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Precise integration of large DNA sequences in plant genomes using PrimeRoot editors

Nature Biotechnology (2023)Cite this article

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Abstract

A technique for chromosomal insertion of large DNA segments is much needed in plant breeding and synthetic biology to facilitate the introduction of desired agronomic traits and signaling and metabolic pathways. Here we describe PrimeRoot, a genome editing approach to generate targeted precise large DNA insertions in plants. Third-generation PrimeRoot editors employ optimized prime editing guide RNA designs, an enhanced plant prime editor and superior recombinases to enable precise large DNA insertions of up to 11.1 kilobases into plant genomes. We demonstrate the use of PrimeRoot to accurately introduce gene regulatory elements in rice. In this study, we also integrated a gene cassette comprising PigmR, which confers rice blast resistance driven by an Act1 promoter, into a predicted genomic safe harbor site of Kitaake rice and obtain edited plants harboring the expected insertion with an efficiency of 6.3%. We found that these rice plants have increased blast resistance. These results establish PrimeRoot as a promising approach to precisely insert large segments of DNA in plants.

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Fig. 1: PrimeRoot combines plant-optimized recombinases and enhanced plant PE to create targeted DNA insertions.
Fig. 2: Development of improved PrimeRoot systems.
Fig. 3: Comparison of targeted DNA insertions mediated by PrimeRoot and NHEJ.
Fig. 4: Prediction of GSH regions and specificity analysis.
Fig. 5: Targeted integration of the Act1P-pigmR gene cassette into GSH1 to confer bacterial blast disease resistance in rice plants.
Fig. 6: PrimeRoot.v3 for efficient precise targeted gene insertion by sequential transformation.

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Data availability

All data supporting the findings of this study are available in the article and its supplementary figures and tables or are available from the corresponding author upon reasonable request. All sequencing data were deposited in the National Center for Biotechnology Information BioProject under accession code PRJNA879048 (ref. 70). For sequence data, rice OsKitaake identifiers (https://phytozome-next.jgi.doe.gov/) are: OsKitaake03g041600 (OsCDC48), OsKitaake08g207700 (OsIPA1), OsKitaake02g183100 (OsALS) and OsKitaake08g018600 (OsS20). Source data are provided with this paper.

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Acknowledgements

We thank Z. He (Institute of Plant Physiology & Ecology, Chinese Academy of Sciences) for providing a pigmR gene coding plasmid. We also thank Y. Liu, Q. Lin, S. Jin and Z. He for helpful advice. This work was supported by grants from the National Key Research and Development Program (2022YFF1002802 to C.G.), the Strategic Priority Research Program of the Chinese Academy of Sciences (Precision Seed Design and Breeding, XDA24020102, to C.G. and XDA24020310 to Y.W.), the Ministry of Agriculture and Rural Affairs of China, the National Natural Science Foundation of China (32122051 to Y.W.) and the Schmidt Science Fellows to K.T.Z.

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  1. These authors contributed equally: Chao Sun, Yuan Lei, Boshu Li.

Authors and Affiliations

  1. State Key Laboratory of Plant Cell and Chromosome Engineering, Center for Genome Editing, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, China

    Chao Sun, Yuan Lei, Boshu Li, Yunjia Li, Hongchao Li, Yanpeng Wang & Caixia Gao

  2. College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China

    Chao Sun, Yuan Lei, Boshu Li, Yunjia Li, Yanpeng Wang & Caixia Gao

  3. Qi Biodesign, Life Science Park, Beijing, China

    Qiang Gao, Zhiwei Wang, Yan Li & Kevin Tianmeng Zhao

  4. State Key Laboratory of Agrobiotechnology and MOA Key Laboratory for Monitoring and Green Management of Crop Pests, China Agricultural University, Beijing, China

    Wen Cao, Chao Yang & Jun Liu

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Contributions

K.T.Z. and C.G. designed the experiments and supervised the project. C.S., Y. Lei and H.L performed experiments. B.L. performed rice transformation experiments. Q.G., Yunjia Li, Z.W. and Yan Li performed the GSH prediction and whole-genome sequencing analysis. W.C. and C.Y. performed blast resistance experiments. Y.W. and J.L. consulted and designed experiments. C.S., Y. Lei, B.L., K.T.Z. and C.G. wrote the manuscript. All authors reviewed the manuscript.

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Correspondence to Kevin Tianmeng Zhao or Caixia Gao.

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The authors have submitted a patent application based on the results reported in this article. K.T.Z. is a founder and employee of Qi Biodesign. Q.G., Z.W. and Y.L. are employees of Qi Biodesign.

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Extended data

Extended Data Fig. 1 Evaluating different site-specific recombinases using a fluorescent reporter directly in rice protoplasts.

Eight recombinases are evaluated with each corresponding recombinase site sequence listed. Microscopy images are of rice protoplasts with or without the corresponding recombinase transformed.

Extended Data Fig. 2 Development and optimization of dual-ePPE system in rice.

a, Schematic overview of dual-PPE system-mediated targeted DNA insertions. NGG and CCN represent the PAMs of two pegRNAs targeting opposing DNA strands; the blue and green lines represent the corresponding PBS/RT template on each DNA strand in each pegRNA and the red line represents the complementary sequence between the two pegRNAs; the blue and green arrows show the directions of reverse transcription. PBS: primer binding site; RT template: reverse transcription template. b, Overview of PPE, ePPE, ePPE-wtCas9, pegRNA, and epegRNA construct architectures. c, Recombinase site insertion (ins) efficiencies mediated by PPE, ePPE, and ePPE-wtCas9 with pegRNA across five endogenous genomic sites in rice protoplasts as measured using high-throughput sequencing; precise ins represent precise insertions; imprecise ins represent insertions comprised of more than half of the insertion sequence inserted but not the complete sequence; other indels represent all other edits; Values and error bars represent the mean and standard error of mean for three independent biological replicates. d, Recombinase site insertion efficiencies mediated by PPE + peg, PPE + epeg, ePPE+peg, and ePPE+epeg across eight endogenous genomic sites in rice protoplasts as measured using high-throughput sequencing; Values and error bars represent the mean and standard error of mean for three independent biological replicates. e, Overview of the ePPE (SpG) and the ePPE (SpRY) construct architectures and their corresponding insertion frequencies with six pairs of epegRNAs at the OsCDC48 site in rice protoplasts as measured using high-throughput sequencing; Values and error bars represent the mean and standard error of mean for three independent biological replicates. f, Statistical overview of dual-ePPE-mediated insertions of recombinase sites in rice plants.

Extended Data Fig. 3 epegRNA or RS sequence optimizations to improve editing efficiency.

a, Overview of pU3-epegRNA and pGS-epegRNA construct architectures. b, Dual-ePPE editing efficiencies mediated by a pU3 or pGS promoter driving epegRNA expression across five endogenous genomic sites in rice protoplasts as measured using high-throughput sequencing; Values and error bars represent the mean and standard error of mean for three independent biological replicates. c, Dual-ePPE editing efficiencies of varying insertion or deletion sizes mediated by a pU3 or pGS promoter driving epegRNA expression at the OsCDC48 genomic site in rice protoplasts as measured using high-throughput sequencing; Values and error bars represent the mean and standard error of mean for three independent biological replicates; P values were obtained using the two-tailed Student’s t-test: ***P < 0.001, ****P < 0.0001. d, Sanger sequencing traces of dual-ePPE editing at OsCDC48 mediated by a pU3 or pGS promoter to drive epegRNA expression; The red line and arrow represent the point of insertion and insertion direction, respectively. e, Dual-ePPE editing efficiencies to generate larger DNA donor insertions mediated by the pGS promoter driving epegRNA expression at the OsCDC48 genomic site in rice protoplasts as measured using high-throughput sequencing; Values and error bars represent the mean and standard error of mean for three independent biological replicates. f, FRT recombinase site truncation and engineered variants. tFRT1 (tF1) represents a truncated form of FRT1 (F1), * identifies key residues recognized by FLP; the red bases represent mutated residues in each variant. g, Percent GFP positive plant protoplast cells reflective of overall insertion efficiencies as evaluated using the all-in-one reporter and measured using flow cytometry; Each bar represents a unique pair of recombinase sites evaluated using the PrimeRoot; Values and error bars represent the mean and standard error of mean for three independent biological replicates. h, GFP insertion efficiencies at OsALS in rice protoplasts as measured using ddPCR; Each bar represents a unique pair of recombinase sites evaluated using the PrimeRoot; Values and error bars represent the mean and standard error of mean for three independent biological replicates.

Extended Data Fig. 4 Comparison of targeted insertions mediated by PrimeRoot and NHEJ.

a, Overview of PrimeRoot construct architectures and NHEJ donor constructs for inserting GFP (720 bp), Act1P (1.4 kb), Act1P-pigmR (4.9 kb) and Act1P-PM (7.7kb). b, Comparison of PrimeRoot and NHEJ editing efficiencies for targeted insertions of the three donors at the OsCDC48, OsS20, and GSH1 sites in rice protoplasts as measured by ddPCR; Values and error bars represent the mean and standard error of mean for three independent biological replicates; P values were obtained using the two-tailed Student’s t-test: nsP > 0.05, *P < 0.05, **P < 0.01. c, Gel electrophoresis of PCR outcomes of the insertion junction between the donor cassette and endogenous genome. sgRNA1 and sgRNA2 are the target sites used in PrimeRoot; sgRNA1 is the Cas9 target site used for NHEJ -F, A-R are the primers for PCR and Sanger sequencing; Blue bases represent sequences from the donor and red bases represent sporadic DNA insertions or deletions; M represents the marker; the numbers behind the red arrow represent the size of PCR outcomes. d, Overview of insertion statistics mediated by PrimeRoot.v2C-Cre or NHEJ.

Source data

Extended Data Fig. 5 Predicting GSH regions and analyzing Agrobacterium insertion events.

a, Schematic overview on annotating rice genomes and predicting conserved GSH regions across 33 rice varieties. b, Schematic overview on using whole genome sequencing to identify insertion events. c, PCR validation of Agrobacteria insertion events as identified by whole-genome sequencing. RB and LB junctions are amplified using primers designed based on surrounding contig sequences. am1 to am10 represent 10 different Agrobacteria-derived mutants. wt represent wild-type rice plants amplified using the junction-spanning primer pairs. d, Overview of Agrobacteria-mediated insertion events and their genome insertion locations.

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Supplementary Fig. 1, Supplementary Tables 1–11, Supplementary Sequences and Supplementary References

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Unprocessed gel, Supplementary Fig. 1.

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Sun, C., Lei, Y., Li, B. et al. Precise integration of large DNA sequences in plant genomes using PrimeRoot editors. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01769-w

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