Development of CRISPR/Cas9 Construct in Rice (Oryza sativa subsp. indica) Using Golden Gate Cloning Method Towards Drought Tolerance

Development of CRISPR/Cas9 Construct in Rice (Oryza sativa subsp. indica) Using Golden Gate Cloning Method Towards Drought Tolerance


  • Nurul Hidayah Samsulrizal Nurul Hidayah Binti Samsulrizal Assistant Professor Kullyyiah of Science IIUM Kuantan Campus 5158
  • Anis Afuza Md Yusof Department of Plant Science, Kulliyyah of Science, International Islamic University of Malaysia, 25200 Kuantan, Pahang
  • Amin-Asyraf Tamizi
  • Nurul Asyikin Mohd Zim
  • Siti Syafiqa Abdul Sattar
  • Mohd Syahmi Salleh
  • Nur Sabrina Ahmad Azmi
  • Zamri Zainal
  • Zarina Zainuddin



CRISPR/Cas9,, Drought, Golden gate cloning, Oryza sativa, sgRNA


Rice (Oryza sativa) is a staple food consumed by the majority of the world’s population. Climate change, however, has created a significant threat to our food security as it posed severe effects on rice production. The emergence of genome editing technology has opened a new era in crop improvement. Hence, this study aims to develop the CRISPR/Cas9 construct of drought tolerance for O. sativa subsp. indica cv. IR64 using Golden Gate cloning method. For this purpose, the generation of CRISPR/Cas9 constructs involved several stages, i.e., characterization of SUMO E2-Conjugating Enzyme (OsSCE1) gene, single-guide RNA (sgRNA) design and vector construction. FGENESH, GeneMarkS, InterProScan, and Blast2GO programmes – were used for the OsSCE1 gene characterisation. The putative OsSCE1 gene isolated from IR64 was then verified by sequencing, and the gene was 585 bp long and showed 99% identity with O. sativa on chromosome 10. In silico analysis concluded the gene is involved in abiotic stress regulation. The 20 bp sgRNA was designed manually with the aid of gRNA prediction programmes including CCTop, and Benchling. The virtual vector was validated using the Golden Gate Cloning approach and later confirmed through sequencing. The assembly involved separate vectors containing the OsSCE1 sgRNA sequence, plant selectable marker, and Cas9 cassette to construct standardised elements for hierarchical modular cloning (MoClo). This study demonstrated that our format, as the gene insertion are achievable, resulting in a speedier and more efficient assembly process which may contribute to improve drought tolerance in indica rice. Further study on the Agrobacterium-mediated transformation using the developed construct may be conducted to determine the efficacy of knocking out candidate genes in improving drought tolerance ability O. sativa

Author Biography

Nurul Hidayah Samsulrizal, Nurul Hidayah Binti Samsulrizal Assistant Professor Kullyyiah of Science IIUM Kuantan Campus 5158

Nurul Hidayah Binti SamsulrizalAssistant Professor


Nagata T, Hosaka-Sasaki A, Kikuchi S (2016) The evolutionary diversification of genes that encode transcription factor proteins in plants. In: Gonzalez DH, eds. Plant Transcription Factors. Academic Press. 73-97.

Sasaki T (2001) Rice genome analysis to understand the rice plant as an assembly of genetic codes. Photosynthesis research 70 (1): 119-127. doi:10.1023/A:101384411049.

Nair KP (2019) Utilizing crop wild relatives to combat global warming. Advances in Agronomy 153: 175-258. doi: 10.1016/bs.agron.2018.09.001.

Oladosu Y, Rafii MY, Samuel C et al. (2019) Drought Resistance in Rice from Conventional to Molecular Breeding: A Review. International Journal of Molecular Sciences 20 (14). doi: 10.3390/ijms20143519.

Nurdiani D, Widyajayantie D, Nugroho S (2018) OsSCE1 Encoding SUMO E2-Conjugating Enzyme Involves in Drought Stress Response of Oryza sativa. Rice Science 25 (2): 73–81. doi: 10.1016/j.rsci.2017.11.002.

Salleh MS, Nordin MS, Shahari R et al. (2021) Response of primed rice (Oryza sativa) seeds towards reproductive stage drought stress. Sains Malaysiana 50 (10): 2913–2921. doi: 10.17576/jsm-2021-5010-06.

Singh CM, Kumar B, Mehandi S, Chandra K (2012) Effect of Drought Stress in Rice: A Review on Morphological and Physiological Characteristics. Trends in Biosciences 5 (4): 261–265.

Zhang J, Zhang S, Cheng M et al. (2018) Effect of drought on agronomic traits of rice and wheat: A meta-analysis. International Journal of Environmental Research and Public Health 15 (5). doi: 10.3390/ijerph15050839.

Sahebi M, Hanafi MM, Rafii MY et al. (2018) Improvement of Drought Tolerance in Rice (Oryza sativa L.): Genetics, Genomic Tools, and the WRKY Gene Family. Biomed Research International 2018: 1-20. doi: 10.1155/2018/3158474.

Bi H, Yang B (2017) Gene editing with TALEN and CRISPR/Cas in rice. Progress in molecular biology and translational science. 149: 81-98. doi: 10.1016/bs.pmbts.2017.04.006.

Gaj T, Gersbach CA, Barbas III CF (2013) ZFN, TALEN and CRISPR/Cas-based methods for genome engineering. Trends in Biotechnology (31) 7. doi: 10.1016/j.tibtech.2013.04.004.ZFN.

Zhou H, Liu B, Weeks DP et al. (2014) Large chromosomal deletions and heritable small genetic changes induced by CRISPR/Cas9 in rice. Nucleic Acids Research 42 (17): 10903–10914. doi: 10.1093/nar/gku806.

Uluisik S, Chapman NH, Smith R et al. (2016) Genetic improvement of tomato by targeted control of fruit softening. Nature Biotechnology 34 (9): 950–952. DOI: 10.1038/nbt.3602.

Zainuddin Z, Mohd-Zim NA, Azmi NSA et al. (2021) Genome editing for the development of rice resistance against stresses: A review. Pertanika Journal of Tropical Agricultural Science 44 (3): 599–616. doi: 10.47836/pjtas.44.3.06.

Fujihara Y, Ikawa M (2014) CRISPR/Cas9-based genome editing in mice by single plasmid injection. In: Doudna JA, Sontheimer EJ, eds. Methods in Enzymology. Academic Press. 546: 319–336. doi: 10.1016/B978-0-12-801185-0.00015-5.

Shen B, Zhang J, Wu H et al. (2013) Generation of gene-modified mice via Cas9/RNA-mediated gene targeting. Cell Research 23 (5): 720–723. doi: 10.1038/cr.2013.46.

Horvath P, Barrangou R (2013) RNA-guided genome editing à la carte. Cell Research 23 (6): 733–734. doi: 10.1038/cr.2013.39.

Ran FA, Hsu PD, Wright J et al. (2013) Genome engineering using the CRISPR-Cas9 system. Nature Protocols 8 (11): 2281–2308. doi: 10.1038/nprot.2013.143.

Nigam N, Singh A, Sahi C et al. (2008) SUMO-conjugating enzyme (Sce) and FK506-binding protein (FKBP) encoding rice (Oryza sativa L.) genes: Genome-wide analysis, expression studies and evidence for their involvement in abiotic stress response. Molecular Genetics and Genomics 279 (4): 371–383. doi: 10.1007/s00438-008-0318-5.

Rosa MTG, Almeida DM, Pires IS et al. (2018) Insights into the transcriptional and post-transcriptional regulation of the rice SUMOylation machinery and into the role of two rice SUMO proteases. BMC Plant Biology 18 (1): 1–18. doi: 10.1186/s12870-018-1547-3.

Besemer J, Lomsadze A, Borodovsky M (2001) GeneMarkS: A self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Research 29 (12): 2607–2618. doi: 10.1093/nar/29.12.2607.

Solovyev V, Kosarev P, Seledsov I, Vorobyev D (2006) Automatic annotation of eukaryotic genes, pseudogenes and promoters. Genome Biology 7 (1): S10. doi: 10.1186/gb-2006-7-s1-s10.

Hasan S, Huang L, Liu Q et al. (2022) The Long Read Transcriptome of Rice (Oryza sativa ssp. japonica var. Nipponbare) Reveals Novel Transcripts. Rice 15 (29): 1–17. doi: 10.1186/s12284-022-00577-1.

Zuo Y, Verheecke-Vaessen C, Molitor C et al. (2022) De novo genome assembly and functional annotation for Fusarium langsethiae. BMC Genomics 23 (158): 1-10. doi: 10.1186/s12864-022-08368-0.

Yu C, Cohen LH (2004). Tissue sample preparation - Not the same old grind. Accessed date: November 2021.

Psifidi A, Dovas CI, Bramis G, et al. (2015). Comparison of eleven methods for genomic DNA extraction suitable for large-scale whole-genome genotyping and long-term DNA banking using blood samples. PLoS one. 10 (1): e0115960. doi: 10.1371/journal.pone.0115960.

Zhang G, Weiner JH (2000) CTAB-mediated purification of PCR products. BioTechniques 29 (5): 982–986. doi: 10.2144/00295bm11.

Chen S, Borza T, Byun B et al. (2017). DNA markers for selection of late blight resistant potato breeding lines. American Journal of Plant Sciences. 8 (6): 1197–1209. doi: 10.4236/ajps.2017.86079.

Stemmer M, Thumberger T, del Sol Keyer M, Wittbrodt J, Mateo JL (2015) CCTop: An intuitive, flexible and reliable CRISPR/Cas9 target prediction tool. PLOS ONE 10 (4): e0176619. doi: 10.1371/journal.pone.0124633.

Labuhn M, Adams FF, Ng M et al. (2018) Refined sgRNA efficacy prediction improves largeand small-scale CRISPR-Cas9 applications. Nucleic Acids Research 46 (3): 1375–1385. doi: 10.1093/nar/gkx1268.

Doench JG, Fusi N, Sullender M et al. (2016) Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature Biotechnology 34 (2): 184–191. doi: 10.1038/nbt.3437.

Allen JE, Pertea M, Salzberg SL (2004) Computational gene prediction using multiple sources of evidence. Genome Research 14 (1): 142–148. doi: 10.1101/gr.1562804.

Wang Z, Chen Y, Li Y (2004) A brief review of computational gene prediction methods. Genomics, Proteomics bioinformatics 2 (4): 216–221. doi: 10.1016/S1672-0229(04)02028-5.

Yu Y, Santat LA, Choi S (2006) Bioinformatics packages for sequence analysis. Applied Mycology and Biotechnology 6: 143–160. doi: 10.1016/S1874-5334(06)80009-2.

Buchfink B, Xie C, Huson DH (2014) Fast and sensitive protein alignment using DIAMOND. Nature Methods 12 (1): 59–60. doi: 10.1038/nmeth.3176.

Blum M, Chang HY, Chuguransky S et al. (2021) The InterPro protein families and domains database: 20 years on. Nucleic Acids Research 49 (D1): D344–D354. doi: 10.1093/nar/gkaa977.

Yu B, Hinchcliffe M, eds. (2011) In Silico Tools for Gene Discovery. 1st Edition. New Jersey: Humana Totowa.

Liu W, Tang X, Qi X et al. (2020) The Ubiquitin Conjugating Enzyme: An Important Ubiquitin Transfer Platform in Ubiquitin-Proteasome System. International Journal of Molecular Science 21 (8): 2894. doi: 10.3390/ijms21082894.

Rani B, Sharma VK (2016) A Modified CTAB Method for Quick Extraction of Genomic DNA from Rice Seed/Grain/Leaves for PCR Analysis. International Journal of Science and Research Methodology 4 (4): 254–260.

Moreira PA, Oliveira DA (2011) Leaf age affects the quality of DNA extracted from Dimorphandra mollis (Fabaceae), a tropical tree species from the Cerrado region of Brazil. Genetics and Molecular Research 10 (1): 353–358. doi: 10.4238/vol10-1gmr1030.

García-Alegría AM, Anduro-Corona I, Pérez-Martínez CJ et al. (2020) Quantification of DNA through the nanodrop spectrophotometer: Methodological validation using standard reference material and sprague dawley rat and human DNA. International Journal of Analytical Chemistry 2020: 1-9. doi: 10.1155/2020/8896738.

Matlock B (2015). Assessment of Nucleic Acid Purity. Accessed date: August 2022.

Abdel-Latif A, Osman G (2017) Comparison of three genomic DNA extraction methods to obtain high DNA quality from maize. Plant Methods 13 (1): 1–9. doi: 10.1186/s13007-016-0152-4.

Yeates C, Gillings MR, Davison AD, Altavilla N, Veal DA. Methods for microbial DNA extraction from soil for PCR amplification. Biological Procedures Online 14 (1): 40-47. doi: 10.1251/bpo6.

Van Campenhout C, Cabochette P, Veillard AC et al. (2019) Guidelines for optimized gene knockout using CRISPR/Cas9. Biotechniques 66 (6): 295–302. doi: 10.2144/btn-2018-0187.

Lucena-Aguilar G, Sánchez-López AM, Barberán-Aceituno C, Carrillo-Ávila JA, López-Guerrero JA, Aguilar-Quesada R (2016) DNA Source Selection for Downstream Applications Based on DNA Quality Indicators Analysis. Biopreservation and Biobanking 14 (4): 264–270. doi: 10.1089/bio.2015.0064.

Liang G, Zhang H, Lou D, Yu D (2016) Selection of highly efficient sgRNAs for CRISPR/Cas9-based plant genome editing. Scientific Reports 6: 21451. doi: 10.1038/srep21451.

Marillonnet S, Grützner R (2020) Synthetic DNA Assembly Using Golden Gate Cloning and the Hierarchical Modular Cloning Pipeline. Current Protocol Molecular Biology 130: e115. doi: 10.1002/cpmb.115.

Renzette N (2011) Generation of transformation competent E. coli. Current Protocols in Microbiology 22: A3L.1-A3L.5. doi: 10.1002/9780471729259.mca03ls22.

Sadeghi S, Ahmadi N, Esmaeili A, Javadi-Zarnaghi F (2017) Blue-white screening as a new readout for deoxyribozyme activity in bacterial cells. RSC Advances 7: 54835–54843. doi: 10.1039/c7ra09679h.

Weber E, Engler C, Gruetzner R et al. (2011) A modular cloning system for standardized assembly of multigene constructs. PLOS One 6 (2): e16765. doi: 10.1371/journal.pone.0016765.