Division of Medical Genetics, Department of Medicine, Department of Genome Sciences, Institute for Stem Cell and Regenerative Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Nat Commun. 2020 Feb 26;11(1):1061. doi: 10.1038/s41467-020-14853-5.
The study of gene regulation is dominated by a focus on the control of gene activation or increase in the level of expression. Just as critical is the process of gene repression or silencing. Chromatin signatures have identified enhancers, however, genome-wide identification of silencers by computational or experimental approaches are lacking. Here, we first define uncharacterized cis-regulatory elements likely containing silencers and find that 41.5% of ~7500 tested elements show silencer activity using massively parallel reporter assay (MPRA). We trained a support vector machine classifier based on MPRA data to predict candidate silencers in over 100 human and mouse cell or tissue types. The predicted candidate silencers exhibit characteristics expected of silencers. Leveraging promoter-capture HiC data, we find that over 50% of silencers are interacting with gene promoters having very low to no expression. Our results suggest a general strategy for genome-wide identification and characterization of silencer elements.
基因调控的研究主要集中在基因激活或表达水平的增加上。同样关键的是基因抑制或沉默的过程。染色质特征已经确定了增强子,然而,通过计算或实验方法对沉默子的全基因组识别还缺乏。在这里,我们首先定义了可能包含沉默子的未表征的顺式调控元件,并发现使用大规模平行报告基因检测(MPRA),约 7500 个测试元件中有 41.5%表现出沉默子活性。我们基于 MPRA 数据训练了一个支持向量机分类器,以预测 100 多种人类和小鼠细胞或组织类型中的候选沉默子。预测的候选沉默子表现出沉默子的特征。利用启动子捕获 HiC 数据,我们发现超过 50%的沉默子与基因启动子相互作用,而这些基因启动子的表达水平非常低或没有表达。我们的结果表明了一种用于全基因组识别和鉴定沉默子元件的一般策略。