Are the current gRNA ranking prediction algorithms useful for genome editing in plants?

Autoři: Fatima Naim aff001;  Kylie Shand aff001;  Satomi Hayashi aff001;  Martin O’Brien aff003;  James McGree aff004;  Alexander A. T. Johnson aff003;  Benjamin Dugdale aff001;  Peter M. Waterhouse aff001
Působiště autorů: Centre for Tropical Crops and Biocommodities, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia aff001;  Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia aff002;  School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia aff003;  School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article


Introducing a new trait into a crop through conventional breeding commonly takes decades, but recently developed genome sequence modification technology has the potential to accelerate this process. One of these new breeding technologies relies on an RNA-directed DNA nuclease (CRISPR/Cas9) to cut the genomic DNA, in vivo, to facilitate the deletion or insertion of sequences. This sequence specific targeting is determined by guide RNAs (gRNAs). However, choosing an optimum gRNA sequence has its challenges. Almost all current gRNA design tools for use in plants are based on data from experiments in animals, although many allow the use of plant genomes to identify potential off-target sites. Here, we examine the predictive uniformity and performance of eight different online gRNA-site tools. Unfortunately, there was little consensus among the rankings by the different algorithms, nor a statistically significant correlation between rankings and in vivo effectiveness. This suggests that important factors affecting gRNA performance and/or target site accessibility, in plants, are yet to be elucidated and incorporated into gRNA-site prediction tools.

Klíčová slova:

CRISPR – Guide RNA – Leaves – Nucleases – Plant genomes – Polymerase chain reaction – Sequence assembly tools – Sequence motif analysis


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2020 Číslo 1
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