELLEDGE S J. Harnessing homologous recombination in vitro to generate recombinant DNA via SLIC[J]. Nature Methods, 2007, 4(3): 251-256. |
58 | DE KOK S, STANTON L H, SLABY T, et al. Rapid and reliable DNA assembly via ligase cycling reaction[J]. ACS Synthetic Biology, 2014, 3(2): 97-106. |
59 | APPLETON E, TAO J, HADDOCK T, et al. Interactive assembly algorithms for molecular cloning[J]. Nature Methods, 2014, 11(6): 657-662. |
60 | SHI Z, VICKERS C E. Molecular Cloning Designer Simulator (MCDS): all-in-one molecular cloning and genetic engineering design, simulation and management software for complex synthetic biology and metabolic engineering projects[J]. Metabolic Engineering Communications, 2016, 3: 173-186. |
61 | PRYOR J M, POTAPOV V, KUCERA R B, et al. Enabling one-pot Golden Gate assemblies of unprecedented complexity using data-optimized assembly design[J]. PLoS One, 2020, 15(9): e0238592. |
62 | HAMEDIRAD M, WEISBERG S, CHAO R, et al. Highly efficient single-pot scarless golden gate assembly[J]. ACS Synthetic Biology, 2019, 8(5): 1047-1054. |
63 | POTAPOV V, ONG J L, KUCERA R B, et al. Comprehensive profiling of four base overhang ligation fidelity by T4 DNA ligase and application to DNA assembly[J]. ACS Synthetic Biology, 2018, 7(11): 2665-2674. |
64 | CASINI A, CHANG F Y, ELUERE R, et al. A pressure test to make 10 molecules in 90 days: external evaluation of methods to engineer biology[J]. Journal of the American Chemical Society, 2018, 140(12): 4302-4316. |
65 | 李洋, 申晓林, 孙新晓, 等. CRISPR基因编辑技术在微生物合成生物学领域的研究进展[J]. 合成生物学, 2021, 2(1): 106-120. |
LI Y, SHEN X L, SUN X X, et al. Advances of CRISPR gene editing in microbial synthetic biology[J]. Synthetic Biology Journal, 2021, 2(1): 106-120. | |
66 | DELTCHEVA E, CHYLINSKI K, SHARMA C M, et al. CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III[J]. Nature, 2011, 471(7340): 602-607. |
67 | GRAHAM D B, ROOT D E. Resources for the design of CRISPR gene editing experiments[J]. Genome Biology, 2015, 16: 260. |
68 | CHUAI G H, WANG Q-L, LIU Q. In silico meets in vivo: towards computational CRISPR-based sgRNA design[J]. Trends in Biotechnology, 2017, 35(1): 12-21. |
69 | 王远立, 啜国晖, 闫继芳, 等. 计算机辅助CRISPR向导RNA设计[J]. 生物工程学报, 2017, 33(10): 1744-1756. |
WANG Y L, CHUAI G H, YAN J F, et al. In silico CRISPR-based sgRNA design[J]. Chinese Journal of Biotechnology, 2017, 33(10): 1744-1756. | |
70 | DOUDNA J A, CHARPENTIER E. The new frontier of genome engineering with CRISPR-Cas9[J]. Science, 2014, 346(6213): 1258096. |
71 | DOENCH J G, FUSI N, SULLENDER M, et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9[J]. Nature Biotechnology, 2016, 34(2): 184-191. |
72 | XU H, XIAO T F, CHEN C H, et al. Sequence determinants of improved CRISPR sgRNA design[J]. Genome Research, 2015, 25(8): 1147-1157. |
73 | WANG T, WEI J J, SABATINI D M, et al. Genetic screens in human cells using the CRISPR-Cas9 system[J]. Science, 2014, 343(6166): 80-84. |
74 | WU X B, SCOTT D A, KRIZ A J, et al. Genome-wide binding of the CRISPR endonuclease Cas9 in mammalian cells[J]. Nature Biotechnology, 2014, 32(7): 670-676. |
75 | DOENCH J G, HARTENIAN E, GRAHAM D B, et al. Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation[J]. Nature Biotechnology, 2014, 32(12): 1262-1267. |
76 | CHARI R, MALI P, MOOSBURNER M, et al. Unraveling CRISPR-Cas9 genome engineering parameters via a library-on-library approach[J]. Nature Methods, 2015, 12(9): 823-826. |
77 | HSU P D, SCOTT D A, WEINSTEIN J A, et al. DNA targeting specificity of RNA-guided Cas9 nucleases[J]. Nature Biotechnology, 2013, 31(9): 827-832. |
78 | KIM D, KIM S, KIM S, et al. Genome-wide target specificities of CRISPR-Cas9 nucleases revealed by multiplex Digenome-seq[J]. Genome Research, 2016, 26(3): 406-415. |
79 | SINGH R, KUSCU C, QUINLAN A, et al. Cas9-chromatin binding information enables more accurate CRISPR off-target prediction[J]. Nucleic Acids Research, 2015, 43(18): e118. |
80 | KIM D, KIM J S. DIG-seq: a genome-wide CRISPR off-target profiling method using chromatin DNA[J]. Genome Research, 2018, 28(12): 1894-1900. |
81 | MORGENS D W, WAINBERG M, BOYLE E A, et al. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens[J]. Nature Communications, 2017, 8: 15178. |
82 | AGUIRRE A J, MEYERS R M, WEIR B A, et al. Genomic copy number dictates a gene-independent cell response to CRISPR/Cas9 targeting[J]. Cancer Discovery, 2016, 6(8): 914-929. |
83 | JIANG W Y, BIKARD D, COX D, et al. RNA-guided editing of bacterial genomes using CRISPR-Cas systems[J]. Nature Biotechnology, 2013, 31(3): 233-239. |
84 | ZHANG Y L, GE X L, YANG F Y, et al. Comparison of non-canonical PAMs for CRISPR/Cas9-mediated DNA cleavage in human cells[J]. Scientific Reports, 2014, 4: 5405. |
85 | PATTANAYAK V, LIN S, GUILINGER J P, et al. High-throughput profiling of off-target DNA cleavage reveals RNA-programmed Cas9 nuclease specificity[J]. Nature Biotechnology, 2013, 31(9): 839-843. |
86 | CRADICK T J, FINE E J, ANTICO C J, et al. CRISPR/Cas9 systems targeting β-globin and CCR5 genes have substantial off-target activity[J]. Nucleic Acids Research, 2013, 41(20): 9584-9592. |
87 | LANGMEAD B, TRAPNELL C, POP M, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome[J]. Genome Biology, 2009, 10(3): R25. |
88 | LI H, DURBIN R. Fast and accurate short read alignment with Burrows-Wheeler transform[J]. Bioinformatics, 2009, 25(14): 1754-1760. |
89 | JIANG H, WONG W H. SeqMap: mapping massive amount of oligonucleotides to the genome[J]. Bioinformatics, 2008, 24(20): 2395-2396. |
90 | BAE S S, PARK J, KIM J S. Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases[J]. Bioinformatics, 2014, 30(10): 1473-1475. |
91 | XIAO A, CHENG Z C, KONG L, et al. CasOT: a genome-wide Cas9/gRNA off-target searching tool[J]. Bioinformatics, 2014, 30(8): 1180-1182. |
92 | CANCELLIERI S, CANVER M C, BOMBIERI N, et al. CRISPRitz: rapid, high-throughput and variant-aware in silico off-target site identification for CRISPR genome editing[J]. Bioinformatics, 2020, 36(7): 2001-2008. |
93 | STEMMER M, THUMBERGER T, DEL SOL KEYER M, et al. CCTop: an intuitive, flexible and reliable CRISPR/Cas9 target prediction tool[J]. PLoS One, 2017, 12(4): e0124633. |
94 | HAEUSSLER M, SCHÖNIG K, ECKERT H, et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR[J]. Genome Biology, 2016, 17(1): 148. |
95 | XIE S S, SHEN B, ZHANG C B, et al. sgRNAcas9: a software package for designing CRISPR sgRNA and evaluating potential off-target cleavage sites[J]. PLoS One, 2014, 9(6): e100448. |
96 | JACQUIN A L S, ODOM D T, LUKK M. Crisflash: open-source software to generate CRISPR guide RNAs against genomes annotated with individual variation[J]. Bioinformatics, 2019, 35(17): 3146-3147. |
97 | MCKENNA A, SHENDURE J. FlashFry: a fast and flexible tool for large-scale CRISPR target design[J]. BMC Biology, 2018, 16(1): 74. |
98 | HEIGWER F, KERR G, BOUTROS M. E-CRISP: fast CRISPR target site identification[J]. Nature Methods, 2014, 11(2): 122-123. |
99 | LIU H L, WEI Z, DOMINGUEZ A, et al. CRISPR-ERA: a comprehensive design tool for CRISPR-mediated gene editing, repression and activation[J]. Bioinformatics, 2015, 31(22): 3676-3678. |
100 | PENG D, TARLETON R. EuPaGDT: a web tool tailored to design CRISPR guide RNAs for eukaryotic pathogens[J]. Microbial Genomics, 2015, 1(4): e000033. |
101 | CONCORDET J P, HAEUSSLER M. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens[J]. Nucleic Acids Research, 2018, 46(W1): W242-W245. |
102 | LABUN K, MONTAGUE T G, GAGNON J A, et al. CHOPCHOP v2: a web tool for the next generation of CRISPR genome engineering[J]. Nucleic Acids Research, 2016, 44(W1): W272-W276. |
103 | LABUN K, MONTAGUE T G, KRAUSE M, et al. CHOPCHOP v3: expanding the CRISPR web toolbox beyond genome editing[J]. Nucleic Acids Research, 2019, 47(W1): W171-W174. |
104 | PULIDO-QUETGLAS C, APARICIO-PRAT E, ARNAN C, et al. Scalable design of paired CRISPR guide RNAs for genomic deletion[J]. PLoS Computational Biology, 2017, 13(3): e1005341. |
105 | LEI Y, LU L, LIU H Y, et al. CRISPR-P: a web tool for synthetic single-guide RNA design of CRISPR-system in plants[J]. Molecular Plant, 2014, 7(9): 1494-1496. |
106 | MORENO-MATEOS M A, VEJNAR C E, BEAUDOIN J D, et al. CRISPRscan: designing highly efficient sgRNAs for CRISPR-Cas9 targeting in vivo [J]. Nature Methods, 2015, 12(10): 982-988. |
107 | WONG N, LIU W J, WANG X W. WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system[J]. Genome Biology, 2015, 16: 218. |
108 | ABADI S, YAN W X, AMAR D, et al. A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action[J]. PLoS Computational Biology, 2017, 13(10): e1005807. |
109 | LISTGARTEN J, WEINSTEIN M, KLEINSTIVER B P, et al. Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs[J]. Nature Biomedical Engineering, 2018, 2(1): 38-47. |
110 | KONSTANTAKOS V, NENTIDIS A, KRITHARA A, et al. CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning[J]. Nucleic Acids Research, 2022, 50(7): 3616-3637. |
111 | WANG D Q, ZHANG C D, WANG B, et al. Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning[J]. Nature Communications, 2019, 10: 4284. |
112 | HWANG G H, PARK J, LIM K, et al. Web-based design and analysis tools for CRISPR base editing[J]. BMC Bioinformatics, 2018, 19(1): 542. |
113 | DANDAGE R, DESPRÉS P C, YACHIE N, et al. Beditor: a computational workflow for designing libraries of guide RNAs for CRISPR-mediated base editing[J]. Genetics, 2019, 212(2): 377-385. |
114 | WANG Y, LIU Y, LI J W, et al. Expanding targeting scope, editing window, and base transition capability of base editing in Corynebacterium glutamicum [J]. Biotechnology and Bioengineering, 2019, 116(11): 3016-3029. |
115 | MANS R, VAN ROSSUM H M, WIJSMAN M, et al. CRISPR/Cas9: a molecular Swiss army knife for simultaneous introduction of multiple genetic modifications in Saccharomyces cerevisiae [J]. FEMS Yeast Research, 2015, 15(2): fov004. |
116 | YANG Y, MAO Y F, LIU Y, et al. GEDpm-cg: genome editing automated design platform for point mutation construction in Corynebacterium glutamicum [J]. Frontiers in Bioengineering and Biotechnology, 2021, 9: 768289. |
117 | TONG Y J, JØRGENSEN T S, WHITFORD C M, et al. A versatile genetic engineering toolkit for E. coli based on CRISPR-prime editing[J]. Nature Communications, 2021, 12: 5206. |
118 | YANG X, YUAN Q Q, LUO H, et al. Systematic design and in vitro validation of novel one-carbon assimilation pathways[J]. Metabolic Engineering, 2019, 56: 142-153. |
119 | LIAO X P, MA H W, TANG Y J. Artificial intelligence: a solution to involution of design-build-test-learn cycle[J]. Current Opinion in Biotechnology, 2022, 75: 102712. |
120 | SABZEVARI M, SZEDMAK S, PENTTILÄ M, et al. Strain design optimization using reinforcement learning[J]. PLoS Computational Biology, 2022, 18(6): e1010177. |
121 | WANG Y, WANG H C, WEI L, et al. Synthetic promoter design in Escherichia coli based on a deep generative network[J]. Nucleic Acids Research, 2020, 48(12): 6403-6412. |
122 | SALIS H M, MIRSKY E A, VOIGT C A. Automated design of synthetic ribosome binding sites to control protein expression[J]. Nature Biotechnology, 2009, 27(10): 946-950. |
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