Gene editing is an innovative style of genetic engineering that revolutionizes human medicine and farming. The technique enables scientists to gain the ability to modify almost any organism’s genome more accurately. Scientists can identify and remove genes those causing rare human diseases or insert essential traits such as drought and disease resistance found elsewhere in a plant species.
At a definite point, a strand of DNA is cut and the cellular repair mechanisms naturally exist, and then the broken DNA strands are fixed more precisely. The way of repairing can affect gene function and when the DNA is cut, new DNA sequences can be delivered and act as templates for an altered sequence to be generated. Genome editing techniques help delete DNA sections or to alter how a gene works.
Genome-wide off-target analysis by two-cell embryo Injection (GOTI) is the technique developed by researchers to detect off-target mutations by editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or base editors. This technique was discovered by researchers from the Institute of Neuroscience (ION) of the Chinese Academy of Sciences (CAS), the Agricultural Genome Institute at Shenzhen, the CAS-MPG Partner Institute for Computational Biology of the Shanghai Institute of Nutrition and Health of CAS, Stanford University.
Two-cell embryo injection (GOTI) off-target analysis is the technique developed by researchers to detect off-target mutations by editing one two-cell mouse embryo blastomer using either CRISPR-Cas9 or base editors. Researchers from the Institute of Neuroscience (ION) of the Chinese Academy of Sciences (CAS), the CAS-MPG Partner Institute for Computational Biology of the CAS Nutrition and Health Institute of Shanghai, Stanford University, and the Shenzhen Agricultural Genome Institute discovered this technique.
Researchers used GOTI technique for evaluating off-target genome-wide effects induced by genome-editing tools including CRISPR/Cas9 and base editors. They found that editors of the cytosine base induced substantial variants of single nucleotides (SNVs) off-target. They also illustrated that in the absence of prediction; GOTI significantly improved the sensitivity of off-target detection and could detect off-target variants generated randomly.
This study established a method of gene-editing off-target detection with greater accuracy, breadth, and accuracy than previous methods. GOTI can be used to develop a new generation of genome-editing tools with greater precision and safety, thus creating a new industry standard.