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.

Protocol to dissociate epithelia from non-pregnant and pregnant mouse cervical tissue for single-cell RNA-sequencing.

A challenge in studying cervical epithelial cell biology at the single-cell level is that differentiated subtypes, in particular mucus-secreting goblet cells, are sensitive to disassociating enzymes making isolation of all epithelial subpopulations difficult. Here we present a protocol to dissociate epithelia from non-pregnant and pregnant mouse cervical tissue for single-cell RNA-sequencing. We describe steps for harvesting cervices, preparing cervical tissue, dissociation of cervical cells, and viability checks. We then detail library preparation, sequencing, and procedure for data analysis. For complete details on the use and execution of this protocol, please refer to Cooley et al. (2023).1.

Large-scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal cross talk.

Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. One limitation of our first protocol for human blastoid generation was relatively low efficiency. We now report an optimized protocol for the efficient generation of large quantities of high-fidelity human blastoids from naive pluripotent stem cells. This enabled proteomics analysis that identified phosphosite-specific signatures potentially involved in the derivation and/or maintenance of the signaling states in human blastoids. Additionally, we uncovered endometrial stromal effects in promoting trophoblast cell survival, proliferation, and syncytialization during co-culture with blastoids and blastocysts. Side-by-side single-cell RNA sequencing revealed similarities and differences in transcriptome profiles between pre-implantation blastoids and blastocysts, as well as post-implantation cultures, and uncovered a population resembling early migratory trophoblasts during co-culture with endometrial stromal cells. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, and tractable model for human blastocysts.

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.

Modeling post-implantation stages of human development into early organogenesis with stem-cell-derived peri-gastruloids.

In vitro stem cell models that replicate human gastrulation have been generated, but they lack the essential extraembryonic cells needed for embryonic development, morphogenesis, and patterning. Here, we describe a robust and efficient method that prompts human extended pluripotent stem cells to self-organize into embryo-like structures, termed peri-gastruloids, which encompass both embryonic (epiblast) and extraembryonic (hypoblast) tissues. Although peri-gastruloids are not viable due to the exclusion of trophoblasts, they recapitulate critical stages of human peri-gastrulation development, such as forming amniotic and yolk sac cavities, developing bilaminar and trilaminar embryonic discs, specifying primordial germ cells, initiating gastrulation, and undergoing early neurulation and organogenesis. Single-cell RNA-sequencing unveiled transcriptomic similarities between advanced human peri-gastruloids and primary peri-gastrulation cell types found in humans and non-human primates. This peri-gastruloid platform allows for further exploration beyond gastrulation and may potentially aid in the development of human fetal tissues for use in regenerative medicine.

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.

Dynamic states of cervical epithelia during pregnancy and epithelial barrier disruption.

The cervical epithelium undergoes changes in proliferation, differentiation, and function that are critical to ensure fertility and maintain pregnancy. Here, we identify cervical epithelial subtypes in non-pregnant, pregnant, and in labor mice using single-cell transcriptome and spatial analysis. We identify heterogeneous subpopulations of epithelia displaying spatial and temporal specificity. Notably in pregnancy, two goblet cell subtypes are present in the most luminal layers with one goblet population expanding earlier in pregnancy than the other goblet population. The goblet populations express novel protective factors and distinct mucosal networks. Single-cell analysis in a model of cervical epithelial barrier disruption indicates untimely basal cell proliferation precedes the expansion of goblet cells with diminished mucosal integrity. These data demonstrate how the cervical epithelium undergoes continuous remodeling to maintain dynamic states of homeostasis in pregnancy and labor, and provide a framework to understand perturbations in epithelial health that increase the risk of premature birth.

Global chromatin landscapes identify candidate noncoding modifiers of cardiac rhythm.

Comprehensive cis-regulatory landscapes are essential for accurate enhancer prediction and disease variant mapping. Although cis-regulatory element (CRE) resources exist for most tissues and organs, many rare - yet functionally important - cell types remain overlooked. Despite representing only a small fraction of the heart's cellular biomass, the cardiac conduction system (CCS) unfailingly coordinates every life-sustaining heartbeat. To globally profile the mouse CCS cis-regulatory landscape, we genetically tagged CCS component-specific nuclei for comprehensive assay for transposase-accessible chromatin-sequencing (ATAC-Seq) analysis. Thus, we established a global CCS-enriched CRE database, referred to as CCS-ATAC, as a key resource for studying CCS-wide and component-specific regulatory functions. Using transcription factor (TF) motifs to construct CCS component-specific gene regulatory networks (GRNs), we identified and independently confirmed several specific TF sub-networks. Highlighting the functional importance of CCS-ATAC, we also validated numerous CCS-enriched enhancer elements and suggested gene targets based on CCS single-cell RNA-Seq data. Furthermore, we leveraged CCS-ATAC to improve annotation of existing human variants related to cardiac rhythm and nominated a potential enhancer-target pair that was dysregulated by a specific SNP. Collectively, our results established a CCS-regulatory compendium, identified novel CCS enhancer elements, and illuminated potential functional associations between human genomic variants and CCS component-specific CREs.

A single factor elicits multilineage reprogramming of astrocytes in the adult mouse striatum.

SignificanceOutside the neurogenic niches, the adult brain lacks multipotent progenitor cells. In this study, we performed a series of in vivo screens and reveal that a single factor can induce resident brain astrocytes to become induced neural progenitor cells (iNPCs), which then generate neurons, astrocytes, and oligodendrocytes. Such a conclusion is supported by single-cell RNA sequencing and multiple lineage-tracing experiments. Our discovery of iNPCs is fundamentally important for regenerative medicine since neural injuries or degeneration often lead to loss/dysfunction of all three neural lineages. Our findings also provide insights into cell plasticity in the adult mammalian brain, which has largely lost the regenerative capacity.

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.

Single-Cell Genomics: Catalyst for Cell Fate Engineering.

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.

FBA: feature barcoding analysis for single cell RNA-Seq.

MOTIVATION: Single cell RNA-Seq (scRNA-Seq) has broadened our understanding of cellular heterogeneity and provided valuable insights into cellular functions. Recent experimental strategies extend scRNA-Seq readouts to include additional features, including cell surface proteins and genomic perturbations. These 'feature barcoding' strategies rely on converting molecular and cellular features to unique sequence barcodes, which are then detected with the transcriptome. RESULTS: Here, we introduce FBA, a flexible and streamlined package to perform quality control, quantification, demultiplexing, multiplet detection, clustering and visualization of feature barcoding assays. AVAILABILITYAND IMPLEMENTATION: FBA is available on PyPi at https://pypi.org/project/fba and on GitHub at https://github.com/jlduan/fba. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Blastocyst-like structures generated from human pluripotent stem cells.

Limited access to embryos has hampered the study of human embryogenesis and disorders that occur during early pregnancy. Human pluripotent stem cells provide an alternative means to study human development in a dish1-7. Recent advances in partial embryo models derived from human pluripotent stem cells have enabled human development to be examined at early post-implantation stages8-14. However, models of the pre-implantation human blastocyst are lacking. Starting from naive human pluripotent stem cells, here we developed an effective three-dimensional culture strategy with successive lineage differentiation and self-organization to generate blastocyst-like structures in vitro. These structures-which we term 'human blastoids'-resemble human blastocysts in terms of their morphology, size, cell number, and composition and allocation of different cell lineages. Single-cell RNA-sequencing analyses also reveal the transcriptomic similarity of blastoids to blastocysts. Human blastoids are amenable to embryonic and extra-embryonic stem cell derivation and can further develop into peri-implantation embryo-like structures in vitro. Using chemical perturbations, we show that specific isozymes of protein kinase C have a critical function in the formation of the blastoid cavity. Human blastoids provide a readily accessible, scalable, versatile and perturbable alternative to blastocysts for studying early human development, understanding early pregnancy loss and gaining insights into early developmental defects.

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.

Author Correction: Using Gjd3-CreEGFP mice to examine atrioventricular node morphology and composition.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples.

Advances in single-cell RNA sequencing (scRNA-Seq) have allowed for comprehensive analyses of single cell data. However, current analyses of scRNA-Seq data usually start from unsupervised clustering or visualization. These methods ignore prior knowledge of transcriptomes and the probable structures of the data. Moreover, cell identification heavily relies on subjective and possibly inaccurate human inspection afterwards. To address these analytical challenges, we developed SCINA (Semi-supervised Category Identification and Assignment), a semi-supervised model that exploits previously established gene signatures using an expectation-maximization (EM) algorithm. SCINA is applicable to scRNA-Seq and flow cytometry/CyTOF data, as well as other data of similar format. We applied SCINA to a wide range of datasets, and showed its accuracy, stability and efficiency, which exceeded most popular unsupervised approaches. SCINA discovered an intermediate stage of oligodendrocytes from mouse brain scRNA-Seq data. SCINA also detected immune cell population changes in cytometry data in a genetically-engineered mouse model. Furthermore, SCINA performed well with bulk gene expression data. Specifically, we identified a new kidney tumor clade with similarity to FH-deficient tumors (FHD), which we refer to as FHD-like tumors (FHDL). Overall, SCINA provides both methodological advances and biological insights from perspectives different from traditional analytical methods.

Rational Reprogramming of Cellular States by Combinatorial Perturbation.

Ectopic expression of transcription factors (TFs) can reprogram cell state. However, because of the large combinatorial space of possible TF cocktails, it remains difficult to identify TFs that reprogram specific cell types. Here, we develop Reprogram-Seq to experimentally screen thousands of TF cocktails for reprogramming performance. Reprogram-Seq leverages organ-specific cell-atlas data with single-cell perturbation and computational analysis to predict, evaluate, and optimize TF combinations that reprogram a cell type of interest. Focusing on the cardiac system, we perform Reprogram-Seq on MEFs using an undirected library of 48 cardiac factors and, separately, a directed library of 10 epicardial-related TFs. We identify a combination of three TFs, which efficiently reprogram MEFs to epicardial-like cells that are transcriptionally, molecularly, morphologically, and functionally similar to primary epicardial cells. Reprogram-Seq holds promise to accelerate the generation of specific cell types for regenerative medicine.