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Effective identification of CRISPR/Cas9-induced and naturally occurred mutations in rice using a multiplex ligation-dependent probe amplification-based method
Tuesday, 2020/08/04 | 08:09:23

Sukumar BiswasRong LiJun HongXiangxiang ZhaoZheng YuanDabing Zhang & Jianxin Shi

Theoretical and Applied Genetics, August 2020;  133:2323–2334


Key message


A multiplex ligation-dependent probe amplification (MLPA)-based method was developed and successfully utilized to efficiently detect both CRISPR/Cas9-induced and naturally occurred mutations in rice.




The site-specific nuclease-based CRISPR/Cas9 system has emerged as one of the most efficient genome editing tools to modify multiple genomic targets simultaneously in various organisms, including plants for both fundamental and applied researches. Screening for both on-target and off-target mutations in CRISPR/Cas9-generated mutants at the early stages is an indispensable step for functional analysis and subsequent application. Various methods have been developed to detect CRISPR/Cas9-induced mutations in plants. Still, very few have focused on the detection of both on- and off-targets simultaneously, let alone the detection of natural mutations. Here, we report a multiplex capable method that allows to detect CRISPR/Cas9 induced on- and off-target mutations as well as naturally occurred mutation based on a multiplex ligation-dependent probe amplification (MLPA) method. We demonstrated that unlike other methods, the modified target-specific MLPA method can accurately identify any INDELs generated naturally or by the CRISPR/Cas9 system and that it can detect natural variation and zygosity of the CRISPR/Cas9-generated mutants in rice as well. Furthermore, its high sensitivity allowed to define INDELs down to 1 bp and substitutions to a single nucleotide. Therefore, this sensitive, reliable, and cheap method would further accelerate functional analysis and marker-assisted breeding in plants, including rice.


See https://link.springer.com/article/10.1007/s00122-020-03600-5

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