使用系统性敲减的CRISPR向导RNA的文库可测量基因表达，这一成果由美国加州大学旧金山分校Jonathan S. Weissman研究小组近日取得。该研究2020年1月13日在线发表于国际一流学术期刊《自然—生物技术》。

研究人员报道了一种使用CRISPR干扰和一系列具有系统调节活性的单向导RNA（sgRNA）来测定人类基因表达的方法。研究人员使用多个细胞模型的大规模测量来表征了包含与目标位点不匹配的sgRNA的活性，并使用深度学习来确定了控制不匹配的sgRNA活性的衍生规则。这些规则使研究人员能够合成一个紧凑的sgRNA文库，从而测定约2400个基因对于稳定细胞生长必不可少的表达，并构建涵盖整个人类基因组的计算机sgRNA文库。沿连续的基因表达水平与单细胞RNA-seq读数相结合的细胞分期显示，在特定于基因的表达阈值下，细胞行为发生了急剧的转变。这项工作提供了一种控制基因表达的通用工具，其应用范围包括从调节生化途径到鉴定基因表达失调疾病的抑制剂。

据了解，缺乏精确控制基因表达的工具，限制了人们评估表达水平与表型之间的关系。

附：英文原文

Title: Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs

Author: Marco Jost, Daniel A. Santos, Reuben A. Saunders, Max A. Horlbeck, John S. Hawkins, Sonia M. Scaria, Thomas M. Norman, Jeffrey A. Hussmann, Christina R. Liem, Carol A. Gross, Jonathan S. Weissman

Issue&Volume: 2020-01-13

Abstract: A lack of tools to precisely control gene expression has limited our ability to evaluate relationships between expression levels and phenotypes. Here, we describe an approach to titrate expression of human genes using CRISPR interference and series of single-guide RNAs (sgRNAs) with systematically modulated activities. We used large-scale measurements across multiple cell models to characterize activities of sgRNAs containing mismatches to their target sites and derived rules governing mismatched sgRNA activity using deep learning. These rules enabled us to synthesize a compact sgRNA library to titrate expression of ~2,400 genes essential for robust cell growth and to construct an in silico sgRNA library spanning the human genome. Staging cells along a continuum of gene expression levels combined with single-cell RNA-seq readout revealed sharp transitions in cellular behaviors at gene-specific expression thresholds. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.

DOI: 10.1038/s41587-019-0387-5

Source: https://www.nature.com/articles/s41587-019-0387-5