A Single-Cell Resolution Enhancer Atlas of Craniofacial Development

项目总结 颅面发育需要许多不同细胞精确协调的分化和迁移 时间和空间上的人口。了解这一动态过程的基因调控是 破译唇腭裂等颅面先天缺陷的遗传基础。我们之前 展示了远距离作用的促进剂在控制头面部发育中的关键作用，如 FaceBase的成员生成了在这一过程中活跃的增强子的全基因组图谱。然而，我们的 研究还强调了全基因组转录组和表观基因组图谱的有限分辨率。 原发块状组织的SEQ和CHIP-SEQ。新技术现在使绘制基因表达和基因图谱成为可能 在单细胞分辨率下增强活性，并能够测试关于细胞类型- 头面部发育中的特殊增强剂。在初步研究中，我们分析了28,000份抄本 单个头面部细胞，为不同的细胞群分配增强子，整合的单细胞转录组和 光学投影层析成像(OPT)数据将增强子标记的单细胞群体映射到三个- 空间解剖，并使用单核ATAC-SEQ在单细胞分辨率下定位开放染色质。这里 我们建议对这些研究进行扩展，以产生一种三维的单细胞分辨率增强器 以及头面部发育的转录组图谱。我们将使用最新一代的单细胞分析 工具，一套独特的鼠标工程技术，以及一个巨大的&gt；300颅面分子工具箱 我们之前在体内对增强剂进行了表征。生成的数据集，也将通过 FaceBase数据门户将为研究颅面基因、增强剂、 和途径，并为解释非编码序列变化提供了亟需的框架 对头面部出生缺陷负责。具体目标是：1)创建单个单元格分辨率 颅面发育的转录组和开放染色质汇编。该参考资料将包括 来自100万个细胞的转录本以及150个头面部增强剂的体内活性数据 这种高分辨率的数据是通过对专门设计的报告鼠的单细胞分析得出的。2)执行 单细胞转录、可及染色质和三维转基因的综合分析 记者选择数据来生成连接增强子和细胞的具有凝聚力、空间和时间分辨率的地图集 人口向发育中面部的特定亚区转移。3)利用这些数据集确定增强剂 与人类颅面畸形相关的变异并评估这些变异的因果作用 通过对具有人类风险和对照等位基因的敲入小鼠进行单细胞鉴定和表型鉴定。这些 研究将提供对颅面发育的细胞和基因调控基础的洞察 史无前例的分辨率并建立了使用单细胞方法来阐明人类如何非编码 变异在机械上增加了头面部出生缺陷的风险。

PROJECT SUMMARY Craniofacial development requires the precisely orchestrated differentiation and migration of many different cell populations in time and space. Understanding the gene regulatory control of this dynamic process is key for deciphering the genetic basis of craniofacial birth defects such as clefts of the lip and palate. We previously demonstrated the critical role of distant-acting enhancers in controlling craniofacial development and, as members of FaceBase, generated genome-wide maps of enhancers active during this process. However, our studies also highlighted the limited resolution of genome-wide transcriptome and epigenome mapping from RNA- seq and ChIP-seq of primary bulk tissues. New technologies now make it possible to map gene expression and enhancer activities at single-cell resolution and enable the testing of hypotheses regarding the role of cell type- specific enhancers in craniofacial development. In preliminary studies, we profiled the transcriptomes of 28,000 single craniofacial cells, assigned enhancers to distinct cell populations, integrated single-cell transcriptome and Optical Projection Tomography (OPT) data to map enhancer-labeled single-cell populations onto three- dimensional anatomy, and used single-nucleus ATAC-seq to map open chromatin at single-cell resolution. Here we propose to expand on these studies to generate a three-dimensional, single-cell resolution enhancer and transcriptome atlas of craniofacial development. We will use the latest generation of single-cell profiling tools, a suite of unique mouse engineering techniques, and a vast molecular toolbox of >300 craniofacial enhancers we characterized previously in vivo. The resulting data sets, which will also be made available through the FaceBase data portal, will create a vast community resource for studies of craniofacial genes, enhancers, and pathways and provide a much-needed framework for the interpretation of non-coding sequence changes responsible for craniofacial birth defects. The specific aims are to: 1) Create a single-cell resolution transcriptome and open chromatin compendium of craniofacial development. This reference will include transcriptomes from >1 million cells, as well as in vivo activity data for 150 craniofacial enhancers mapped onto this high-resolution data through single-cell analysis of purpose-engineered reporter mice. 2) Perform integrative analysis of single-cell transcriptomic, accessible chromatin, and three-dimensional transgenic reporter OPT data to generate a cohesive, spatially and temporally resolved atlas linking enhancers and cell populations to specific subregions of the developing face. 3) Leverage these data sets to identify enhancer variants associated with human craniofacial malformations and assess a causal role of these variants through single-cell characterization and phenotyping of knock-in mice with human risk and control alleles. These studies will provide insight into the cellular and gene regulatory basis of craniofacial development at unprecedented resolution and establish the use of single-cell methods for elucidating how human non-coding variants mechanistically contribute to the risk for craniofacial birth defects.