2019年11月29日，《自然—遗传学》杂志发表了MIT-哈佛大学博德研究所Jesse M. Engreitz、Eric S. Lander等研究人员的合作成果。他们利用新研发的技术，建立了数千种CRISPR扰动引起的增强子-启动子调控的接触活动模型。

研究人员开发了一种叫做CRISPRi-FlowFISH实验方法来打乱基因组中的增强子，并将其用于测试30个基因中的超过3500个潜在增强子与基因的连接。

研究人员发现一个简单的接触活动模型在预测CRISPR数据集中的复杂连接方面远胜过先前的方法。通过接触活动模型，研究人员可以在染色质状态测量的基础上，构建特定细胞类型中增强子与基因的连接的全基因组图谱。

CRISPRi-FlowFISH和接触活动模型共同提供了一种系统的方法来定位和预测哪些增强子调节哪些基因，并将有助于解释非编码基因组中数千种疾病风险变体的功能。

据了解，人类基因组中的增强子元件可控制基因在特定细胞类型中的表达方式，并包含成千上万的遗传变异，这些变异会影响常见疾病。然而，人们仍然不知道增强子如何调控特定基因，并且缺乏通用规则来预测不同细胞类型的增强子与基因的连接。

附：英文原文

Title: Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations

Author: Charles P. Fulco, Joseph Nasser, Thouis R. Jones, Glen Munson, Drew T. Bergman, Vidya Subramanian, Sharon R. Grossman, Rockwell Anyoha, Benjamin R. Doughty, Tejal A. Patwardhan, Tung H. Nguyen, Michael Kane, Elizabeth M. Perez, Neva C. Durand, Caleb A. Lareau, Elena K. Stamenova, Erez Lieberman Aiden, Eric S. Lander, Jesse M. Engreitz

Issue&Volume: 2019-11-29

Abstract: Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1,2,3,4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer–gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test>3,500potential enhancer–gene connections for 30genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer–gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

DOI: 10.1038/s41588-019-0538-0

Source: https://www.nature.com/articles/s41588-019-0538-0