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New Off-target Detection Method GOTI Improves Precision of Safety Evaluation of Genome Editing Tools
Authors:PICB    Time:2019-03-01   Read:24

On Feb. 28th, 2019, a paper named “Cytosine base editor generates substantial off-target single nucleotide variants in mouse embryos” was published on Science. In this work, researchers developed a method named “GOTI”, abbreviated by “Genome-wide Off-target Analysis by Two-cell Embryo Injection”. The research team applied the method to evaluate the genome-wide off-target effects induced by genome editing tools including CRISPR/Cas9 and base editors, and found that cytosine base editor induced substantial off-target single nucleotide variants (SNVs). GOTI significantly improved the sensitivity of off-target detection without prediction in advance and could also detect randomly generated off-target variants. Thus, GOTI has provided a new breathtaking method for the safety evaluation of genome editing tools, which could be taken as industry standard.

This work was accomplished by Institute of Neuroscience (ION) of Chinese Academy of Sciences (CAS), CAS-MPG Partner Institute for Computational Biology (PICB) of Shanghai Institute of Nutrition and Health of CAS, Department of Genetics of Stanford University and Agricultural Genome Institute at Shenzhen (AGIS) of Chinese Agricultural Academy of Sciences. 

CRISPR/Cas9 is a new generation of gene editing tools that have been widely used. Since the appearance in 2012, it has aroused great attention for its efficiency and specificity. Scientists generally believed that clinical application based on CRISPR/Cas9 and its derivatives will make great contribution to human health. However, the risk of off-target has been a concern since the advent of CRISPR/Cas9. The potential off-target effects may cause many side effects including cancer if CRISPR/Cas9 and its derivatives are used for clinical application. Thus, a robust off-target detection method will be the key to the clinical application of CRISPR/Cas9 and its derivatives.

A variety of off-target detection schemes have been developed before. However, most of these methods relied on the prediction of off-target sites based on sequence similarity, or in vitro amplification which may introduce large amount of noise, making it difficult to separate off-target signals from background noise. So whether CRISPR/Cas9 would induce off-target effects has been controversial. Therefore, a precise off-target detection method independent of computational prediction and with sufficient signal-to-noise ratio is needed.

In order to achieve this goal, Prof. LI Yixue's research team and collaborators established an off-target detection method named GOTI. When the mouse embryo developed into two-cell stage, a blastomere is edited and labeled with a red fluorescent protein and the other was unedited. The progeny cells of the edited and non-edited blastomeres were then sorted by Fluorescence-activated cell sorting (FACS) based on tdTomato expression in gene-edited cells at embryonic day14.5 (E14.5). Whole genome sequencing (WGS) was then performed separately on the tdTomato+ and tdTomato- cells. SNVs and indels were called by three algorithms in the tdTomato+ sample, with the tdTomato- sample from the same embryo as the reference. This method avoids the noise problem caused by in vitro amplification. Moreover, since the experimental group and the control group are from the same embryo, the genetic background is completely identical, so the difference between the two cell population can be considered to be caused by genome editing tools.

With the joint efforts of all members, the GOTI system was successfully established. By application of this system, the team members first tested the CRISPR/Cas9 system and found that the well-designed CRISPR/Cas9 did not have obvious off-target effects. This result ended the controversial of CRISPR/Cas9 off-target effects previously. The team also tested another CRISPR/Cas9-derived technology, BE3, which was reported to introduce point mutations, and no significant off-target problems have been found in previous studies. However, under the detection of GOTI, BE3 was found to generate substantial off-target SNVs, which were not predicted by traditional off-target prediction methods. They also found that some of the off-target sites appear on the oncogene and tumor suppressor genes, so the classic version of BE3 buried great concern for clinical application.

Based on the off-target detection by GOTI, researchers found that some of the gene editing tools represented by BE3 have unpredictable off-target risks, allowing the world to re-examine the risks of these emerging technologies. More importantly, this work has established a genetic editing off-target detection method with higher precision, breadth and accuracy than before. GOTI can be applied to develop a new generation of genome editing tools with higher accuracy and safety and thus establish the new Industry Standard.

This work was accomplished by Dr. ZUO Erwei from ION, SUN Yidi from Shanghai Institute of Biochemistry and Cell Biology of CAS, Prof. WEI Wu from PICB, and YUAN Tanglong from AGIS, under the direction of Prof. YANG Hui from ION, Prof. LI Yixue from PICB and Prof. Lars M. Steinmetz from Department of Genetics of Stanford University. This work was also accompanied by other group members in the labs and the FACS facility of ION. 

This study was sponsored by grants of R&D Program of China, CAS Strategic Priority Research Program, National Natural Science Foundation of China, Shanghai Municipal Science and Technology Major Project, Shanghai City Committee of Science and Technology Project, and NIH P01 Center grant.