Single-cell chromatin state analysis with Signac

Mapping genotypes to chromatin accessibility profiles in single cells

In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.

Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity

Single-cell epigenomic data has been growing continuously at an unprecedented pace, but their characteristics such as high dimensionality and sparsity pose substantial challenges to downstream analysis. Although deep learning models-especially variational autoencoders-have been widely used to capture low-dimensional feature embeddings, the prevalent Gaussian assumption somewhat disagrees with real data, and these models tend to struggle to incorporate reference information from abundant cell atlases. Here we propose CASTLE, a deep generative model based on the vector-quantized variational autoencoder framework to extract discrete latent embeddings that interpretably characterize single-cell chromatin accessibility sequencing data. We validate the performance and robustness of CASTLE for accurate cell-type identification and reasonable visualization compared with state-of-the-art methods. We demonstrate the advantages of CASTLE for effective incorporation of existing massive reference datasets in a weakly supervised or supervised manner. We further demonstrate CASTLE's capacity for intuitively distilling cell-type-specific feature spectra that unveil cell heterogeneity and biological implications quantitatively.

Projection-TAGs enable multiplex projection tracing and multi-modal profiling of projection neurons

Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes. By using Projection-TAGs, we performed multiplex projection tracing of the mouse cortex and high-throughput single-cell profiling of the transcriptional and epigenetic landscapes of the cortical projection neurons. Projection-TAGs can be leveraged to obtain a snapshot of activity-dependent recruitment of distinct projection neurons and their molecular features in the context of a specific stimulus. Given its flexibility, usability, and compatibility, we envision that Projection-TAGs can be readily applied to build a comprehensive multi-modal map of brain neuronal cell types and their projections.

RAG suppresses group 2 innate lymphoid cells

Antigen specificity is the central trait distinguishing adaptive from innate immune function. Assembly of antigen-specific T cell and B cell receptors occurs through V(D)J recombination mediated by the Recombinase Activating Gene endonucleases RAG1 and RAG2 (collectively called RAG). In the absence of RAG, mature T and B cells do not develop and thus RAG is critically associated with adaptive immune function. In addition to adaptive T helper 2 (Th2) cells, group 2 innate lymphoid cells (ILC2s) contribute to type 2 immune responses by producing cytokines like Interleukin-5 (IL-5) and IL-13. Although it has been reported that RAG expression modulates the function of innate natural killer (NK) cells, whether other innate immune cells such as ILC2s are affected by RAG remains unclear. We find that in RAG-deficient mice, ILC2 populations expand and produce increased IL-5 and IL-13 at steady state and contribute to increased inflammation in atopic dermatitis (AD)-like disease. Further, we show that RAG modulates ILC2 function in a cell-intrinsic manner independent of the absence or presence of adaptive T and B lymphocytes. Lastly, employing multiomic single cell analyses of RAG1 lineage-traced cells, we identify key transcriptional and epigenomic ILC2 functional programs that are suppressed by a history of RAG expression. Collectively, our data reveal a novel role for RAG in modulating innate type 2 immunity through suppression of ILC2s.

Single-cell insights: pioneering an integrated atlas of chromatin accessibility and transcriptomic landscapes in diabetic cardiomyopathy

BACKGROUND

Diabetic cardiomyopathy (DCM) poses a growing health threat, elevating heart failure risk in diabetic individuals. Understanding DCM is crucial, with fibroblasts and endothelial cells playing pivotal roles in driving myocardial fibrosis and contributing to cardiac dysfunction. Advances in Multimodal single-cell profiling, such as scRNA-seq and scATAC-seq, provide deeper insights into DCM's unique cell states and molecular landscape for targeted therapeutic interventions.

METHODS

Single-cell RNA and ATAC data from 10x Multiome libraries were processed using Cell Ranger ARC v2.0.1. Gene expression and ATAC data underwent Seurat and Signac filtration. Differential gene expression and accessible chromatin regions were identified. Transcription factor activity was estimated with chromVAR, and Cis-coaccessibility networks were calculated using Cicero. Coaccessibility connections were compared to the GeneHancer database. Gene Ontology analysis, biological process scoring, cell-cell communication analysis, and gene-motif correlation was performed to reveal intricate molecular changes. Immunofluorescent staining utilized various antibodies on paraffin-embedded tissues to verify the findings.

RESULTS

This study integrated scRNA-seq and scATAC-seq data obtained from hearts of WT and DCM mice, elucidating molecular changes at the single-cell level throughout the diabetic cardiomyopathy progression. Robust and accurate clustering analysis of the integrated data revealed altered cell proportions, showcasing decreased endothelial cells and macrophages, coupled with increased fibroblasts and myocardial cells in the DCM group, indicating enhanced fibrosis and endothelial damage. Chromatin accessibility analysis unveiled unique patterns in cell types, with heightened transcriptional activity in myocardial cells. Subpopulation analysis highlighted distinct changes in cardiomyocytes and fibroblasts, emphasizing pathways related to fatty acid metabolism and cardiac contraction. Fibroblast-centered communication analysis identified interactions with endothelial cells, implicating VEGF receptors. Endothelial cell subpopulations exhibited altered gene expressions, emphasizing contraction and growth-related pathways. Candidate regulators, including Tcf21, Arnt, Stat5a, and Stat5b, were identified, suggesting their pivotal roles in DCM development. Immunofluorescence staining validated marker genes of cell subpopulations, confirming PDK4, PPARγ and Tpm1 as markers for metabolic pattern-altered cardiomyocytes, activated fibroblasts and endothelial cells with compromised proliferation.

CONCLUSION

Our integrated scRNA-seq and scATAC-seq analysis unveils intricate cell states and molecular alterations in diabetic cardiomyopathy. Identified cell type-specific changes, transcription factors, and marker genes offer valuable insights. The study sheds light on potential therapeutic targets for DCM.

Single-cell multiomics guided mechanistic understanding of Fontan-associated liver disease

The Fontan operation is the current standard of care for single-ventricle congenital heart disease. Individuals with a Fontan circulation (FC) exhibit central venous hypertension and face life-threatening complications of hepatic fibrosis, known as Fontan-associated liver disease (FALD). The fundamental biology and mechanisms of FALD are little understood. Here, we generated a transcriptomic and epigenomic atlas of human FALD at single-cell resolution using multiomic snRNA-ATAC-seq. We found profound cell type-specific transcriptomic and epigenomic changes in FC livers. Central hepatocytes (cHep) exhibited the most substantial changes, featuring profound metabolic reprogramming. These cHep changes preceded substantial activation of hepatic stellate cells and liver fibrosis, suggesting cHep as a potential first "responder" in the pathogenesis of FALD. We also identified a network of ligand-receptor pairs that transmit signals from cHep to hepatic stellate cells, which may promote their activation and liver fibrosis. We further experimentally demonstrated that activins A and B promote fibrotic activation in vitro and identified mechanisms of activin A's transcriptional activation in FALD. Together, our single-cell transcriptomic and epigenomic atlas revealed mechanistic insights into the pathogenesis of FALD and may aid identification of potential therapeutic targets.

Computational tools for plant genomics and breeding

Plant genomics and crop breeding are at the intersection of biotechnology and information technology. Driven by a combination of high-throughput sequencing, molecular biology and data science, great advances have been made in omics technologies at every step along the central dogma, especially in genome assembling, genome annotation, epigenomic profiling, and transcriptome profiling. These advances further revolutionized three directions of development. One is genetic dissection of complex traits in crops, along with genomic prediction and selection. The second is comparative genomics and evolution, which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery. The third direction is the development of deep learning approaches for the rational design of biological sequences, especially proteins, for synthetic biology. All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.

Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells

Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.

scMoresDB: A comprehensive database of single-cell multi-omics data for human respiratory system

The human respiratory system is a complex and important system that can suffer a variety of diseases. Single-cell sequencing technologies, applied in many respiratory disease studies, have enhanced our ability in characterizing molecular and phenotypic features at a single-cell resolution. The exponentially increasing data from these studies have consequently led to difficulties in data sharing and analysis. Here, we present scMoresDB, a single-cell multi-omics database platform with extensive omics types tailored for human respiratory diseases. scMoresDB re-analyzes single-cell multi-omics datasets, providing a user-friendly interface with cross-omics search capabilities, interactive visualizations, and analytical tools for comprehensive data sharing and integrative analysis. Our example applications highlight the potential significance of BSG receptor in SARS-CoV-2 infection as well as the involvement of HHIP and TGFB2 in the development and progression of chronic obstructive pulmonary disease. scMoresDB significantly increases accessibility and utility of single-cell data relevant to human respiratory system and associated diseases.

TIM-3+ CD8 T cells with a terminally exhausted phenotype retain functional capacity in hematological malignancies

Chronic antigen stimulation is thought to generate dysfunctional CD8 T cells. Here, we identify a CD8 T cell subset in the bone marrow tumor microenvironment that, despite an apparent terminally exhausted phenotype (TPHEX), expressed granzymes, perforin, and IFN-γ. Concurrent gene expression and DNA accessibility revealed that genes encoding these functional proteins correlated with BATF expression and motif accessibility. IFN-γ+ TPHEX effectively killed myeloma with comparable efficacy to transitory effectors, and disease progression correlated with numerical deficits in IFN-γ+ TPHEX. We also observed IFN-γ+ TPHEX within CD19-targeted chimeric antigen receptor T cells, which killed CD19+ leukemia cells. An IFN-γ+ TPHEX gene signature was recapitulated in TEX cells from human cancers, including myeloma and lymphoma. Here, we characterize a TEX subset in hematological malignancies that paradoxically retains function and is distinct from dysfunctional TEX found in chronic viral infections. Thus, IFN-γ+ TPHEX represent a potential target for immunotherapy of blood cancers.

Epigenetic dysregulation in Alzheimer's disease peripheral immunity

The peripheral immune system in Alzheimer's disease (AD) has not been thoroughly studied with modern sequencing methods. To investigate epigenetic and transcriptional alterations to the AD peripheral immune system, we used single-cell sequencing strategies, including assay for transposase-accessible chromatin and RNA sequencing. We reveal a striking amount of open chromatin in peripheral immune cells in AD. In CD8 T cells, we uncover a cis-regulatory DNA element co-accessible with the CXC motif chemokine receptor 3 gene promoter. In monocytes, we identify a novel AD-specific RELA transcription factor binding site adjacent to an open chromatin region in the nuclear factor kappa B subunit 2 gene. We also demonstrate apolipoprotein E genotype-dependent epigenetic changes in monocytes. Surprisingly, we also identify differentially accessible chromatin regions in genes associated with sporadic AD risk. Our findings provide novel insights into the complex relationship between epigenetics and genetic risk factors in AD peripheral immunity.

A germline point mutation in the MYC-FBW7 phosphodegron initiates hematopoietic malignancies

Oncogenic activation of MYC in cancers predominantly involves increased transcription rather than coding region mutations. However, MYC-dependent lymphomas frequently acquire point mutations in the MYC phosphodegron, including at threonine 58 (T58), where phosphorylation permits binding via the FBW7 ubiquitin ligase triggering MYC degradation. To understand how T58 phosphorylation functions in normal cell physiology, we introduced an alanine mutation at T58 (T58A) into the endogenous c-Myc locus in the mouse germline. While MYC-T58A mice develop normally, lymphomas and myeloid leukemias emerge in ∼60% of adult homozygous T58A mice. We found that primitive hematopoietic progenitor cells from MYC-T58A mice exhibit aberrant self-renewal normally associated with hematopoietic stem cells (HSCs) and up-regulate a subset of MYC target genes important in maintaining stem/progenitor cell balance. In lymphocytes, genomic occupancy by MYC-T58A was increased at all promoters compared with WT MYC, while genes differentially expressed in a T58A-dependent manner were significantly more proximal to MYC-bound enhancers. MYC-T58A lymphocyte progenitors exhibited metabolic alterations and decreased activation of inflammatory and apoptotic pathways. Our data demonstrate that a single point mutation stabilizing MYC is sufficient to skew target gene expression, producing a profound gain of function in multipotential hematopoietic progenitors associated with self-renewal and initiation of lymphomas and leukemias.

The chromatin accessibility dynamics during cell fate specifications in zebrafish early embryogenesis

Chromatin accessibility plays a critical role in the regulation of cell fate decisions. Although gene expression changes have been extensively profiled at the single-cell level during early embryogenesis, the dynamics of chromatin accessibility at cis-regulatory elements remain poorly studied. Here, we used a plate-based single-cell ATAC-seq method to profile the chromatin accessibility dynamics of over 10 000 nuclei from zebrafish embryos. We investigated several important time points immediately after zygotic genome activation (ZGA), covering key developmental stages up to dome. The results revealed key chromatin signatures in the first cell fate specifications when cells start to differentiate into enveloping layer (EVL) and yolk syncytial layer (YSL) cells. Finally, we uncovered many potential cell-type specific enhancers and transcription factor motifs that are important for the cell fate specifications.

Contrasting somatic mutation patterns in aging human neurons and oligodendrocytes

Characterizing somatic mutations in the brain is important for disentangling the complex mechanisms of aging, yet little is known about mutational patterns in different brain cell types. Here, we performed whole-genome sequencing (WGS) of 86 single oligodendrocytes, 20 mixed glia, and 56 single neurons from neurotypical individuals spanning 0.4-104 years of age and identified >92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). Although both cell types accumulate somatic mutations linearly with age, oligodendrocytes accumulated sSNVs 81% faster than neurons and indels 28% slower than neurons. Correlation of mutations with single-nucleus RNA profiles and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed across the genome similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These stark differences suggest an assortment of active mutagenic processes in oligodendrocytes and neurons.

OpenAnnotateApi: Python and R packages to efficiently annotate and analyze chromatin accessibility of genomic regions

Summary

Chromatin accessibility serves as a critical measurement of physical contact between nuclear macromolecules and DNA sequence, providing valuable insights into the comprehensive landscape of regulatory mechanisms, thus we previously developed the OpenAnnotate web server. However, as an increasing number of epigenomic analysis software tools emerged, web-based annotation often faced limitations and inconveniences when integrated into these software pipelines. To address these issues, we here develop two software packages named OpenAnnotatePy and OpenAnnotateR. In addition to web-based functionalities, these packages encompass supplementary features, including the capability for simultaneous annotation across multiple cell types, advanced searching of systems, tissues and cell types, and converting the result to the data structure of mainstream tools. Moreover, we applied the packages to various scenarios, including cell type revealing, regulatory element prediction, and integration into mainstream single-cell ATAC-seq analysis pipelines including EpiScanpy, Signac, and ArchR. We anticipate that OpenAnnotateApi will significantly facilitate the deciphering of gene regulatory mechanisms, and offer crucial assistance in the field of epigenomic studies.

Availability and implementation

OpenAnnotateApi for R is available at https://github.com/ZjGaothu/OpenAnnotateR and for Python is available at https://github.com/ZjGaothu/OpenAnnotatePy.

Single-cell multiomics reveals the interplay of clonal evolution and cellular plasticity in hepatoblastoma

Hepatoblastomas (HB) display heterogeneous cellular phenotypes that influence the clinical outcome, but the underlying mechanisms are poorly understood. Here, we use a single-cell multiomic strategy to unravel the molecular determinants of this plasticity. We identify a continuum of HB cell states between hepatocytic (scH), liver progenitor (scLP) and mesenchymal (scM) differentiation poles, with an intermediate scH/LP population bordering scLP and scH areas in spatial transcriptomics. Chromatin accessibility landscapes reveal the gene regulatory networks of each differentiation pole, and the sequence of transcription factor activations underlying cell state transitions. Single-cell mapping of somatic alterations reveals the clonal architecture of each tumor, showing that each genetic subclone displays its own range of cellular plasticity across differentiation states. The most scLP subclones, overexpressing stem cell and DNA repair genes, proliferate faster after neo-adjuvant chemotherapy. These results highlight how the interplay of clonal evolution and epigenetic plasticity shapes the potential of HB subclones to respond to chemotherapy.

ARID1A orchestrates SWI/SNF-mediated sequential binding of transcription factors with ARID1A loss driving pre-memory B cell fate and lymphomagenesis

ARID1A, a subunit of the canonical BAF nucleosome remodeling complex, is commonly mutated in lymphomas. We show that ARID1A orchestrates B cell fate during the germinal center (GC) response, facilitating cooperative and sequential binding of PU.1 and NF-kB at crucial genes for cytokine and CD40 signaling. The absence of ARID1A tilts GC cell fate toward immature IgM+CD80-PD-L2- memory B cells, known for their potential to re-enter new GCs. When combined with BCL2 oncogene, ARID1A haploinsufficiency hastens the progression of aggressive follicular lymphomas (FLs) in mice. Patients with FL with ARID1A-inactivating mutations preferentially display an immature memory B cell-like state with increased transformation risk to aggressive disease. These observations offer mechanistic understanding into the emergence of both indolent and aggressive ARID1A-mutant lymphomas through the formation of immature memory-like clonal precursors. Lastly, we demonstrate that ARID1A mutation induces synthetic lethality to SMARCA2/4 inhibition, paving the way for potential precision therapy for high-risk patients.

Single-cell systems pharmacology identifies development-driven drug response and combination therapy in B cell acute lymphoblastic leukemia

Leukemia can arise at various stages of the hematopoietic differentiation hierarchy, but the impact of developmental arrest on drug sensitivity is unclear. Applying network-based analyses to single-cell transcriptomes of human B cells, we define genome-wide signaling circuitry for each B cell differentiation stage. Using this reference, we comprehensively map the developmental states of B cell acute lymphoblastic leukemia (B-ALL), revealing its strong correlation with sensitivity to asparaginase, a commonly used chemotherapeutic agent. Single-cell multi-omics analyses of primary B-ALL blasts reveal marked intra-leukemia heterogeneity in asparaginase response: resistance is linked to pre-pro-B-like cells, with sensitivity associated with the pro-B-like population. By targeting BCL2, a driver within the pre-pro-B-like cell signaling network, we find that venetoclax significantly potentiates asparaginase efficacy in vitro and in vivo. These findings demonstrate a single-cell systems pharmacology framework to predict effective combination therapies based on intra-leukemia heterogeneity in developmental state, with potentially broad applications beyond B-ALL.

SMARCA4 is a haploinsufficient B cell lymphoma tumor suppressor that fine-tunes centrocyte cell fate decisions

SMARCA4 encodes one of two mutually exclusive ATPase subunits in the BRG/BRM associated factor (BAF) complex that is recruited by transcription factors (TFs) to drive chromatin accessibility and transcriptional activation. SMARCA4 is among the most recurrently mutated genes in human cancer, including ∼30% of germinal center (GC)-derived Burkitt lymphomas. In mice, GC-specific Smarca4 haploinsufficiency cooperated with MYC over-expression to drive lymphomagenesis. Furthermore, monoallelic Smarca4 deletion drove GC hyperplasia with centroblast polarization via significantly increased rates of centrocyte recycling to the dark zone. Mechanistically, Smarca4 loss reduced the activity of TFs that are activated in centrocytes to drive GC-exit, including SPI1 (PU.1), IRF family, and NF-κB. Loss of activity for these factors phenocopied aberrant BCL6 activity within murine centrocytes and human Burkitt lymphoma cells. SMARCA4 therefore facilitates chromatin accessibility for TFs that shape centrocyte trajectories, and loss of fine-control of these programs biases toward centroblast cell-fate, GC hyperplasia and lymphoma.

Ruxolitinib Improves Immune-Dysregulation Features but not Epigenetic Abnormality in a Patient with STAT1 GOF

PURPOSE

Patients with STAT1 gain-of-function (GOF) mutations often exhibit autoimmune features. The JAK1/2 inhibitor ruxolitinib can be administered to alleviate autoimmune symptoms; however, it is unclear how immune cells are molecularly changed by ruxolitinib treatment. Then, we aimed to investigate the trnscriptional and epigenetic status of immune cells before and after ruxolitinib treatment in a patient with STAT1 GOF.

METHODS

A patient with a heterozygous STAT1 GOF variant (p.Ala267Val), exhibiting autoimmune features, was treated with ruxolitinib, and peripheral blood mononuclear cells (PBMCs) were longitudinally collected. PBMCs were transcriptionally analyzed by single-cell cellular indexing of the transcriptomes and epitopes by sequencing (CITE-seq), and epigenetically analyzed by assay of transposase-accessible chromatin sequencing (ATAC-seq).

RESULTS

CITE-seq analysis revealed that before treatment, the patient's PBMCs exhibited aberrantly activated inflammatory features, especially IFN-related features. In particular, monocytes showed high expression levels of a subset of IFN-stimulated genes (ISGs). Ruxolitinib treatment substantially downregulated aberrantly overexpressed ISGs, and improved autoimmune features. However, epigenetic analysis demonstrated that genetic regions of ISGs-e.g., STAT1, IRF1, MX1, and OAS1-were highly accessible even after ruxolitinib treatment. When ruxolitinib was temporarily discontinued, the patient's autoimmune features were aggravated, which is in line with sustained epigenetic abnormality.

CONCLUSIONS

In a patient with STAT1 GOF, ruxolitinib treatment improved autoimmune features and downregulated aberrantly overexpressed ISGs, but did not correct epigenetic abnormality of ISGs.

Single-cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveal heterogeneity of endothelial subtype and response to activating perturbations

Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.

Deciphering cell types by integrating scATAC-seq data with genome sequences

The single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) technology provides insight into gene regulation and epigenetic heterogeneity at single-cell resolution, but cell annotation from scATAC-seq remains challenging due to high dimensionality and extreme sparsity within the data. Existing cell annotation methods mostly focus on the cell peak matrix without fully utilizing the underlying genomic sequence. Here we propose a method, SANGO, for accurate single-cell annotation by integrating genome sequences around the accessibility peaks within scATAC data. The genome sequences of peaks are encoded into low-dimensional embeddings, and then iteratively used to reconstruct the peak statistics of cells through a fully connected network. The learned weights are considered as regulatory modes to represent cells, and utilized to align the query cells and the annotated cells in the reference data through a graph transformer network for cell annotations. SANGO was demonstrated to consistently outperform competing methods on 55 paired scATAC-seq datasets across samples, platforms and tissues. SANGO was also shown to be able to detect unknown tumor cells through attention edge weights learned by the graph transformer. Moreover, from the annotated cells, we found cell-type-specific peaks that provide functional insights/biological signals through expression enrichment analysis, cis-regulatory chromatin interaction analysis and motif enrichment analysis.

Chromatin Remodeling in Patient-Derived Colorectal Cancer Models

Patient-Derived Organoids (PDO) and Xenografts (PDX) are the current gold standards for patient-derived models of cancer (PDMC). Nevertheless, how patient tumor cells evolve in these models and the impact on drug response remains unclear. Herein, the transcriptomic and chromatin accessibility landscapes of matched colorectal cancer (CRC) PDO, PDX, PDO-derived PDX (PDOX), and original patient tumors (PT) are compared. Two major remodeling axes are discovered. The first axis delineates PDMC from PT, and the second axis distinguishes PDX and PDO. PDOX are more similar to PDX than PDO, indicating the growth environment is a driving force for chromatin adaptation. Transcription factors (TF) that differentially bind to open chromatins between matched PDO and PDOX are identified. Among them, KLF14 and EGR2 footprints are enriched in PDOX relative to matched PDO, and silencing of KLF14 or EGR2 promoted tumor growth. Furthermore, EPHA4, a shared downstream target gene of KLF14 and EGR2, altered tumor sensitivity to MEK inhibitor treatment. Altogether, patient-derived CRC cells undergo both common and distinct chromatin remodeling in PDO and PDX/PDOX, driven largely by their respective microenvironments, which results in differences in growth and drug sensitivity and needs to be taken into consideration when interpreting their ability to predict clinical outcome.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning

MOTIVATION

Single-cell clustering plays a crucial role in distinguishing between cell types, facilitating the analysis of cell heterogeneity mechanisms. While many existing clustering methods rely solely on gene expression data obtained from single-cell RNA sequencing techniques to identify cell clusters, the information contained in mono-omic data is often limited, leading to suboptimal clustering performance. The emergence of single-cell multi-omics sequencing technologies enables the integration of multiple omics data for identifying cell clusters, but how to integrate different omics data effectively remains challenging. In addition, designing a clustering method that performs well across various types of multi-omics data poses a persistent challenge due to the data's inherent characteristics.

RESULTS

In this paper, we propose a graph-regularized multi-view ensemble clustering (GRMEC-SC) model for single-cell clustering. Our proposed approach can adaptively integrate multiple omics data and leverage insights from multiple base clustering results. We extensively evaluate our method on five multi-omics datasets through a series of rigorous experiments. The results of these experiments demonstrate that our GRMEC-SC model achieves competitive performance across diverse multi-omics datasets with varying characteristics.

AVAILABILITY AND IMPLEMENTATION

Implementation of GRMEC-SC, along with examples, can be found on the GitHub repository: https://github.com/polarisChen/GRMEC-SC.

Single-cell epigenomic dysregulation of Systemic Sclerosis fibroblasts via CREB1/EGR1 axis in self-assembled human skin equivalents

Systemic sclerosis (SSc) is an autoimmune disease characterized by skin fibrosis, internal organ involvement and vascular dropout. We previously developed and phenotypically characterized an in vitro 3D skin-like tissue model of SSc, and now analyze the transcriptomic (scRNA-seq) and epigenetic (scATAC-seq) characteristics of this model at single-cell resolution. SSc 3D skin-like tissues were fabricated using autologous fibroblasts, macrophages, and plasma from SSc patients or healthy control (HC) donors. SSc tissues displayed increased dermal thickness and contractility, as well as increased α-SMA staining. Single-cell transcriptomic and epigenomic analyses identified keratinocytes, macrophages, and five populations of fibroblasts (labeled FB1 - 5). Notably, FB1 APOE-expressing fibroblasts were 12-fold enriched in SSc tissues and were characterized by high EGR1 motif accessibility. Pseudotime analysis suggests that FB1 fibroblasts differentiate from a TGF-β1-responsive fibroblast population and ligand-receptor analysis indicates that the FB1 fibroblasts are active in macrophage crosstalk via soluble ligands including FGF2 and APP. These findings provide characterization of the 3D skin-like model at single cell resolution and establish that it recapitulates subsets of fibroblasts and macrophage phenotypes observed in skin biopsies.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data

Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference-target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.

NR4a1/2 deletion promotes accumulation of TCF1+ stem-like precursors of exhausted CD8+ T cells in the tumor microenvironment

T cell exhaustion impairs tumor immunity and contributes to resistance against immune checkpoint inhibitors. The nuclear receptor subfamily 4 group A (NR4a) family of nuclear receptors plays a crucial role in driving T cell exhaustion. In this study, we observe that NR4a1 and NR4a2 deficiency in CD8+ tumor-infiltrating lymphocytes (TILs) results in potent tumor eradication and exhibits not only reduced exhaustion characteristics but also an increase in the precursors/progenitors of exhausted T (Pre-Tex) cell fraction. Serial transfers of NR4a1-/-NR4a2-/-CD8+ TILs into tumor-bearing mice result in the expansion of TCF1+ (Tcf7+) stem-like Pre-Tex cells, whereas wild-type TILs are depleted upon secondary transfer. NR4a1/2-deficient CD8+ T cells express higher levels of stemness/memory-related genes and illustrate potent mitochondrial oxidative phosphorylation. Collectively, these findings suggest that inhibiting NR4a in tumors represents a potent immuno-oncotherapy strategy by increasing stem-like Pre-Tex cells and reducing exhaustion of CD8+ T cells.

Chronic hypoxia remodels the tumor microenvironment to support glioma stem cell growth

Cerebral organoids co-cultured with patient derived glioma stem cells (GLICOs) are an experimentally tractable research tool useful for investigating the role of the human brain tumor microenvironment in glioblastoma. Here we describe long-term GLICOs, a novel model in which COs are grown from embryonic stem cell cultures containing low levels of GSCs and tumor development is monitored over extended durations (ltGLICOs). Single-cell profiling of ltGLICOs revealed an unexpectedly long latency period prior to GSC expansion, and that normal organoid development was unimpaired by the presence of low numbers of GSCs. However, as organoids age they experience chronic hypoxia and oxidative stress which remodels the tumor microenvironment to promote GSC expansion. Receptor-ligand modelling identified astrocytes, which secreted various pro-tumorigenic ligands including FGF1, as the primary cell type for GSC crosstalk and single-cell multi-omic analysis revealed these astrocytes were under the control of ischemic regulatory networks. Functional validation confirmed hypoxia as a driver of pro-tumorigenic astrocytic ligand secretion and that GSC expansion was accelerated by pharmacological induction of oxidative stress. When controlled for genotype, the close association between glioma aggressiveness and patient age has very few proposed biological explanations. Our findings indicate that age-associated increases in cerebral vascular insufficiency and associated regional chronic cerebral hypoxia may contribute to this phenomenon.

PACS allows comprehensive dissection of multiple factors governing chromatin accessibility from snATAC-seq data

Single nucleus ATAC-seq (snATAC-seq) experimental designs have become increasingly complex with multiple factors that might affect chromatin accessibility, including genotype, cell type, tissue of origin, sample location, batch, etc., whose compound effects are difficult to test by existing methods. In addition, current snATAC-seq data present statistical difficulties due to their sparsity and variations in individual sequence capture. To address these problems, we present a zero-adjusted statistical model, Probability model of Accessible Chromatin of Single cells (PACS), that can allow complex hypothesis testing of factors that affect accessibility while accounting for sparse and incomplete data. For differential accessibility analysis, PACS controls the false positive rate and achieves on average a 17% to 122% higher power than existing tools. We demonstrate the effectiveness of PACS through several analysis tasks including supervised cell type annotation, compound hypothesis testing, batch effect correction, and spatiotemporal modeling. We apply PACS to several datasets from a variety of tissues and show its ability to reveal previously undiscovered insights in snATAC-seq data.

txci-ATAC-seq: a massive-scale single-cell technique to profile chromatin accessibility

We develop a large-scale single-cell ATAC-seq method by combining Tn5-based pre-indexing with 10× Genomics barcoding, enabling the indexing of up to 200,000 nuclei across multiple samples in a single reaction. We profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16-/-) model. Our study of CC16-/- nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.

Childhood cancer mutagenesis caused by transposase-derived PGBD5

Genomic rearrangements are a hallmark of most childhood tumors, including medulloblastoma, one of the most common brain tumors in children, but their causes remain largely unknown. Here, we show that PiggyBac transposable element derived 5 (Pgbd5) promotes tumor development in multiple developmentally accurate mouse models of Sonic Hedgehog (SHH) medulloblastoma. Most Pgbd5-deficient mice do not develop tumors, while maintaining normal cerebellar development. Ectopic activation of SHH signaling is sufficient to enforce cerebellar granule cell progenitor-like cell states, which exhibit Pgbd5-dependent expression of distinct DNA repair and neurodevelopmental factors. Mouse medulloblastomas expressing Pgbd5 have increased numbers of somatic structural DNA rearrangements, some of which carry PGBD5-specific sequences at their breakpoints. Similar sequence breakpoints recurrently affect somatic DNA rearrangements of known tumor suppressors and oncogenes in medulloblastomas in 329 children. This identifies PGBD5 as a medulloblastoma mutator and provides a genetic mechanism for the generation of oncogenic DNA rearrangements in childhood cancer.

Maternal inflammation regulates fetal emergency myelopoiesis

Neonates are highly susceptible to inflammation and infection. Here, we investigate how late fetal liver (FL) mouse hematopoietic stem and progenitor cells (HSPCs) respond to inflammation, testing the hypothesis that deficits in the engagement of emergency myelopoiesis (EM) pathways limit neutrophil output and contribute to perinatal neutropenia. We show that fetal HSPCs have limited production of myeloid cells at steady state and fail to activate a classical adult-like EM transcriptional program. Moreover, we find that fetal HSPCs can respond to EM-inducing inflammatory stimuli in vitro but are restricted by maternal anti-inflammatory factors, primarily interleukin-10 (IL-10), from activating EM pathways in utero. Accordingly, we demonstrate that the loss of maternal IL-10 restores EM activation in fetal HSPCs but at the cost of fetal demise. These results reveal the evolutionary trade-off inherent in maternal anti-inflammatory responses that maintain pregnancy but render the fetus unresponsive to EM activation signals and susceptible to infection.

The transcription factor NF-κB orchestrates nucleosome remodeling during the primary response to Toll-like receptor 4 signaling

Inducible nucleosome remodeling at hundreds of latent enhancers and several promoters shapes the transcriptional response to Toll-like receptor 4 (TLR4) signaling in macrophages. We aimed to define the identities of the transcription factors that promote TLR-induced remodeling. An analysis strategy based on ATAC-seq and single-cell ATAC-seq that enriched for genomic regions most likely to undergo remodeling revealed that the transcription factor nuclear factor κB (NF-κB) bound to all high-confidence peaks marking remodeling during the primary response to the TLR4 ligand, lipid A. Deletion of NF-κB subunits RelA and c-Rel resulted in the loss of remodeling at high-confidence ATAC-seq peaks, and CRISPR-Cas9 mutagenesis of NF-κB-binding motifs impaired remodeling. Remodeling selectivity at defined regions was conferred by collaboration with other inducible factors, including IRF3- and MAP-kinase-induced factors. Thus, NF-κB is unique among TLR4-activated transcription factors in its broad contribution to inducible nucleosome remodeling, alongside its ability to activate poised enhancers and promoters assembled into open chromatin.

Chronic SIV-Induced neuroinflammation disrupts CCR7+ CD4+ T cell immunosurveillance in the rhesus macaque brain

CD4+ T cells survey and maintain immune homeostasis in the brain, yet their differentiation states and functional capabilities remain unclear. Our approach, combining single-cell transcriptomic analysis, ATAC-Seq, spatial transcriptomics, and flow cytometry, revealed a distinct subset of CCR7+ CD4+ T cells resembling lymph node central memory (TCM) cells. We observed chromatin accessibility at the CCR7, CD28, and BCL-6 loci, defining molecular features of TCM. Brain CCR7+ CD4+ T cells exhibited recall proliferation and interleukin-2 production ex vivo, showcasing their functional competence. We identified the skull bone marrow as a local niche for these cells alongside CNS border tissues. Sequestering TCM cells in lymph nodes using FTY720 led to reduced CCR7+ CD4+ T cell frequencies in the cerebrospinal fluid, accompanied by increased monocyte levels and soluble markers indicating immune activation. In macaques chronically infected with SIVCL757 and experiencing viral rebound due to cessation of antiretroviral therapy, a decrease in brain CCR7+ CD4+ T cells was observed, along with increased microglial activation and initiation of neurodegenerative pathways. Our findings highlight a role for CCR7+ CD4+ T cells in CNS immune surveillance, and their decline during chronic SIV highlights their responsiveness to neuroinflammation.

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

Thalamocortical organoids enable in vitro modeling of 22q11.2 microdeletion associated with neuropsychiatric disorders

Thalamic dysfunction has been implicated in multiple psychiatric disorders. We sought to study the mechanisms by which abnormalities emerge in the context of the 22q11.2 microdeletion, which confers significant genetic risk for psychiatric disorders. We investigated early stages of human thalamus development using human pluripotent stem cell-derived organoids and show that the 22q11.2 microdeletion underlies widespread transcriptional dysregulation associated with psychiatric disorders in thalamic neurons and glia, including elevated expression of FOXP2. Using an organoid co-culture model, we demonstrate that the 22q11.2 microdeletion mediates an overgrowth of thalamic axons in a FOXP2-dependent manner. Finally, we identify ROBO2 as a candidate molecular mediator of the effects of FOXP2 overexpression on thalamic axon overgrowth. Together, our study suggests that early steps in thalamic development are dysregulated in a model of genetic risk for schizophrenia and contribute to neural phenotypes in 22q11.2 deletion syndrome.

Ex vivo expansion potential of murine hematopoietic stem cells is a rare property only partially predicted by phenotype

The scarcity of hematopoietic stem cells (HSCs) restricts their use in both clinical settings and experimental research. Here, we examined a recently developed method for expanding rigorously purified murine HSCs ex vivo. After 3 weeks of culture, only 0.1% of cells exhibited the input HSC phenotype, but these accounted for almost all functional long-term HSC activity. Input HSCs displayed varying potential for ex vivo self-renewal, with alternative outcomes revealed by single-cell multimodal RNA and ATAC sequencing profiling. While most HSC progeny offered only transient in vivo reconstitution, these cells efficiently rescued mice from lethal myeloablation. The amplification of functional HSC activity allowed for long-term multilineage engraftment in unconditioned hosts that associated with a return of HSCs to quiescence. Thereby, our findings identify several key considerations for ex vivo HSC expansion, with major implications also for assessment of normal HSC activity.

Safety, efficacy and determinants of response of allogeneic CD19-specific CAR-NK cells in CD19+ B cell tumors: a phase 1/2 trial

There is a pressing need for allogeneic chimeric antigen receptor (CAR)-immune cell therapies that are safe, effective and affordable. We conducted a phase 1/2 trial of cord blood-derived natural killer (NK) cells expressing anti-CD19 chimeric antigen receptor and interleukin-15 (CAR19/IL-15) in 37 patients with CD19+ B cell malignancies. The primary objectives were safety and efficacy, defined as day 30 overall response (OR). Secondary objectives included day 100 response, progression-free survival, overall survival and CAR19/IL-15 NK cell persistence. No notable toxicities such as cytokine release syndrome, neurotoxicity or graft-versus-host disease were observed. The day 30 and day 100 OR rates were 48.6% for both. The 1-year overall survival and progression-free survival were 68% and 32%, respectively. Patients who achieved OR had higher levels and longer persistence of CAR-NK cells. Receiving CAR-NK cells from a cord blood unit (CBU) with nucleated red blood cells ≤ 8 × 107 and a collection-to-cryopreservation time ≤ 24 h was the most significant predictor for superior outcome. NK cells from these optimal CBUs were highly functional and enriched in effector-related genes. In contrast, NK cells from suboptimal CBUs had upregulation of inflammation, hypoxia and cellular stress programs. Finally, using multiple mouse models, we confirmed the superior antitumor activity of CAR/IL-15 NK cells from optimal CBUs in vivo. These findings uncover new features of CAR-NK cell biology and underscore the importance of donor selection for allogeneic cell therapies. ClinicalTrials.gov identifier: NCT03056339 .

Nano-CUT&Tag for multimodal chromatin profiling at single-cell resolution

The ability to comprehensively analyze the chromatin state with single-cell resolution is crucial for understanding gene regulatory principles in heterogenous tissues or during development. Recently, we developed a nanobody-based single-cell CUT&Tag (nano-CT) protocol to simultaneously profile three epigenetic modalities-two histone marks and open chromatin state-from the same single cell. Nano-CT implements a new set of secondary nanobody-Tn5 fusion proteins to direct barcoded tagmentation by Tn5 transposase to genomic targets labeled by primary antibodies raised in different species. Such nanobody-Tn5 fusion proteins are currently not commercially available, and their in-house production and purification can be completed in 3-4 d by following our detailed protocol. The single-cell indexing in nano-CT is performed on a commercially available platform, making it widely accessible to the community. In comparison to other multimodal methods, nano-CT stands out in data complexity, low sample requirements and the flexibility to choose two of the three modalities. In addition, nano-CT works efficiently with fresh brain samples, generating multimodal epigenomic profiles for thousands of brain cells at single-cell resolution. The nano-CT protocol can be completed in just 3 d by users with basic skills in standard molecular biology and bioinformatics, although previous experience with single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) is beneficial for more in-depth data analysis. As a multimodal assay, nano-CT holds immense potential to reveal interactions of various chromatin modalities, to explore epigenetic heterogeneity and to increase our understanding of the role and interplay that chromatin dynamics has in cellular development.

Identification of a distal enhancer regulating hedgehog interacting protein gene in human lung epithelial cells

BACKGROUND

An intergenic region at chromosome 4q31 is one of the most significant regions associated with COPD susceptibility and lung function in GWAS. In this region, the implicated causal gene HHIP has a unique epithelial expression pattern in adult human lungs, in contrast to dominant expression in fibroblasts in murine lungs. However, the mechanism underlying the species-dependent cell type-specific regulation of HHIP remains largely unknown.

METHODS

We employed snATAC-seq analysis to identify open chromatin regions within the COPD GWAS region in various human lung cell types. ChIP-quantitative PCR, reporter assays, chromatin conformation capture assays and Hi-C assays were conducted to characterize the regulatory element in this region. CRISPR/Cas9-editing was performed in BEAS-2B cells to generate single colonies with stable knockout of the regulatory element. RT-PCR and Western blot assays were used to evaluate expression of HHIP and epithelial-mesenchymal transition (EMT)-related marker genes.

FINDINGS

We identified a distal enhancer within the COPD 4q31 GWAS locus that regulates HHIP transcription at baseline and after TGFβ treatment in a SMAD3-dependent, but Hedgehog-independent manner in human bronchial epithelial cells. The distal enhancer also maintains chromatin topological domains near 4q31 locus and HHIP gene. Reduced HHIP expression led to increased EMT induced by TGFβ in human bronchial epithelial cells.

INTERPRETATION

A distal enhancer regulates HHIP expression both under homeostatic condition and upon TGFβ treatment in human bronchial epithelial cells. The interaction between HHIP and TGFβ signalling possibly contributes to COPD pathogenesis.

FUNDING

Supported by NIH grants R01HL127200, R01HL148667 and R01HL162783 (to X. Z).

A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson's disease-associated glial changes

Age is the primary risk factor for Parkinson's disease (PD), but how aging changes the expression and regulatory landscape of the brain remains unclear. Here we present a single-nuclei multiomic study profiling shared gene expression and chromatin accessibility of young, aged and PD postmortem midbrain samples. Combined multiomic analysis along a pseudopathogenesis trajectory reveals that all glial cell types are affected by age, but microglia and oligodendrocytes are further altered in PD. We present evidence for a disease-associated oligodendrocyte subtype and identify genes lost over the aging and disease process, including CARNS1, that may predispose healthy cells to develop a disease-associated phenotype. Surprisingly, we found that chromatin accessibility changed little over aging or PD within the same cell types. Peak-gene association patterns, however, are substantially altered during aging and PD, identifying cell-type-specific chromosomal loci that contain PD-associated single-nucleotide polymorphisms. Our study suggests a previously undescribed role for oligodendrocytes in aging and PD.

Mechanisms of action and resistance in histone methylation-targeted therapy

Epigenomes enable the rectification of disordered cancer gene expression, thereby providing new targets for pharmacological interventions. The clinical utility of targeting histone H3 lysine trimethylation (H3K27me3) as an epigenetic hallmark has been demonstrated1-7. However, in actual therapeutic settings, the mechanism by which H3K27me3-targeting therapies exert their effects and the response of tumour cells remain unclear. Here we show the potency and mechanisms of action and resistance of the EZH1-EZH2 dual inhibitor valemetostat in clinical trials of patients with adult T cell leukaemia/lymphoma. Administration of valemetostat reduced tumour size and demonstrated durable clinical response in aggressive lymphomas with multiple genetic mutations. Integrative single-cell analyses showed that valemetostat abolishes the highly condensed chromatin structure formed by the plastic H3K27me3 and neutralizes multiple gene loci, including tumour suppressor genes. Nevertheless, subsequent long-term treatment encounters the emergence of resistant clones with reconstructed aggregate chromatin that closely resemble the pre-dose state. Acquired mutations at the PRC2-compound interface result in the propagation of clones with increased H3K27me3 expression. In patients free of PRC2 mutations, TET2 mutation or elevated DNMT3A expression causes similar chromatin recondensation through de novo DNA methylation in the H3K27me3-associated regions. We identified subpopulations with distinct metabolic and gene translation characteristics implicated in primary susceptibility until the acquisition of the heritable (epi)mutations. Targeting epigenetic drivers and chromatin homeostasis may provide opportunities for further sustained epigenetic cancer therapies.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

Evaluating the Utilities of Foundation Models in Single-cell Data Analysis

Foundation Models (FMs) have made significant strides in both industrial and scientific domains. In this paper, we evaluate the performance of FMs in single-cell sequencing data analysis through comprehensive experiments across eight downstream tasks pertinent to single-cell data. By comparing ten different single-cell FMs with task-specific methods, we found that single-cell FMs may not consistently excel in all tasks than task-specific methods. However, the emergent abilities and the successful applications of cross-species/cross-modality transfer learning of FMs are promising. In addition, we present a systematic evaluation of the effects of hyper-parameters, initial settings, and stability for training single-cell FMs based on a proposed scEval framework, and provide guidelines for pre-training and fine-tuning. Our work summarizes the current state of single-cell FMs and points to their constraints and avenues for future development.

SHARE-Topic: Bayesian interpretable modeling of single-cell multi-omic data

Multi-omic single-cell technologies, which simultaneously measure the transcriptional and epigenomic state of the same cell, enable understanding epigenetic mechanisms of gene regulation. However, noisy and sparse data pose fundamental statistical challenges to extract biological knowledge from complex datasets. SHARE-Topic, a Bayesian generative model of multi-omic single cell data using topic models, aims to address these challenges. SHARE-Topic identifies common patterns of co-variation between different omic layers, providing interpretable explanations for the data complexity. Tested on data from different technological platforms, SHARE-Topic provides low dimensional representations recapitulating known biology and defines associations between genes and distal regulators in individual cells.

Cross-Omic Transcription Factor Analysis: An Insight on Transcription Factor Accessibility and Expression Correlation

It is well known how sequencing technologies propelled cellular biology research in recent years, providing incredible insight into the basic mechanisms of cells. Single-cell RNA sequencing is at the front in this field, with single-cell ATAC sequencing supporting it and becoming more popular. In this regard, multi-modal technologies play a crucial role, allowing the possibility to simultaneously perform the mentioned sequencing modalities on the same cells. Yet, there still needs to be a clear and dedicated way to analyze these multi-modal data. One of the current methods is to calculate the Gene Activity Matrix (GAM), which summarizes the accessibility of the genes at the genomic level, to have a more direct link with the transcriptomic data. However, this concept is not well defined, and it is unclear how various accessible regions impact the expression of the genes. Moreover, the transcription process is highly regulated by the transcription factors that bind to the different DNA regions. Therefore, this work presents a continuation of the meta-analysis of Genomic-Annotated Gene Activity Matrix (GAGAM) contributions, aiming to investigate the correlation between the TF expression and motif information in the different functional genomic regions to understand the different Transcription Factors (TFs) dynamics involved in different cell types.