Biology subjects

Greenleaf, W. J.

Publications and source records attributed to Greenleaf, W. J..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Systematic discovery and perturbation of regulatory genes in human T cells reveals the architecture of immune networks

Complex gene regulatory networks ensure that important genes are expressed at precise levels. When gene expression is sufficiently perturbed it can lead to disease. To understand how gene expression disruptions percolate through a network, we must first map connections between regulatory genes and their downstream targets. However, we lack comprehensive knowledge of the upstream regulators of most genes. Here we developed an approach for systematic discovery of upstream regulators of critical immune factors - IL2RA, IL-2, and CTLA4 - in primary human T cells. Then, we mapped the network of these regulators target genes and enhancers using CRISPR perturbations, RNA-Seq, and ATAC-Seq. These regulators form densely interconnected networks with extensive feedback loops. Furthermore, this network is highly enriched for immune-associated disease variants and genes. These results provide insight into how immune-associated disease genes are regulated in T cells and broader principles about the structure of human gene regulatory networks. HighlightsO_LIA systematic approach to identify upstream regulators of key immune genes in primary human cells C_LIO_LIComprehensive RNA-Seq and ATAC-Seq perturbation maps after KO of individual discovered regulators C_LIO_LIAnalysis uncovers a highly interconnected regulatory network of enhancers and genes in T cells C_LIO_LIThis network is highly enriched for immune disease variants and genes shedding light on the trans-regulatory connections among key immune genes in health and disease C_LI

genomics↗

bioRxiv2021

Direct profiling of genome-wide dCas9 and Cas9 specificity using ssDNA mapping (CasKAS)

Detecting and mitigating off-target activity is critical to the practical application of CRISPR-mediated genome and epigenome editing. While numerous methods have been developed to map Cas9 binding specificity genome-wide, they are generally time-consuming and/or expensive, and not applicable to catalytically dead CRISPR enzymes. We have developed a rapid, inexpensive, and facile assay for identifying off-target CRISPR enzyme binding and cleavage by chemically mapping the unwound single-stranded DNA structures formed upon binding of a sgRNA-loaded Cas9 protein ("CasKAS"). We demonstrate this method in both in vitro and in vivo contexts.

genomics↗

bioRxiv2021

LKB1 inactivation modulates chromatin accessibility to drive metastatic progression

Metastasis is the leading cause of cancer-related deaths, enabling cancer cells to expand to secondary sites and compromise organ function1. Given that primary tumors and metastases often share the same constellation of driver mutations2-4, the mechanisms driving their distinct phenotypes are unclear. Here, we show that inactivation of the frequently mutated tumor suppressor gene, liver kinase B1 (LKB1), has evolving effects throughout lung cancer progression, leading to the differential epigenetic re-programming of early-stage primary tumors compared to late-stage metastases. By integrating genome-scale CRISPR/Cas9 screening with bulk and single-cell multi-omic analyses, we unexpectedly identify LKB1 as a master regulator of chromatin accessibility in lung adenocarcinoma primary tumors. Using an in vivo model of metastatic progression, we further reveal that loss of LKB1 activates the early endoderm transcription factor SOX17 in metastases and a metastatic-like sub-population of cancer cells within primary tumors. SOX17 expression is necessary and sufficient to drive a second wave of epigenetic changes in LKB1-deficient cells that enhances metastatic ability. Overall, our study demonstrates how the downstream effects of an individual driver mutation can appear to change throughout cancer development, with implications for stage-specific therapeutic resistance mechanisms and the gene regulatory underpinnings of metastatic evolution.

cancer biology↗

bioRxiv2021

Single-cell analyses reveal a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer

To chart cell composition and cell state changes that occur during the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC), we generated 451,886 single-cell chromatin accessibility profiles and 208,557 single-cell transcriptomes from 48 polyps, 27 normal tissues, and 6 CRCs collected from patients with and without germline APC mutations. A large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from normal to CRC. Advanced polyps contain increasing numbers of stem-like cells, regulatory T-cells, and a subtype of FOX-regulated pre-cancer associated fibroblasts. In the cancerous state, we observe T-cell exhaustion, RUNX1-regulated cancer associated fibroblasts, and increasing accessibility associated with HNF4A motifs in epithelia. Methylation changes in sporadic CRC are strongly anti-correlated with accessibility changes along this continuum, further identifying regulatory markers for molecular staging of polyps.

genomics↗

bioRxiv2021

Increased ACTL6A Occupancy Within mSWI/SNF Chromatin Remodelers Drives Human Squamous Cell Carcinoma

Mammalian SWI/SNF (BAF) chromatin remodelers play dosage-sensitive roles in many human malignancies and neurologic disorders. The gene encoding the BAF subunit, ACTL6A, is amplified at an early stage in the development of squamous cell carcinomas (SCCs), but its oncogenic role remains unclear. Here we demonstrate that ACTL6A overexpression leads to its stoichiometric assembly into BAF complexes and drives its interaction and engagement with specific regulatory regions in the genome. In normal epithelial cells, ACTL6A was sub-stoichiometric to other BAF subunits. However, increased ACTL6A levels by ectopic expression or in SCC cells led to near-saturation of ACTL6A within BAF complexes. Increased ACTL6A occupancy enhanced polycomb opposition over the genome activating SCC genes and also enhanced the recruitment of transcription factor TEAD with its co-activator YAP, promoting their chromatin binding and enhancer accessibility. Both of these mechanisms appeared to be critical and function as a molecular AND gate for SCC initiation and maintenance, thereby explaining the specificity of the role of ACTL6A amplification in SCCs. HighlightsO_LIACTL6A occupancy within BAF complexes is sub-stoichiometric in normal epithelial cells. C_LIO_LISCC cells upregulate ACTL6A thus increasing ACTL6A assembly with BAF complexes. C_LIO_LIGenome-wide chromatin profiling identifies ACTL6A-dependent regulatory regions. C_LIO_LIIncreasing ACTL6A incorporation enhances TEAD-YAP binding to BAF complexes. C_LIO_LIACTL6A overexpression counteracts polycomb-mediated repression at SCC signature genes. C_LI

molecular biology↗

bioRxiv2021

Integrated single-cell transcriptomics and epigenomics reveals strong germinal center-associated etiology of autoimmune risk loci

The germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting auto-reactive B cells. Dysfunction in these processes can lead to defects in immune response to pathogens or contribute to autoimmune disease. To understand the gene regulatory principles underlying the GC response, we generated a single-cell transcriptomic and epigenomic atlas of the human tonsil, a widely studied and representative lymphoid tissue. We characterize diverse immune cell subsets and build a trajectory of dynamic gene expression and transcription factor activity during B cell activation, GC formation, and plasma cell differentiation. We subsequently leverage cell type-specific transcriptomic and epigenomic maps to interpret potential regulatory impact of genetic variants implicated in autoimmunity, revealing that many exhibit their greatest regulatory potential in GC cell populations. Together, these analyses provide a powerful new cell type-resolved resource for the interpretation of cellular and genetic causes underpinning autoimmune disease. One sentence summarySingle-cell chromatin accessibility landscapes of immune cell subsets reveal regulatory potential of autoimmune-associated genetic variants during the germinal center response.

genomics↗

bioRxiv2020

Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution

Genetic perturbations of cerebral cortical development can lead to neurodevelopmental disease, including autism spectrum disorder (ASD). To identify genomic regions crucial to corticogenesis, we mapped the activity of gene-regulatory elements generating a single-cell atlas of gene expression and chromatin accessibility both independently and jointly. This revealed waves of gene regulation by key transcription factors (TFs) across a nearly continuous differentiation trajectory into glutamatergic neurons, distinguished the expression programs of glial lineages, and identified lineage-determining TFs that exhibited strong correlation between linked gene-regulatory elements and expression levels. These highly connected genes adopted an active chromatin state in early differentiating cells, consistent with lineage commitment. Basepair-resolution neural network models identified strong cell-type specific enrichment of noncoding mutations predicted to be disruptive in a cohort of ASD subjects and identified frequently disrupted TF binding sites. This approach illustrates how cell-type specific mapping can provide insights into the programs governing human development and disease.

neuroscience↗

bioRxiv2020

Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19

Our understanding of protective vs. pathologic immune responses to SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses reveal widespread dysfunction of peripheral innate immunity in severe and fatal COVID-19, with the most profound disturbances including a prominent neutrophil hyperactivation signature and monocytes with anti-inflammatory features. We further demonstrate that emergency myelopoiesis is a prominent feature of fatal COVID-19. Collectively, our results reveal disease severity-associated immune phenotypes in COVID-19 and identify pathogenesis-associated pathways that are potential targets for therapeutic intervention. One Sentence SummarySingle-cell profiling demonstrates multifarious dysregulation of innate immune phenotype associated with COVID-19 severity.

immunology↗

bioRxiv2020

High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

Spear-ATAC is a modified droplet-based single-cell ATAC-seq (scATAC-seq) protocol that enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at a time. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations revealed the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles, demonstrating a high-throughput method for perturbing and evaluating dynamic single-cell epigenetic states.

genomics↗

bioRxiv2020

The dynamic, combinatorial cis-regulatory lexicon of epidermal differentiation

Transcription factors (TFs) bind DNA sequence motif vocabularies in cis-regulatory elements (CREs) to modulate chromatin state and gene expression during cell state transitions. A quantitative understanding of how motif lexicons influence dynamic regulatory activity has been elusive due to the combinatorial nature of the cis-regulatory code. To address this, we undertook multi-omic data profiling of chromatin and expression dynamics across epidermal differentiation to identify 40,103 dynamic CREs associated with 3,609 dynamically expressed genes, then applied an interpretable deep learning framework to model the cis-regulatory logic of chromatin accessibility. This identified cooperative DNA sequence rules in dynamic CREs regulating synchronous gene modules with diverse roles in skin differentiation. Massively parallel reporter analysis validated temporal dynamics and cooperative cis-regulatory logic. Variants linked to human polygenic skin disease were enriched in these time-dependent combinatorial motif rules. This integrative approach reveals the combinatorial cis-regulatory lexicon of epidermal differentiation and represents a general framework for deciphering the organizational principles of the cis-regulatory code in dynamic gene regulation. HIGHLIGHTSO_LIAn integrative multi-omic resource profiling chromatin and expression dynamics across keratinocyte differentiation C_LIO_LIPredictive deep learning models of chromatin dynamics reveal a high-resolution cis-regulatory DNA motif lexicon of epidermal differentiation C_LIO_LIModel interpretation enables discovery of combinatorial cis-regulatory logic of homotypic and heterotypic motif combinations C_LIO_LIMassively parallel reporter experiments validate temporal dynamics and cis-regulatory logic of the combinatorial motif lexicon C_LI

genomics↗

bioRxiv2020

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data has hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage, then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target significantly influences Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to "proofreading" capability. Finally, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

biochemistry↗

bioRxiv2020

Single-cell epigenomic identification of inherited risk loci in Alzheimer's and Parkinson's disease

Genome-wide association studies (GWAS) have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimers disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinsons disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.

genomics↗

bioRxiv2019

A single cell framework for multi-omic analysis of disease identifies malignant regulatory signatures in mixed phenotype acute leukemia

In order to identify the molecular determinants of human diseases, such as cancer, that arise from a diverse range of tissue, it is necessary to accurately distinguish normal and pathogenic cellular programs.1-3 Here we present a novel approach for single-cell multi-omic deconvolution of healthy and pathological molecular signatures within phenotypically heterogeneous malignant cells. By first creating immunophenotypic, transcriptomic and epigenetic single-cell maps of hematopoietic development from healthy peripheral blood and bone marrow mononuclear cells, we identify cancer-specific transcriptional and chromatin signatures from single cells in a cohort of mixed phenotype acute leukemia (MPAL) clinical samples. MPALs are a high-risk subtype of acute leukemia characterized by a heterogeneous malignant cell population expressing both myeloid and lymphoid lineage-specific markers.4, 5 Our results reveal widespread heterogeneity in the pathogenetic gene regulatory and expression programs across patients, yet relatively consistent changes within patients even across malignant cells occupying diverse portions of the hematopoietic lineage. An integrative analysis of transcriptomic and epigenetic maps identifies 91,601 putative gene-regulatory interactions and classifies a number of transcription factors that regulate leukemia specific genes, including RUNX1-linked regulatory elements proximal to CD69. This work provides a template for integrative, multi-omic analysis for the interpretation of pathogenic molecular signatures in the context of developmental origin.

genomics↗

bioRxiv2019

Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion

Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here we present a massively parallel droplet-based platform for mapping transposase-accessible chromatin in tens of thousands of single cells per sample (scATAC-seq). We obtain and analyze chromatin profiles of over 200,000 single cells in two primary human systems. In blood, scATAC-seq allows marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping of disease-associated enhancer activity, and reconstruction of trajectories of differentiation from progenitors to diverse and rare immune cell types. In basal cell carcinoma, scATAC-seq reveals regulatory landscapes of malignant, stromal, and immune cell types in the tumor microenvironment. Moreover, scATAC-seq of serial tumor biopsies before and after PD-1 blockade allows identification of chromatin regulators and differentiation trajectories of therapy-responsive intratumoral T cell subsets, revealing a shared regulatory program driving CD8+ T cell exhaustion and CD4+ T follicular helper cell development. We anticipate that droplet-based single-cell chromatin accessibility will provide a broadly applicable means of identifying regulatory factors and elements that underlie cell type and function.

genomics↗

bioRxiv2019

Automated design of highly diverse riboswitches

Riboswitches that couple binding of ligands to recruitment of molecular machines offer sensors and control elements for RNA synthetic biology and medical biotechnology. Current approaches to riboswitch design enable significant changes in output activity in the presence vs. absence of input ligands. However, design of these riboswitches has so far required expert intuition and explicit specification of complete target secondary structures, both of which limit the structure-toggling mechanisms that have been explored. We present a fully automated method called RiboLogic for these design tasks and high-throughput experimental tests of 2,875 molecules using RNA-MaP (RNA on a massively parallel array) technology. RiboLogic designs explore an unprecedented diversity of structure-toggling mechanisms validated through experimental tests. These synthetic molecules consistently modulate their affinity to the MS2 bacteriophage coat protein upon binding of flavin mononucleotide, tryptophan, theophylline, and microRNA miR-208a, achieving activation ratios of up to 20 and significantly better performance than control designs. The data enable dissection of features of structure-toggling mechanisms that correlate with higher performance. The diversity of RiboLogic designs and their quantitative experimental characterization provides a rich resource for further improvement of riboswitch models and design methods.

biophysics↗

bioRxiv2019

Quantitative high-throughput tests of ubiquitous RNA secondary structure prediction algorithms via RNA/protein binding

Nearest-neighbor (NN) rules provide a simple and powerful quantitative framework for RNA structure prediction that is strongly supported for canonical Watson-Crick duplexes from a plethora of thermodynamic measurements. Predictions of RNA secondary structure based on nearest-neighbor (NN) rules are routinely used to understand biological function and to engineer and control new functions in biotechnology. However, NN applications to RNA structural features such as internal and terminal loops rely on approximations and assumptions, with sparse experimental coverage of the vast number of possible sequence and structural features. To test to what extent NN rules accurately predict thermodynamic stabilities across RNAs with non-WC features, we tested their predictions using a quantitative high-throughput assay platform, RNA-MaP. Using a thermodynamic assay with coupled protein binding, we carried out equilibrium measurements for over 1000 RNAs with a range of predicted secondary structure stabilities. Our results revealed substantial scatter and systematic deviations between NN predictions and observed stabilities. Solution salt effects and incorrect or omitted loop parameters contribute to these observed deviations. Our results demonstrate the need to independently and quantitatively test NN computational algorithms to identify their capabilities and limitations. RNA-MaP and related approaches can be used to test computational predictions and can be adapted to obtain experimental data to improve RNA secondary structure and other prediction algorithms.\n\nSignificance statementRNA secondary structure prediction algorithms are routinely used to understand, predict and design functional RNA structures in biology and biotechnology. Given the vast number of RNA sequence and structural features, these predictions rely on a series of approximations, and independent tests are needed to quantitatively evaluate the accuracy of predicted RNA structural stabilities. Here we measure the stabilities of over 1000 RNA constructs by using a coupled protein binding assay. Our results reveal substantial deviations from the RNA stabilities predicted by popular algorithms, and identify factors contributing to the observed deviations. We demonstrate the importance of quantitative, experimental tests of computational RNA structure predictions and present an approach that can be used to routinely test and improve the prediction accuracy.

biophysics↗

bioRxiv2019

Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements

Pooled CRISPR-Cas9 screens have recently emerged as a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we conducted a genome-scale screen for essential CTCF loop anchors in the K562 leukemia cell line. Surprisingly, the primary drivers of signal in this screen were single guide RNAs (sgRNAs) with low specificity scores. After removing these guides, we found that there were no CTCF loop anchors critical for cell growth. We also observed this effect in an independent screen fine-mapping the core motifs in enhancers of the GATA1 gene. We then conducted screens in parallel with CRISPRi and CRISPRa, which do not induce DNA damage, and found that an unexpected and distinct set of off-targets also caused strong confounding growth effects with these epigenome-editing platforms. Promisingly, strict filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and allowed for the identification of essential enhancers, which we validated extensively. Together, our results show off-target activity can severely limit identification of essential functional motifs by active Cas9, while strictly filtered CRISPRi screens can be reliably used for assaying larger regulatory elements.

genomics↗

bioRxiv2018

Long-range single-molecule mapping of chromatin accessibility in eukaryotes

Active regulatory elements in eukaryotes are typically characterized by an open, nucleosome-depleted chromatin structure; mapping areas of open chromatin has accordingly emerged as a widely used tool in the arsenal of modern functional genomics. However, existing approaches for profiling chromatin accessibility are limited by their reliance on DNA fragmentation and short read sequencing, which leaves them unable to provide information about the state of chromatin on larger scales or reveal coordination between the chromatin state of individual distal regulatory elements. To address these limitations, we have developed a method for profiling accessibility of individual chromatin fibers at multi-kilobase length scale (SMAC-seq, or Single-Molecule long-read Accessible Chromatin mapping sequencing assay), enabling the simultaneous, high-resolution, single-molecule assessment of the chromatin state of distal genomic elements. Our strategy is based on combining the preferential methylation of open chromatin regions by DNA methyltransferases (CpG and GpC 5-methylcytosine (5mC) and N6-methyladenosine (m6A) enzymes) and the ability of long-read single-molecule nanopore sequencing to directly read out the methylation state of individual DNA bases. Applying SMAC-seq to the budding yeast Saccharomyces cerevisiae, we demonstrate that aggregate SMAC-seq signals match bulk-level accessibility measurements, observe single-molecule protection footprints of nucleosomes and transcription factors, and quantify the correlation between the chromatin states of distal genomic elements.

genomics↗