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Regev, A.

Publications and source records attributed to Regev, A..

At least 145 records · Page 8Linked to original sources
bioRxiv2019

Systematic comparative analysis of single cell RNA-sequencing methods

A multitude of single-cell RNA sequencing methods have been developed in recent years, with dramatic advances in scale and power, and enabling major discoveries and large scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single cell and/or single nucleus profiling from three types of samples - cell lines, peripheral blood mononuclear cells and brain tissue - generating 36 libraries in six separate experiments in a single center. To analyze these datasets, we developed and applied scumi, a flexible computational pipeline that can be used for any scRNA-seq method. We evaluated the methods for both basic performance and for their ability to recover known biological information in the samples. Our study will help guide experiments with the methods in this study as well as serve as a benchmark for future studies and for computational algorithm development.

genomics↗
bioRxiv2019

A cellular and spatial map of the choroid plexus across brain ventricles and ages

The choroid plexus (ChP), located in each brain ventricle, produces cerebrospinal fluid (CSF) and forms the blood-CSF barrier, but is under-characterized. Here, we combine single cell RNA-Seq and spatial mapping of RNA and proteins to construct an atlas of each ChP in the developing and adult mouse brain. Each ChP comprises of epithelial, endothelial, mesenchymal, immune, neuronal, and glial cells, with distinct subtypes, differentiation states and anatomical locations. Epithelial, fibroblast, and macrophage populations had ventricle-specific, regionalized gene expression programs across the developing brain. Key cell types are retained in adult, with loss of developmental signatures and maturation of ventricle-specific regionalization in the epithelial cells. Expression of cognate ligand-receptor pairs across cell subtypes suggests substantial cell-cell interactions within the ChP. Our atlas sheds new light on the development and function of the ChP brain barrier system, and will facilitate future studies on its role in brain development, homeostasis and disease.

neuroscience↗
bioRxiv2019

High-density spatial transcriptomics arrays for in situ tissue profiling

Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays either lack global transcriptome information or are not at the single-cell level. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are then randomly deposited in individual wells on a slide. The barcoded beads are decoded and coupled to a specific spatial address. We then capture and spatially in situ label RNA from the same histological tissue sections placed on the bead array slide. HDST recovers hundreds of thousands of transcript-coupled barcodes per experiment at 2 m resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to 2D spatial analysis of tissues at high resolution.

genomics↗
bioRxiv2019

A cellular taxonomy of the bone marrow stroma in homeostasis and leukemia demonstrates cancer-crosstalk with stroma to impair normal tissue function

Stroma is a poorly defined non-parenchymal component of virtually every organ with key roles in organ development, homeostasis and repair. Studies of the bone marrow stroma have defined individual populations in the stem cell niche regulating hematopoietic regeneration and capable of initiating leukemia. Here, we use single-cell RNA-seq to define a cellular taxonomy of the mouse bone marrow stroma and its perturbation by malignancy. We identified seventeen stromal subsets expressing distinct hematopoietic regulatory genes, spanning new fibroblastic, and osteoblastic subpopulations. Emerging acute myeloid leukemia resulted in impaired osteogenic differentiation and reduced production of hematopoietic regulatory molecules necessary for normal hematopoiesis. Thus, cancer can affect tissue stroma in which they reside to disadvantage normal parenchymal cells. Our taxonomy of the regulatory stromal compartment provides experimental support for a model where malignant clone is not a destroyer of normal tissue but an architect of it, remodeling tissue stroma to enable emergent cancer.

cell biology↗
bioRxiv2019

Kidney organoid reproducibility across multiple human iPSC lines and diminished off target cells after transplantation revealed by single cell transcriptomics

Human iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we used single cell RNA-Seq (scRNA-Seq) to profile 415,775 cells to show that organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes were largely reproducible across iPSC lines, time points, protocols, and replicates, cell proportions were variable between different iPSC lines. Off-target cell proportions were the most variable. Prolonged in vitro culture did not alter cell types, but organoid transplantation under the mouse kidney capsule diminished off-target cells. Our work shows how scRNA-seq can help score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells.

genomics↗
bioRxiv2019

scSVA: an interactive tool for big data visualization and exploration in single-cell omics

We present scSVA (single-cell Scalable Visualization and Analytics), a lightweight R package for interactive two- and three-dimensional visualization and exploration of massive single-cell omics data. Building in part of methods originally developed for astronomy datasets, scSVA is memory efficient for more than hundreds of millions of cells, can be run locally or in a cloud, and generates high-quality figures. In particular, we introduce a numerically efficient method for single-cell data embedding in 3D which combines an optimized implementation of diffusion maps with a 3D force-directed layout, enabling generation of 3D data visualizations at the scale of a million cells. To facilitate reproducible research, scSVA supports interactive analytics in a cloud with containerized tools. scSVA is available online at https://github.com/klarman-cell-observatory/scSVA.

bioinformatics↗
bioRxiv2019

Longitudinal single cell profiling of regulatory T cells identifies IL-33 as a driver of tumor immunosuppression

Regulatory T cells (Tregs) can impair anti-tumor immune responses and are associated with poor prognosis in multiple cancer types. Tregs in human tumors span diverse transcriptional states distinct from those of peripheral Tregs, but their contribution to tumor development remains unknown. Here, we used single cell RNA-Seq to longitudinally profile conventional CD4+ T cells (Tconv) and Tregs in a genetic mouse model of lung adenocarcinoma. Tissue-infiltrating and peripheral CD4+ T cells differed, highlighting divergent pathways of activation during tumorigenesis. Longitudinal shifts in Treg heterogeneity suggested increased terminal differentiation and stabilization of an effector phenotype over time. In particular, effector Tregs had enhanced expression of the interleukin 33 receptor ST2. Treg-specific deletion of ST2 reduced effector Tregs, increased infiltration of CD8+ T cells into tumors, and decreased tumor burden. Our study shows that ST2 plays a critical role in Treg-mediated immunosuppression in cancer, highlighting new potential paths for therapeutic intervention.

cancer biology↗
bioRxiv2018

Nuclei multiplexing with barcoded antibodies for single-nucleus genomics

Single-nucleus RNA-Seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate, including frozen clinical samples. This opens the way, in principle, to large studies, such as those required for human genetics, clinical trials, or precise cell atlases of large organs. However, such applications are currently limited by batch effects, sequential processing, and costs. To address these challenges, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies against the nuclear pore complex to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled in multiplex with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter the recovered transcriptome profiles. We further developed demuxEM, a novel computational tool that robustly detects inter-sample nucleus multiplets and assigns singlets to their samples of origin by antibody barcodes, and validated its accuracy using gender-specific gene expression, species-mixing and natural genetic variation. Nucleus hashing significantly reduces cost per nucleus, recovering up to about 5 times as many single nuclei per microfluidc channel. Our approach provides a robust technique for diverse studies including tissue atlases of isogenic model organisms or from a single larger human organ, multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.

genomics↗
bioRxiv2018

DNA microscopy: Optics-free spatio-genetic imaging by a stand-alone chemical reaction

Analyzing the spatial organization of molecules in cells and tissues is a cornerstone of biological research and clinical practice. However, despite enormous progress in profiling the molecular constituents of cells, spatially mapping these constituents remains a disjointed and machinery-intensive process, relying on either light microscopy or direct physical registration and capture. Here, we demonstrate DNA microscopy, a new imaging modality for scalable, optics-free mapping of relative biomolecule positions. In DNA microscopy of transcripts, transcript molecules are tagged in situ with randomized nucleotides, labeling each molecule uniquely. A second in situ reaction then amplifies the tagged molecules, concatenates the resulting copies, and adds new randomized nucleotides to uniquely label each concatenation event. An algorithm decodes molecular proximities from these concatenated sequences, and infers physical images of the original transcripts at cellular resolution. Because its imaging power derives entirely from diffusive molecular dynamics, DNA microscopy constitutes a chemically encoded microscopy system.

bioengineering↗
bioRxiv2018

Skin inflammation driven by differentiation of quiescent tissue-resident ILCs into a spectrum of pathogenic effectors

Psoriasis pathology is driven by the type 3 cytokines IL-17 and Il-22, but little is understood about the dynamics that initiate alterations in tissue homeostasis. Here, we use mouse models, single-cell RNA-seq (scRNA-seq), computational inference and cell lineage mapping to show that psoriasis induction reconfigures the functionality of skin-resident ILCs to initiate disease. Tissue-resident ILCs amplified an initial IL-23 trigger and were sufficient, without circulatory ILCs, to drive pathology, indicating that ILC tissue remodeling initiates psoriasis. Skin ILCs expressed type 2 cytokines IL-5 and IL-13 in steady state, but were epigenetically poised to become ILC3-like cells. ScRNA-seq profiles of ILCs from psoriatic and naive skin of wild type (WT) and Rag1-/- mice form a dense continuum, consistent with this model of fluid ILC states. We inferred biological \"topics\" underlying these states and their relative importance in each cell with a generative model of latent Dirichlet allocation, showing that ILCs from untreated skin span a spectrum of states, including a naive/quiescent-like state and one expressing the Cd74 and Il13 but little Il5. Upon disease induction, this spectrum shifts, giving rise to a greater proportion of classical Il5- and Il13- expressing \"ILC2s\" and a new, mixed ILC2/ILC3-like subset, expressing Il13, Il17, and Il22. Using these key topics, we related the cells through transitions, revealing a quiescence-ILC2-ILC3s state trajectory. We demonstrated this plasticity in vivo, combining an IL-5 fate mouse with IL-17A and IL-22 reporters, validating the transition of IL-5-producing ILC2s to IL-22- and IL-17A-producing cells during disease initiation. Thus, steady-state skin ILCs are actively repressed and cued for a plastic, type 2 response, which, upon induction, morphs into a type 3 response that drives psoriasis. This suggests a general model where specific immune activities are primed in healthy tissue, dynamically adapt to provocations, and left unchecked, drive pathological remodeling.

immunology↗
bioRxiv2018

Single-cell transcriptomics of the aged mouse brain reveals convergent, divergent and unique aging signatures

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how the brain is affected with aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide a comprehensive dataset of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell type specific manner, even at times in opposite directions. Thus, our data reveals that aging, rather than inducing a universal program drives a distinct transcriptional course in each cell population. These data provide an important resource for the aging community and highlight key molecular processes, including ribosomal biogenesis, underlying aging. We believe that this large-scale dataset, which is publicly accessible online (aging-mouse-brain), will facilitate additional discoveries directed towards understanding and modifying the aging process.

neuroscience↗
bioRxiv2018

Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina

High acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible model organisms lack a fovea, its specialized function and dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate and validate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >65 cell types match between the two regions, but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved, but that projection neuron types and programs diverge, despite conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 6 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species.

neuroscience↗
bioRxiv2018

Regulatory network controlling tumor-promoting inflammation in human cancers

Using an inducible, inflammatory model of breast cellular transformation, we describe the transcriptional regulatory network mediated by STAT3, NF-{kappa}B, and AP-1 factors on a genomic scale. These regulators form transcriptional complexes that directly regulate the expression of hundreds of genes in oncogenic pathways via a positive feedback loop. This inflammatory feedback loop, which functions to various extents in many types of cancer cells and patient tumors, is the basis for an \"inflammation\" index that defines cancer types by functional criteria. We identify a network of non-inflammatory genes whose expression is well correlated with the cancer inflammatory index. Conversely, the inflammation index is negatively correlated with expression of genes involved in DNA metabolism, and transformation is associated with genome instability. Inflammatory tumors are preferentially associated with infiltrating immune cells that might be recruited to the site of the tumor via inflammatory molecules produced by the cancer cells.

cancer biology↗
bioRxiv2018

A single cell-based atlas of human microglial states reveals associations with neurological disorders and histopathological features of the aging brain

Recent studies of bulk microglia have provided insights into the role of this immune cell type in central nervous system development, homeostasis and dysfunction. Nonetheless, our understanding of the diversity of human microglial cell states remains limited; microglia are highly plastic and have multiple different roles, making the extent of phenotypic heterogeneity a central question, especially in light of the development of therapies targeting this cell type. Here, we investigated the population structure of human microglia by single-cell RNA-sequencing. Using surgical- and autopsy-derived cortical brain samples, we identified 14 human microglial subpopulations and noted substantial intra- and inter-individual heterogeneity. These putative subpopulations display divergent associations with Alzheimers disease, multiple sclerosis, and other diseases. Several states show enrichment for genes found in disease-associated mouse microglial states, suggesting additional diversity among human microglia. Overall, human microglia appear to exist in different functional states with varying levels of involvement in different brain pathologies.

neuroscience↗
bioRxiv2018

Conservation and divergence in modules of the transcriptional programs of the human and mouse immune systems

Studies in mouse have shed important light on human hematopoietic differentiation and disease. However, substantial differences between the two species often limit the translation of findings from mouse to human.\n\nHere, we compare previously defined modules of co-expressed genes in human and mouse immune cells based on compendia of genome-wide profiles. We show that the overall modular organization of the transcriptional program is conserved. We highlight modules of co-expressed genes in one species that dissolve or split in the other species. Many of the associated regulatory mechanisms - as reflected by computationally inferred trans regulators, or enriched cis-regulatory elements - are conserved between the species. Nevertheless, the degree of conservation in regulatory mechanism is lower than that of expression, suggesting that distinct regulation may underlie some of the conserved transcriptional responses.

bioinformatics↗
bioRxiv2017

A quantitative model for characterizing the evolutionary history of mammalian gene expression

Characterizing the evolutionary history of a genes expression profile is a critical component for understanding the relationship between genotype, expression, and phenotype. However, it is not well-established how best to distinguish the different evolutionary forces acting on gene expression. Here, we use RNA-seq across 7 tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein-Uhlenbeck (OU) process. This stochastic process models expression trajectories across time as Gaussian distributions whose variance is parameterized by the rate of genetic drift and strength of stabilizing selection. We use these mathematical properties to identify expression pathways under neutral, stabilizing, and directional selection, and quantify the extent of selective pressure on a genes expression. We further detect deleterious expression levels outside expected evolutionary distributions in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.\n\nOne Sentence SummaryWe demonstrate the power of a stochastic model for quantifying selective pressure on expression and estimating evolutionary distributions of optimal gene expression.

genomics↗
bioRxiv2017

Deciphering cis-regulatory logic with 100 million synthetic promoters

Deciphering cis-regulation, the code by which transcription factors (TFs) interpret regulatory DNA sequence to control gene expression levels, is a long-standing challenge. Previous studies of native or engineered sequences have remained limited in scale. Here, we use random sequences as an alternative, allowing us to measure the expression output of over 100 million synthetic yeast promoters. Random sequences yield a broad range of reproducible expression levels, indicating that the fortuitous binding sites in random DNA are functional. From these data we learn models of transcriptional regulation that predict over 94% of the expression driven from independent test data and nearly 89% from sequences from yeast promoters. These models allow us to characterize the activity of TFs and their interactions with chromatin, and help refine cis-regulatory motifs. We find that strand, position, and helical face preferences of TFs are widespread and depend on interactions with neighboring chromatin. Such massive-throughput regulatory assays of random DNA provide the diverse examples necessary to learn complex models of cis-regulatory logic.

genomics↗