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巢式上位性增强子网络介导稳健的基因组调控
作者:小柯机器人 发布时间:2022/8/14 9:27:50

美国斯坦福大学Lei S. Qi团队发现,巢式上位性增强子网络介导稳健的基因组调控。2022年8月11日,《科学》杂志在线发表了这项成果。

研究人员将多重CRISPRi筛选与机器学习结合起来定义了定量的增强子-增强子相互作用。研究人员发现,超长距离的增强子网络拥有一个巢式多层结构,赋予了基因表达的功能稳健性。实验特征显示,增强子上位性是通过三维染色体相互作用和BRD4凝聚来维持的。机器学习对协同增强子的预测提供了一种有效的策略,可以在全基因组关联研究(GWAS)分析之外,识别与疾病中致病基因相关的非编码变体对。这项工作揭示了巢式上位性增强子网络,它可以更好地解释细胞内和疾病中的增强子功能。
 
据介绍,哺乳动物基因组拥有多个跨越超长距离(>基因组)的增强子来调节重要的基因,但目前还不清楚这些增强子如何协调来实现这一任务。
 
附:英文原文

Title: Nested epistasis enhancer networks for robust genome regulation

Author: Xueqiu Lin, Yanxia Liu, Shuai Liu, Xiang Zhu, Lingling Wu, Yanyu Zhu, Dehua Zhao, Xiaoshu Xu, Augustine Chemparathy, Haifeng Wang, Yaqiang Cao, Muneaki Nakamura, Jasprina N. Noordermeer, Marie La Russa, Wing Hung Wong, Keji Zhao, Lei S. Qi

Issue&Volume: 2022-08-11

Abstract: Mammalian genomes possess multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, yet it is unclear how these enhancers coordinate to achieve this task. Here, we combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network possesses a nested multi-layer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify non-coding variant pairs associated with pathogenic genes in diseases beyond Genome-Wide Association Studies (GWAS) analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases.

DOI: abk3512

Source: https://www.science.org/doi/10.1126/science.abk3512

 

期刊信息
Science:《科学》,创刊于1880年。隶属于美国科学促进会,最新IF:41.037