Identification and characterization of cellular heterogeneity within the developing renal interstitium.

Kidney formation requires the coordinated growth of multiple cell types including the collecting ducts, nephrons, vasculature and interstitium. There is a long-held belief that interactions between progenitors of the collecting ducts and nephrons are primarily responsible for kidney development. However, over the last several years, it has become increasingly clear that multiple aspects of kidney development require signaling from the interstitium. How the interstitium orchestrates these various roles is poorly understood. Here, we show that during development the interstitium is a highly heterogeneous patterned population of cells that occupies distinct positions correlated to the adjacent parenchyma. Our analysis indicates that the heterogeneity is not a mere reflection of different stages in a linear developmental trajectory but instead represents several novel differentiated cell states. Further, we find that ß-catenin has a cell autonomous role in the development of a medullary subset of the interstitium and that this non-autonomously affects the development of the adjacent epithelia. These findings suggest the intriguing possibility that the different interstitial subtypes may create microenvironments that play unique roles in development of the adjacent epithelia and endothelia.

Computational identification of clonal cells in single-cell CRISPR screens.

BACKGROUND: Single-cell CRISPR screens are powerful tools to understand genome function by linking genetic perturbations to transcriptome-wide phenotypes. However, since few cells can be affordably sequenced in these screens, biased sampling of cells could affect data interpretation. One potential source of biased sampling is clonal cell expansion. RESULTS: Here, we identify clonal cells in single cell screens using multiplexed sgRNAs as barcodes. We find that the cells in each clone share transcriptional similarities and bear segmental copy number changes. These analyses suggest that clones are genetically distinct. Finally, we show that the transcriptional similarities of clonally expanded cells contribute to false positives in single-cell CRISPR screens. CONCLUSIONS: Experimental conditions that reduce clonal expansion or computational filtering of clonal cells will improve the reliability of single-cell CRISPR screens.

Breaking enhancers to gain insights into developmental defects.

Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes.

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

CHD-associated enhancers shape human cardiomyocyte lineage commitment.

Enhancers orchestrate gene expression programs that drive multicellular development and lineage commitment. Thus, genetic variants at enhancers are thought to contribute to developmental diseases by altering cell fate commitment. However, while many variant-containing enhancers have been identified, studies to endogenously test the impact of these enhancers on lineage commitment have been lacking. We perform a single-cell CRISPRi screen to assess the endogenous roles of 25 enhancers and putative cardiac target genes implicated in genetic studies of congenital heart defects (CHDs). We identify 16 enhancers whose repression leads to deficient differentiation of human cardiomyocytes (CMs). A focused CRISPRi validation screen shows that repression of TBX5 enhancers delays the transcriptional switch from mid- to late-stage CM states. Endogenous genetic deletions of two TBX5 enhancers phenocopy epigenetic perturbations. Together, these results identify critical enhancers of cardiac development and suggest that misregulation of these enhancers could contribute to cardiac defects in human patients.

Global Analysis of Enhancer Targets Reveals Convergent Enhancer-Driven Regulatory Modules.

Single-cell screens enable high-throughput functional assessment of enhancers in their endogenous genomic context. However, the design of current studies limits their application to identifying the primary gene targets of enhancers. Here, we improve the experimental and computational parameters of single-cell enhancer screens to identify the secondary gene targets of enhancers. Our analysis of >500 putative enhancers in K562 cells reveals an interwoven enhancer-driven gene regulatory network. We find that enhancers from distinct genomic loci converge to modulate the expression of common sub-modules, including the α- and ß-globin loci, by directly regulating transcription factors. Our analysis suggests that several genetic variants associated with myeloid blood cell traits alter the activity of a distal enhancer of MYB (∼140 kb away), with downstream consequences on hemoglobin genes expression and cell state. These data have implications for the understanding of enhancer-associated traits and emphasize the flexibility of controlling transcriptional systems by modifying enhancer activity.

Frequent sgRNA-barcode recombination in single-cell perturbation assays.

Simultaneously detecting CRISPR-based perturbations and induced transcriptional changes in the same cell is a powerful approach to unraveling genome function. Several lentiviral approaches have been developed, some of which rely on the detection of distally located genetic barcodes as an indirect proxy of sgRNA identity. Since barcodes are often several kilobases from their corresponding sgRNAs, viral recombination-mediated swapping of barcodes and sgRNAs is feasible. Using a self-circularization-based sgRNA-barcode library preparation protocol, we estimate the recombination rate to be ~50% and we trace this phenomenon to the pooled viral packaging step. Recombination is random, and decreases the signal-to-noise ratio of the assay. Our results suggest that alternative approaches can increase the throughput and sensitivity of single-cell perturbation assays.