Showing papers by "Cole Trapnell published in 2018"

Joint profiling of chromatin accessibility and gene expression in thousands of single cells

Abstract: Although we can increasingly measure transcription, chromatin, methylation, and other aspects of molecular biology at single-cell resolution, most assays survey only one aspect of cellular biology. Here we describe sci-CAR, a combinatorial indexing–based coassay that jointly profiles chromatin accessibility and mRNA (CAR) in each of thousands of single cells. As a proof of concept, we apply sci-CAR to 4825 cells, including a time series of dexamethasone treatment, as well as to 11,296 cells from the adult mouse kidney. With the resulting data, we compare the pseudotemporal dynamics of chromatin accessibility and gene expression, reconstruct the chromatin accessibility profiles of cell types defined by RNA profiles, and link cis-regulatory sites to their target genes on the basis of the covariance of chromatin accessibility and transcription across large numbers of single cells.

The cis-regulatory dynamics of embryonic development at single-cell resolution

Abstract: An improved assay for chromatin accessibility at single-cell resolution in Drosophila melanogaster embryos enables identification of developmental-stage- and cell-lineage-specific patterns of chromatin-level transcriptional regulation. Active gene regulatory elements shape the output of gene transcription and can be mapped across the genome by measuring chromatin accessibility. Eileen Furlong and colleagues apply a technique called ATAC sequencing to profile chromatin accessibility at a single-cell resolution during three stages of Drosophila embryogenesis. They map tissue-specific regulatory elements and show that the chromatin accessibility landscape is sufficient to infer individual cell types and developmental trajectories. A group of cells is found to use regulatory elements of both mesoderm and endoderm, which suggests the existence of a mesendoderm lineage in Drosophila. Understanding how gene regulatory networks control the progressive restriction of cell fates is a long-standing challenge. Recent advances in measuring gene expression in single cells are providing new insights into lineage commitment. However, the regulatory events underlying these changes remain unclear. Here we investigate the dynamics of chromatin regulatory landscapes during embryogenesis at single-cell resolution. Using single-cell combinatorial indexing assay for transposase accessible chromatin with sequencing (sci-ATAC-seq)1, we profiled chromatin accessibility in over 20,000 single nuclei from fixed Drosophila melanogaster embryos spanning three landmark embryonic stages: 2–4 h after egg laying (predominantly stage 5 blastoderm nuclei), when each embryo comprises around 6,000 multipotent cells; 6–8 h after egg laying (predominantly stage 10–11), to capture a midpoint in embryonic development when major lineages in the mesoderm and ectoderm are specified; and 10–12 h after egg laying (predominantly stage 13), when each of the embryo’s more than 20,000 cells are undergoing terminal differentiation. Our results show that there is spatial heterogeneity in the accessibility of the regulatory genome before gastrulation, a feature that aligns with future cell fate, and that nuclei can be temporally ordered along developmental trajectories. During mid-embryogenesis, tissue granularity emerges such that individual cell types can be inferred by their chromatin accessibility while maintaining a signature of their germ layer of origin. Analysis of the data reveals overlapping usage of regulatory elements between cells of the endoderm and non-myogenic mesoderm, suggesting a common developmental program that is reminiscent of the mesendoderm lineage in other species2,3,4. We identify 30,075 distal regulatory elements that exhibit tissue-specific accessibility. We validated the germ-layer specificity of a subset of these predicted enhancers in transgenic embryos, achieving an accuracy of 90%. Overall, our results demonstrate the power of shotgun single-cell profiling of embryos to resolve dynamic changes in the chromatin landscape during development, and to uncover the cis-regulatory programs of metazoan germ layers and cell types.

Highly scalable generation of DNA methylation profiles in single cells.

Abstract: We present a highly scalable assay for whole-genome methylation profiling of single cells. We use our approach, single-cell combinatorial indexing for methylation analysis (sci-MET), to produce 3,282 single-cell bisulfite sequencing libraries and achieve read alignment rates of 68 ± 8%. We apply sci-MET to discriminate the cellular identity of a mixture of three human cell lines and to identify excitatory and inhibitory neuronal populations from mouse cortical tissue.

Extreme heterogeneity of influenza virus infection in single cells

Abstract: When viruses infect cells, they take over the cell’s machinery and use it to express their own genes. This process has mostly been studied by looking at the average outcome of infection when many viruses infect many cells. However, it is less clear what happens in individual cells. For example, does the virus take over every cell to make lots of viral gene products, or do some cells produce far more viral gene products than others? Russell et al. have now used a new technique called single-cell RNA sequencing to look at how well influenza virus genes were expressed in hundreds of individual mammalian cells. The goal was to work out how the outcome of infection varied between different cells. One way to quantify variability – also known as heterogeneity – is by using a statistical measure called the Gini coefficient. This statistic is often used to assess the inequality in incomes across a nation.In the hypothetical situation where everyone earned the same income, the Gini coefficient would equal zero; while if only one person had all the income and all others had none, the value would be very close to one. In reality, countries fall somewhere in between these two extremes. In the United States for instance, the Gini coefficient for income is 0.47. When Russell et al. worked out the Gini coefficient for the amount of viral genes expressed in different cells, the value was at least 0.64. This indicates that there is more unevenness in viral gene expression for influenza than there is income inequality in the United States. So, what characterizes the “Bill Gates” cells and viruses that have the highest viral gene expression? Influenza viruses sometimes fail to express some of their genes. Russell et al. found that this failure often led to “poor” viruses that were less productive than “rich” viruses that expressed all the critical genes. However, the results suggest that there are also other factors that contribute a lot to the heterogeneity. Real influenza virus infections are usually started by very few viruses, so this new understanding of the variability that occurs when individual viruses infect individual cells might prove important for understanding the properties of infections at larger scales too.

On the design of CRISPR-based single-cell molecular screens.

Abstract: Several groups recently coupled CRISPR perturbations and single-cell RNA-seq for pooled genetic screens. We demonstrate that vector designs of these studies are susceptible to ∼50% swapping of guide RNA-barcode associations because of lentiviral template switching. We optimized a published alternative, CROP-seq, in which the guide RNA also serves as the barcode, and here confirm that this strategy performs robustly and doubled the rate at which guides are assigned to cells to 94%.

Aligning Single-Cell Developmental and Reprogramming Trajectories Identifies Molecular Determinants of Myogenic Reprogramming Outcome

Abstract: Summary Cellular reprogramming through manipulation of defined factors holds great promise for large-scale production of cell types needed for use in therapy and for revealing principles of gene regulation. However, most reprogramming systems are inefficient, converting only a fraction of cells to the desired state. Here, we analyze MYOD-mediated reprogramming of human fibroblasts to myotubes, a well-characterized model system for direct conversion by defined factors, at pseudotemporal resolution using single-cell RNA-seq. To expose barriers to efficient conversion, we introduce a novel analytic technique, trajectory alignment, which enables quantitative comparison of gene expression kinetics across two biological processes. Reprogrammed cells navigate a trajectory with branch points that correspond to two alternative decision points, with cells that select incorrect branches terminating at aberrant or incomplete reprogramming outcomes. Analysis of these branch points revealed insulin and BMP signaling as crucial molecular determinants of reprogramming. Single-cell trajectory alignment enables rigorous quantitative comparisons between biological trajectories found in diverse processes in development, reprogramming, and other contexts.

iPSC-Derived Macrophages Effectively Treat Pulmonary Alveolar Proteinosis in Csf2rb-Deficient Mice.

Abstract: Summary Induced pluripotent stem cell (iPSC)-derived hematopoietic cells represent a highly attractive source for cell and gene therapy. Given the longevity, plasticity, and self-renewal potential of distinct macrophage subpopulations, iPSC-derived macrophages (iPSC-Mφ) appear of particular interest in this context. We here evaluated the airway residence, plasticity, and therapeutic efficacy of iPSC-Mφ in a murine model of hereditary pulmonary alveolar proteinosis (herPAP). We demonstrate that single pulmonary macrophage transplantation (PMT) of 2.5–4 × 106 iPSC-Mφ yields efficient airway residence with conversion of iPSC-Mφ to an alveolar macrophage (AMφ) phenotype characterized by a distinct surface marker and gene expression profile within 2 months. Moreover, PMT significantly improves alveolar protein deposition and other critical herPAP disease parameters. Thus, our data indicate iPSC-Mφ as a source of functional macrophages displaying substantial plasticity and therapeutic potential that upon pulmonary transplantation will integrate into the lung microenvironment, adopt an AMφ phenotype and gene expression pattern, and profoundly ameliorate pulmonary disease phenotypes.

Towards inferring causal gene regulatory networks from single cell expression Measurements

Abstract: Single-cell transcriptome sequencing now routinely samples thousands of cells, potentially providing enough data to reconstruct causal gene regulatory networks from observational data. Here, we present Scribe, a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe employs Restricted Directed Information to determine causality by estimating the strength of information transferred from a potential regulator to its downstream target. We apply Scribe and other leading approaches for causal network reconstruction to several types of single-cell measurements and show that there is a dramatic drop in performance for "pseudotime" ordered single-cell data compared to true time series data. We demonstrate that performing causal inference requires temporal coupling between measurements. We show that methods such as "RNA velocity" restore some degree of coupling through an analysis of chromaffin cell fate commitment. These analyses therefore highlight an important shortcoming in experimental and computational methods for analyzing gene regulation at single-cell resolution and point the way towards overcoming it.

On the design of CRISPR-based single cell molecular screens

Abstract: Several groups recently reported coupling CRISPR/Cas9 perturbations and single cell RNA-seq as a potentially powerful approach for forward genetics. Here we demonstrate that vector designs for such screens that rely on cis linkage of guides and distally located barcodes suffer from swapping of intended guide-barcode associations at rates approaching 50% due to template switching during lentivirus production, greatly reducing sensitivity. We optimize a published strategy, CROP-seq, that instead uses a Pol II transcribed copy of the sgRNA sequence itself, doubling the rate at which guides are assigned to cells to 94%. We confirm this strategy performs robustly and further explore experimental best practices for CRISPR/Cas9-based single cell molecular screens.

Activated CARD11 accelerates germinal center kinetics, promoting mTORC1 and terminal differentiation.

Abstract: Activating mutations in the adapter protein CARD11 associated with diffuse large B cell lymphomas (DLBCLs) are predicted to arise during germinal center (GC) responses, leading to inappropriate activation of NF-κB signaling. Here, we modeled the B cell-intrinsic impact of the L251P activating mutation in CARD11 (aCARD11) on the GC response. Global B cell aCARD11 expression led to a modest increase in splenic B cells and a severe reduction in B1 B cell numbers, respectively. Following T cell-dependent immunization, aCARD11 cells exhibited increased rates of GC formation, resolution, and differentiation. Restriction of aCARD11 to GC B cells similarly altered the GC response and B cell differentiation. In this model, aCARD11 promoted dark zone skewing along with increased cycling, AID levels, and class switch recombination. Furthermore, aCard11 GC B cells displayed increased biomass and mTORC1 signaling, suggesting a novel strategy for targeting aCARD11-driven DLBCL. While aCARD11 potently impacts GC responses, the rapid GC contraction suggests it requires collaboration with events that limit terminal differentiation to promote lymphoma.

crisprQTL mapping as a genome-wide association framework for cellular genetic screens

Abstract: Expression quantitative trait locus (eQTL) and genome-wide association studies (GWAS) are powerful paradigms for mapping the determinants of gene expression and organismal phenotypes, respectively. However, eQTL mapping and GWAS are limited in scope (to naturally occurring, common genetic variants) and resolution (by linkage disequilibrium). Here, we present crisprQTL mapping, a framework in which large numbers of CRISPR/Cas9 perturbations are introduced to each cell on an isogenic background, followed by single-cell RNA-seq (scRNA-seq). crisprQTL mapping is analogous to conventional human eQTL studies, but with individual humans replaced by individual cells; genetic variants replaced by unique combinations of unlinked guide RNA (gRNA)-programmed perturbations per cell; and tissue-level RNA-seq of many individuals replaced by scRNA-seq of many cells. By randomly introducing gRNAs, a single population of cells can be leveraged to test for association between each perturbation and the expression of any potential target gene, analogous to how eQTL studies leverage populations of humans to test millions of genetic variants for associations with expression in a genome-wide manner. However, crisprQTL mapping is neither limited to naturally occurring, common genetic variants nor by linkage disequilibrium. As a proof-of-concept, we applied crisprQTL mapping to evaluate 1,119 candidate enhancers with no strong a priori hypothesis as to their target gene(s). Perturbations were made by a nuclease-dead Cas9 tethered to KRAB, and introduced at a mean "allele frequency" of 1.1% into a population of 47,650 profiled human K562 cells (median of 15 gRNAs identified per cell). We tested for differential expression of all genes within 1 megabase of each candidate enhancer, effectively evaluating 17,584 potential enhancer-target gene relationships within a single experiment. At an empirical false discovery rate of 10%, we identify 128 cis crisprQTLs (11%) whose targeting resulted in downregulation of 105 nearby genes. crisprQTLs were strongly enriched for proximity to their target genes (median 34.3 kilobases) and the strength of H3K27ac, p300, and lineage-specific transcription factor ChIP-seq peaks. Our results establish the power of the eQTL mapping paradigm as applied to programmed variation in populations of cells, rather than natural variation in populations of individuals. We anticipate that crisprQTL mapping will facilitate the comprehensive elucidation of the cis-regulatory architecture of the human genome.

Developmental and conditional dynamics of gene expression in single root cells of A. thaliana

Abstract: Single-cell RNA-seq can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach to A. thaliana root cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single-cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single-cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

CRISPR-Cas9 Screens Reveal Genes Regulating a G0-Like State in Human Neural Progenitors

Abstract: The coordination of developmental potential and proliferation in stem and progenitor cells is essential for mammalian development and tissue homeostasis. To better understand this coordination in human neural progenitor cells (hNPCs), we performed CRISPR-Cas9 screens and identified genes that limit their expansion. These screens revealed that knockout of growth-limiting genes, including CREBBP, NF2, PTPN14, TAOK1, or TP53, caused increased hNPC expansion via skipping of a transient G0-like state, accompanied by transcriptional reprogramming of G1 subpopulations. Hallmarks of the G0-like state included expression of genes associated with quiescent neural stem cells and neural development and molecular features found in quiescent cells (e.g., hypophosphorylated Rb, CDK2low activity, and p27high). Further, G0-skip genes act through both distinct and convergent downstream effectors, including cell cycle, Hippo-YAP, and novel targets. The results suggest that hNPC expansion is constrained by a transient G0-like state, regulated by multiple pathways, that facilitates retention of neurodevelopmental identity.

Connect-seq to superimpose molecular on anatomical neural circuit maps

Abstract: The mouse brain contains ~100 million neurons interconnected in a vast array of neural circuits. The identities and functions of individual neuronal components of most circuits are undefined. Here we describe a method, termed ‘Connect-seq’, which combines retrograde viral tracing and single cell transcriptomics to uncover the molecular identities of upstream neurons in a specific circuit and the signaling molecules they use to communicate. Connect-seq can generate a molecular map that can be superimposed on a neuroanatomical map to permit molecular and genetic interrogation of how the neuronal components of a circuit control its function. Application of this method to hypothalamic neurons controlling physiological responses to fear and stress reveal subsets of upstream neurons that express diverse constellations of signaling molecules and can be distinguished by their anatomical locations.

The accessible chromatin landscape of the hippocampus at single-cell resolution

Abstract: Here we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq), a software suite, scitools, for the rapid processing and visualization of single-cell combinatorial indexing datasets, and a valuable resource of hippocampal regulatory networks at single-cell resolution. We utilized sci-ATAC-seq to produce 2,346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. Using this dataset, we identified eight distinct major clusters of cells representing both neuronal and non-neuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. We then applied a recently described co-accessibility framework, Cicero, which identified 146,818 links between promoters and putative distal regulatory DNA. Identified co-accessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we carried out an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared to nuclei from hippocampal tissue. This dataset and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.

CRISPR-Cas9 Screens Reveal Genes Regulating a G0-like State in Human Neural Progenitors

Abstract: The coordination of developmental potential and proliferation in stem and progenitor cells is essential for mammalian development and tissue homeostasis. We performed CRISPR-Cas9 screens in human neural progenitor cells (hNPCs) and identified genes, including CREBBP, NF2, PTPN14, TAOK1, or TP53, that limit expansion. Knockout of these genes causes increased hNPC proliferation via skipping of a transient G0-like state, characterized by expression of genes associated with quiescent neural stem cells and neural development and molecular features of quiescent cells (e.g., hypophosphorylated Rb, low CDK2 activity, and p27 stabilization). Single-cell RNA- sequencing of hNPCs revealed distinct G0/G1 populations, altered in G0-skip mutants through both distinct and convergent downstream effectors, including cell cycle, Hippo- YAP, and novel targets. Our results provide a molecular and phenotypic portrait of expanding hNPCs including a gene expression map of their cell cycle and characterization of antiproliferative factors that regulate cell cycle exit with likely roles in maintaining developmental potential.