Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA.
Department of Genome Sciences, University of Washington, Seattle, WA 98105, USA.
Cell. 2019 Jan 10;176(1-2):377-390.e19. doi: 10.1016/j.cell.2018.11.029. Epub 2019 Jan 3.
Over one million candidate regulatory elements have been identified across the human genome, but nearly all are unvalidated and their target genes uncertain. Approaches based on human genetics are limited in scope to common variants and in resolution by linkage disequilibrium. We present a multiplex, expression quantitative trait locus (eQTL)-inspired framework for mapping enhancer-gene pairs by introducing random combinations of CRISPR/Cas9-mediated perturbations to each of many cells, followed by single-cell RNA sequencing (RNA-seq). Across two experiments, we used dCas9-KRAB to perturb 5,920 candidate enhancers with no strong a priori hypothesis as to their target gene(s), measuring effects by profiling 254,974 single-cell transcriptomes. We identified 664 (470 high-confidence) cis enhancer-gene pairs, which were enriched for specific transcription factors, non-housekeeping status, and genomic and 3D conformational proximity to their target genes. This framework will facilitate the large-scale mapping of enhancer-gene regulatory interactions, a critical yet largely uncharted component of the cis-regulatory landscape of the human genome.
已经在人类基因组中鉴定出超过一百万种候选调控元件，但几乎所有这些都未经验证，其靶基因也不确定。基于人类遗传学的方法在范围上仅限于常见变体，在分辨率上受到连锁不平衡的限制。我们提出了一种多重、基于表达数量性状基因座（eQTL）的框架，通过在许多细胞中的每一个细胞中引入 CRISPR/Cas9 介导的随机组合干扰，随后进行单细胞 RNA 测序（RNA-seq），来绘制增强子-基因对。在两项实验中，我们使用 dCas9-KRAB 来干扰 5920 个候选增强子，这些候选增强子没有强烈的先验假设来确定它们的靶基因（s），通过分析 254974 个单细胞转录组来测量效果。我们鉴定了 664 个（470 个高可信度）顺式增强子-基因对，这些对与靶基因在转录因子、非管家状态以及基因组和 3D 构象上的接近性方面富集。该框架将有助于大规模绘制增强子-基因调控相互作用图谱，这是人类基因组顺式调控景观中一个关键但在很大程度上尚未被探索的组成部分。
