Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (6): 1023-1033.doi: 10.3864/j.issn.0578-1752.2024.06.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Screening of High-Efficient sgRNA for Targeted Knockout of GhAGL16 Gene in Cotton

LEI JianFeng1(), YOU YangZi2, ZHANG JinEn2, DAI PeiHong2, YU Li2, DU ZhengYang1, LI Yue2, LIU XiaoDong2()   

  1. 1 College of Agronomy, Xinjiang Agricultural University/Cotton Engineering Research Center, Ministry of Education, Urumqi 830052
    2 College of Life Sciences, Xinjiang Agricultural University, Urumqi 830052
  • Received:2023-09-04 Accepted:2023-11-03 Online:2024-03-16 Published:2024-03-25
  • Contact: LIU XiaoDong

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Abstract:

【Objective】 As an important negative transcriptional regulator in cotton MADS-box gene family, AGL16 plays an important role in resisting drought and salt stress. Virus-induced gene editing (VIGE) was used to screen sgRNAs that knockout the cotton GhAGL16 and verify the specificity of these sgRNAs, which laid a foundation for the creation of cotton agl16 mutants.【Method】 Three sgRNAs could knockout GhAGL16 were predicted based on the actual GhAGL16 genomic sequence cloned on subgroup A and D in cotton YZ-1; Three CLCrV-AtU6-26::GhAGL16-sgRNAs vectors were constructed based on the cotton leaf crumple virus (CLCrV)-mediated VIGE system; The expression of Cas9 in Cas9 over-expression (Cas9-OE) plants was detected by qPCR to determine whether Cas9 was stably genetically expressed; Three CLCrV-AtU6-26::GhAGL16-sgRNAs vectors were transformed respectively into Cas9-OE cotton cotyledons and detected the mutations of the three targets by PCR/RE; The secondary structures of three GhAGL16-sgRNAs were analyzed by bioinformatics; Hi-TOM high-throughput sequencing was performed on mutant plants to determine the efficiency of gene editing. Meanwhile, the off-target rate of GhAGL16-sgRNA2 mutant plants were identified to detect the specificity of gene editing.【Result】 Three sgRNAs capable of simultaneously knocking out GhAGL16-A and D subgroups were successfully constructed. The detection results of Cas9 expression showed that Cas9 was stably expressed in different Cas9-OE cotton plants. PCR/RE mutation detection results showed that GhAGL16-sgRNA2 could be effectively used for the knockout of GhAGL16. Different mutation types with base deletions appeared at the target sites of cotton subgroups A and D, while GhAGL16-sgRNA1 and GhAGL16-sgRNA3 were two invalid sgRNAs. The secondary structure analysis results of three GhAGL16-sgRNAs indicated that GhAGL16-sgRNA1 and GhAGL16-sgRNA3 might have a phenomenon that the guide sequence was easy to pair with other sequences and difficult to unwind, which interfered with the recognition of the target site by the guide sequences and lead to the invalid sgRNA. To further quantify the editing efficiency of GhAGL16-sgRNA2 on GhAGL16, the mutation detection results of each Cas9-OE plant transformed with CLCrV-AtU6-26::GhAGL16-sgRNA2 showed that six of the nine Cas9-OE plants were mutated, with a mutation efficiency of 66.67%. In addition, Hi-TOM high-throughput sequencing results showed that the editing efficiency of GhAGL16-sgRNA2 for GhAGL16 was 13.69%-54.42%. The off-target identification results showed that no off-target phenomenon was detected at the four predicted off-target sites, indicating that GhAGL16-sgRNA2 not only has high gene editing efficiency, but also has specific gene editing specificity.【Conclusion】 A sgRNA that can effectively knocking out the GhAGL16 was obtained by transforming Cas9-OE cotton using the CLCrV-mediated VIGE system, providing an ideal sgRNA for creating cotton agl16 mutants.

Key words: cotton, GhAGL16, sgRNA, mutant, VIGE, off-target

Table 1

Primer sequences used in this study"

引物Primer 序列Sequence (5′-3′) 目的Destination
GhAGL16-sgRNA1F GATTGCTACGATTTCGCTAGCACC 构建AtU6-26::GhAGL16-sgRNA1
Construction of AtU6-26::GhAGL16-sgRNA1
GhAGL16-sgRNA1R AAACGGTGCTAGCGAAATCGTAGC
GhAGL16-sgRNA2F GATTGCTGCTGTGGCTGGCTTAGC 构建AtU6-26::GhAGL16-sgRNA2
Construction of AtU6-26::GhAGL16-sgRNA2
GhAGL16-sgRNA2R AAACGCTAAGCCAGCCACAGCAGC
GhAGL16-sgRNA3F GATTGGTAAAAGATTTACAGAATT 构建AtU6-26::GhAGL16-sgRNA3
Construction of AtU6-26::GhAGL16-sgRNA3
GhAGL16-sgRNA3R AAACAATTCTGTAAATCTTTTACC
M1-GhAGL16F AAATAACCTCCATTGCATTTCTCTT PCR扩增涵盖GhAGL16靶位点1区域（509 bp）
PCR amplification contains the GhAGL16 gene target site 1 region (509 bp)
M1-GhAGL16R CAACATTTTACCGTCACATTTAATC
M2-GhAGL16F TCCGTATGAAGAAGGTTTGAAAATT PCR扩增涵盖 GhAGL16靶位点2区域（797 bp）
PCR amplification contains the GhAGL16 gene target site 2 region (797 bp)
M2-GhAGL16R GAGAAGCATAACTTTTGGAACC
M3-GhAGL16F CCATATAAATCACTATATCAAACGTG PCR扩增涵盖 GhAGL16靶位点3区域（682 bp）
PCR amplification contains the GhAGL16 gene target site 3 region (682 bp)
M3-GhAGL16R ATTTTCAAACCTTCTTCATACGGA
HiT-GhAGL16F GGAGTGAGTACGGTGTGCCAAGGGATGTCAATGGTGCA 高通量测序检测GhAGL16编辑效率
Detection of GhAGL16 gene editing efficiency by high-throughput sequencing
HiT-GhAGL16R GAGTTGGATGCTGGATGGTGGAGATCAGTTTGTGGCAA
Q-GhUBQ7F GAAGGCATTCCACCTGACCAAC PCR扩增GhUBQ7部分片段
PCR amplification of partial fragments of GhUBQ7 gene
Q-GhUBQ7R CTTGACCTTCTTCTTCTTGTGCTTG
Q-Cas9F GTCATTACGGACGAGTACAAG qPCR分析Cas9 mRNA表达量
qPCR analysis of Cas9 mRNA expression
Q-Cas9R AGGTAGCAGATCCGATTCTTT
Gh_A06G030400-F GGAGTGAGTACGGTGTGCGAACTTTCTGGATTGGGTGTAA 高通量测序检测Gh_A06G030400
Detection of Gh_A06G030400 gene by high-throughput sequencing
Gh_A06G030400-R GAGTTGGATGCTGGATGGATTGCAGTCCCAAGTTTGTAG
Gh_A06G081500-F GGAGTGAGTACGGTGTGCGCCAATCCAAATATGTCCAGC 高通量测序检测Gh_A06G081500
Detection of Gh_A06G081500 gene by high-throughput sequencing
Gh_A06G081500-R GAGTTGGATGCTGGATGGTTAGCCACACCGTCTTCCA
Gh_A08G005400-F GGAGTGAGTACGGTGTGCTTACTTCCAGAGCAGACAC 高通量测序检测Gh_A08G005400
Detection of Gh_A08G005400 gene by high-throughput sequencing
Gh_A08G005400-R GAGTTGGATGCTGGATGGGCATATGGTCGACTTAGCA
Gh_A09G158200-F GGAGTGAGTACGGTGTGCAGTGGTGCAAAAGGGGAG 高通量测序检测Gh_A09G158200
Detection of Gh_A09G158200 gene by high-throughput sequencing
Gh_A09G158200-R GAGTTGGATGCTGGATGGCTTAATGAGATAGTTGCTGGC

Fig. 1

Identification of CLCrV-AtU6-26::GhAGL16-sgRNAs expression vector by enzyme digestion M: 2K PlusⅡ DNA Marker; 1: Identification of CLCrV-AtU6-26:: GhAGL16-sgRNA1 by restriction enzyme digestion; 2: Identification of CLCrV-AtU6-26::GhAGL16-sgRNA2 by restriction enzyme digestion; 3: Identification of CLCrV-AtU6-26::GhAGL16-sgRNA3 by restriction enzyme digestion"

Fig.2

Detection of Cas9 expressions by qPCR Different letters indicate significant differences at the 0.05 probability"

Fig. 3

CLCrV-mediated targeted knockout of cotton GhAGL16 gene A: Detection of GhAGL16-sgRNA2 mutation, WT: Control; 1: CLCrV-AtU6-26::GhAGL16-sgRNA2; M: 2K PlusⅡ DNA marker. B: DdeⅠrestriction site deletion mutation type. Green color indicates the PAM sequence, underline in blue indicates the restriction site on the target sequence, the short red lines indicate deletion bases, the yellow labeled bases are used to distinguish A/D subgroups. C: GhAGL16 mutation sequencing peak map. M1-M4 indicates the GhAGL16 mutation sequence"

Fig. 4

Analysis of secondary structure of GhAGL16-sgRNAs A: The secondary structure of GhAGL16-sgRNA1; B: The secondary structure of GhAGL16-sgRNA2; C: The secondary structure of GhAGL16-sgRNA3"

Fig. 5

Detection of GhAGL16 mutant single plant M：2K PlusⅡ DNA marker"

Table 2

Analysis of mutation efficiency of GhAGL16 gene"

基因组<BOLD>G</BOLD>enome 植株编号
Plant number		 样本读取数量
No. of sample
reads		 突变比例
Mutation ratio
(%)		 突变类型
Mutation
type		 突变序列
Mutations in the sequence		 突变位点（sgRNA2）
Mutation site
(sgRNA2, 5′-3′)
A亚组
Subgroup A		 WT 403 100 WT - CCAGCTAAGCCAGCCACAGCAGC
#2 584 87.29 WT - CCAGCTAAGCCAGCCACAGCAGC
39 5.83 2D CT CCAG- -AAGCCAGCCACAGCAGC
25 3.74 2D AA CCAGCT- -GCCAGCCACAGCAGC
21 3.14 1D A CCAGCT-AGCCAGCCACAGCAGC
#6 921 79.60 WT - CCAGCTAAGCCAGCCACAGCAGC
127 10.98 2D CT CCAG- -AAGCCAGCCACAGCAGC
71 6.14 1D A CCAGCT-AGCCAGCCACAGCAGC
38 3.28 4D AAGC CCAGCT- - - -CAGCCACAGCAGC
#7 569 90.61 WT - CCAGCTAAGCCAGCCACAGCAGC
59 9.39 2D CT CCAG- -AAGCCAGCCACAGCAGC
#8 485 84.79 WT - CCAGCTAAGCCAGCCACAGCAGC
59 10.31 SNP A<G CCAGCTAGGCCAGCCACAGCAGC
28 4.90 3D AAG CCAGCT- - -CCAGCCACAGCAGC
#9 412 91.76 WT - CCAGCTAAGCCAGCCACAGCAGC
37 8.24 2D CT CCAG- -AAGCCAGCCACAGCAGC
D亚组
Subgroup D		 WT 531 100 WT - CCAGCTAAGCCAGCCACAGCAGC
#4 500 96.71 WT - CCAGCTAAGCCAGCCACAGCAGC
17 3.29 3D AAG CCAGCT- - -CCAGCCACAGCAGC
#6 64 65.98 WT - CCAGCTAAGCCAGCCACAGCAGC
18 18.56 2D CT CCAG- -AAGCCAGCCACAGCAGC
15 15.46 5D AAGCC CCAGCT- - - - -AGCCACAGCAGC
#8 408 86.99 WT - CCAGCTAAGCCAGCCACAGCAGC
61 13.01 1D A CCAGCT-AGCCAGCCACAGCAGC
#9 434 94.55 WT - CCAGCTAAGCCAGCCACAGCAGC
25 5.45 1D A CCAGCT-AGCCAGCCACAGCAGC

Fig. 6

Sequence alignment analysis of four potential off- target sites"

Table 3

Detection and analysis of potential off-target sites"

潜在脱靶位点的序列
Sequence of the putative off-target
site (5′-3′)		 匹配碱基数量（包括PAM）
No. of matching bases (include PAM)		 基因
Gene		 区域
Region		 样本读取数量
No. of sample reads		 检测脱靶数量
No. of off-target events
GTTGCTGTGGCTGGCACAGCTGG 20 Gh_A06G030400 CDS 976 0
GCTGCTGTGACTGGCATTGATGG 19 Gh_A06G081500 CDS 965 0
GCTGCTGTGGCTGTTCAAGCTGG 19 Gh_A08G005400 CDS 1021 0
GCTGCTGCTGCTGGCTATGCAGG 18 Gh_A09G158200 CDS 855 0
[1]
LI Y, CHEN H, LI S T, YANG C L, DING Q Y, SONG C P, WANG D J. GhWRKY46 from upland cotton positively regulates the drought and salt stress responses in plant. Environmental and Experimental Botany, 2021, 186: 104438.

doi: 10.1016/j.envexpbot.2021.104438
[2]
ZHANG F, LI S F, YANG S M, WANG L K, GUO W Z. Overexpression of a cotton annexin gene, GhAnn1, enhances drought and salt stress tolerance in transgenic cotton. Plant Molecular Biology, 2015, 87(1/2): 47-67.

doi: 10.1007/s11103-014-0260-3
[3]
SHI J B, WANG N, ZHOU H, XU Q H, YAN G T. The role of gibberellin synthase gene GhGA2ox1 in upland cotton (Gossypium hirsutum L.) responses to drought and salt stress. Biotechnology and Applied Biochemistry, 2019, 66(3): 298-308.

doi: 10.1002/bab.2019.66.issue-3
[4]
LI Z, LI L, ZHOU K H, ZHANG Y H, HAN X, DIN Y, GE X Y, QIN W Q, WANG P, LI F G, MA Z Y, YANG Z E. GhWRKY6 acts as a negative regulator in both transgenic Arabidopsis and cotton during drought and salt stress. Frontiers in Genetics, 2019, 10: 392.

doi: 10.3389/fgene.2019.00392
[5]
HU Z Y, LEI J F, DAI P H, LIU C, WUGALIHAN A, LIU X D, LI Y. A small Gtp-Binding protein GhROP3 interacts with GhGGB protein and negatively regulates drought tolerance in cotton (Gossypium hirsutum L.). Plants, 2022, 11(12): 1580.

doi: 10.3390/plants11121580
[6]
JIA H H, HAO L L, GUO X L, LIU S C, YAN Y, GUO X Q. A Raf-like MAPKKK gene, GhRaf19, negatively regulates tolerance to drought and salt and positively regulates resistance to cold stress by modulating reactive oxygen species in cotton. Plant Science, 2016, 252: 267-281.

doi: 10.1016/j.plantsci.2016.07.014
[7]
FARBOUD B, MEYER B J. Dramatic enhancement of genome editing by CRISPR/Cas9 through improved guide RNA design. Genetics, 2015, 199(4): 959-971.

doi: 10.1534/genetics.115.175166 pmid: 25695951
[8]
KAUFMANN K, MELZER R, THEISSEN G. MIKC-type MADS- domain proteins: structural modularity, protein interactions and network evolution in land plants. Gene, 2005, 347(2): 183-198.

doi: 10.1016/j.gene.2004.12.014
[9]
TAPIA-LÓPEZ R, GARCÍA-PONCE B, DUBROVSKY J G, GARAY- ARROYO A, PÉREZ-RUÍZ R V, KIM S H, ACEVEDO F, PELAZ S, ALVAREZ-BUYLLA E R. An AGAMOUS-related MADS-box gene, XAL1 (AGL12), regulates root meristem cell proliferation and flowering transition in Arabidopsis. Plant Physiology, 2008, 146(3): 1182-1192.

doi: 10.1104/pp.107.108647
[10]
YU L H, MIAO Z Q, QI G F, WU J, CAI X T, MAO J L, XIANG C B. MADS-box transcription factor AGL21 regulates lateral root development and responds to multiple external and physiological signals. Molecular Plant, 2014, 7(11): 1653-1669.

doi: 10.1093/mp/ssu088
[11]
YU L H, WU J, ZHANG Z S, MIAO Z Q, ZHAO P X, WANG Z, XIANG C B. Arabidopsis MADS-Box transcription factor AGL21 acts as environmental surveillance of seed germination by regulating ABI5 expression. Molecular Plant, 2017, 10(6): 834-845.

doi: 10.1016/j.molp.2017.04.004
[12]
LI A Z, CHEN G P, YU X H, ZHU Z G, ZHANG L C, ZHOU S G, HU Z L. The tomato MADS-box gene SlMBP9 negatively regulates lateral root formation and apical dominance by reducing auxin biosynthesis and transport. Plant Cell Reports, 2019, 38(8): 951-963.

doi: 10.1007/s00299-019-02417-x
[13]
ROSIN F M, HART J K, VAN ONCKELEN H, HANNAPEL D J. Suppression of a vegetative MADS box gene of potato activates axillary meristem development. Plant Physiology, 2003, 131(4): 1613-1622.

pmid: 12692320
[14]
YE L X, ZHANG J X, HOU X J, QIU M Q, WANG W F, ZHANG J X, HU C G, ZHANG J Z. A MADS-Box gene CiMADS43 is involved in Citrus flowering and leaf development through interaction with CiAGL9. International Journal of Molecular Sciences, 2021, 22(10): 5205.

doi: 10.3390/ijms22105205
[15]
ZHAO P X, MIAO Z Q, ZHANG J, CHEN S Y, LIU Q Q, XIANG C B. Arabidopsis MADS-box factor AGL16 negatively regulates drought resistance via stomatal density and stomatal movement. Journal of Experimental Botany, 2020, 71(19): 6092-6106.

doi: 10.1093/jxb/eraa303
[16]
ZHAO P X, ZHANG J, CHEN S Y, WU J, XIA J Q, SUN L Q, MA S S, XIANG C B. Arabidopsis MADS-box factor AGL16 is a negative regulator of plant response to salt stress by downregulating salt-responsive genes. The New Phytologist, 2021, 232(6): 2418-2439.

doi: 10.1111/nph.v232.6
[17]
周冠彤, 雷建峰, 代培红, 刘超, 李月, 刘晓东. 棉花CRISPR/ Cas9基因编辑有效sgRNA高效筛选体系的研究. 作物学报, 2021, 47(3): 427-437.

doi: 10.3724/SP.J.1006.2021.04178
ZHOU G T, LEI J F, DAI P H, LIU C, LI Y, LIU X D. Efficient screening system of effective sgRNA for cotton CRISPR/Cas9 gene editing. Acta Agronomica Sinica, 2021, 47(3): 427-437. (in Chinese)

doi: 10.3724/SP.J.1006.2021.04178
[18]
XIE X R, MA X L, ZHU Q L, ZENG D C, LI G S, LIU Y G. CRISPR- GE: A convenient software toolkit for CRISPR-based genome editing. Molecular Plant, 2017, 10(9): 1246-1249.

doi: 10.1016/j.molp.2017.06.004
[19]
雷建峰, 徐新霞, 李月, 代培红, 刘超, 刘晓东. CRISPR/Cas9介导靶向敲除拟南芥GGB基因突变体的鉴定. 西北植物学报, 2016, 36(5): 857-864.
LEI J F, XU X X, LI Y, DAI P H, LIU C, LIU X D. Identification of GGB mutant caused by CRISPR/Cas9 in Arabidopsis. Acta Botanica Boreali-Occidentalia Sinica, 2016, 36(5): 857-864. (in Chinese)
[20]
LIVAK K J, SCHMITTGEN T D. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods, 2001, 25(4): 402-408.

doi: 10.1006/meth.2001.1262
[21]
GAO W, LONG L, TIAN X Q, XU F C, LIU J, SINGH P K, BOTELLA J R, SONG C P. Genome editing in cotton with the CRISPR/Cas9 system. Frontiers in Plant Science, 2017, 8: 1364.

doi: 10.3389/fpls.2017.01364 pmid: 28824692
[22]
QIN L X, ZHANG H Y, LI J, ZHU Y H, JIAO G L, WANG C Y, WU S J. Down-regulation of GhADF1 in cotton (Gossypium hirsutum) improves plant drought tolerance and increases fiber yield. The Crop Journal, 2022, 10(4): 1037-1048.

doi: 10.1016/j.cj.2021.12.012
[23]
赵燚, 雷建峰, 刘敏, 胡子曜, 代培红, 刘超, 李月, 刘晓东. CLCrV介导的VIGE体系承载力的研究. 生物技术通报, 2022, 38(11): 210-219.

doi: 10.13560/j.cnki.biotech.bull.1985.2022-0173
ZHAO Y, LEI J F, LIU M, HU Z Y, DAI P H, LIU C, LI Y, LIU X D. Research on the carrying capacity of CLCrV-mediated VIGE system. Biotechnology Bulletin, 2022, 38(11): 210-219. (in Chinese)

doi: 10.13560/j.cnki.biotech.bull.1985.2022-0173
[24]
LEI J F, LI Y, DAI P H, LIU C, ZHAO Y, YOU Y Z, QU Y Y, CHEN Q J, LIU X D. Efficient virus-mediated genome editing in cotton using the CRISPR/Cas9 system. Frontiers in Plant Science, 2022, 13: 1032799.

doi: 10.3389/fpls.2022.1032799
[25]
HU J C, LI S, LI Z L, LI H Y, SONG W B, ZHAO H M, LAI J S, XIA L Q, LI D W, ZHANG Y L. A barley stripe mosaic virus-based guide RNA delivery system for targeted mutagenesis in wheat and maize. Molecular Plant Pathology, 2019, 20(10): 1463-1474.

doi: 10.1111/mpp.12849 pmid: 31273916
[26]
LI T D, HU J C, SUN Y, LI B S, ZHANG D L, LI W L, LIU J X, LI D W, GAO C X, ZHANG Y L, WANG Y P. Highly efficient heritable genome editing in wheat using an RNA virus and bypassing tissue culture. Molecular Plant, 2021, 14(11): 1787-1798.

doi: 10.1016/j.molp.2021.07.010 pmid: 34274523
[27]
LUO Y J, NA R, NOWAK J S, QIU Y, LU Q S, YANG C Y, MARSOLAIS F, TIAN L N. Development of a Csy4-processed guide RNA delivery system with soybean-infecting virus ALSV for genome editing. BMC Plant Biology, 2021, 21(1): 419.

doi: 10.1186/s12870-021-03138-8 pmid: 34517842
[28]
MA X L, ZHANG Q Y, ZHU Q L, LIU W, CHEN Y, QIU R, WANG B, YANG Z F, LI H Y, LIN Y R, XIE Y Y, SHEN R X, CHEN S F, WANG Z, CHEN Y L, GUO J X, CHEN L T, ZHAO X C, DONG Z C, LIU Y G. A robust CRISPR/Cas9 system for convenient, high- efficiency multiplex genome editing in monocot and dicot plants. Molecular Plant, 2015, 8(8): 1274-1284.

doi: 10.1016/j.molp.2015.04.007
[29]
LIANG G, ZHANG H M, LOU D J, YU D Q. Selection of highly efficient sgRNAs for CRISPR/Cas9-based plant genome editing. Scientific Reports, 2016, 6: 21451.

doi: 10.1038/srep21451 pmid: 26891616
[30]
LI J Y, MANGHWAR H, SUN L, WANG P C, WANG G Y, SHENG H Y, ZHANG J, LIU H, QIN L, RUI H P, LI B, LINDSEY K, DANIELL H, JIN S X, ZHANG X L. Whole genome sequencing reveals rare off-target mutations and considerable inherent genetic or/and somaclonal variations in CRISPR/Cas9-edited cotton plants. Plant Biotechnology Journal, 2019, 17(5): 858-868.

doi: 10.1111/pbi.13020 pmid: 30291759
[31]
WANG X H, TU M X, WANG Y, YIN W C, ZHANG Y, WU H S, GU Y C, LI Z, XI Z M, WANG X P. Whole-genome sequencing reveals rare off-target mutations in CRISPR/Cas9-edited grapevine. Horticulture Research, 2021, 8: 114.

doi: 10.1038/s41438-021-00549-4 pmid: 33931634
[32]
FU Y F, FODEN J A, KHAYTER C, MAEDER M L, REYON D, JOUNG J K, SANDER J D. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nature Biotechnology, 2013, 31(9): 822-826.

doi: 10.1038/nbt.2623 pmid: 23792628
[33]
SHI L N, TANG X Q, TANG G L. GUIDE-seq to detect genome-wide double-stranded breaks in plants. Trends in Plant Science, 2016, 21(10): 815-818.

doi: S1360-1385(16)30115-7 pmid: 27593568
[34]
TSAI S Q, NGUYEN N T, MALAGON-LOPEZ J, TOPKAR V V, ARYEE M J, JOUNG J K. CIRCLE-seq: A highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets. Nature Methods, 2017, 14(6): 607-614.

doi: 10.1038/nmeth.4278 pmid: 28459458
[35]
LAZZAROTTO C R, MALININ N L, LI Y C, ZHANG R C, YANG Y, LEE G, COWLEY E, HE Y H, LAN X, JIVIDEN K, KATTA V, KOLMAKOVA N G, PETERSEN C T, QI Q, STRELCOV E, MARAGH S, KRENCIUTE G, MA J, CHENG Y, TSAI S Q. CHANGE-seq reveals genetic and epigenetic effects on CRISPR- Cas9 genome- wide activity. Nature Biotechnology, 2020, 38(11): 1317-1327.

doi: 10.1038/s41587-020-0555-7
[36]
ELLISON E E, NAGALAKSHMI U, GAMO M E, HUANG P J, DINESH-KUMAR S, VOYTAS D F. Multiplexed heritable gene editing using RNA viruses and mobile single guide RNAs. Nature Plants, 2020, 6(6): 620-624.

doi: 10.1038/s41477-020-0670-y pmid: 32483329
[37]
LEI J F, DAI P H, LI Y, ZHANG W Q, ZHOU G T, LIU C, LIU X D. Heritable gene editing using FT mobile guide RNAs and DNA viruses. Plant Methods, 2021, 17(1): 20.

doi: 10.1186/s13007-021-00719-4
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