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.

Public Health Relevance

The human face is a critical component of personal identity, and birth defects of the face cause major psychosocial, speech, feeding, and breathing problems and require costly and stressful surgical correction. The development of the face requires the precise activation of genes, a process that is orchestrated by noncoding DNA sequences called enhancers. To help researchers understand how disruptions of genetic and cellular components required for facial development cause birth defects, we will use a set of advanced functional genomics tools to generate a three-dimensional atlas of enhancers and gene activation for prenatal face development, describing the process at the resolution of single cells.

National Institute of Health (NIH)
National Institute of Dental & Craniofacial Research (NIDCR)
Research Project (R01)
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Genomics, Computational Biology and Technology Study Section (GCAT)
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Wang, Lu
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Lawrence Berkeley National Laboratory
United States
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