新技術揭示影響CRISPR-Cas9全基因組活性的遺傳和表觀遺傳因素
作者：
小柯機器人發布時間：2020/6/17 22:27:49
美國聖猶大兒童研究醫院Shengdar Q. Tsai研究小組利用CHANGE-seq技術，揭示了影響CRISPR-Cas9全基因組活性的遺傳和表觀遺傳因素。相關論文於2020年6月15日在線發表在《自然—生物技術》雜誌上。
研究人員報導了「通過測序對核酸酶全基因組效應進行高通量分析的循環化」（CHANGE-seq）技術，這是一種可擴展的、基於tagmentation的體外Cas9全基因組活性測量方法。研究人員將CHANGE-seq應用於人類原代T細胞中13個治療相關基因座上的110個單向導RNA靶標，並鑑定了201,934個脫靶位點，從而能夠訓練機器學習模型來預測脫靶活性。
通過比較匹配的全基因組脫靶、染色質修飾和可及性以及轉錄數據，研究人員發現細胞脫靶活性發生在活躍動子、增強子和轉錄區域附近的可能性增至兩倍至四倍。最後，對八個獨立基因組中六個目標的CHANGE-seq分析顯示，人類單核苷酸變異在約15.2％的脫靶位點上對活性有顯著影響。因此，CHANGE-seq是一種簡化、敏感且可擴展的方法，可用於了解基因組編輯器的特異性。
據悉，當前的方法可以闡明CRISPR–Cas9核酸酶的全基因組活性，但不容易擴展到充分理解控制Cas9特異性原理所需的通量。
附：英文原文
Title: CHANGE-seq reveals genetic and epigenetic effects on CRISPR–Cas9 genome-wide activity
Author: Cicera R. Lazzarotto, Nikolay L. Malinin, Yichao Li, Ruochi Zhang, Yang Yang, GaHyun Lee, Eleanor Cowley, Yanghua He, Xin Lan, Kasey Jividen, Varun Katta, Natalia G. Kolmakova, Christopher T. Petersen, Qian Qi, Evgheni Strelcov, Samantha Maragh, Giedre Krenciute, Jian Ma, Yong Cheng, Shengdar Q. Tsai
Issue&Volume: 2020-06-15
Abstract: Current methods can illuminate the genome-wide activity of CRISPR–Cas9 nucleases, but are not easily scalable to the throughput needed to fully understand the principles that govern Cas9 specificity. Here we describe 『circularization for high-throughput analysis of nuclease genome-wide effects by sequencing』 (CHANGE-seq), a scalable, automatable tagmentation-based method for measuring the genome-wide activity of Cas9 in vitro. We applied CHANGE-seq to 110 single guide RNA targets across 13 therapeutically relevant loci in human primary T cells and identified 201,934 off-target sites, enabling the training of a machine learning model to predict off-target activity. Comparing matched genome-wide off-target, chromatin modification and accessibility, and transcriptional data, we found that cellular off-target activity was two to four times more likely to occur near active promoters, enhancers and transcribed regions. Finally, CHANGE-seq analysis of six targets across eight individual genomes revealed that human single-nucleotide variation had significant effects on activity at ~15.2% of off-target sites analyzed. CHANGE-seq is a simplified, sensitive and scalable approach to understanding the specificity of genome editors.
DOI: 10.1038/s41587-020-0555-7
Source: https://www.nature.com/articles/s41587-020-0555-7