Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
Commun Biol. 2023 May 26;6(1):563. doi: 10.1038/s42003-023-04954-4.
Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to correlate gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we find that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we predict 89,885 significant enhancer-enhancer associations between nearby enhancers. We find that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. We provide a set of predicted enhancer-enhancer associations based on correlation derived from a single cell line, which can be further investigated for functional relevance.
非编码调控元件,如增强子,是控制基因的细胞类型特异性和时空表达的关键。为了驱动对遗传变异和环境压力具有稳健性的稳定和精确的基因转录,基因通常被具有冗余作用的多个增强子靶向。然而,尚不清楚靶向同一基因的增强子是否同时具有活性,或者某些增强子组合是否比其他组合更经常共同活跃。在这里,我们利用单细胞技术的最新进展,这些进展允许在同一单个细胞中评估染色质状态(scATAC-seq)和基因表达(scRNA-seq),将基因表达与多个增强子的活性相关联。在对 24844 个人类淋巴母细胞单细胞进行测量后,我们发现与同一基因相关的大多数增强子在其染色质图谱中表现出显著的相关性。对于与增强子相关的 6944 个表达基因,我们预测了附近增强子之间 89885 个显著的增强子-增强子关联。我们发现相关的增强子具有相似的转录因子结合谱,并且基因的必需性与更高的增强子共同活性有关。我们提供了一组基于来自单个细胞系的相关性得出的预测增强子-增强子关联,可进一步研究其功能相关性。