Multiplexed Engineering and Analysis of Combinatorial Enhancer Activity in Single Cells

Massively parallel techniques for cataloguing the regulome of the human brain

Complex brain disorders are highly heritable and arise from a complex polygenic risk architecture. Many disease-associated loci are found in non-coding regions that house regulatory elements. These elements influence the transcription of target genes-many of which demonstrate cell-type-specific expression patterns-and thereby affect phenotypically relevant molecular pathways. Thus, cell-type-specificity must be considered when prioritizing candidate risk loci, variants and target genes. This Review discusses the use of high-throughput assays in human induced pluripotent stem cell-based neurodevelopmental models to probe genetic risk in a cell-type- and patient-specific manner. The application of massively parallel reporter assays in human induced pluripotent stem cells can characterize the human regulome and test the transcriptional responses of putative regulatory elements. Parallel CRISPR-based screens can further functionally dissect this genetic regulatory architecture. The integration of these emerging technologies could decode genetic risk into medically actionable information, thereby improving genetic diagnosis and identifying novel points of therapeutic intervention.

Critical cancer vulnerabilities identified by unbiased CRISPR/Cas9 screens inform on efficient cancer Immunotherapy

The mutational landscape of human cancers is highly complex. While next generation sequencing aims to comprehensively catalogue somatic alterations in tumor cells, it fails to delineate driver from passenger mutations. Functional genomic approaches, particularly CRISPR/Cas9, enable both gene discovery, and annotation of gene function. Indeed, recent CRISPR/Cas9 technologies have flourished with the development of more sophisticated and versatile platforms capable of gene knockouts to high throughput genome wide editing of a single nucleotide base. With new platforms constantly emerging, it can be challenging to navigate what CRISPR tools are available and how they can be effectively applied to understand cancer biology. This review provides an overview of current and emerging CRISPR technologies and their power to model cancer and identify novel treatments. Specifically, how CRISPR screening approaches have been exploited to enhance immunotherapies through the identification of tumor intrinsic and extrinsic mechanisms to escape immune recognition will be discussed.

A Versatile Nonviral Delivery System for Multiplex Gene-Editing in the Liver

Recent advances in CRISPR present attractive genome-editing toolsets for therapeutic strategies at the genetic level. Here, a liposome-coated mesoporous silica nanoparticle (lipoMSN) is reported as an effective CRISPR delivery system for multiplex gene-editing in the liver. The MSN provides efficient loading of Cas9 plasmid as well as Cas9 protein/guide RNA ribonucleoprotein complex (RNP), while liposome-coating offers improved serum stability and enhanced cell uptake. Hypothesizing that loss-of-function mutation in the lipid-metabolism-related genes pcsk9, apoc3, and angptl3 would improve cardiovascular health by lowering blood cholesterol and triglycerides, the lipoMSN is used to deliver a combination of RNPs targeting these genes. When targeting a single gene, the lipoMSN achieved a 54% gene-editing efficiency, besting the state-of-art Lipofectamine CRISPRMax. For multiplexing, lipoMSN maintained significant gene-editing at each gene target despite reduced dosage of target-specific RNP. By delivering combinations of targeting RNPs in the same nanoparticle, synergistic effects on lipid metabolism are observed in vitro and vivo. These effects, such as a 50% decrease in serum cholesterol after 4 weeks of post-treatment with lipoMSN carrying both pcsk9 and angptl3-targeted RNPs, could not be reached with a single gene-editing approach. Taken together, this lipoMSN represents a versatile platform for the development of efficient, combinatorial gene-editing therapeutics.

Cell-type-specific 3D epigenomes in the developing human cortex

Lineage-specific epigenomic changes during human corticogenesis have remained elusive due to challenges with sample availability and tissue heterogeneity. For example, previous studies used single-cell RNA sequencing to identify at least nine major cell types and up to 26 distinct subtypes in the dorsal cortex alone^1,2. Here, we characterize cell type-specific cis-regulatory chromatin interactions, open chromatin peaks, and transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, and interneurons isolated from mid-gestational human cortex samples. We show that chromatin interactions underlie multiple aspects of gene regulation, with transposable elements and disease-associated variants enriched at distal interacting regions in a cell type-specific manner. In addition, promoters with significantly increased levels of chromatin interactivity, termed super interactive promoters, are enriched for lineage-specific genes, suggesting that interactions at these loci contribute to the fine-tuning of transcription. Finally, we develop CRISPRview, a novel technique integrating immunostaining, CRISPRi, RNAscope, and image analysis for validating cell type-specific cis-regulatory elements in heterogeneous populations of primary cells. Our study presents the first cell type-specific characterization of 3D epigenomes in the developing human cortex, advancing our understanding of gene regulation and lineage specification during this critical developmental window.

Modulating gene regulation to treat genetic disorders

Over a thousand diseases are caused by mutations that alter gene expression levels. The potential of nuclease-deficient zinc fingers, TALEs or CRISPR fusion systems to treat these diseases by modulating gene expression has recently emerged. These systems can be applied to modify the activity of gene-regulatory elements - promoters, enhancers, silencers and insulators, subsequently changing their target gene expression levels to achieve therapeutic benefits - an approach termed cis-regulation therapy (CRT). Here, we review emerging CRT technologies and assess their therapeutic potential for treating a wide range of diseases caused by abnormal gene dosage. The challenges facing the translation of CRT into the clinic are discussed.

High-throughput single-cell functional elucidation of neurodevelopmental disease-associated genes reveals convergent mechanisms altering neuronal differentiation

The overwhelming success of exome- and genome-wide association studies in discovering thousands of disease-associated genes necessitates developing novel high-throughput functional genomics approaches to elucidate the molecular mechanisms of these genes. Here, we have coupled multiplexed repression of neurodevelopmental disease–associated genes to single-cell transcriptional profiling in differentiating human neurons to rapidly assay the functions of multiple genes in a disease-relevant context, assess potentially convergent mechanisms, and prioritize genes for specific functional assays. For a set of 13 autism spectrum disorder (ASD)–associated genes, we show that this approach generated important mechanistic insights, revealing two functionally convergent modules of ASD genes: one that delays neuron differentiation and one that accelerates it. Five genes that delay neuron differentiation (ADNP, ARID1B, ASH1L, CHD2, and DYRK1A) mechanistically converge, as they all dysregulate genes involved in cell-cycle control and progenitor cell proliferation. Live-cell imaging after individual ASD-gene repression validated this functional module, confirming that these genes reduce neural progenitor cell proliferation and neurite growth. Finally, these functionally convergent ASD gene modules predicted shared clinical phenotypes among individuals with mutations in these genes. Altogether, these results show the utility of a novel and simple approach for the rapid functional elucidation of neurodevelopmental disease-associated genes.

Integrative Methods and Practical Challenges for Single-Cell Multi-omics

Fast-developing single-cell multimodal omics (scMulti-omics) technologies enable the measurement of multiple modalities, such as DNA methylation, chromatin accessibility, RNA expression, protein abundance, gene perturbation, and spatial information, from the same cell. scMulti-omics can comprehensively explore and identify cell characteristics, while also presenting challenges to the development of computational methods and tools for integrative analyses. Here, we review these integrative methods and summarize the existing tools for studying a variety of scMulti-omics data. The various functionalities and practical challenges in using the available tools in the public domain are explored through several case studies. Finally, we identify remaining challenges and future trends in scMulti-omics modeling and analyses.

Mapping regulators of cell fate determination: Approaches and challenges

Given the limited regenerative capacities of most organs, strategies are needed to efficiently generate large numbers of parenchymal cells capable of integration into the diseased organ. Although it was initially thought that terminally differentiated cells lacked the ability to transdifferentiate, it has since been shown that cellular reprogramming of stromal cells to parenchymal cells through direct lineage conversion holds great potential for the replacement of post-mitotic parenchymal cells lost to disease. To this end, an assortment of genetic, chemical, and mechanical cues have been identified to reprogram cells to different lineages both in vitro and in vivo. However, some key challenges persist that limit broader applications of reprogramming technologies. These include: (1) low reprogramming efficiencies; (2) incomplete functional maturation of derived cells; and (3) difficulty in determining the typically multi-factor combinatorial recipes required for successful transdifferentiation. To improve efficiency by comprehensively identifying factors that regulate cell fate, large scale genetic and chemical screening methods have thus been utilized. Here, we provide an overview of the underlying concept of cell reprogramming as well as the rationale, considerations, and limitations of high throughput screening methods. We next follow with a summary of unique hits that have been identified by high throughput screens to induce reprogramming to various parenchymal lineages. Finally, we discuss future directions of applying this technology toward human disease biology via disease modeling, drug screening, and regenerative medicine.

Gene regulatory programmes of tissue regeneration

Regeneration is the process by which organisms replace lost or damaged tissue, and regenerative capacity can vary greatly among species, tissues and life stages. Tissue regeneration shares certain hallmarks of embryonic development, in that lineage-specific factors can be repurposed upon injury to initiate morphogenesis; however, many differences exist between regeneration and embryogenesis. Recent studies of regenerating tissues in laboratory model organisms - such as acoel worms, frogs, fish and mice - have revealed that chromatin structure, dedicated enhancers and transcriptional networks are regulated in a context-specific manner to control key gene expression programmes. A deeper mechanistic understanding of the gene regulatory networks of regeneration pathways might ultimately enable their targeted reactivation as a means to treat human injuries and degenerative diseases. In this Review, we consider the regeneration of body parts across a range of tissues and species to explore common themes and potentially exploitable elements.

Self-Reporting Transposons Enable Simultaneous Readout of Gene Expression and Transcription Factor Binding in Single Cells

Cellular heterogeneity confounds in situ assays of transcription factor (TF) binding. Single-cell RNA sequencing (scRNA-seq) deconvolves cell types from gene expression, but no technology links cell identity to TF binding sites (TFBS) in those cell types. We present self-reporting transposons (SRTs) and use them in single-cell calling cards (scCC), a novel assay for simultaneously measuring gene expression and mapping TFBS in single cells. The genomic locations of SRTs are recovered from mRNA, and SRTs deposited by exogenous, TF-transposase fusions can be used to map TFBS. We then present scCC, which map SRTs from scRNA-seq libraries, simultaneously identifying cell types and TFBS in those same cells. We benchmark multiple TFs with this technique. Next, we use scCC to discover BRD4-mediated cell-state transitions in K562 cells. Finally, we map BRD4 binding sites in the mouse cortex at single-cell resolution, establishing a new method for studying TF biology in situ.

CAR T cells targeting BAFF-R can overcome CD19 antigen loss in B cell malignancies

CAR T cells targeting CD19 provide promising options for treatment of B cell malignancies. However, tumor relapse from antigen loss can limit efficacy. We developed humanized, second-generation CAR T cells against another B cell-specific marker, B cell activating factor receptor (BAFF-R), which demonstrated cytotoxicity against human lymphoma and acute lymphoblastic leukemia (ALL) lines. Adoptively transferred BAFF-R-CAR T cells eradicated 10-day preestablished tumor xenografts after a single treatment and retained efficacy against xenografts deficient in CD19 expression, including CD19-negative variants within a background of CD19-positive lymphoma cells. Four relapsed, primary ALLs with CD19 antigen loss obtained after CD19-directed therapy retained BAFF-R expression and activated BAFF-R-CAR, but not CD19-CAR, T cells. BAFF-R-CAR, but not CD19-CAR, T cells also demonstrated antitumor effects against an additional CD19 antigen loss primary patient-derived xenograft (PDX) in vivo. BAFF-R is amenable to CAR T cell therapy, and its targeting may prevent emergence of CD19 antigen loss variants.

Circular RNAs: The Brain Transcriptome Comes Full Circle

Circular RNAs (circRNAs) are a class of RNA molecules with a covalently closed loop structure formed by back-splicing of exon-exon junctions. The detection of circRNAs across many eukaryotic species, often with cell-type- and tissue-type-specific expression, has catalyzed a growing interest in understanding circRNA biogenesis and their potential functions. circRNAs are enriched in the brain, and accumulate upon neuronal differentiation and depolarization, suggesting that these RNAs are an integral component of the brain transcriptome, and may play functional roles. Here, we give an overview of the current understanding of circRNA biogenesis and function, discuss how circRNAs contribute to transcriptome complexity in the brain, and discuss recent data on the functional roles of circRNAs in the brain. We also discuss emerging data on the role of circRNAs in brain disorders and address common challenges of circRNA quantification in postmortem human brain.

Combinatorial single-cell CRISPR screens by direct guide RNA capture and targeted sequencing

Single-cell CRISPR screens enable the exploration of mammalian gene function and genetic regulatory networks. However, use of this technology has been limited by reliance on indirect indexing of single-guide RNAs (sgRNAs). Here we present direct-capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct-capture Perturb-seq enables detection of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries that contain dual-guide expression vectors. We demonstrate the utility of this approach for high-throughput investigations of genetic interactions and, leveraging this ability, dissect epistatic interactions between cholesterol biogenesis and DNA repair. Using direct capture Perturb-seq, we also show that targeting individual genes with multiple sgRNAs per cell improves efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for single-cell screens. Last, we show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments.

Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants

Most neuropsychiatric disease risk variants are in noncoding sequences and lack functional interpretation. Because regulatory sequences often reside in open chromatin, we reasoned that neuropsychiatric disease risk variants may affect chromatin accessibility during neurodevelopment. Using human induced pluripotent stem cell (iPSC)-derived neurons that model developing brains, we identified thousands of genetic variants exhibiting allele-specific open chromatin (ASoC). These neuronal ASoCs were partially driven by altered transcription factor binding, overrepresented in brain gene enhancers and expression quantitative trait loci, and frequently associated with distal genes through chromatin contacts. ASoCs were enriched for genetic variants associated with brain disorders, enabling identification of functional schizophrenia risk variants and their cis-target genes. This study highlights ASoC as a functional mechanism of noncoding neuropsychiatric risk variants, providing a powerful framework for identifying disease causal variants and genes.

Computational Methods for Analysis of Large-Scale CRISPR Screens

Large-scale CRISPR-Cas pooled screens have shown great promise to investigate functional links between genotype and phenotype at the genome-wide scale. In addition to technological advancement, there is a need to develop computational methods to analyze the large datasets obtained from high-throughput CRISPR screens. Many computational methods have been developed to identify reliable gene hits from various screens. In this review, we provide an overview of the technology development of CRISPR screening platforms, with a focus on recent advances in computational methods to identify and model gene effects using CRISPR screen datasets. We also discuss existing challenges and opportunities for future computational methods development.

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.

A Single-Cell Transcriptomics CRISPR-Activation Screen Identifies Epigenetic Regulators of the Zygotic Genome Activation Program

Zygotic genome activation (ZGA) is an essential transcriptional event in embryonic development that coincides with extensive epigenetic reprogramming. Complex manipulation techniques and maternal stores of proteins preclude large-scale functional screens for ZGA regulators within early embryos. Here, we combined pooled CRISPR activation (CRISPRa) with single-cell transcriptomics to identify regulators of ZGA-like transcription in mouse embryonic stem cells, which serve as a tractable, in vitro proxy of early mouse embryos. Using multi-omics factor analysis (MOFA+) applied to ∼200,000 single-cell transcriptomes comprising 230 CRISPRa perturbations, we characterized molecular signatures of ZGA and uncovered 24 factors that promote a ZGA-like response. Follow-up assays validated top screen hits, including the DNA-binding protein Dppa2, the chromatin remodeler Smarca5, and the transcription factor Patz1, and functional experiments revealed that Smarca5’s regulation of ZGA-like transcription is dependent on Dppa2. Together, our single-cell transcriptomic profiling of CRISPRa-perturbed cells provides both system-level and molecular insights into the mechanisms that orchestrate ZGA.

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Large-scale pooled CRISPR-activation screen with single-cell RNA-seq for 230 genes

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MOFA+ identified 24 screen hits that induced a ZGA-like signature

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Nine genes were independently validated as regulators of ZGA-like transcription

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Smarca5 regulates ZGA-like transcription in a Dppa2-dependent manner

Technologies and Computational Analysis Strategies for CRISPR Applications

The CRISPR-Cas system offers a programmable platform for eukaryotic genome and epigenome editing. The ability to perform targeted genetic and epigenetic perturbations enables researchers to perform a variety of tasks, ranging from investigating questions in basic biology to potentially developing novel therapeutics for the treatment of disease. While CRISPR systems have been engineered to target DNA and RNA with increased precision, efficiency, and flexibility, assays to identify off-target editing are becoming more comprehensive and sensitive. Furthermore, techniques to perform high-throughput genome and epigenome editing can be paired with a variety of readouts and are uncovering important cellular functions and mechanisms. These technological advances drive and are driven by accompanying computational approaches. Here, we briefly present available CRISPR technologies and review key computational advances and considerations for various CRISPR applications. In particular, we focus on the analysis of on- and off-target editing and CRISPR pooled screen data.

Evaluating Enhancer Function and Transcription

Cell-type- and condition-specific profiles of gene expression require coordination between protein-coding gene promoters and cis-regulatory sequences called enhancers. Enhancers can stimulate gene activity at great genomic distances from their targets, raising questions about how enhancers communicate with specific gene promoters and what molecular mechanisms underlie enhancer function. Characterization of enhancer loci has identified the molecular features of active enhancers that accompany the binding of transcription factors and local opening of chromatin. These characteristics include coactivator recruitment, histone modifications, and noncoding RNA transcription. However, it remains unclear which of these features functionally contribute to enhancer activity. Here, we discuss what is known about how enhancers regulate their target genes and how enhancers and promoters communicate. Further, we describe recent data demonstrating many similarities between enhancers and the gene promoters they control, and we highlight unanswered questions in the field, such as the potential roles of transcription at enhancers.

CRISPR Tools for Physiology and Cell State Changes: Potential of Transcriptional Engineering and Epigenome Editing

Given the large amount of genome-wide data that have been collected during the last decades, a good understanding of how and why cells change during development, homeostasis, and disease might be expected. Unfortunately, the opposite is true; triggers that cause cellular state changes remain elusive, and the underlying molecular mechanisms are poorly understood. Although genes with the potential to influence cell states are known, the historic dependency on methods that manipulate gene expression outside the endogenous chromatin context has prevented us from understanding how cells organize, interpret, and protect cellular programs. Fortunately, recent methodological innovations are now providing options to answer these outstanding questions, by allowing to target and manipulate individual genomic and epigenomic loci. In particular, three experimental approaches are now feasible due to DNA targeting tools, namely, activation and/or repression of master transcription factors in their endogenous chromatin context; targeting transcription factors to endogenous, alternative, or inaccessible sites; and finally, functional manipulation of the chromatin context. In this article, we discuss the molecular basis of DNA targeting tools and review the potential of these new technologies before we summarize how these have already been used for the manipulation of cellular states and hypothesize about future applications.

Targeted Perturb-seq enables genome-scale genetic screens in single cells

The transcriptome contains rich information on molecular, cellular and organismal phenotypes. However, experimental and statistical limitations constrain sensitivity and throughput of genetic screening with single-cell transcriptomics readout. To overcome these limitations, we introduce targeted Perturb-seq (TAP-seq), a sensitive, inexpensive and platform-independent method focusing single-cell RNA-seq coverage on genes of interest, thereby increasing the sensitivity and scale of genetic screens by orders of magnitude. TAP-seq permits routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. We apply TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5% of the human genome. We thereby show that enhancer-target association is jointly determined by three-dimensional contact frequency and epigenetic states, allowing accurate prediction of enhancer targets throughout the genome. In addition, we demonstrate that TAP-seq can identify cell subtypes with only 100 sequencing reads per cell.

Towards a comprehensive catalogue of validated and target-linked human enhancers

The human gene catalogue is essentially complete, but we lack an equivalently vetted inventory of bona fide human enhancers. Hundreds of thousands of candidate enhancers have been nominated via biochemical annotations; however, only a handful of these have been validated and confidently linked to their target genes. Here we review emerging technologies for discovering, characterizing and validating human enhancers at scale. We furthermore propose a new framework for operationally defining enhancers that accommodates the heterogeneous and complementary results that are emerging from reporter assays, biochemical measurements and CRISPR screens.

Fine-mapping within eQTL credible intervals by expression CROP-seq

The majority of genome-wide association study (GWAS)-identified SNPs are located in noncoding regions of genes and are likely to influence disease risk and phenotypes by affecting gene expression. Since credible intervals responsible for genome-wide associations typically consist of ≥100 variants with similar statistical support, experimental methods are needed to fine map causal variants. We report here a moderate-throughput approach to identifying regulatory GWAS variants, expression CROP-seq, which consists of multiplex CRISPR-Cas9 genome editing combined with single-cell RNAseq to measure perturbation in transcript abundance. Mutations were induced in the HL60/S4 myeloid cell line nearby 57 SNPs in three genes, two of which, rs2251039 and rs35675666, significantly altered CISD1 and PARK7 expression, respectively, with strong replication and validation in single-cell clones. The sites overlap with chromatin accessibility peaks and define causal variants for inflammatory bowel disease at the two loci. This relatively inexpensive approach should be scalable for broad surveys and is also implementable for the fine mapping of individual genes.

Functional genomic approaches to elucidate the role of enhancers during development

Successful development depends on the precise tissue-specific regulation of genes by enhancers, genetic elements that act as switches to control when and where genes are expressed. Because enhancers are critical for development, and the majority of disease-associated mutations reside within enhancers, it is essential to understand which sequences within enhancers are important for function. Advances in sequencing technology have enabled the rapid generation of genomic data that predict putative active enhancers, but functionally validating these sequences at scale remains a fundamental challenge. Herein, we discuss the power of genome-wide strategies used to identify candidate enhancers, and also highlight limitations and misconceptions that have arisen from these data. We discuss the use of massively parallel reporter assays to test enhancers for function at scale. We also review recent advances in our ability to study gene regulation during development, including CRISPR-based tools to manipulate genomes and single-cell transcriptomics to finely map gene expression. Finally, we look ahead to a synthesis of complementary genomic approaches that will advance our understanding of enhancer function during development. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Developmental Biology > Developmental Processes in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods.

Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction

Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.

Proteomic Profiling of the ECM of Xenograft Breast Cancer Metastases in Different Organs Reveals Distinct Metastatic Niches

Metastasis causes most cancer-related deaths, and one poorly understood aspect of metastatic cancer is the adaptability of cells from a primary tumor to create new niches and survive in multiple, different secondary sites. We used quantitative mass spectrometry to analyze the extracellular matrix (ECM), a critical component of metastatic niches, in metastases to the brain, lungs, liver, and bone marrow, all derived from parental MDA-MB-231 triple-negative breast cancer cells. Tumor and stromal cells cooperated in forming niches; stromal cells produced predominantly core, structural ECM proteins and tumor cells produced a diverse array of ECM-associated proteins, including secreted factors and modulators of the matrix. In addition, tumor and stromal cells together created distinct niches in each tissue. Downregulation of SERPINB1, a protein elevated in brain metastases, led to a reduction in brain metastasis, suggesting that some niche-specific ECM proteins may be involved in metastatic tropism. SIGNIFICANCE: Tumor and stromal cells together create distinct ECM niches in breast cancer metastases to various tissues, providing new insight into how tumor cells adapt to survive in different tissue environments.

scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens

We present scMAGeCK, a computational framework to identify genomic elements associated with multiple expression-based phenotypes in CRISPR/Cas9 functional screening that uses single-cell RNA-seq as readout. scMAGeCK outperforms existing methods, identifies genes and enhancers with known and novel functions in cell proliferation, and enables an unbiased construction of genotype-phenotype network. Single-cell CRISPR screening on mouse embryonic stem cells identifies key genes associated with different pluripotency states. Applying scMAGeCK on multiple datasets, we identify key factors that improve the power of single-cell CRISPR screening. Collectively, scMAGeCK is a novel tool to study genotype-phenotype relationships at a single-cell level.

Identification and transfer of spatial transcriptomics signatures for cancer diagnosis

BACKGROUND

Distinguishing ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC) regions in clinical biopsies constitutes a diagnostic challenge. Spatial transcriptomics (ST) is an in situ capturing method, which allows quantification and visualization of transcriptomes in individual tissue sections. In the past, studies have shown that breast cancer samples can be used to study their transcriptomes with spatial resolution in individual tissue sections. Previously, supervised machine learning methods were used in clinical studies to predict the clinical outcomes for cancer types.

METHODS

We used four publicly available ST breast cancer datasets from breast tissue sections annotated by pathologists as non-malignant, DCIS, or IDC. We trained and tested a machine learning method (support vector machine) based on the expert annotation as well as based on automatic selection of cell types by their transcriptome profiles.

RESULTS

We identified expression signatures for expert annotated regions (non-malignant, DCIS, and IDC) and build machine learning models. Classification results for 798 expression signature transcripts showed high coincidence with the expert pathologist annotation for DCIS (100%) and IDC (96%). Extending our analysis to include all 25,179 expressed transcripts resulted in an accuracy of 99% for DCIS and 98% for IDC. Further, classification based on an automatically identified expression signature covering all ST spots of tissue sections resulted in prediction accuracy of 95% for DCIS and 91% for IDC.

CONCLUSIONS

This concept study suggest that the ST signatures learned from expert selected breast cancer tissue sections can be used to identify breast cancer regions in whole tissue sections including regions not trained on. Furthermore, the identified expression signatures can classify cancer regions in tissue sections not used for training with high accuracy. Expert-generated but even automatically generated cancer signatures from ST data might be able to classify breast cancer regions and provide clinical decision support for pathologists in the future.

Decoding pluripotency: Genetic screens to interrogate the acquisition, maintenance, and exit of pluripotency

Pluripotent stem cells have the ability to unlimitedly self-renew and differentiate to any somatic cell lineage. A number of systems biology approaches have been used to define this pluripotent state. Complementary to systems level characterization, genetic screens offer a unique avenue to functionally interrogate the pluripotent state and identify the key players in pluripotency acquisition and maintenance, exit of pluripotency, and lineage differentiation. Here we review how genetic screens have helped us decode pluripotency regulation. We will summarize results from RNA interference (RNAi) based screens, discuss recent advances in CRISPR/Cas-based genetic perturbation methods, and how these advances have made it possible to more comprehensively interrogate pluripotency and differentiation through genetic screens. Such investigations will not only provide a better understanding of this unique developmental state, but may enhance our ability to use pluripotent stem cells as an experimental model to study human development and disease progression. Functional interrogation of pluripotency also provides a valuable roadmap for utilizing genetic perturbation to gain systems level understanding of additional cellular states, from later stages of development to pathological disease states. This article is categorized under: Developmental Biology > Stem Cell Biology and Regeneration Developmental Biology > Developmental Processes in Health and Disease Biological Mechanisms > Cell Fates.

Advancing CRISPR-Based Programmable Platforms beyond Genome Editing in Mammalian Cells

Human diseases are caused by dysregulation of cellular biological programs that are encoded in DNA. Unveiling the endogenous programs and encoding new programs into the genome are key to creating novel diagnostic and therapeutic strategies. CRISPR/Cas9, originally identified in bacteria, has revolutionized genome editing in mammalian cells. Recent advances in CRISPR technologies have provided new programmable platforms for modifying cell function and behavior. CRISPR-based transcriptional regulators and modified gRNAs have enabled multiplexed regulation and visualization of genome dynamics with spatiotemporal precision. Using these toolkits, genome-scale screening platforms can identify key genetic elements or combinations thereof that modulate phenotypes in mammalian cells. In addition, imaging platforms for multiplexed genomic labeling have been created to study the conformation and dynamics of chromatin in living cells, which are essential for genome function. Furthermore, CRISPR-based computation and memory platforms have been built in living mammalian cells by using DNA as a data processing and storage medium to regulate and monitor cellular behaviors. The conditional regulation of CRISPR-based parts has enabled the design of complex multilayered biological programs. CRISPR-based memory platforms can continuously record biological events as mutations in defined DNA loci. By making use of base editors, CRISPR-based computation and memory platforms have been interconnected to perform logic operations based on past events. These technologies open up new avenues for understanding biological phenomena and designing mammalian cells as living machines for biomedical applications.

Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations

Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer-gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

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 β-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.

Xie et al. apply improved strategies for single-cell screens to identify an enhancer-driven transcriptional regulatory network in K562 cells. They demonstrate that the same group of genes can be indirectly regulated by enhancers from distinct genomic loci. These data have implications for the understanding of enhancer-associated traits.

Neurobiological functions of transcriptional enhancers

Transcriptional enhancers are regulatory DNA elements that underlie the specificity and dynamic patterns of gene expression. Over the past decade, large-scale functional genomics projects have driven transformative progress in our understanding of enhancers. These data have relevance for identifying mechanisms of gene regulation in the CNS, elucidating the function of non-coding regulatory sequences in neurobiology and linking sequence variation within enhancers to genetic risk for neurological and psychiatric disorders. However, the sheer volume and complexity of genomic data presents a challenge to interpreting enhancer function in normal and pathogenic neurobiological processes. Here, to advance the application of genome-scale enhancer data, we offer a primer on current models of enhancer function in the CNS, we review how enhancers regulate gene expression across the neuronal lifespan, and we suggest how emerging findings regarding the role of non-coding sequence variation offer opportunities for understanding brain disorders and developing new technologies for neuroscience.

Genetic association of molecular traits: A help to identify causative variants in complex diseases

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

Transcriptionally active HERV-H retrotransposons demarcate topologically associating domains in human pluripotent stem cells

Chromatin architecture has been implicated in cell type-specific gene regulatory programs, yet how chromatin remodels during development remains to be fully elucidated. Here, by interrogating chromatin reorganization during human pluripotent stem cell (hPSC) differentiation, we discover a role for the primate-specific endogenous retrotransposon human endogenous retrovirus subfamily H (HERV-H) in creating topologically associating domains (TADs) in hPSCs. Deleting these HERV-H elements eliminates their corresponding TAD boundaries and reduces the transcription of upstream genes, while de novo insertion of HERV-H elements can introduce new TAD boundaries. The ability of HERV-H to create TAD boundaries depends on high transcription, as transcriptional repression of HERV-H elements prevents the formation of boundaries. This ability is not limited to hPSCs, as these actively transcribed HERV-H elements and their corresponding TAD boundaries also appear in pluripotent stem cells from other hominids but not in more distantly related species lacking HERV-H elements. Overall, our results provide direct evidence for retrotransposons in actively shaping cell type- and species-specific chromatin architecture.

A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition

Integrating single-cell trajectory analysis with pooled genetic screening could reveal the genetic architecture that guides cellular decisions in development and disease. We applied this paradigm to probe the genetic circuitry that controls epithelial-to-mesenchymal transition (EMT). We used single-cell RNA sequencing to profile epithelial cells undergoing a spontaneous spatially determined EMT in the presence or absence of transforming growth factor-β. Pseudospatial trajectory analysis identified continuous waves of gene regulation as opposed to discrete 'partial' stages of EMT. KRAS was connected to the exit from the epithelial state and the acquisition of a fully mesenchymal phenotype. A pooled single-cell CRISPR-Cas9 screen identified EMT-associated receptors and transcription factors, including regulators of KRAS, whose loss impeded progress along the EMT. Inhibiting the KRAS effector MEK and its upstream activators EGFR and MET demonstrates that interruption of key signaling events reveals regulatory 'checkpoints' in the EMT continuum that mimic discrete stages, and reconciles opposing views of the program that controls EMT.

Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future

Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.

The next generation of CRISPR-Cas technologies and applications

The prokaryote-derived CRISPR-Cas genome editing systems have transformed our ability to manipulate, detect, image and annotate specific DNA and RNA sequences in living cells of diverse species. The ease of use and robustness of this technology have revolutionized genome editing for research ranging from fundamental science to translational medicine. Initial successes have inspired efforts to discover new systems for targeting and manipulating nucleic acids, including those from Cas9, Cas12, Cascade and Cas13 orthologues. Genome editing by CRISPR-Cas can utilize non-homologous end joining and homology-directed repair for DNA repair, as well as single-base editing enzymes. In addition to targeting DNA, CRISPR-Cas-based RNA-targeting tools are being developed for research, medicine and diagnostics. Nuclease-inactive and RNA-targeting Cas proteins have been fused to a plethora of effector proteins to regulate gene expression, epigenetic modifications and chromatin interactions. Collectively, the new advances are considerably improving our understanding of biological processes and are propelling CRISPR-Cas-based tools towards clinical use in gene and cell therapies.

Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development

The development of the human cerebral cortex is a complex and dynamic process, in which neural stem cell proliferation, neuronal migration, and post-migratory neuronal organization need to occur in a well-organized fashion. Alterations at any of these crucial stages can result in malformations of cortical development (MCDs), a group of genetically heterogeneous neurodevelopmental disorders that present with developmental delay, intellectual disability and epilepsy. Recent progress in genetic technologies, such as next generation sequencing, most often focusing on all protein-coding exons (e.g., whole exome sequencing), allowed the discovery of more than a 100 genes associated with various types of MCDs. Although this has considerably increased the diagnostic yield, most MCD cases remain unexplained. As Whole Exome Sequencing investigates only a minor part of the human genome (1-2%), it is likely that patients, in which no disease-causing mutation has been identified, could harbor mutations in genomic regions beyond the exome. Even though functional annotation of non-coding regions is still lagging behind that of protein-coding genes, tremendous progress has been made in the field of gene regulation. One group of non-coding regulatory regions are enhancers, which can be distantly located upstream or downstream of genes and which can mediate temporal and tissue-specific transcriptional control via long-distance interactions with promoter regions. Although some examples exist in literature that link alterations of enhancers to genetic disorders, a widespread appreciation of the putative roles of these sequences in MCDs is still lacking. Here, we summarize the current state of knowledge on cis-regulatory regions and discuss novel technologies such as massively-parallel reporter assay systems, CRISPR-Cas9-based screens and computational approaches that help to further elucidate the emerging role of the non-coding genome in disease. Moreover, we discuss existing literature on mutations or copy number alterations of regulatory regions involved in brain development. We foresee that the future implementation of the knowledge obtained through ongoing gene regulation studies will benefit patients and will provide an explanation to part of the missing heritability of MCDs and other genetic disorders.

Widespread epigenetic changes to the enhancer landscape of mouse liver induced by a specific xenobiotic agonist ligand of the nuclear receptor CAR

CAR (Nr1i3), a liver nuclear receptor and xenobiotic sensor, induces drug, steroid and lipid metabolism and dysregulates genes linked to hepatocellular carcinogenesis, but its impact on the liver epigenome is poorly understood. TCPOBOP, a halogenated xenochemical and highly specific CAR agonist ligand, induces localized chromatin opening or closing at several thousand mouse liver genomic regions, discovered as differential DNase-hypersensitive sites (ΔDHS). Active enhancer and promoter histone marks induced by TCPOBOP were enriched at opening DHS and TCPOBOP-inducible genes. Enrichment of CAR binding and CAR motifs was seen at opening DHS and their inducible drug/lipid metabolism gene targets, and at many constitutively open DHS located nearby. TCPOBOP-responsive cell cycle and DNA replication genes co-dependent on MET/EGFR signaling for induction were also enriched for CAR binding. A subset of opening DHS and many closing DHS mapping to TCPOBOP-responsive target genes did not bind CAR, indicating an indirect mechanism for their changes in chromatin accessibility. TCPOBOP-responsive DHS were also enriched for induced binding of RXRA, CEBPA and CEBPB, and for motifs for liver-enriched factors that may contribute to liver-specific transcriptional responses to TCPOBOP exposure. These studies elucidate the enhancer landscape of TCPOBOP-exposed liver and the widespread epigenetic changes that are induced by both direct and indirect mechanisms linked to CAR activation. The global maps of thousands of environmental chemical-induced epigenetic changes described here constitute a rich resource for further research on xenochemical effects on liver chromatin states and the epigenome.

Reversible Disruption of Specific Transcription Factor-DNA Interactions Using CRISPR/Cas9

The control of gene expression by transcription factor binding sites frequently determines phenotype. However, it is difficult to determine the function of single transcription factor binding sites within larger transcription networks. Here, we use deactivated Cas9 (dCas9) to disrupt binding to specific sites, a method we term CRISPRd. Since CRISPR guide RNAs are longer than transcription factor binding sites, flanking sequence can be used to target specific sites. Targeting dCas9 to an Oct4 site in the Nanog promoter displaced Oct4 from this site, reduced Nanog expression, and slowed division. In contrast, disrupting the Oct4 binding site adjacent to Pax6 upregulated Pax6 transcription and disrupting Nanog binding its own promoter upregulated its transcription. Thus, we can easily distinguish between activating and repressing binding sites and examine autoregulation. Finally, multiple guide RNA expression allows simultaneous inhibition of multiple binding sites, and conditionally destabilized dCas9 allows rapid reversibility.

Genomic annotation of disease-associated variants reveals shared functional contexts

Variation in non-coding DNA, encompassing gene regulatory regions such as enhancers and promoters, contributes to risk for complex disorders, including type 2 diabetes. While genome-wide association studies have successfully identified hundreds of type 2 diabetes loci throughout the genome, the vast majority of these reside in non-coding DNA, which complicates the process of determining their functional significance and level of priority for further study. Here we review the methods used to experimentally annotate these non-coding variants, to nominate causal variants and to link them to diabetes pathophysiology. In recent years, chromatin profiling, massively parallel sequencing, high-throughput reporter assays and CRISPR gene editing technologies have rapidly become indispensable tools. Rather than treating individual variants in isolation, we discuss the importance of accounting for context, both genetic (such as flanking DNA sequence) and environmental (such as cellular state or environmental exposure). Incorporating these features shows promise in terms of revealing biologically convergent molecular signatures across distant and seemingly unrelated loci. Studying regulatory elements in the proper context will be crucial for interpreting the functional significance of disease-associated variants and applying the resulting knowledge to improve patient care.

Single-Cell RNA-Sequencing-Based CRISPRi Screening Resolves Molecular Drivers of Early Human Endoderm Development

Studies in vertebrates have outlined conserved molecular control of definitive endoderm (END) development. However, recent work also shows that key molecular aspects of human END regulation differ even from rodents. Differentiation of human embryonic stem cells (ESCs) to END offers a tractable system to study the molecular basis of normal and defective human-specific END development. Here, we interrogated dynamics in chromatin accessibility during differentiation of ESCs to END, predicting DNA-binding proteins that may drive this cell fate transition. We then combined single-cell RNA-seq with parallel CRISPR perturbations to comprehensively define the loss-of-function phenotype of those factors in END development. Following a few candidates, we revealed distinct impairments in the differentiation trajectories for mediators of TGFβ signaling and expose a role for the FOXA2 transcription factor in priming human END competence for human foregut and hepatic END specification. Together, this single-cell functional genomics study provides high-resolution insight on human END development.

New insights into hematopoietic differentiation landscapes from single-cell RNA sequencing

Single-cell transcriptomics has recently emerged as a powerful tool to analyze cellular heterogeneity, discover new cell types, and infer putative differentiation routes. The technique has been rapidly embraced by the hematopoiesis research community, and like other technologies before, single-cell molecular profiling is widely expected to make important contributions to our understanding of the hematopoietic hierarchy. Much of this new interpretation relies on inference of the transcriptomic landscape as a representation of existing cellular states and associated transitions among them. Here we review how this model allows, under certain assumptions, charting of time-resolved differentiation trajectories with unparalleled resolution and how the landscape of multipotent cells may be rather devoid of discrete structures, challenging our preconceptions about stem and progenitor cell types and their organization. Finally, we highlight how promising technological advances may convert static differentiation landscapes into a dynamic cell flux model and thus provide a more holistic understanding of normal hematopoiesis and blood disorders.

Shaping the nebulous enhancer in the era of high-throughput assays and genome editing

Since the 1st discovery of transcriptional enhancers in 1981, their textbook definition has remained largely unchanged in the past 37 years. With the emergence of high-throughput assays and genome editing, which are switching the paradigm from bottom-up discovery and testing of individual enhancers to top-down profiling of enhancer activities genome-wide, it has become increasingly evidenced that this classical definition has left substantial gray areas in different aspects. Here we survey a representative set of recent research articles and report the definitions of enhancers they have adopted. The results reveal that a wide spectrum of definitions is used usually without the definition stated explicitly, which could lead to difficulties in data interpretation and downstream analyses. Based on these findings, we discuss the practical implications and suggestions for future studies.

Experimental and Computational Approaches for Single-Cell Enhancer Perturbation Assay

Transcriptional enhancers drive cell-type-specific gene expression patterns, and thus play key roles in development and disease. Large-scale consortia have extensively cataloged >one million putative enhancers encoded in the human genome. But few enhancers have been endogenously tested for function. For almost all enhancers, it remains unknown what genes they target and how much they contribute to target gene expression. We have previously developed a method called Mosaic-seq, which enables the high-throughput interrogation of enhancer activity by performing pooled CRISPRi-based epigenetic suppression of enhancers with a single-cell transcriptomic readout. Here, we describe an optimized version of this method, Mosaic-seq2. We have made several key improvements that have significantly simplified the library preparation process and increased the overall sensitivity and throughput of the method.