Synthetic Directed Evolution in Plants: Unlocking Trait Engineering and Improvement
KAUST DepartmentBiological and Environmental Science and Engineering (BESE) Division
Desert Agriculture Initiative
Permanent link to this recordhttp://hdl.handle.net/10754/671139
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AbstractABSTRACT Genetic variation accelerates adaptation and resilience and enables the survival of species to their changing environment. Increasing the genetic diversity of crop species is essential to improve their yield and enhance food security. Synthetic directed evolution (SDE) employs localized sequence diversification (LSD) of gene sequence and selection pressure to evolve gene variants with better fitness, improved properties, and desired phenotypes. Recently, CRISPR-Cas dependent and independent technologies have been applied for LSD to mediate synthetic evolution in diverse species, including plants. SDE holds excellent promise to discover, accelerate, and expand the range of traits of value in crop species. Here, we highlight the efficient SDE approaches for the LSD of plant genes, selection strategies, and critical traits for targeted improvement. We discuss the potential of emerging technologies, including CRISPR-Cas base editing, retron editing, EvolvR, and prime editing, to establish efficient SDE in plants. Moreover, we cover CRISPR-Cas independent technologies, including T7 polymerase editor for continuous evolution. We highlight the key challenges and potential solutions of applying SDE technologies to improve plant traits of value.
CitationGundra, S. R., Jiang, W., & Mahfouz, M. (2021). Synthetic Directed Evolution in Plants: Unlocking Trait Engineering and Improvement. Synthetic Biology. doi:10.1093/synbio/ysab025
SponsorsThis work is supported by KAUST core funding to MM.
We would like to thank members of the genome engineering and synthetic biology laboratory at KAUST for critical discussions.
PublisherOxford University Press (OUP)
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License , which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.