Synthetic directed evolution in plants: unlocking trait engineering and improvement
Author(s) -
Gundra Sivakrishna Rao,
Wenjun Jiang,
Magdy M. Mahfouz
Publication year - 2021
Publication title -
synthetic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.769
H-Index - 8
ISSN - 2397-7000
DOI - 10.1093/synbio/ysab025
Subject(s) - trait , synthetic biology , computer science , directed evolution , biochemical engineering , artificial intelligence , computational biology , biology , engineering , programming language , genetics , mutant , gene
Genetic variation accelerates adaptation and resilience and enables the survival of species in 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 the 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 the plant traits of the value.
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