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BREEDIT : a multiplex genome editing strategy to improve complex quantitative traits in maize

Christian Lorenzo (UGent) , Kevin Debray (UGent) , Denia Herwegh (UGent) , Ward Develtere (UGent) , Lennert Impens (UGent) , Dries Schaumont, Wout Vandeputte (UGent) , Stijn Aesaert (UGent) , Griet Coussens (UGent) , Yara De Boe, et al.
(2023) PLANT CELL. 35(1). p.218-238
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Abstract
Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs. BREEDIT is a gene discovery pipeline that combines multiplex CRISPR/Cas9 genome editing of whole gene families with crossing schemes to improve complex quantitative traits.
Keywords
Cell Biology, Plant Science, TRANSCRIPTION FACTORS, GIBBERELLIC-ACID, CELL-DIVISION, SIZE CONTROL, LEAF GROWTH, OVEREXPRESSION, FUTURE, YIELD, IMPACTS, PROTEIN

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Citation

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MLA
Lorenzo, Christian, et al. “BREEDIT : A Multiplex Genome Editing Strategy to Improve Complex Quantitative Traits in Maize.” PLANT CELL, vol. 35, no. 1, 2023, pp. 218–38, doi:10.1093/plcell/koac243.
APA
Lorenzo, C., Debray, K., Herwegh, D., Develtere, W., Impens, L., Schaumont, D., … Inzé, D. (2023). BREEDIT : a multiplex genome editing strategy to improve complex quantitative traits in maize. PLANT CELL, 35(1), 218–238. https://doi.org/10.1093/plcell/koac243
Chicago author-date
Lorenzo, Christian, Kevin Debray, Denia Herwegh, Ward Develtere, Lennert Impens, Dries Schaumont, Wout Vandeputte, et al. 2023. “BREEDIT : A Multiplex Genome Editing Strategy to Improve Complex Quantitative Traits in Maize.” PLANT CELL 35 (1): 218–38. https://doi.org/10.1093/plcell/koac243.
Chicago author-date (all authors)
Lorenzo, Christian, Kevin Debray, Denia Herwegh, Ward Develtere, Lennert Impens, Dries Schaumont, Wout Vandeputte, Stijn Aesaert, Griet Coussens, Yara De Boe, Kirin Demuynck, Tom Van Hautegem, Laurens Pauwels, Thomas B. Jacobs, Tom Ruttink, Hilde Nelissen, and Dirk Inzé. 2023. “BREEDIT : A Multiplex Genome Editing Strategy to Improve Complex Quantitative Traits in Maize.” PLANT CELL 35 (1): 218–238. doi:10.1093/plcell/koac243.
Vancouver
1.
Lorenzo C, Debray K, Herwegh D, Develtere W, Impens L, Schaumont D, et al. BREEDIT : a multiplex genome editing strategy to improve complex quantitative traits in maize. PLANT CELL. 2023;35(1):218–38.
IEEE
[1]
C. Lorenzo et al., “BREEDIT : a multiplex genome editing strategy to improve complex quantitative traits in maize,” PLANT CELL, vol. 35, no. 1, pp. 218–238, 2023.
@article{8768105,
  abstract     = {{Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs. BREEDIT is a gene discovery pipeline that combines multiplex CRISPR/Cas9 genome editing of whole gene families with crossing schemes to improve complex quantitative traits.}},
  author       = {{Lorenzo, Christian and Debray, Kevin and Herwegh, Denia and Develtere, Ward and Impens, Lennert and Schaumont, Dries and Vandeputte, Wout and Aesaert, Stijn and Coussens, Griet and De Boe, Yara and Demuynck, Kirin and Van Hautegem, Tom and Pauwels, Laurens and Jacobs, Thomas B. and Ruttink, Tom and Nelissen, Hilde and Inzé, Dirk}},
  issn         = {{1040-4651}},
  journal      = {{PLANT CELL}},
  keywords     = {{Cell Biology,Plant Science,TRANSCRIPTION FACTORS,GIBBERELLIC-ACID,CELL-DIVISION,SIZE CONTROL,LEAF GROWTH,OVEREXPRESSION,FUTURE,YIELD,IMPACTS,PROTEIN}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{218--238}},
  title        = {{BREEDIT : a multiplex genome editing strategy to improve complex quantitative traits in maize}},
  url          = {{http://doi.org/10.1093/plcell/koac243}},
  volume       = {{35}},
  year         = {{2023}},
}

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