ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis

Determinants of renin cell differentiation: a single cell epi-transcriptomics approach

Rationale

Renin cells are essential for survival. They control the morphogenesis of the kidney arterioles, and the composition and volume of our extracellular fluid, arterial blood pressure, tissue perfusion, and oxygen delivery. It is known that renin cells and associated arteriolar cells descend from FoxD1 + progenitor cells, yet renin cells remain challenging to study due in no small part to their rarity within the kidney. As such, the molecular mechanisms underlying the differentiation and maintenance of these cells remain insufficiently understood.

Objective

We sought to comprehensively evaluate the chromatin states and transcription factors (TFs) that drive the differentiation of FoxD1 + progenitor cells into those that compose the kidney vasculature with a focus on renin cells.

Methods and Results

We isolated single nuclei of FoxD1 + progenitor cells and their descendants from FoxD1 ^cre/+ ; R26R-mTmG mice at embryonic day 12 (E12) (n _cells =1234), embryonic day 18 (E18) (n _cells =3696), postnatal day 5 (P5) (n _cells =1986), and postnatal day 30 (P30) (n _cells =1196). Using integrated scRNA-seq and scATAC-seq we established the developmental trajectory that leads to the mosaic of cells that compose the kidney arterioles, and specifically identified the factors that determine the elusive, myo-endocrine adult renin-secreting juxtaglomerular (JG) cell. We confirm the role of Nfix in JG cell development and renin expression, and identified the myocyte enhancer factor-2 (MEF2) family of TFs as putative drivers of JG cell differentiation.

Conclusions

We provide the first developmental trajectory of renin cell differentiation as they become JG cells in a single-cell atlas of kidney vascular open chromatin and highlighted novel factors important for their stage-specific differentiation. This improved understanding of the regulatory landscape of renin expressing JG cells is necessary to better learn the control and function of this rare cell population as overactivation or aberrant activity of the RAS is a key factor in cardiovascular and kidney pathologies.

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data

Single-cell analysis is a valuable approach for dissecting the cellular heterogeneity, and single-cell chromatin accessibility sequencing (scCAS) can profile the epigenetic landscapes for thousands of individual cells. It is challenging to analyze scCAS data, because of its high dimensionality and a higher degree of sparsity compared with scRNA-seq data. Topic modeling in single-cell data analysis can lead to robust identification of the cell types and it can provide insight into the regulatory mechanisms. Reference-guided approach may facilitate the analysis of scCAS data by utilizing the information in existing datasets. We present RefTM (Reference-guided Topic Modeling of single-cell chromatin accessibility data), which not only utilizes the information in existing bulk chromatin accessibility and annotated scCAS data, but also takes advantage of topic models for single-cell data analysis. RefTM simultaneously models: (1) the shared biological variation among reference data and the target scCAS data; (2) the unique biological variation in scCAS data; (3) other variations from known covariates in scCAS data.

Integration of spatial and single-cell data across modalities with weak linkage

single-cell sequencing methods have enabled the profiling of multiple types of molecular readouts at cellular resolution, and recent developments in spatial barcoding, in situ hybridization, and in situ sequencing allow such molecular readouts to retain their spatial context. Since no technology can provide complete characterization across all layers of biological modalities within the same cell, there is pervasive need for computational cross-modal integration (also called diagonal integration) of single-cell and spatial omics data. For current methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori "linked" features. When such linked features are few or uninformative, a scenario that we call "weak linkage", existing methods fail. We developed MaxFuse, a cross-modal data integration method that, through iterative co-embedding, data smoothing, and cell matching, leverages all information in each modality to obtain high-quality integration. MaxFuse is modality-agnostic and, through comprehensive benchmarks on single-cell and spatial ground-truth multiome datasets, demonstrates high robustness and accuracy in the weak linkage scenario. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, we demonstrate how MaxFuse enables the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

scMEGA: single-cell multi-omic enhancer-based gene regulatory network inference

Summary

The increasing availability of single-cell multi-omics data allows to quantitatively characterize gene regulation. We here describe scMEGA (Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference) that enables an end-to-end analysis of multi-omics data for gene regulatory network inference including modalities integration, trajectory analysis, enhancer-to-promoter association, network analysis and visualization. This enables to study the complex gene regulation mechanisms for dynamic biological processes, such as cellular differentiation and disease-driven cellular remodeling. We provide a case study on gene regulatory networks controlling myofibroblast activation in human myocardial infarction.

Availability and implementation

scMEGA is implemented in R, released under the MIT license and available from https://github.com/CostaLab/scMEGA. Tutorials are available from https://costalab.github.io/scMEGA.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

INKILN is a novel long noncoding RNA promoting vascular smooth muscle inflammation via scaffolding MKL1 and USP10

Background

Activation of vascular smooth muscle cells (VSMCs) inflammation is vital to initiate vascular disease. However, the role of human-specific long noncoding RNAs (lncRNAs) in VSMC inflammation is poorly understood.

Methods

Bulk RNA-seq in differentiated human VSMCs revealed a novel human-specific lncRNA called IN flammatory M K L1 I nteracting L ong N oncoding RNA ( INKILN ). INKILN expression was assessed in multiple in vitro and ex vivo models of VSMC phenotypic modulation and human atherosclerosis and abdominal aortic aneurysm (AAA) samples. The transcriptional regulation of INKILN was determined through luciferase reporter system and chromatin immunoprecipitation assay. Both loss- and gain-of-function approaches and multiple RNA-protein and protein-protein interaction assays were utilized to uncover the role of INKILN in VSMC proinflammatory gene program and underlying mechanisms. Bacterial Artificial Chromosome (BAC) transgenic (Tg) mice were utilized to study INKLIN expression and function in ligation injury-induced neointimal formation.

Results

INKILN expression is downregulated in contractile VSMCs and induced by human atherosclerosis and abdominal aortic aneurysm. INKILN is transcriptionally activated by the p65 pathway, partially through a predicted NF-κB site within its proximal promoter. INKILN activates the proinflammatory gene expression in cultured human VSMCs and ex vivo cultured vessels. Mechanistically, INKILN physically interacts with and stabilizes MKL1, a key activator of VSMC inflammation through the p65/NF-κB pathway. INKILN depletion blocks ILIβ-induced nuclear localization of both p65 and MKL1. Knockdown of INKILN abolishes the physical interaction between p65 and MKL1, and the luciferase activity of an NF-κB reporter. Further, INKILN knockdown enhances MKL1 ubiquitination, likely through the reduced physical interaction with the deubiquitinating enzyme, USP10. INKILN is induced in injured carotid arteries and exacerbates ligation injury-induced neointimal formation in BAC Tg mice.

Conclusions

These findings elucidate an important pathway of VSMC inflammation involving an INKILN /MKL1/USP10 regulatory axis. Human BAC Tg mice offer a novel and physiologically relevant approach for investigating human-specific lncRNAs under vascular disease conditions.

Chromatin Remodeling Drives Immune-Fibroblast Crosstalk in Heart Failure Pathogenesis

Chronic inflammation and tissue fibrosis are common stress responses that worsen organ function, yet the molecular mechanisms governing their crosstalk are poorly understood. In diseased organs, stress-induced changes in gene expression fuel maladaptive cell state transitions and pathological interaction between diverse cellular compartments. Although chronic fibroblast activation worsens dysfunction of lung, liver, kidney, and heart, and exacerbates many cancers, the stress-sensing mechanisms initiating the transcriptional activation of fibroblasts are not well understood. Here, we show that conditional deletion of the transcription co-activator Brd4 in Cx3cr1-positive myeloid cells ameliorates heart failure and is associated with a dramatic reduction in fibroblast activation. Analysis of single-cell chromatin accessibility and BRD4 occupancy in vivo in Cx3cr1-positive cells identified a large enhancer proximal to Interleukin-1 beta (Il1b), and a series of CRISPR deletions revealed the precise stress-dependent regulatory element that controlled expression of Il1b in disease. Secreted IL1B functioned non-cell autonomously to activate a p65/RELA-dependent enhancer near the transcription factor MEOX1, resulting in a profibrotic response in human cardiac fibroblasts. In vivo, antibody-mediated IL1B neutralization prevented stress-induced expression of MEOX1, inhibited fibroblast activation, and improved cardiac function in heart failure. The elucidation of BRD4-dependent crosstalk between a specific immune cell subset and fibroblasts through IL1B provides new therapeutic strategies for heart disease and other disorders of chronic inflammation and maladaptive tissue remodeling.

AgeAnno: a knowledgebase of single-cell annotation of aging in human

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of aging and elucidation of the detailed biological mechanisms of aging-related genes at the single-cell level can help to understand the heterogeneous aging process and design targeted anti-aging therapeutics. Here, we built AgeAnno (https://relab.xidian.edu.cn/AgeAnno/#/), a knowledgebase of single cell annotation of aging in human, aiming to provide comprehensive characterizations for aging-related genes across diverse tissue-cell types in human by using single-cell RNA and ATAC sequencing data (scRNA and scATAC). The current version of AgeAnno houses 1 678 610 cells from 28 healthy tissue samples with ages ranging from 0 to 110 years. We collected 5580 aging-related genes from previous resources and performed dynamic functional annotations of the cellular context. For the scRNA data, we performed analyses include differential gene expression, gene variation coefficient, cell communication network, transcription factor (TF) regulatory network, and immune cell proportionc. AgeAnno also provides differential chromatin accessibility analysis, motif/TF enrichment and footprint analysis, and co-accessibility peak analysis for scATAC data. AgeAnno will be a unique resource to systematically characterize aging-related genes across diverse tissue-cell types in human, and it could facilitate antiaging and aging-related disease research.

Macrophage inflammatory and regenerative response periodicity is programmed by cell cycle and chromatin state

Cell cycle (CC) facilitates cell division via robust, cyclical gene expression. Protective immunity requires the expansion of pathogen-responsive cell types, but whether CC confers unique gene expression programs that direct the subsequent immunological response remains unclear. Here, we demonstrate that single macrophages (MFs) adopt different plasticity states in CC, which leads to heterogeneous cytokine-induced polarization, priming, and repolarization programs. Specifically, MF plasticity to interferon gamma (IFNG) is substantially reduced during S-G2/M, whereas interleukin 4 (IL-4) induces S-G2/M-biased gene expression, mediated by CC-biased enhancers. Additionally, IL-4 polarization shifts the CC-phase distribution of MFs toward the G2/M phase, providing a subpopulation-specific mechanism for IL-4-induced, dampened IFNG responsiveness. Finally, we demonstrate CC-dependent MF responses in murine and human disease settings in vivo, including Th2-driven airway inflammation and pulmonary fibrosis, where MFs express an S-G2/M-biased tissue remodeling gene program. Therefore, MF inflammatory and regenerative responses are gated by CC in a cyclical, phase-dependent manner.

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data

SUMMARY

Recent innovations in single-cell chromatin accessibility sequencing (scCAS) have revolutionized the characterization of epigenomic heterogeneity. Estimation of the number of cell types is a crucial step for downstream analyses and biological implications. However, efforts to perform estimation specifically for scCAS data are limited. Here, we propose ASTER, an ensemble learning-based tool for accurately estimating the number of cell types in scCAS data. ASTER outperformed baseline methods in systematic evaluation on 27 datasets of various protocols, sizes, numbers of cell types, degrees of cell-type imbalance, cell states and qualities, providing valuable guidance for scCAS data analysis.

AVAILABILITY AND IMPLEMENTATION

ASTER along with detailed documentation is freely accessible at https://aster.readthedocs.io/ under the MIT License. It can be seamlessly integrated into existing scCAS analysis workflows. The source code is available at https://github.com/biox-nku/aster.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Aging-associated HELIOS deficiency in naive CD4+ T cells alters chromatin remodeling and promotes effector cell responses

Immune aging combines cellular defects in adaptive immunity with the activation of pathways causing a low-inflammatory state. Here we examined the influence of age on the kinetic changes in the epigenomic and transcriptional landscape induced by T cell receptor (TCR) stimulation in naive CD4+ T cells. Despite attenuated TCR signaling in older adults, TCR activation accelerated remodeling of the epigenome and induced transcription factor networks favoring effector cell differentiation. We identified increased phosphorylation of STAT5, at least in part due to aberrant IL-2 receptor and lower HELIOS expression, as upstream regulators. Human HELIOS-deficient, naive CD4+ T cells, when transferred into human-synovium-mouse chimeras, infiltrated tissues more efficiently. Inhibition of IL-2 or STAT5 activity in T cell responses of older adults restored the epigenetic response pattern to the one seen in young adults. In summary, reduced HELIOS expression in non-regulatory naive CD4+ T cells in older adults directs T cell fate decisions toward inflammatory effector cells that infiltrate tissue.

Destin2: Integrative and cross-modality analysis of single-cell chromatin accessibility data

We propose Destin2, a novel statistical and computational method for cross-modality dimension reduction, clustering, and trajectory reconstruction for single-cell ATAC-seq data. The framework integrates cellular-level epigenomic profiles from peak accessibility, motif deviation score, and pseudo-gene activity and learns a shared manifold using the multimodal input, followed by clustering and/or trajectory inference. We apply Destin2 to real scATAC-seq datasets with both discretized cell types and transient cell states and carry out benchmarking studies against existing methods based on unimodal analyses. Using cell-type labels transferred with high confidence from unmatched single-cell RNA sequencing data, we adopt four performance assessment metrics and demonstrate how Destin2 corroborates and improves upon existing methods. Using single-cell RNA and ATAC multiomic data, we further exemplify how Destin2's cross-modality integrative analyses preserve true cell-cell similarities using the matched cell pairs as ground truths. Destin2 is compiled as a freely available R package available at https://github.com/yuchaojiang/Destin2.

Characterizing cis-regulatory elements using single-cell epigenomics

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

maxATAC: Genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks

Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge highlighted the value of chromatin accessibility data to TFBS prediction, establishing state-of-the-art methods for TFBS prediction from DNase-seq. However, the more recent Assay-for-Transposase-Accessible-Chromatin (ATAC)-seq has surpassed DNase-seq as the most widely-used chromatin accessibility profiling method. Furthermore, ATAC-seq is the only such technique available at single-cell resolution from standard commercial platforms. While ATAC-seq datasets grow exponentially, suboptimal motif scanning is unfortunately the most common method for TFBS prediction from ATAC-seq. To enable community access to state-of-the-art TFBS prediction from ATAC-seq, we (1) curated an extensive benchmark dataset (127 TFs) for ATAC-seq model training and (2) built "maxATAC", a suite of user-friendly, deep neural network models for genome-wide TFBS prediction from ATAC-seq in any cell type. With models available for 127 human TFs, maxATAC is the largest collection of high-performance TFBS prediction models for ATAC-seq. maxATAC performance extends to primary cells and single-cell ATAC-seq, enabling improved TFBS prediction in vivo. We demonstrate maxATAC's capabilities by identifying TFBS associated with allele-dependent chromatin accessibility at atopic dermatitis genetic risk loci.

resVAE ensemble: Unsupervised identification of gene sets in multi-modal single-cell sequencing data using deep ensembles

Feature identification and manual inspection is currently still an integral part of biological data analysis in single-cell sequencing. Features such as expressed genes and open chromatin status are selectively studied in specific contexts, cell states or experimental conditions. While conventional analysis methods construct a relatively static view on gene candidates, artificial neural networks have been used to model their interactions after hierarchical gene regulatory networks. However, it is challenging to identify consistent features in this modeling process due to the inherently stochastic nature of these methods. Therefore, we propose using ensembles of autoencoders and subsequent rank aggregation to extract consensus features in a less biased manner. Here, we performed sequencing data analyses of different modalities either independently or simultaneously as well as with other analysis tools. Our resVAE ensemble method can successfully complement and find additional unbiased biological insights with minimal data processing or feature selection steps while giving a measurement of confidence, especially for models using stochastic or approximation algorithms. In addition, our method can also work with overlapping clustering identity assignment suitable for transitionary cell types or cell fates in comparison to most conventional tools.

Deciphering the distinct transcriptomic and gene regulatory map in adult macaque basal ganglia cells

BACKGROUND

The basal ganglia are a complex of interconnected subcortical structures located beneath the mammalian cerebral cortex. The degeneration of dopaminergic neurons in the basal ganglia is the primary pathological feature of Parkinson's disease. Due to a lack of integrated analysis of multiomics datasets across multiple basal ganglia brain regions, very little is known about the regulatory mechanisms of this area.

FINDINGS

We utilized high-throughput transcriptomic and epigenomic analysis to profile over 270,000 single-nucleus cells to create a cellular atlas of the basal ganglia, characterizing the cellular composition of 4 regions of basal ganglia in adult macaque brain, including the striatum, substantia nigra (SN), globus pallidum, and amygdala. We found a distinct epigenetic regulation on gene expression of neuronal and nonneuronal cells across regions in basal ganglia. We identified a cluster of SN-specific astrocytes associated with neurodegenerative diseases and further explored the conserved and primate-specific transcriptomics in SN cell types across human, macaque, and mouse. Finally, we integrated our epigenetic landscape of basal ganglia cells with human disease heritability and identified a regulatory module consisting of candidate cis-regulatory elements that are specific to medium spiny neurons and associated with schizophrenia.

CONCLUSIONS

In general, our macaque basal ganglia atlas provides valuable insights into the comprehensive transcriptome and epigenome of the most important and populous cell populations in the macaque basal ganglia. We have identified 49 cell types based on transcriptomic profiles and 47 cell types based on epigenomic profiles, some of which exhibit region specificity, and characterized the molecular relationships underlying these brain regions.

Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease

To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We contrasted regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts, which enabled optimization of in vitro differentiation of epicardial cells. Further, we interpreted sequence based deep learning models of cell-type-resolved chromatin accessibility profiles to decipher underlying TF motif lexicons. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in congenital heart disease (CHD) cases vs. controls. In vitro studies in iPSCs validated the functional impact of identified variation on the predicted developmental cell types. This work thus defines the cell-type-resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements in CHD.

Temporal molecular program of human hematopoietic stem and progenitor cells after birth

Hematopoietic stem and progenitor cells (HSPCs) give rise to the blood system and maintain hematopoiesis throughout the human lifespan. Here, we report a transcriptional census of human bone-marrow-derived HSPCs from the neonate, infant, child, adult, and aging stages, showing two subpopulations of multipotent progenitors separated by CD52 expression. From birth to the adult stage, stem and multipotent progenitors shared similar transcriptional alterations, and erythroid potential was enhanced after the infant stage. By integrating transcriptome, chromatin accessibility, and functional data, we further showed that aging hematopoietic stem cells (HSCs) exhibited a bias toward megakaryocytic differentiation. Finally, in comparison with the HSCs from the cord blood, neonate bone-marrow-derived HSCs were more quiescent and had higher long-term regeneration capability and durable self-renewal. Taken together, this work provides an integral transcriptome landscape of HSPCs and identifies their dynamics in post-natal steady-state hemopoiesis, thereby helping explore hematopoiesis in development and diseases.

scATAC-Seq reveals heterogeneity associated with spermatogonial differentiation in cultured male germline stem cells

Spermatogonial stem cells are the most primitive spermatogonia in testis, which can self-renew to maintain the stem cell pool or differentiate to give rise to germ cells including haploid spermatids. All-trans-retinoic acid (RA), a bioactive metabolite of vitamin A, plays a fundamental role in initiating spermatogonial differentiation. In this study, single-cell ATAC-seq (scATAC-seq) was used to obtain genome-wide chromatin maps of cultured germline stem cells (GSCs) that were in control and RA-induced differentiation states. We showed that different subsets of GSCs can be distinguished based on chromatin accessibility of self-renewal and differentiation signature genes. Importantly, both progenitors and a subset of stem cells are able to respond to RA and give rise to differentiating cell subsets with distinct chromatin accessibility profiles. In this study, we identified regulatory regions that undergo chromatin remodeling and are associated with the retinoic signaling pathway. Moreover, we reconstructed the differentiation trajectory and identified novel transcription factor candidates enriched in different spermatogonia subsets. Collectively, our work provides a valuable resource for understanding the heterogeneity associated with differentiation and RA response in GSCs.

Chromatin accessibility illuminates single-cell regulatory dynamics of rice root tips

BACKGROUND

Root development and function have central roles in plant adaptation to the environment. The modification of root traits has additionally been a major driver of crop performance since the green revolution; however, the molecular underpinnings and the regulatory programmes defining root development and response to environmental stress remain largely unknown. Single-cell reconstruction of gene regulatory programmes provides an important tool to understand the cellular phenotypic variation in complex tissues and their response to endogenous and environmental stimuli. While single-cell transcriptomes of several plant organs have been elucidated, the underlying chromatin landscapes associated with cell type-specific gene expression remain largely unexplored.

RESULTS

To comprehensively delineate chromatin accessibility during root development of an important crop, we applied single-cell ATAC-seq (scATAC-seq) to 46,758 cells from rice root tips under normal and heat stress conditions. Our data revealed cell type-specific accessibility variance across most of the major cell types and allowed us to identify sets of transcription factors which associate with accessible chromatin regions (ACRs). Using root hair differentiation as a model, we demonstrate that chromatin and gene expression dynamics during cell type differentiation correlate in pseudotime analyses. In addition to developmental trajectories, we describe chromatin responses to heat and identify cell type-specific accessibility changes to this key environmental stimulus.

CONCLUSIONS

We report chromatin landscapes during rice root development at single-cell resolution. Our work provides a framework for the integrative analysis of regulatory dynamics in this important crop organ at single-cell resolution.

A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates

We present a multiomic cell atlas of human lung development that combines single-cell RNA and ATAC sequencing, high-throughput spatial transcriptomics, and single-cell imaging. Coupling single-cell methods with spatial analysis has allowed a comprehensive cellular survey of the epithelial, mesenchymal, endothelial, and erythrocyte/leukocyte compartments from 5-22 post-conception weeks. We identify previously uncharacterized cell states in all compartments. These include developmental-specific secretory progenitors and a subtype of neuroendocrine cell related to human small cell lung cancer. Our datasets are available through our web interface (https://lungcellatlas.org). To illustrate its general utility, we use our cell atlas to generate predictions about cell-cell signaling and transcription factor hierarchies which we rigorously test using organoid models.

LY6D marks pre-existing resistant basosquamous tumor subpopulations

Improved response to canonical therapies requires a mechanistic understanding of dynamic tumor heterogeneity by identifying discrete cellular populations with enhanced cellular plasticity. We have previously demonstrated distinct resistance mechanisms in skin basal cell carcinomas, but a comprehensive understanding of the cellular states and markers associated with these populations remains poorly understood. Here we identify a pre-existing resistant cellular population in naive basal cell carcinoma tumors marked by the surface marker LY6D. LY6D+ tumor cells are spatially localized and possess basal cell carcinoma and squamous cell carcinoma-like features. Using computational tools, organoids, and spatial tools, we show that LY6D+ basosquamous cells represent a persister population lying on a central node along the skin lineage-associated spectrum of epithelial states with local environmental and applied therapies determining the kinetics of accumulation. Surprisingly, LY6D+ basosquamous populations exist in many epithelial tumors, such as pancreatic adenocarcinomas, which have poor outcomes. Overall, our results identify the resistant LY6D+ basosquamous population as an important clinical target and suggest strategies for future therapeutic approaches to target them.

Loss of Epigenetic Regulation Disrupts Lineage Integrity, Induces Aberrant Alveogenesis, and Promotes Breast Cancer

Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent "long-tail" breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 ("EpiDrivers"), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology.

SIGNIFICANCE

Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis. This article is highlighted in the In This Issue feature, p. 2711.

Human fetal cerebellar cell atlas informs medulloblastoma origin and oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumour1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3-5 have not fully defined the compositional heterogeneity of MBs. Here we undertook single-cell profiling of freshly isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group 3 and metastatic tumours. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group 3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group 3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group 3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs show potential cell populations predisposed to transformation and regulatory circuitries underlying tumour cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

Acly Deficiency Enhances Myelopoiesis through Acetyl Coenzyme A and Metabolic-Epigenetic Cross-Talk

Hematopoiesis integrates cytokine signaling, metabolism, and epigenetic modifications to regulate blood cell generation. These processes are linked, as metabolites provide essential substrates for epigenetic marks. In this study, we demonstrate that ATP citrate lyase (Acly), which metabolizes citrate to generate cytosolic acetyl-CoA and is of clinical interest, can regulate chromatin accessibility to limit myeloid differentiation. Acly was tested for a role in murine hematopoiesis by small-molecule inhibition or genetic deletion in lineage-depleted, c-Kit-enriched hematopoietic stem and progenitor cells from Mus musculus. Treatments increased the abundance of cell populations that expressed the myeloid integrin CD11b and other markers of myeloid differentiation. When single-cell RNA sequencing was performed, we found that Acly inhibitor-treated hematopoietic stem and progenitor cells exhibited greater gene expression signatures for macrophages and enrichment of these populations. Similarly, the single-cell assay for transposase-accessible chromatin sequencing showed increased chromatin accessibility at genes associated with myeloid differentiation, including CD11b, CD11c, and IRF8. Mechanistically, Acly deficiency altered chromatin accessibility and expression of multiple C/EBP family transcription factors known to regulate myeloid differentiation and cell metabolism, with increased Cebpe and decreased Cebpa and Cebpb. This effect of Acly deficiency was accompanied by altered mitochondrial metabolism with decreased mitochondrial polarization but increased mitochondrial content and production of reactive oxygen species. The bias to myeloid differentiation appeared due to insufficient generation of acetyl-CoA, as exogenous acetate to support alternate compensatory pathways to produce acetyl-CoA reversed this phenotype. Acly inhibition thus can promote myelopoiesis through deprivation of acetyl-CoA and altered histone acetylome to regulate C/EBP transcription factor family activity for myeloid differentiation.

Multiomic analysis reveals conservation of cancer-associated fibroblast phenotypes across species and tissue of origin

Cancer-associated fibroblasts (CAFs) are integral to the solid tumor microenvironment. CAFs were once thought to be a relatively uniform population of matrix-producing cells, but single-cell RNA sequencing has revealed diverse CAF phenotypes. Here, we further probed CAF heterogeneity with a comprehensive multiomics approach. Using paired, same-cell chromatin accessibility and transcriptome analysis, we provided an integrated analysis of CAF subpopulations over a complex spatial transcriptomic and proteomic landscape to identify three superclusters: steady state-like (SSL), mechanoresponsive (MR), and immunomodulatory (IM) CAFs. These superclusters are recapitulated across multiple tissue types and species. Selective disruption of underlying mechanical force or immune checkpoint inhibition therapy results in shifts in CAF subpopulation distributions and affected tumor growth. As such, the balance among CAF superclusters may have considerable translational implications. Collectively, this research expands our understanding of CAF biology, identifying regulatory pathways in CAF differentiation and elucidating therapeutic targets in a species- and tumor-agnostic manner.

Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution

Human brain development is underpinned by cellular and molecular reconfigurations continuing into the third decade of life. To reveal cell dynamics orchestrating neural maturation, we profiled human prefrontal cortex gene expression and chromatin accessibility at single-cell resolution from gestation to adulthood. Integrative analyses define the dynamic trajectories of each cell type, revealing major gene expression reconfiguration at the prenatal-to-postnatal transition in all cell types followed by continuous reconfiguration into adulthood and identifying regulatory networks guiding cellular developmental programs, states, and functions. We uncover links between expression dynamics and developmental milestones, characterize the diverse timing of when cells acquire adult-like states, and identify molecular convergence from distinct developmental origins. We further reveal cellular dynamics and their regulators implicated in neurological disorders. Finally, using this reference, we benchmark cell identities and maturation states in organoid models. Together, this captures the dynamic regulatory landscape of human cortical development.

Spatially resolved gene regulatory and disease-related vulnerability map of the adult Macaque cortex

Single cell approaches have increased our knowledge about the cell type composition of the non-human primate (NHP), but a detailed characterization of area-specific regulatory features remains outstanding. We generated single-cell transcriptomic and chromatin accessibility (single-cell ATAC) data of 358,237 cells from prefrontal cortex (PFC), primary motor cortex (M1) and primary visual cortex (V1) of adult female cynomolgus monkey brain, and integrated this dataset with Stereo-seq (spatial enhanced resolution omics-sequencing) of the corresponding cortical areas to assign topographic information to molecular states. We identified area-specific chromatin accessible sites and their targeted genes, including the cell type-specific transcriptional regulatory network associated with excitatory neurons heterogeneity. We reveal calcium ion transport and axon guidance genes related to specialized functions of PFC and M1, identified the similarities and differences between adult macaque and human oligodendrocyte trajectories, and mapped the genetic variants and gene perturbations of human diseases to NHP cortical cells. This resource establishes a transcriptomic and chromatin accessibility combinatory regulatory landscape at a single-cell and spatially resolved resolution in NHP cortex.

Single-cell multiomics identifies clinically relevant mesenchymal stem-like cells and key regulators for MPNST malignancy

Malignant peripheral nerve sheath tumor (MPNST), a highly aggressive Schwann cell (SC)-derived soft tissue sarcoma, arises from benign neurofibroma (NF); however, the identity, heterogeneity and origins of tumor populations remain elusive. Nestin+ cells have been implicated as tumor stem cells in MPNST; unexpectedly, single-cell profiling of human NF and MPNST and their animal models reveal a broad range of nestin-expressing SC lineage cells and dynamic acquisition of discrete cancer states during malignant transformation. We uncover a nestin-negative mesenchymal neural crest-like subpopulation as a previously unknown malignant stem-like state common to murine and human MPNSTs, which correlates with clinical severity. Integrative multiomics profiling further identifies unique regulatory networks and druggable targets against the malignant subpopulations in MPNST. Targeting key epithelial-mesenchymal transition and stemness regulators including ZEB1 and ALDH1A1 impedes MPNST growth. Together, our studies reveal the underlying principles of tumor cell-state evolution and their regulatory circuitries during NF-to-MPNST transformation, highlighting a hitherto unrecognized mesenchymal stem-like subpopulation in MPNST disease progression.

Divergent clonal differentiation trajectories of T cell exhaustion

Chronic antigen exposure during viral infection or cancer promotes an exhausted T cell (Tex) state with reduced effector function. However, whether all antigen-specific T cell clones follow the same Tex differentiation trajectory remains unclear. Here, we generate a single-cell multiomic atlas of T cell exhaustion in murine chronic viral infection that redefines Tex phenotypic diversity, including two late-stage Tex subsets with either a terminal exhaustion (Texterm) or a killer cell lectin-like receptor-expressing cytotoxic (TexKLR) phenotype. We use paired single-cell RNA and T cell receptor sequencing to uncover clonal differentiation trajectories of Texterm-biased, TexKLR-biased or divergent clones that acquire both phenotypes. We show that high T cell receptor signaling avidity correlates with Texterm, whereas low avidity correlates with effector-like TexKLR fate. Finally, we identify similar clonal differentiation trajectories in human tumor-infiltrating lymphocytes. These findings reveal clonal heterogeneity in the T cell response to chronic antigen that influences Tex fates and persistence.

IReNA: Integrated regulatory network analysis of single-cell transcriptomes and chromatin accessibility profiles

Recently, single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) have been developed to separately measure transcriptomes and chromatin accessibility profiles at the single-cell resolution. However, few methods can reliably integrate these data to perform regulatory network analysis. Here, we developed integrated regulatory network analysis (IReNA) for network inference through the integrated analysis of scRNA-seq and scATAC-seq data, network modularization, transcription factor enrichment, and construction of simplified intermodular regulatory networks. Using public datasets, we showed that integrated network analysis of scRNA-seq data with scATAC-seq data is more precise to identify known regulators than scRNA-seq data analysis alone. Moreover, IReNA outperformed currently available methods in identifying known regulators. IReNA facilitates the systems-level understanding of biological regulatory mechanisms and is available at https://github.com/jiang-junyao/IReNA.

In situ tools for chromatin structural epigenomics

Technological progress over the past 15 years has fueled an explosion in genome-wide chromatin profiling tools that take advantage of low-cost short-read sequencing technologies to map particular chromatin features. Here, we survey the recent development of epigenomic tools that provide precise positions of chromatin proteins genome-wide in intact cells or nuclei. Some profiling tools are based on tethering Micrococcal Nuclease to chromatin proteins of interest in situ, whereas others similarly tether Tn5 transposase to integrate DNA sequencing adapters (tagmentation) and so eliminate the need for library preparation. These in situ cleavage and tagmentation tools have gained in popularity over the past few years, with many protocol enhancements and adaptations for single-cell and spatial chromatin profiling. The application of experimental and computational tools to address problems in gene regulation, eukaryotic development, and human disease are helping to define the emerging field of chromatin structural epigenomics.

Targeting cathepsin B by cycloastragenol enhances antitumor immunity of CD8 T cells via inhibiting MHC-I degradation

BACKGROUND

The loss of tumor antigens and depletion of CD8 T cells caused by the PD-1/PD-L1 pathway are important factors for tumor immune escape. In recent years, there has been increasing research on traditional Chinese medicine in tumor treatment. Cycloastragenol (CAG), an effective active molecule in Astragalus membranaceus, has been found to have antiviral, anti-aging, anti-inflammatory, and other functions. However, its antitumor effect and mechanism are not clear.

METHODS

The antitumor effect of CAG was investigated in MC38 and CT26 mouse transplanted tumor models. The antitumor effect of CAG was further analyzed via single-cell multiomics sequencing. Target responsive accessibility profiling technology was used to find the target protein of CAG. Subsequently, the antitumor mechanism of CAG was explored using confocal microscopy, coimmunoprecipitation and transfection of mutant plasmids. Finally, the combined antitumor effect of CAG and PD-1 antibodies in mice or organoids were investigated.

RESULTS

We found that CAG effectively inhibited tumor growth in vivo. Our single-cell multiomics atlas demonstrated that CAG promoted the presentation of tumor cell-surface antigens and was characterized by the enhanced killing function of CD8⁺ T cells. Mechanistically, CAG bound to its target protein cathepsin B, which then inhibited the lysosomal degradation of major histocompatibility complex I (MHC-I) and promoted the aggregation of MHC-I to the cell membrane, boosting the presentation of the tumor antigen. Meanwhile, the combination of CAG with PD-1 antibody effectively enhanced the tumor killing ability of CD8⁺ T cells in xenograft mice and colorectal cancer organoids.

CONCLUSION

Our data reported for the first time that cathepsin B downregulation confers antitumor immunity and explicates the antitumor mechanism of natural product CAG.

Dynamic changes in chromatin accessibility are associated with the atherogenic transitioning of vascular smooth muscle cells

AIMS

De-differentiation and activation of pro-inflammatory pathways are key transitions vascular smooth muscle cells (SMCs) make during atherogenesis. Here, we explored the upstream regulators of this 'atherogenic transition'.

METHODS AND RESULTS

Genome-wide sequencing studies, including Assay for Transposase-Accessible Chromatin using sequencing and RNA-seq, were performed on cells isolated from both murine SMC-lineage-tracing models of atherosclerosis and human atherosclerotic lesions. At the bulk level, alterations in chromatin accessibility were associated with the atherogenic transitioning of lesional SMCs, especially in relation to genes that govern differentiation status and complement-dependent inflammation. Using computational biology, we observed that a transcription factor previously related to coronary artery disease, Activating transcription factor 3 (ATF3), was predicted to be an upstream regulator of genes altered during the transition. At the single-cell level, our results indicated that ATF3 is a key repressor of SMC transitioning towards the subset of cells that promote vascular inflammation by activating the complement cascade. The expression of ATF3 and complement component C3 was negatively correlated in SMCs from human atherosclerotic lesions, suggesting translational relevance. Phenome-wide association studies indicated that genetic variation that results in reduced expression of ATF3 is correlated with an increased risk for atherosclerosis, and the expression of ATF3 was significantly down-regulated in humans with advanced vascular disease.

CONCLUSION

Our study indicates that the plasticity of atherosclerotic SMCs may in part be explained by dynamic changes in their chromatin architecture, which in turn may contribute to their maladaptive response to inflammation-induced stress.

Sex Differences in the Molecular Programs of Pancreatic Cells Contribute to the Differential Risks of Type 2 Diabetes

Epidemiology studies demonstrate that women are at a significantly lower risk of developing type 2 diabetes (T2D) compared to men. However, the molecular basis of this risk difference is not well understood. In this study, we examined the sex differences in the genetic programs of pancreatic endocrine cells. We combined pancreas perifusion data and single-cell genomic data from our laboratory and from publicly available data sets to investigate multiple axes of the sex differences in the human pancreas at the single-cell type and single-cell level. We systematically compared female and male islet secretion function, gene expression program, and regulatory principles of pancreatic endocrine cells. The perifusion data indicate that female endocrine cells have a higher secretion capacity than male endocrine cells. Single-cell RNA-sequencing analysis suggests that endocrine cells in male controls have molecular signatures that resemble T2D. In addition, we identified genomic elements associated with genome-wide association study T2D loci to have differential accessibility between female and male delta cells. These genomic elements may play a sex-specific causal role in the pathogenesis of T2D. We provide molecular mechanisms that explain the differential risk of T2D between women and men. Knowledge gained from our study will accelerate the development of diagnostics and therapeutics in sex-aware precision medicine for diabetes.

Highly sensitive single-cell chromatin accessibility assay and transcriptome coassay with METATAC

The thriving field of single-cell genomics allows researchers to dissect the complexity and heterogeneity of tissues at single-cell resolution at large scale, involving transcriptome and epigenome. However, single-cell chromatin accessibility profiling methods exhibit low sensitivity. Here, we increased accessible chromatin detection sensitivity in single cells with METATAC, a single-cell ATAC-seq technique, with the help of META amplification strategy and other biochemical modifications. METATAC reached the highest accessible chromatin region detection efficiency compared with existing techniques, allowing more accurate cis-regulatory element coaccessibility measurement and allele-specific chromatin accessibility analysis in complex tissue samples. In combination with a high-resolution single-cell RNA sequencing assay, we further developed a high-sensitivity joint single-cell ATAC–RNA strategy, which helps us to better resolve gene regulatory programs.

Recent advances in single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) and its coassays have transformed the field of single-cell epigenomics and transcriptomics. However, the low detection efficiency of current methods has limited our understanding of the true complexity of chromatin accessibility and its relationship with gene expression in single cells. Here, we report a high-sensitivity scATAC-seq method, termed multiplexed end-tagging amplification of transposase accessible chromatin (METATAC), which detects a large number of accessible sites per cell and is compatible with automation. Our high detectability and statistical framework allowed precise linking of enhancers to promoters without merging single cells. We systematically investigated allele-specific accessibility in the mouse cerebral cortex, revealing allele-specific accessibility of promotors of certain imprinted genes but biallelic accessibility of their enhancers. Finally, we combined METATAC with our high-sensitivity single-cell RNA sequencing (scRNA-seq) method, multiple annealing and looping based amplification cycles for digital transcriptomics (MALBAC-DT), to develop a joint ATAC–RNA assay, termed METATAC and MALBAC-DT coassay by sequencing (M2C-seq). M2C-seq achieved significant improvements for both ATAC and RNA compared with previous methods, with consistent performance across cell lines and early mouse embryos.

A multi-omics approach to visualize early neuronal differentiation from hESCs in 4D

Neuronal differentiation of pluripotent stem cells is an established method to study physiology, disease, and medication safety. However, the sequence of events in human neuronal differentiation and the ability of in vitro models to recapitulate early brain development are poorly understood. We developed a protocol optimized for the study of early human brain development and neuropharmacological applications. We comprehensively characterized gene expression and epigenetic profiles at four timepoints, because the cells differentiate from embryonic stem cells towards a heterogeneous population of progenitors, immature and mature neurons bearing telencephalic signatures. A multi-omics roadmap of neuronal differentiation, combined with searchable interactive gene analysis tools, allows for extensive exploration of early neuronal development and the effect of medications.

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Multi-omics charting a new neuronal differentiation protocol for human ES cells

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Single-cell analyses reveal marker genes during neuronal differentiation

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Identified transcriptional waves similar to early human brain development

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Searchable tools to visualize single-cell gene expression and chromatin state

Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation

Somatic mutations in cancer genes have been detected in clonal expansions across healthy human tissue, including in clonal hematopoiesis. However, because mutated and wild-type cells are admixed, we have limited ability to link genotypes with phenotypes. To overcome this limitation, we leveraged multi-modality single-cell sequencing, capturing genotype, transcriptomes and methylomes in progenitors from individuals with DNMT3A R882 mutated clonal hematopoiesis. DNMT3A mutations result in myeloid over lymphoid bias, and an expansion of immature myeloid progenitors primed toward megakaryocytic-erythroid fate, with dysregulated expression of lineage and leukemia stem cell markers. Mutated DNMT3A leads to preferential hypomethylation of polycomb repressive complex 2 targets and a specific CpG flanking motif. Notably, the hypomethylation motif is enriched in binding motifs of key hematopoietic transcription factors, serving as a potential mechanistic link between DNMT3A mutations and aberrant transcriptional phenotypes. Thus, single-cell multi-omics paves the road to defining the downstream consequences of mutations that drive clonal mosaicism.

scATACpipe: A nextflow pipeline for comprehensive and reproducible analyses of single cell ATAC-seq data

Single cell ATAC-seq (scATAC-seq) has become the most widely used method for profiling open chromatin landscape of heterogeneous cell populations at a single-cell resolution. Although numerous software tools and pipelines have been developed, an easy-to-use, scalable, reproducible, and comprehensive pipeline for scATAC-seq data analyses is still lacking. To fill this gap, we developed scATACpipe, a Nextflow pipeline, for performing comprehensive analyses of scATAC-seq data including extensive quality assessment, preprocessing, dimension reduction, clustering, peak calling, differential accessibility inference, integration with scRNA-seq data, transcription factor activity and footprinting analysis, co-accessibility inference, and cell trajectory prediction. scATACpipe enables users to perform the end-to-end analysis of scATAC-seq data with three sub-workflow options for preprocessing that leverage 10x Genomics Cell Ranger ATAC software, the ultra-fast Chromap procedures, and a set of custom scripts implementing current best practices for scATAC-seq data preprocessing. The pipeline extends the R package ArchR for downstream analysis with added support to any eukaryotic species with an annotated reference genome. Importantly, scATACpipe generates an all-in-one HTML report for the entire analysis and outputs cluster-specific BAM, BED, and BigWig files for visualization in a genome browser. scATACpipe eliminates the need for users to chain different tools together and facilitates reproducible and comprehensive analyses of scATAC-seq data from raw reads to various biological insights with minimal changes of configuration settings for different computing environments or species. By applying it to public datasets, we illustrated the utility, flexibility, versatility, and reliability of our pipeline, and demonstrated that our scATACpipe outperforms other workflows.

Single cell atlas of spinal cord injury in mice reveals a pro-regenerative signature in spinocerebellar neurons

After spinal cord injury, tissue distal to the lesion contains undamaged cells that could support or augment recovery. Targeting these cells requires a clearer understanding of their injury responses and capacity for repair. Here, we use single nucleus RNA sequencing to profile how each cell type in the lumbar spinal cord changes after a thoracic injury in mice. We present an atlas of these dynamic responses across dozens of cell types in the acute, subacute, and chronically injured spinal cord. Using this resource, we find rare spinal neurons that express a signature of regeneration in response to injury, including a major population that represent spinocerebellar projection neurons. We characterize these cells anatomically and observed axonal sparing, outgrowth, and remodeling in the spinal cord and cerebellum. Together, this work provides a key resource for studying cellular responses to injury and uncovers the spontaneous plasticity of spinocerebellar neurons, uncovering a potential candidate for targeted therapy.

Matson et al. performed single nucleus sequencing of the “spared” spinal cord tissue distal to an injury in mice. They found that spinocerebellar neurons expressed a pro-regenerative gene signature and showed axon outgrowth after injury.

Single-cell gene regulation network inference by large-scale data integration

Single-cell ATAC-seq (scATAC-seq) has proven to be a state-of-art approach to investigating gene regulation at the single-cell level. However, existing methods cannot precisely uncover cell-type-specific binding of transcription regulators (TRs) and construct gene regulation networks (GRNs) in single-cell. ChIP-seq has been widely used to profile TR binding sites in the past decades. Here, we developed SCRIP, an integrative method to infer single-cell TR activity and targets based on the integration of scATAC-seq and a large-scale TR ChIP-seq reference. Our method showed improved performance in evaluating TR binding activity compared to the existing motif-based methods and reached a higher consistency with matched TR expressions. Besides, our method enables identifying TR target genes as well as building GRNs at the single-cell resolution based on a regulatory potential model. We demonstrate SCRIP's utility in accurate cell-type clustering, lineage tracing, and inferring cell-type-specific GRNs in multiple biological systems. SCRIP is freely available at https://github.com/wanglabtongji/SCRIP.

Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utilize internal mitochondrial DNA data to improve bias estimation. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. Furthermore, we show strong effects of intrinsic biases in single-cell ATAC-seq data, and develop the first single-cell ATAC-seq intrinsic bias correction model to improve cell clustering. SELMA can enhance the performance of existing bioinformatics tools and improve the analysis of both bulk and single-cell chromatin accessibility sequencing data.

Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. Here the authors develop a computational model, SELMA, to estimate and correct enzymatic cleavage biases in chromatin accessibility profiling data.

The Genomic Architecture of Pregnancy-Associated Plasticity in the Maternal Mouse Hippocampus

Pregnancy is associated with extraordinary plasticity in the maternal brain. Studies in humans and other mammals suggest extensive structural and functional remodeling of the female brain during and after pregnancy. However, we understand remarkably little about the molecular underpinnings of this natural phenomenon. To gain insight into pregnancy-associated hippocampal plasticity, we performed single nucleus RNA sequencing (snRNA-seq) and snATAC-seq from the mouse hippocampus before, during, and after pregnancy. We identified cell type-specific transcriptional and epigenetic signatures associated with pregnancy and postpartum adaptation. In addition, we analyzed receptor-ligand interactions and transcription factor (TF) motifs that inform hippocampal cell type identity and provide evidence of pregnancy-associated adaption. In total, these data provide a unique resource of coupled transcriptional and epigenetic data across a dynamic time period in the mouse hippocampus and suggest opportunities for functional interrogation of hormone-mediated plasticity.

Protocol for single-nucleus ATAC sequencing and bioinformatic analysis in frozen human brain tissue

Single-nucleus ATAC sequencing (snATAC-seq) employs a hyperactive Tn5 transposase to gain precise information about the cis-regulatory elements in specific cell types. However, the standard protocol of snATAC-seq is not optimized for all tissues, including the brain. Here, we present a modified protocol for single-nuclei isolation from postmortem frozen human brain tissue, followed by snATAC-seq library preparation and sequencing. We also describe an integrated bioinformatics analysis pipeline using an R package (ArchRtoSignac) to robustly analyze snATAC-seq data. For complete details on the use and execution of this protocol, please refer to Morabito et al. (2021).

sciCAN: single-cell chromatin accessibility and gene expression data integration via cycle-consistent adversarial network

The boom in single-cell technologies has brought a surge of high dimensional data that come from different sources and represent cellular systems from different views. With advances in these single-cell technologies, integrating single-cell data across modalities arises as a new computational challenge. Here, we present an adversarial approach, sciCAN, to integrate single-cell chromatin accessibility and gene expression data in an unsupervised manner. We benchmarked sciCAN with 5 existing methods in 5 scATAC-seq/scRNA-seq datasets, and we demonstrated that our method dealt with data integration with consistent performance across datasets and better balance of mutual transferring between modalities than the other 5 existing methods. We further applied sciCAN to 10X Multiome data and confirmed that the integrated representation preserves biological relationships within the hematopoietic hierarchy. Finally, we investigated CRISPR-perturbed single-cell K562 ATAC-seq and RNA-seq data to identify cells with related responses to different perturbations in these different modalities.

Human-gained heart enhancers are associated with species-specific cardiac attributes

The heart, a vital organ which is first to develop, has adapted its size, structure and function in order to accommodate the circulatory demands for a broad range of animals. Although heart development is controlled by a relatively conserved network of transcriptional/chromatin regulators, how the human heart has evolved species-specific features to maintain adequate cardiac output and function remains to be defined. Here, we show through comparative epigenomic analysis the identification of enhancers and promoters that have gained activity in humans during cardiogenesis. These cis-regulatory elements (CREs) are associated with genes involved in heart development and function, and may account for species-specific differences between human and mouse hearts. Supporting these findings, genetic variants that are associated with human cardiac phenotypic/disease traits, particularly those differing between human and mouse, are enriched in human-gained CREs. During early stages of human cardiogenesis, these CREs are also gained within genomic loci of transcriptional regulators, potentially expanding their role in human heart development. In particular, we discovered that gained enhancers in the locus of the early human developmental regulator ZIC3 are selectively accessible within a subpopulation of mesoderm cells which exhibits cardiogenic potential, thus possibly extending the function of ZIC3 beyond its conserved left-right asymmetry role. Genetic deletion of these enhancers identified a human gained enhancer that was required for not only ZIC3 and early cardiac gene expression at the mesoderm stage but also cardiomyocyte differentiation. Overall, our results illuminate how human gained CREs may contribute to human-specific cardiac attributes, and provide insight into how transcriptional regulators may gain cardiac developmental roles through the evolutionary acquisition of enhancers.

Fundamental and practical approaches for single-cell ATAC-seq analysis

Assays for transposase-accessible chromatin through high-throughput sequencing (ATAC-seq) are effective tools in the study of genome-wide chromatin accessibility landscapes. With the rapid development of single-cell technology, open chromatin regions that play essential roles in epigenetic regulation have been measured at the single-cell level using single-cell ATAC-seq approaches. The application of scATAC-seq has become as popular as that of scRNA-seq. However, owing to the nature of scATAC-seq data, which are sparse and noisy, processing the data requires different methodologies and empirical experience. This review presents a practical guide for processing scATAC-seq data, from quality evaluation to downstream analysis, for various applications. In addition to the epigenomic profiling from scATAC-seq, we also discuss recent studies in which the function of non-coding variants has been investigated based on cell type-specific cis-regulatory elements and how to use the by-product genetic information obtained from scATAC-seq to infer single-cell copy number variants and trace cell lineage. We anticipate that this review will assist researchers in designing and implementing scATAC-seq assays to facilitate research in diverse fields.

Functional inference of gene regulation using single-cell multi-omics

Cells require coordinated control over gene expression when responding to environmental stimuli. Here we apply scATAC-seq and single-cell RNA sequencing (scRNA-seq) in resting and stimulated human blood cells. Collectively, we generate ~91,000 single-cell profiles, allowing us to probe the cis-regulatory landscape of the immunological response across cell types, stimuli, and time. Advancing tools to integrate multi-omics data, we develop functional inference of gene regulation (FigR), a framework to computationally pair scA-TAC-seq with scRNA-seq cells, connect distal cis-regulatory elements to genes, and infer gene-regulatory networks (GRNs) to identify candidate transcription factor (TF) regulators. Utilizing these paired multi-omics data, we define domains of regulatory chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility and gene expression at timescales of minutes. Construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

Single-cell methods for measuring chromatin accessibility (ATAC-seq) and gene expression (RNA-seq) are rapidly evolving, but tools to integrate data and infer gene-regulatory relationships remain limited. Here we generate multi-omics data of resting and stimulated human blood cells and present a new computational framework for constructing gene-regulatory networks (GRNs). Specifically, we describe functional inference of gene regulation (FigR), a workflow to (1) pair scATAC-seq with scRNA-seq, (2) connect cis-regulatory elements to target genes, and (3) identify TF-gene relationships.

Spatial profiling of chromatin accessibility in mouse and human tissues

Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context1. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping2-5, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry6 and microfluidic deterministic barcoding5. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.

scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC) shows great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain important challenges in the analysis of scATAC data due to the inherent high dimensionality and sparsity. Here we introduce scBasset, a sequence-based convolutional neural network method to model scATAC data. We show that by leveraging the DNA sequence information underlying accessibility peaks and the expressiveness of a neural network model, scBasset achieves state-of-the-art performance across a variety of tasks on scATAC and single-cell multiome datasets, including cell clustering, scATAC profile denoising, data integration across assays and transcription factor activity inference.