Topologically associating domain (TAD) boundaries partition the genome into distinct regulatory territories. Anecdotal evidence suggests that their disruption may interfere with normal gene expression and cause disease phenotypes^1–3, but the overall extent to which this occurs remains unknown. Here we demonstrate that targeted deletions of TAD boundaries cause a range of disruptions to normal in vivo genome function and organismal development. We used CRISPR genome editing in mice to individually delete eight TAD boundaries (11–80 kb in size) from the genome. All deletions examined resulted in detectable molecular or organismal phenotypes, which included altered chromatin interactions or gene expression, reduced viability, and anatomical phenotypes. We observed changes in local 3D chromatin architecture in 7 of 8 (88%) cases, including the merging of TADs and altered contact frequencies within TADs adjacent to the deleted boundary. For 5 of 8 (63%) loci examined, boundary deletions were associated with increased embryonic lethality or other developmental phenotypes. For example, a TAD boundary deletion near Smad3/Smad6 caused complete embryonic lethality, while a deletion near Tbx5/Lhx5 resulted in a severe lung malformation. Our findings demonstrate the importance of TAD boundary sequences for in vivo genome function and reinforce the critical need to carefully consider the potential pathogenicity of noncoding deletions affecting TAD boundaries in clinical genetics screening.

Mouse models are a critical tool for studying human diseases, particularly developmental disorders¹. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse². Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing³ to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions^4,5. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be ‘decomposable’ through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.