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Record W3095381385 · doi:10.1111/pbi.13508

Efficient multiplex genome editing by CRISPR/Cas9 in common wheat

2020· article· en· W3095381385 on OpenAlexaff
Jihu Li, Shujuan Zhang, Rongzhi Zhang, Jie Gao, Yiping Qi, Guoqi Song, Wěi Li, Yulian Li, Genying Li

Bibliographic record

VenuePlant Biotechnology Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMinistry of Agriculture
FundersNational Natural Science Foundation of China
KeywordsBiologyCRISPRMultiplexGenome editingCas9Computational biologyGenomeGeneticsGene

Abstract

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Common wheat has a large genome with three subgenomes (A, B and D), making it challenging to create mutations at multiple genomic sites simultaneously. The CRISPR/Cas9 system offers a game-changing tool for editing crop genomes (Chen et al., 2019). Three main strategies have been developed to produce multiple single-guide RNAs (sgRNAs), including the conventional multiplex system with tandem repeats of separate U3 or U6 promoters (TRSP), the tRNA-processing system (Xie et al., 2015) and the ribozyme-processing system (Gao and Zhao, 2014). Although CRISPR/Cas9-mediated genome editing was previously achieved by biolistic (Wang et al., 2014, 2018) and Agrobacterium transformation (Zhang et al., 2019a), a most efficient CRISPR/Cas9 system for multiplex editing in wheat remains elusive. To address this important question, we designed three multiplex editing constructs corresponding to these three systems, based on the pBUE411 vector (Figure 1a). For the TRSP system, wheat Pol III promoters, TaU3, TaU6.3 and TaU6.1 (Zhang et al., 2019a), were used to drive sgRNA expression independently. For the tRNA system, a TaU3 promoter was also used to express the tRNA-sgRNA cassettes in a single transcript unit. For the ribozyme system, a Pol II promoter, Cestrum yellow leaf curling virus (CmYLCV) promoter (Cermak et al., 2017), was employed for expressing hammerhead ribozyme (HH)–sgRNA–hepatitis delta virus (HDV) ribozyme cassettes in a single transcript unit. A longer sgRNA scaffold was applied in three vectors to optimize the sgRNA structure (Dang et al., 2015). Wheat codon-optimized Cas9 was driven under a maize (Zea mays) ubiquitin promoter (Ubip). Three genes, TaDA1, TaPDS and TaNCED1, were selected for simultaneous editing. The sgRNA for TaDA1 could target its homoeologous genes on A and B chromosomes, while the sgRNAs for TaPDS and TaNCED1 were designed to target all three homoeologous genes, respectively (Zhang et al., 2019b). In total, three sgRNAs could target 8 genomic sites in common wheat (Figure 1b). The sgRNA cassettes in the vectors were all arranged in the same order for close comparison. These T-DNA vectors were introduced into hexaploid wheat Fielder via Agrobacterium tumefaciens-mediated transformation. A total of 22, 26 and 27 T0 plants were generated from the transformed calli of TRSP, tRNA and ribozyme systems, respectively. The genotype of each plant was characterized by Hi-TOM sequencing of the PCR amplicons with primers flanking each target site (Liu et al., 2019). The editing efficiency of individual genes was first analysed. Edits of TaDA1-A and TaDA1-B were detected in all three systems, and the ribozyme system was most effective (Figure 1c). The superior editing ability of the ribozyme system was also observed at TaPDS where mutations could cause albino phenotype. Impressively, 22 out of 27 plants showed albino phenotype in the ribozyme system, whereas only 5 plants displayed albino phenotype in either the TRSP or tRNA system. Sequencing results supported the observation as the ribozyme system achieved the highest efficiency, up to 100.00% (Figure 1c). Although fewer plants showed albino phenotype, the editing efficiencies in TRSP and tRNA systems still reached to 86.36% and 92.31%, respectively. For TaNCED1, all three vectors exhibited low activity, and the tRNA and ribozyme systems resulted in higher gene editing rates than the TRSP system (Figure 1c). The three systems showed similar mutation profiles for individual genes where small deletions and 1bp insertions predominated (Figure 1d). The ability to target multiple genomic sites was further analysed for three systems. Compared with the TRSP system, more plants with over 4 edited sites were identified in the tRNA and ribozyme systems (Figure 1e), and the ribozyme system generated the highest simultaneous editing rates. The efficiencies of simultaneous editing in three genes in the tRNA and ribozyme systems were 34.62% and 37.04%, respectively, which were about twofold higher than that in the TRSP system (Figure 1f). Thus, the tRNA and ribozyme systems are more effective than TRSP, and the ribozyme system appeared to be most robust. The high editing efficiency of the ribozyme system might partly result from the use of the Pol II promoter, CmYLCV, for sgRNA expression. The phenotype caused by gene editing depends on the genotype in individual plants. Therefore, we investigated the ratio of mutated reads at each target site in each plant through Hi-TOM sequencing (Liu et al., 2019). No significant differences were detected at all targeted sites between the TRSP and tRNA systems, but the ratios of edited reads were significantly increased in the ribozyme system except for TaNCED1 (Figure 1g). Ratios of edited reads in the ribozyme system were about threefold higher for TaDA1 and twofold higher for TaPDS than those in the TRSP and tRNA systems, respectively. The results suggested that the ribozyme system greatly decreased the proportions of unedited reads at multiplex chromosomes and therefore increased the probability of the loss-of-function phenotype in T0 generation. This might explain the discrepancy between the high editing efficiency and less albino phenotype caused by TaPDS mutation in the TRSP and tRNA systems. Although over 86.00% of the plants carried edited TaPDS in the TRSP and tRNA systems, the editing ratios in most plants were not enough to display albino phenotype. To further quantify the relationship between ratios of the edited reads and observable phenotype, we compared the ratios of edited reads for TaPDS-A, TaPDS-B and TaPDS-D among three groups of plants as no albino, chimeric and albino phenotype, respectively (Figure 1h). Positive correlation between the phenotype and editing ratio was observed (Figure 1i). The lowest average ratio for plants with albino phenotype was 80.59%, indicating an editing threshold for displaying loss-of-function phenotype. Wild type alleles were not detected at TaPDS in 6 lines of the ribozyme system despite different levels of chimerism (Figure 1j). These results collectively revealed that the phenotype caused by targeted mutagenesis occurred only when the ratios of edited homoeologous genes achieved a higher level at all homoeologous chromosomes simultaneously. In summary, we compared three multiplex CRISPR/Cas9 systems for simultaneous genome editing at 8 target sites in common wheat. The tRNA and ribozyme systems were more effective than the TRSP system in multiplex genome editing. Furthermore, the ribozyme system could significantly increase the ratios of edited homoeologous genes at multiplex chromosomes in individual plants and therefore generated more plants with loss-of-function phenotypes. The ribozyme system established in our study would greatly aid fundamental and translational research in wheat. We appreciated Qixin Sun’s group of China Agricultural University for providing us with the pBUE411 vector. This work was funded by grants from Agricultural Variety Improvement Project of Shandong Province (2019LZGC015, 2019LZGC001), the Ministry of Science and Technology of China (2016YFD0100500), the National Natural Science Foundation of China (31701428) and the Agricultural Science and Technology Innovation Project of Shandong Academy of Agricultural Sciences (CXGC2019G02). The work was also supported by the start-up funds from University of Maryland, College Park. The authors declare no conflicts of interest. J.L. and S.Z. constructed the vectors, analysed the data and wrote the manuscript. R.Z. designed the sgRNAs and performed Hi-TOM sequencing. G.S. and W.L. collected samples and extracted DNA. J.G. performed the wheat transformation. Y.Q. analysed the data and revised the manuscript. Y.L. and G.L supervised the project.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.249
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations68
Published2020
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