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

Accelerating the understanding of cancer biology through the lens of genomics

A core mission of cancer genomics is to comprehensively chart molecular underpinnings of cancer-driving events and to provide personalized therapeutic strategies. Primarily focused on cancer cells, cancer genomics studies have successfully uncovered many drivers for major cancer types. Since the emergence of cancer immune evasion as a critical cancer hallmark, the paradigm has been elevated to the holistic tumor ecosystem, with distinct cellular components and their functional states elucidated. We highlight the milestones of cancer genomics, depict the evolving path of the field, and discuss future directions in completing the understanding of the tumor ecosystem and in advancing therapeutic strategies.

Parallel recovery of chromatin accessibility and gene expression dynamics from frozen human regulatory T cells

Epigenetic features such as DNA accessibility dictate transcriptional regulation in a cell type- and cell state- specific manner, and mapping this in health vs. disease in clinically relevant material is opening the door to new mechanistic insights and new targets for therapy. Assay for Transposase Accessible Chromatin Sequencing (ATAC-seq) allows chromatin accessibility profiling from low cell input, making it tractable on rare cell populations, such as regulatory T (Treg) cells. However, little is known about the compatibility of the assay with cryopreserved rare cell populations. Here we demonstrate the robustness of an ATAC-seq protocol comparing primary Treg cells recovered from fresh or cryopreserved PBMC samples, in the steady state and in response to stimulation. We extend this method to explore the feasibility of conducting simultaneous quantitation of chromatin accessibility and transcriptome from a single aliquot of 50,000 cryopreserved Treg cells. Profiling of chromatin accessibility and gene expression in parallel within the same pool of cells controls for cellular heterogeneity and is particularly beneficial when constrained by limited input material. Overall, we observed a high correlation of accessibility patterns and transcription factor dynamics between fresh and cryopreserved samples. Furthermore, highly similar transcriptomic profiles were obtained from whole cells and from the supernatants recovered from ATAC-seq reactions. We highlight the feasibility of applying these techniques to profile the epigenomic landscape of cells recovered from cryopreservation biorepositories.

Cellcano: supervised cell type identification for single cell ATAC-seq data

Computational cell type identification is a fundamental step in single-cell omics data analysis. Supervised celltyping methods have gained increasing popularity in single-cell RNA-seq data because of the superior performance and the availability of high-quality reference datasets. Recent technological advances in profiling chromatin accessibility at single-cell resolution (scATAC-seq) have brought new insights to the understanding of epigenetic heterogeneity. With continuous accumulation of scATAC-seq datasets, supervised celltyping method specifically designed for scATAC-seq is in urgent need. Here we develop Cellcano, a computational method based on a two-round supervised learning algorithm to identify cell types from scATAC-seq data. The method alleviates the distributional shift between reference and target data and improves the prediction performance. After systematically benchmarking Cellcano on 50 well-designed celltyping tasks from various datasets, we show that Cellcano is accurate, robust, and computationally efficient. Cellcano is well-documented and freely available at https://marvinquiet.github.io/Cellcano/ .

Regulation and Immunotherapeutic Targeting of the Epigenome in Exhausted CD8 T Cell Responses

Exhaustion is a state of CD8 T cell differentiation that occurs in settings of chronic Ag such as tumors, chronic viral infection, and autoimmunity. Cellular differentiation is driven by a series of environmental signals that promote epigenetic landscapes that set transcriptomes needed for function. For CD8 T cells, the epigenome that underlies exhaustion is distinct from effector and memory cell differentiation, suggesting that signals early on set in motion a process where the epigenome is modified to promote a trajectory toward a dysfunctional state. Although we know many signals that promote exhaustion, putting this in the context of the epigenetic changes that occur during differentiation has been less clear. In this review, we aim to summarize the epigenetic changes associated with exhaustion in the context of signals that promote it, highlighting immunotherapeutic studies that support these observations or areas for future therapeutic opportunities.

Epigenetic signals that direct cell type-specific interferon beta response in mouse cells

The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNβ treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type-specific antiviral response.

Genomic Analysis of Foxp3 Function in Regulatory T Cells

Regulatory T (Treg) cells are critical for tolerance to self-antigens and for preventing autoimmunity. Foxp3 has been identified as a Treg cell lineage-defining transcription factor controlling Treg cell differentiation and function. In this article, we review the current mechanistic and systemic understanding of Foxp3 function enabled by experimental and computational advances in high-throughput genomics.

Tensor decomposition discriminates tissues using scATAC-seq

ATAC-seq is a powerful tool for measuring the landscape structure of a chromosome. scATAC-seq is a recently updated version of ATAC-seq performed in a single cell. The problem with scATAC-seq is data sparsity and most of the genomic sites are inaccessible. Here, tensor decomposition (TD) was used to fill in missing values. In this study, TD was applied to massive scATAC-seq datasets generated by approximately 200 bp intervals, and this number can reach 13,627,618. Currently, no other methods can deal with large sparse matrices. The proposed method could not only provide UMAP embedding that coincides with tissue specificity, but also select genes associated with various biological enrichment terms and transcription factor targeting. This suggests that TD is a useful tool to process a large sparse matrix generated from scATAC-seq.

Single-cell analysis of bidirectional reprogramming between early embryonic states reveals mechanisms of differential lineage plasticities

Two distinct fates, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common progenitor cells, the inner cell mass (ICM), in mammalian embryos. To study how these sister identities are forged, we leveraged embryonic (ES) and eXtraembryonic ENdoderm (XEN) stem cells - in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses uncovered distinct rates, efficiencies and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4, KLF4 and SOX2-induced XEN-to-iPS reprogramming progressed with diminished efficiency and kinetics. The dominant PrE transcriptional program, safeguarded by Gata4, and globally elevated chromatin accessibility of EPI underscored the differential plasticities of the two states. Mapping in vitro trajectories to embryos revealed reprogramming in either direction tracked along, and toggled between, EPI and PrE in vivo states without transitioning through the ICM.

Single-cell multiome sequencing clarifies enteric glial diversity and identifies an intraganglionic population poised for neurogenesis

The enteric nervous system (ENS) consists of glial cells (EGCs) and neurons derived from neural crest precursors. EGCs retain capacity for large-scale neurogenesis in culture, and in vivo lineage tracing has identified neurons derived from glial cells in response to inflammation. We thus hypothesize that EGCs possess a chromatin structure poised for neurogenesis. We use single-cell multiome sequencing to simultaneously assess transcription and chromatin accessibility in EGCs undergoing spontaneous neurogenesis in culture, as well as small intestine myenteric plexus EGCs. Cultured EGCs maintain open chromatin at genomic loci accessible in neurons, and neurogenesis from EGCs involves dynamic chromatin rearrangements with a net decrease in accessible chromatin. A subset of in vivo EGCs, highly enriched within the myenteric ganglia and that persist into adulthood, have a gene expression program and chromatin state consistent with neurogenic potential. These results clarify the mechanisms underlying EGC potential for neuronal fate transition.

Key transcription factors influence the epigenetic landscape to regulate retinal cell differentiation

How the diverse neural cell types emerge from multipotent neural progenitor cells during central nervous system development remains poorly understood. Recent scRNA-seq studies have delineated the developmental trajectories of individual neural cell types in many neural systems including the neural retina. Further understanding of the formation of neural cell diversity requires knowledge about how the epigenetic landscape shifts along individual cell lineages and how key transcription factors regulate these changes. In this study, we dissect the changes in the epigenetic landscape during early retinal cell differentiation by scATAC-seq and identify globally the enhancers, enriched motifs, and potential interacting transcription factors underlying the cell state/type specific gene expression in individual lineages. Using CUT&Tag, we further identify the enhancers bound directly by four key transcription factors, Otx2, Atoh7, Pou4f2 and Isl1, including those dependent on Atoh7, and uncover the sequential and combinatorial interactions of these factors with the epigenetic landscape to control gene expression along individual retinal cell lineages such as retinal ganglion cells (RGCs). Our results reveal a general paradigm in which transcription factors collaborate and compete to regulate the emergence of distinct retinal cell types such as RGCs from multipotent retinal progenitor cells (RPCs).

Integrative epigenetic analysis reveals AP-1 promotes activation of tumor-infiltrating regulatory T cells in HCC

Regulatory T (Treg) cells that infiltrate human tumors exhibit stronger immunosuppressive activity compared to peripheral blood Treg cells (PBTRs), thus hindering the induction of effective antitumor immunity. Previous transcriptome studies have identified a set of genes that are conserved in tumor-infiltrating Treg cells (TITRs). However, epigenetic profiles of TITRs have not yet been completely deciphered. Here, we employed ATAC-seq and CUT&Tag assays to integrate transcriptome profiles and identify functional regulatory elements in TITRs. We observed a global difference in chromatin accessibility and enhancer landscapes between TITRs and PBTRs. We identified two types of active enhancer formation in TITRs. The H3K4me1-predetermined enhancers are poised to be activated in response to tumor microenvironmental stimuli. We found that AP-1 family motifs are enriched at the enhancer regions of TITRs. Finally, we validated that c-Jun binds at regulatory regions to regulate signature genes of TITRs and AP-1 is required for Treg cells activation in vitro. High c-Jun expression is correlated with poor survival in human HCC. Overall, our results provide insights into the mechanism of AP-1-mediated activation of TITRs and can hopefully be used to develop new therapeutic strategies targeting TITRs in liver cancer treatment.

Enzalutamide-induced signatures revealed by epigenetic plasticity using single-cell multi-omics sequencing in prostate cancer

Prostate cancer is morphologically and molecularly heterogeneous, which poses obstacles for early diagnosis and treatment. Advancements in understanding the heterogeneity of prostate cancer will help navigate through these challenges and ultimately benefit patients. In this study, we integrated single-cell sequencing for transposase-accessible chromatin and whole transcriptome in prostate cancer cell lines, aiming to decode the epigenetic plasticity upon enzalutamide (ENZ) treatment. By comparing the cell populations representing early-treatment response or resistance to the initial tumor cells, we identified seven signature gene sets; they present consistent trends of chromatin closing co-occurred with down-regulated genes during early response and chromatin opening with up-regulated genes upon maintaining drug resistance. In the molecular signatures, we found genes ZNF337, MAPK15, and ESRRG are favorable in progression-free prognosis during early response, while genes CCDC150, CCDC18, and POC1A marked poor prognosis underpinning the pre-existing drug resistance in The Cancer Genome Atlas prostate adenocarcinoma cohort. Ultimately, drug-target analyses nominated combinatory drug candidates to either enhance early-treatment response or potentially overcome ENZ resistance. Together, our integrative, single-cell multi-omics approach in pre-clinical models is effective in identifying informative signatures from complex molecular events, illustrating diverse drug responses in prostate cancer, and invoking novel combinatory drug strategies to inform clinical decision making.

CD4+ T cells in cancer

Cancer immunology and immunotherapy are driving forces of research and development in oncology, mostly focusing on CD8⁺ T cells and the tumor microenvironment. Recent progress highlights the importance of CD4⁺ T cells, corresponding to the long-known fact that CD4⁺ T cells are central players and coordinators of innate and antigen-specific immune responses. Moreover, they have now been recognized as anti-tumor effector cells in their own right. Here we review the current status of CD4⁺ T cells in cancer, which hold great promise for improving knowledge and therapies in cancer.

The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism

The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

High-Capacity Sample Multiplexing for Single Cell Chromatin Accessibility Profiling

Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.

Integrative Single-Cell Analysis Reveals Transcriptional and Epigenetic Regulatory Features of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC.

SIGNIFICANCE

A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

Discovery of Targets for Immune-Metabolic Antitumor Drugs Identifies Estrogen-Related Receptor Alpha

Drugs that kill tumors through multiple mechanisms have the potential for broad clinical benefits. Here, we first developed an in silico multiomics approach (BipotentR) to find cancer cell-specific regulators that simultaneously modulate tumor immunity and another oncogenic pathway and then used it to identify 38 candidate immune-metabolic regulators. We show the tumor activities of these regulators stratify patients with melanoma by their response to anti-PD-1 using machine learning and deep neural approaches, which improve the predictive power of current biomarkers. The topmost identified regulator, ESRRA, is activated in immunotherapy-resistant tumors. Its inhibition killed tumors by suppressing energy metabolism and activating two immune mechanisms: (i) cytokine induction, causing proinflammatory macrophage polarization, and (ii) antigen-presentation stimulation, recruiting CD8+ T cells into tumors. We also demonstrate a wide utility of BipotentR by applying it to angiogenesis and growth suppressor evasion pathways. BipotentR (http://bipotentr.dfci.harvard.edu/) provides a resource for evaluating patient response and discovering drug targets that act simultaneously through multiple mechanisms.

SIGNIFICANCE

BipotentR presents resources for evaluating patient response and identifying targets for drugs that can kill tumors through multiple mechanisms concurrently. Inhibition of the topmost candidate target killed tumors by suppressing energy metabolism and effects on two immune mechanisms. This article is highlighted in the In This Issue feature, p. 517.

Massively Parallel Profiling of Accessible Chromatin and Proteins with ASAP-Seq

While methods such as the Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) enable a comprehensive characterization of regulatory DNA, additional measurements are required to characterize the multifaceted nature of eukaryotic cells. Here, we delineate the ATAC with Select Antigen Profiling by sequencing (ASAP-seq) protocol, a scalable approach to quantifying proteins via oligo-tagged antibodies alongside accessible DNA in thousands of single cells. Critically, our method utilizes a custom bridge oligo that enables the utilization of a variety of oligo-conjugated antibodies, enabling the utilization and repurposing of other commercial products. The ASAP-seq method can be completed with straightforward experimental and computational modifications existing single-cell ATAC-seq workflows but yields distinct modalities underlying complex cellular states, including estimation of protein abundance on the cell surface as well as intracellular and intranuclear factors.

Simultaneous Single-Cell Profiling of the Transcriptome and Accessible Chromatin Using SHARE-seq

The ability to analyze the transcriptomic and epigenomic states of individual single cells has in recent years transformed our ability to measure and understand biological processes. Recent advancements have focused on increasing sensitivity and throughput to provide richer and deeper biological insights at the cellular level. The next frontier is the development of multiomic methods capable of analyzing multiple features from the same cell, such as the simultaneous measurement of the transcriptome and the chromatin accessibility of candidate regulatory elements. In this chapter, we discuss and describe SHARE-seq (Simultaneous high-throughput ATAC, and RNA expression with sequencing) for carrying out simultaneous chromatin accessibility and transcriptome measurements in single cells, together with the experimental and analytical considerations for achieving optimal results.

MacroH2A histone variants modulate enhancer activity to repress oncogenic programs and cellular reprogramming

Considerable efforts have been made to characterize active enhancer elements, which can be annotated by accessible chromatin and H3 lysine 27 acetylation (H3K27ac). However, apart from poised enhancers that are observed in early stages of development and putative silencers, the functional significance of cis-regulatory elements lacking H3K27ac is poorly understood. Here we show that macroH2A histone variants mark a subset of enhancers in normal and cancer cells, which we coined 'macro-Bound Enhancers', that modulate enhancer activity. We find macroH2A variants localized at enhancer elements that are devoid of H3K27ac in a cell type-specific manner, indicating a role for macroH2A at inactive enhancers to maintain cell identity. In following, reactivation of macro-bound enhancers is associated with oncogenic programs in breast cancer and their repressive role is correlated with the activity of macroH2A2 as a negative regulator of BRD4 chromatin occupancy. Finally, through single cell epigenomic profiling of normal mammary stem cells derived from mice, we show that macroH2A deficiency facilitates increased activity of transcription factors associated with stem cell activity.

Dynamic states of cervical epithelia during pregnancy and epithelial barrier disruption

The cervical epithelium undergoes changes in proliferation, differentiation, and function that are critical to ensure fertility and maintain pregnancy. Here, we identify cervical epithelial subtypes in non-pregnant, pregnant, and in labor mice using single-cell transcriptome and spatial analysis. We identify heterogeneous subpopulations of epithelia displaying spatial and temporal specificity. Notably in pregnancy, two goblet cell subtypes are present in the most luminal layers with one goblet population expanding earlier in pregnancy than the other goblet population. The goblet populations express novel protective factors and distinct mucosal networks. Single-cell analysis in a model of cervical epithelial barrier disruption indicates untimely basal cell proliferation precedes the expansion of goblet cells with diminished mucosal integrity. These data demonstrate how the cervical epithelium undergoes continuous remodeling to maintain dynamic states of homeostasis in pregnancy and labor, and provide a framework to understand perturbations in epithelial health that increase the risk of premature birth.

Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating CD8+ T cells

Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying the heterogeneous functional and dysfunctional states of human tumor-infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify gene-regulatory landscapes in a wide breadth of functional and dysfunctional CD8⁺ TIL states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor-entity-matching samples and prioritize cell-state-specific genes by super-enhancer analysis. Besides revealing entity-specific chromatin remodeling in exhausted TILs, our analyses identify a common chromatin trajectory to TIL dysfunction and determine key enhancers, transcriptional regulators, and deregulated genes involved in this process. Finally, we validate enhancer regulation at immunotherapeutically relevant loci by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study provides a framework for understanding and manipulating cell-state-specific gene-regulatory cues from human tumor-infiltrating lymphocytes.

Inflammation induces bitter taste oversensitization via epigenetic changes in Tas2r gene clusters

T2R bitter receptors, encoded by Tas2r genes, are not only critical for bitter taste signal transduction but also important for defense against bacteria and parasites. However, little is known about whether and how Tas2r gene expression are regulated. Here we show that, in an inflammation model mimicking bacterial infection, the expression of many Tas2rs are significantly up-regulated and mice displayed markedly increased neural and behavioral responses to bitter compounds. Using single-cell assays for transposase-accessible chromatin with sequencing (scATAC-seq), we found that the chromatin accessibility of Tas2rs was highly cell type specific and inflammation increased the accessibility of many Tas2rs . scATAC-seq also revealed substantial chromatin remodeling in immune response genes in taste tissue stem cells, suggesting potential long-term effects. Together, our results suggest an epigenetic mechanism connecting inflammation, Tas2r gene regulation, and altered bitter taste, which may explain heightened bitter taste that can occur with infections and cancer treatments.

Deletion of SNX9 alleviates CD8 T cell exhaustion for effective cellular cancer immunotherapy

Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. We here report on a human antigen-specific ex vivo model to explore new therapeutic options for T cell immunotherapies. T cells generated with this model resemble tumor-infiltrating exhausted T cells on a phenotypic and transcriptional level. Using a targeted pooled CRISPR-Cas9 screen and individual gene knockout validation experiments, we uncover sorting nexin-9 (SNX9) as a mediator of T cell exhaustion. Upon TCR/CD28 stimulation, deletion of SNX9 in CD8 T cells decreases PLCγ1, Ca²⁺, and NFATc2-mediated T cell signaling and reduces expression of NR4A1/3 and TOX. SNX9 knockout enhances memory differentiation and IFNγ secretion of adoptively transferred T cells and results in improved anti-tumor efficacy of human chimeric antigen receptor T cells in vivo. Our findings highlight that targeting SNX9 is a strategy to prevent T cell exhaustion and enhance anti-tumor immunity.

Rebalancing TGFβ1/BMP signals in exhausted T cells unlocks responsiveness to immune checkpoint blockade therapy

T cell dysfunctionality prevents the clearance of chronic infections and cancer. Furthermore, epigenetic programming in dysfunctional CD8+ T cells limits their response to immunotherapies, including immune checkpoint blockade (ICB). However, it is unclear which upstream signals drive acquisition of dysfunctional epigenetic programs, and whether therapeutically targeting these signals can remodel terminally dysfunctional T cells to an ICB-responsive state. Here we innovate an in vitro model system of stable human T cell dysfunction and show that chronic TGFβ1 signaling in posteffector CD8+ T cells accelerates their terminal dysfunction through stable epigenetic changes. Conversely, boosting bone morphogenetic protein (BMP) signaling while blocking TGFβ1 preserved effector and memory programs in chronically stimulated human CD8+ T cells, inducing superior responses to tumors and synergizing the ICB responses during chronic viral infection. Thus, rebalancing TGFβ1/BMP signals provides an exciting new approach to unleash dysfunctional CD8+ T cells and enhance T cell immunotherapies.

Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural, unmodified nucleotides and only a low fraction of fluorescently labeled nucleotides, which allows for high polymerase processivity and lower costs. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5' and 3' scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Benchmarking shows that results from mnSBS-based scRNA-seq are very similar to those using Illumina sequencing, with minor differences in results related to the position of reads relative to annotated gene boundaries, owing to single-end reads of Ultima being closer to gene ends than reads from Illumina. The method is thus compatible with state-of-the-art scRNA-seq libraries independent of the sequencing technology. We expect mnSBS to be of particular utility for cost-effective large-scale scRNA-seq projects.

Complex hierarchical structures in single-cell genomics data unveiled by deep hyperbolic manifold learning

With the advances in single-cell sequencing techniques, numerous analytical methods have been developed for delineating cell development. However, most are based on Euclidean space, which would distort the complex hierarchical structure of cell differentiation. Recently, methods acting on hyperbolic space have been proposed to visualize hierarchical structures in single-cell RNA-seq (scRNA-seq) data and have been proven to be superior to methods acting on Euclidean space. However, these methods have fundamental limitations and are not optimized for the highly sparse single-cell count data. To address these limitations, we propose scDHMap, a model-based deep learning approach to visualize the complex hierarchical structures of scRNA-seq data in low-dimensional hyperbolic space. The evaluations on extensive simulation and real experiments show that scDHMap outperforms existing dimensionality-reduction methods in various common analytical tasks as needed for scRNA-seq data, including revealing trajectory branches, batch correction, and denoising the count matrix with high dropout rates. In addition, we extend scDHMap to visualize single-cell ATAC-seq data.

Atlas-scale single-cell chromatin accessibility using nanowell-based combinatorial indexing

Here we present advancements in single-cell combinatorial indexed Assay for Transposase Accessible Chromatin (sciATAC) to measure chromatin accessibility that leverage nanowell chips to achieve atlas-scale cell throughput (>10⁵ cells) at low cost. The platform leverages the core of the sciATAC workflow where multiple indexed tagmentation reactions are performed, followed by pooling and distribution to a second set of reaction wells for polymerase chain reaction (PCR)-based indexing. In this work, we instead leverage a chip containing 5184 nanowells at the PCR stage of indexing, enabling a 52-fold improvement in scale and reduction in per-cell preparation costs. We detail three variants that balance cell throughput and depth of coverage, and apply these methods to banked mouse brain tissue, producing maps of cell types as well as neuronal subtypes that include integration with existing single-cell Assay for Transposase Accessible Chromatin (scATAC) and scRNA-seq data sets. Our optimized workflow achieves a high fraction of reads that fall within called peaks (>80%) and low cell doublet rates. The high cell coverage technique produces high unique reads per cell, while retaining high enrichment for open chromatin regions, enabling the assessment of >70,000 unique accessible loci on average for each cell profiled. When compared to current methods in the field, our technique provides similar or superior per-cell information with very low levels of cell-to-cell cross talk, and achieves this at a cost point much lower than existing assays.

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.

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes

MOTIVATION

Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate.

RESULTS

In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making

The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.

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.

Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes

Altered function and gene regulation of pancreatic islet beta cells is a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of mechanisms driving T2D is still missing. Here we integrate information from measurements of chromatin activity, gene expression and function in single beta cells with genetic association data to identify disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 non-diabetic, pre-T2D and T2D donors, we robustly identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift in T2D. Subtype-defining active chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is likely induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for identifying mechanisms of complex diseases.

Revisiting Aire and tissue-restricted antigens at single-cell resolution

The thymus is a highly specialized organ that plays an indispensable role in the establishment of self-tolerance, a process characterized by the "education" of developing T-cells. To provide competent T-cells tolerant to self-antigens, medullary thymic epithelial cells (mTECs) orchestrate negative selection by ectopically expressing a wide range of genes, including various tissue-restricted antigens (TRAs). Notably, recent advancements in the high-throughput single-cell analysis have revealed remarkable heterogeneity in mTECs, giving us important clues for dissecting the mechanisms underlying TRA expression. We overview how recent single-cell studies have furthered our understanding of mTECs, with a focus on the role of Aire in inducing mTEC heterogeneity to encompass TRAs.

Early transcriptional and epigenetic divergence of CD8+ T cells responding to acute versus chronic infection

During a microbial infection, responding CD8+ T cells give rise to effector cells that provide acute host defense and memory cells that provide sustained protection. An alternative outcome is exhaustion, a state of T cell dysfunction that occurs in the context of chronic infections and cancer. Although it is evident that exhausted CD8+ T (TEX) cells are phenotypically and molecularly distinct from effector and memory CD8+ T cells, the factors regulating the earliest events in the differentiation process of TEX cells remain incompletely understood. Here, we performed single-cell RNA-sequencing and single-cell ATAC-sequencing of CD8+ T cells responding to LCMV-Armstrong (LCMV-Arm) or LCMV-Clone 13 (LCMV-Cl13), which result in acute or chronic infections, respectively. Compared to CD8+ T cells that had undergone their first division in response to LCMV-Arm (Div1ARM) cells, CD8+ T cells that had undergone their first division in response to LCMV-Cl13 (Div1CL13) expressed higher levels of genes encoding transcription factors previously associated with exhaustion, along with higher levels of Ezh2, the catalytic component of the Polycomb Repressive Complex 2 (PRC2) complex, which mediates epigenetic silencing. Modulation of Ezh2 resulted in altered expression of exhaustion-associated molecules by CD8+ T cells responding to LCMV-Cl13, though the specific cellular and infectious contexts, rather than simply the level of Ezh2 expression, likely determine the eventual outcome. Taken together, these findings suggest that the differentiation paths of CD8+ T cells responding to acute versus chronic infections may diverge earlier than previously appreciated.

Application of ATAC-seq in tumor-specific T cell exhaustion

Researches show that chronic viral infection and persistent antigen and/or inflammatory signal exposure in cancer causes the functional status of T cells to be altered, mainly by major changes in the epigenetic and metabolic environment, which then leads to T cell exhaustion. The discovery of the immune checkpoint pathway is an important milestone in understanding and reversing T cell exhaustion. Antibodies targeting these pathways have shown superior ability to reverse T cell exhaustion. However, there are still some limitations in immune checkpoint blocking therapy, such as the short-term nature of therapeutic effects and high individual heterogeneity. Assay for transposase-accessible chromatin with sequencing(ATAC-seq) is a method used to analyze the accessibility of whole-genome chromatin. It uses hyperactive Tn5 transposase to assess chromatin accessibility. Recently, a growing number of studies have reported that ATAC-seq can be used to characterize the dynamic changes of epigenetics in the process of T cell exhaustion. It has been determined that immune checkpoint blocking can only temporarily restore the function of exhausted T cells because of an irreversible change in the epigenetics of exhausted T cells. In this study, we review the latest developments, which provide a clearer molecular understanding of T cell exhaustion, reveal potential new therapeutic targets for persistent viral infection and cancer, and provide new insights for designing effective immunotherapy for treating cancer and chronic infection.

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.

scAVENGERS: a genotype-based deconvolution of individuals in multiplexed single-cell ATAC-seq data without reference genotypes

Genetic differences inferred from sequencing reads can be used for demultiplexing of pooled single-cell RNA-seq (scRNA-seq) data across multiple donors without WGS-based reference genotypes. However, such methods could not be directly applied to single-cell ATAC-seq (scATAC-seq) data owing to the lower read coverage for each variant compared to scRNA-seq. We propose a new software, scATAC-seq Variant-based EstimatioN for GEnotype ReSolving (scAVENGERS), which resolves this issue by calling more individual-specific germline variants and using an optimized mixture model for the scATAC-seq. The benchmark conducted with three synthetic multiplexed scATAC-seq datasets of peripheral blood mononuclear cells and prefrontal cortex tissues showed outstanding performance compared to existing methods in terms of accuracy, doublet detection, and a portion of donor-assigned cells. Furthermore, analyzing the effect of the improved sections provided insight into handling pooled single-cell data in the future. Our source code of the devised software is available at GitHub: https://github.com/kaistcbfg/scAVENGERS.

GAGAM v1.2: An Improvement on Peak Labeling and Genomic Annotated Gene Activity Matrix Construction

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is rapidly becoming a powerful technology for assessing the epigenetic landscape of thousands of cells. However, the sparsity of the resulting data poses significant challenges to their interpretability and informativeness. Different computational methods are available, proposing ways to generate significant features from accessibility data and process them to obtain meaningful results. Foremost among them is the peak calling, which interprets the raw scATAC-seq data generating the peaks as features. However, scATAC-seq data are not trivially comparable with single-cell RNA sequencing (scRNA-seq) data, an increasingly pressing challenge since the necessity of multimodal experiments integration. For this reason, this study wants to improve the concept of the Gene Activity Matrix (GAM), which links the accessibility data to the genes, by proposing an improved version of the Genomic-Annotated Gene Activity Matrix (GAGAM) concept. Specifically, this paper presents GAGAM v1.2, a new and better version of GAGAM v1.0. GAGAM aims to label the peaks and link them to the genes through functional annotation of the whole genome. Using genes as features in scATAC-seq datasets makes different datasets comparable and allows linking gene accessibility and expression. This link is crucial for gene regulation understanding and fundamental for the increasing impact of multi-omics data. Results confirm that our method performs better than the previous GAMs and shows a preliminary comparison with scRNA-seq data.

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.

Single-cell chromatin accessibility identifies enhancer networks driving gene expression during spinal cord development in mouse

Spinal cord development is precisely orchestrated by spatiotemporal gene regulatory programs. However, the underlying epigenetic mechanisms remain largely elusive. Here, we profiled single-cell chromatin accessibility landscapes in mouse neural tubes spanning embryonic days 9.5-13.5. We identified neuronal-cell-cluster-specific cis-regulatory elements in neural progenitors and neurons. Furthermore, we applied a novel computational method, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression data and identify the hub enhancers within enhancer networks. It was experimentally validated in vivo for Atoh1 that knockout of the hub enhancers, but not the non-hub enhancers, markedly decreased Atoh1 expression and reduced dp1/dI1 cells. Together, our work provides insights into the epigenetic regulation of spinal cord development and a proof-of-concept demonstration of enhancer networks as a general mechanism in transcriptional regulation.

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.

Single-Cell DNA Methylation Analysis in Cancer

Morphological, transcriptomic, and genomic defects are well-explored parameters of cancer biology. In more recent years, the impact of epigenetic influences, such as DNA methylation, is becoming more appreciated. Aberrant DNA methylation has been implicated in many types of cancers, influencing cell type, state, transcriptional regulation, and genomic stability to name a few. Traditionally, large populations of cells from the tissue of interest are coalesced for analysis, producing averaged methylome data. Considering the inherent heterogeneity of cancer, analysing populations of cells as a whole denies the ability to discover novel aberrant methylation patterns, identify subpopulations, and trace cell lineages. Due to recent advancements in technology, it is now possible to obtain methylome data from single cells. This has both research and clinical implications, ranging from the identification of biomarkers to improved diagnostic tools. As with all emerging technologies, distinct experimental, bioinformatic, and practical challenges present themselves. This review begins with exploring the potential impact of single-cell sequencing on understanding cancer biology and how it could eventually benefit a clinical setting. Following this, the techniques and experimental approaches which made this technology possible are explored. Finally, the present challenges currently associated with single-cell DNA methylation sequencing are described.

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.

Fibroblast inflammatory priming determines regenerative versus fibrotic skin repair in reindeer

Adult mammalian skin wounds heal by forming fibrotic scars. We report that full-thickness injuries of reindeer antler skin (velvet) regenerate, whereas back skin forms fibrotic scar. Single-cell multi-omics reveal that uninjured velvet fibroblasts resemble human fetal fibroblasts, whereas back skin fibroblasts express inflammatory mediators mimicking pro-fibrotic adult human and rodent fibroblasts. Consequently, injury elicits site-specific immune responses: back skin fibroblasts amplify myeloid infiltration and maturation during repair, whereas velvet fibroblasts adopt an immunosuppressive phenotype that restricts leukocyte recruitment and hastens immune resolution. Ectopic transplantation of velvet to scar-forming back skin is initially regenerative, but progressively transitions to a fibrotic phenotype akin to the scarless fetal-to-scar-forming transition reported in humans. Skin regeneration is diminished by intensifying, or enhanced by neutralizing, these pathologic fibroblast-immune interactions. Reindeer represent a powerful comparative model for interrogating divergent wound healing outcomes, and our results nominate decoupling of fibroblast-immune interactions as a promising approach to mitigate scar.

Identification of human progenitors of exhausted CD8+ T cells associated with elevated IFN-γ response in early phase of viral infection

T cell exhaustion is a hallmark of hepatitis C virus (HCV) infection and limits protective immunity in chronic viral infections and cancer. Limited knowledge exists of the initial viral and immune dynamics that characterise exhaustion in humans. We studied longitudinal blood samples from a unique cohort of individuals with primary infection using single-cell multi-omics to identify the functions and phenotypes of HCV-specific CD8⁺ T cells. Early elevated IFN-γ response against the transmitted virus is associated with the rate of immune escape, larger clonal expansion, and early onset of exhaustion. Irrespective of disease outcome, we find heterogeneous subsets of progenitors of exhaustion, based on the level of PD-1 expression and loss of AP-1 transcription factors. Intra-clonal analysis shows distinct trajectories with multiple fates and evolutionary plasticity of precursor cells. These findings challenge the current paradigm on the contribution of CD8⁺ T cells to HCV disease outcome and provide data for future studies on T cell differentiation in human infections.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

Single-cell chromatin landscapes of mouse skin development

The coat of mammals is produced by hair follicles, and hair follicle is an important and complex accessory organ of skin. As a complex physiological regulation process, hair follicle morphogenesis is regulated by a series of signal pathway factors, involves the interaction of multiple cell types and begins in the early embryonic stage. However, its transcriptional regulatory mechanism is unclear. We have therefore utilized single-cell ATAC sequencing to obtain the chromatin accessibility landscapes of 6,928, 6,961 and 7,374 high-quality cells from the dorsal skins of E13.5, E16.5 and P0 mice (Mus musculus), respectively. Based on marker gene activity clustering, we defined 6, 8 and 5 distinct cell types in E13.5, E16.5 and P0 stages, respectively. Furtherly, we integrated the fibroblasts and keratinocytes clusters, performed further analysis and re-clustered. The single cell map of the chromatin open area was drawn from each cell type and the mechanism of cell transcription regulation was explored. Collectively, our data provide a reference for deeply exploring the epigenetic regulation mechanism of mouse hair follicles development.