Single-cell chromatin state analysis with Signac

Clustering single-cell multimodal omics data with jrSiCKLSNMF

Introduction: The development of multimodal single-cell omics methods has enabled the collection of data across different omics modalities from the same set of single cells. Each omics modality provides unique information about cell type and function, so the ability to integrate data from different modalities can provide deeper insights into cellular functions. Often, single-cell omics data can prove challenging to model because of high dimensionality, sparsity, and technical noise. Methods: We propose a novel multimodal data analysis method called joint graph-regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization (jrSiCKLSNMF, pronounced "junior sickles NMF") that extracts latent factors shared across omics modalities within the same set of single cells. Results: We compare our clustering algorithm to several existing methods on four sets of data simulated from third party software. We also apply our algorithm to a real set of cell line data. Discussion: We show overwhelmingly better clustering performance than several existing methods on the simulated data. On a real multimodal omics dataset, we also find our method to produce scientifically accurate clustering results.

The chromatin landscape of healthy and injured cell types in the human kidney

There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.

Epigenomic landscape exhibits interferon signaling suppression in the patient of myocarditis after BNT162b2 vaccination

After the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, a novel mRNA vaccine (BNT162b2) was developed at an unprecedented speed. Although most countries have achieved widespread immunity from vaccines and infections, yet people, even who have recovered from SARS-CoV-2 infection, are recommended to receive vaccination due to their effectiveness in lowering the risk of recurrent infection. However, the BNT162b2 vaccine has been reported to increase the risk of myocarditis. To our knowledge, for the first time in this study, we tracked changes in the chromatin dynamics of peripheral blood mononuclear cells (PBMCs) in the patient who underwent myocarditis after BNT162b2 vaccination. A longitudinal study of chromatin accessibility using concurrent analysis of single-cell assays for transposase-accessible chromatin with sequencing and single-cell RNA sequencing showed downregulation of interferon signaling and upregulated RUNX2/3 activity in PBMCs. Considering BNT162b2 vaccination increases the level of interferon-α/γ in serum, our data highlight the immune responses different from the conventional responses to the vaccination, which is possibly the key to understanding the side effects of BNT162b2 vaccination.

Integration site-dependent HIV-1 promoter activity shapes host chromatin conformation

HIV-1 integration introduces ectopic transcription factor binding sites into host chromatin. We postulate that the integrated provirus serves as an ectopic enhancer that recruits additional transcription factors to the integration locus, increases chromatin accessibility, changes 3D chromatin interactions, and enhances both retroviral and host gene expression. We used four well-characterized HIV-1-infected cell line clones having unique integration sites and low to high levels of HIV-1 expression. Using single-cell DOGMA-seq, which captured the heterogeneity of HIV-1 expression and host chromatin accessibility, we found that HIV-1 transcription correlated with HIV-1 accessibility and host chromatin accessibility. HIV-1 integration increased local host chromatin accessibility within an ∼5- to 30-kb distance. CRISPRa- and CRISPRi-mediated HIV-1 promoter activation and inhibition confirmed integration site-dependent HIV-1-driven changes of host chromatin accessibility. HIV-1 did not drive chromatin confirmation changes at the genomic level (by Hi-C) or the enhancer connectome (by H3K27ac HiChIP). Using 4C-seq to interrogate HIV-1-chromatin interactions, we found that HIV-1 interacted with host chromatin ∼100-300 kb from the integration site. By identifying chromatin regions having both increased transcription factor activity (by ATAC-seq) and HIV-1-chromatin interaction (by 4C-seq), we identified enrichment of ETS, RUNT, and ZNF-family transcription factor binding that may mediate HIV-1-host chromatin interactions. Our study has found that HIV-1 promoter activity increases host chromatin accessibility, and HIV-1 interacted with host chromatin within the existing chromatin boundaries in an integration site-dependent manner.

Neural cell diversity in the light of single-cell transcriptomics

The development of highly parallel and affordable high-throughput single-cell transcriptomics technologies has revolutionized our understanding of brain complexity. These methods have been used to build cellular maps of the brain, its different regions, and catalog the diversity of cells in each of them during development, aging and even in disease. Now we know that cellular diversity is way beyond what was previously thought. Single-cell transcriptomics analyses have revealed that cell types previously considered homogeneous based on imaging techniques differ depending on several factors including sex, age and location within the brain. The expression profiles of these cells have also been exploited to understand which are the regulatory programs behind cellular diversity and decipher the transcriptional pathways driving them. In this review, we summarize how single-cell transcriptomics have changed our view on the cellular diversity in the human brain, and how it could impact the way we study neurodegenerative diseases. Moreover, we describe the new computational approaches that can be used to study cellular differentiation and gain insight into the functions of individual cell populations under different conditions and their alterations in disease.

Nanobody-tethered transposition enables multifactorial chromatin profiling at single-cell resolution

Chromatin states are functionally defined by a complex combination of histone modifications, transcription factor binding, DNA accessibility and other factors. Current methods for defining chromatin states cannot measure more than one aspect in a single experiment at single-cell resolution. Here we introduce nanobody-tethered transposition followed by sequencing (NTT-seq), an assay capable of measuring the genome-wide presence of up to three histone modifications and protein-DNA binding sites at single-cell resolution. NTT-seq uses recombinant Tn5 transposase fused to a set of secondary nanobodies (nb). Each nb-Tn5 fusion protein specifically binds to different immunoglobulin-G antibodies, enabling a mixture of primary antibodies binding different epitopes to be used in a single experiment. We apply bulk-cell and single-cell NTT-seq to generate high-resolution multimodal maps of chromatin states in cell culture and in human immune cells. We also extend NTT-seq to enable simultaneous profiling of cell surface protein expression and multimodal chromatin states to study cells of the immune system.

Single-nucleus multi-omics of human stem cell-derived islets identifies deficiencies in lineage specification

Insulin-producing β cells created from human pluripotent stem cells have potential as a therapy for insulin-dependent diabetes, but human pluripotent stem cell-derived islets (SC-islets) still differ from their in vivo counterparts. To better understand the state of cell types within SC-islets and identify lineage specification deficiencies, we used single-nucleus multi-omic sequencing to analyse chromatin accessibility and transcriptional profiles of SC-islets and primary human islets. Here we provide an analysis that enabled the derivation of gene lists and activity for identifying each SC-islet cell type compared with primary islets. Within SC-islets, we found that the difference between β cells and awry enterochromaffin-like cells is a gradient of cell states rather than a stark difference in identity. Furthermore, transplantation of SC-islets in vivo improved cellular identities overtime, while long-term in vitro culture did not. Collectively, our results highlight the importance of chromatin and transcriptional landscapes during islet cell specification and maturation.

macroH2A2 antagonizes epigenetic programs of stemness in glioblastoma

Self-renewal is a crucial property of glioblastoma cells that is enabled by the choreographed functions of chromatin regulators and transcription factors. Identifying targetable epigenetic mechanisms of self-renewal could therefore represent an important step toward developing effective treatments for this universally lethal cancer. Here we uncover an epigenetic axis of self-renewal mediated by the histone variant macroH2A2. With omics and functional assays deploying patient-derived in vitro and in vivo models, we show that macroH2A2 shapes chromatin accessibility at enhancer elements to antagonize transcriptional programs of self-renewal. macroH2A2 also sensitizes cells to small molecule-mediated cell death via activation of a viral mimicry response. Consistent with these results, our analyses of clinical cohorts indicate that high transcriptional levels of this histone variant are associated with better prognosis of high-grade glioma patients. Our results reveal a targetable epigenetic mechanism of self-renewal controlled by macroH2A2 and suggest additional treatment approaches for glioblastoma patients.

Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line

Non-coding regulatory elements such as enhancers are key in controlling the cell-type specificity and spatio-temporal expression of genes. To drive stable and precise gene transcription robust to genetic variation and environmental stress, genes are often targeted by multiple enhancers with redundant action. However, it is unknown whether enhancers targeting the same gene display simultaneous activity or whether some enhancer combinations are more often co-active than others. Here, we take advantage of recent developments in single cell technology that permit assessing chromatin status (scATAC-seq) and gene expression (scRNA-seq) in the same single cells to correlate gene expression to the activity of multiple enhancers. Measuring activity patterns across 24,844 human lymphoblastoid single cells, we find that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles. For 6944 expressed genes associated with enhancers, we predict 89,885 significant enhancer-enhancer associations between nearby enhancers. We find that associated enhancers share similar transcription factor binding profiles and that gene essentiality is linked with higher enhancer co-activity. We provide a set of predicted enhancer-enhancer associations based on correlation derived from a single cell line, which can be further investigated for functional relevance.

Direct androgen receptor regulation of sexually dimorphic gene expression in the mammalian kidney

Mammalian organs exhibit distinct physiology, disease susceptibility and injury responses between the sexes. In the mouse kidney, sexually dimorphic gene activity maps predominantly to proximal tubule (PT) segments. Bulk RNA-seq data demonstrated sex differences were established from 4 and 8 weeks after birth under gonadal control. Hormone injection studies and genetic removal of androgen and estrogen receptors demonstrated androgen receptor (AR) mediated regulation of gene activity in PT cells as the regulatory mechanism. Interestingly, caloric restriction feminizes the male kidney. Single-nuclear multiomic analysis identified putative cis-regulatory regions and cooperating factors mediating PT responses to AR activity in the mouse kidney. In the human kidney, a limited set of genes showed conserved sex-linked regulation while analysis of the mouse liver underscored organ-specific differences in the regulation of sexually dimorphic gene expression. These findings raise interesting questions on the evolution, physiological significance, and disease and metabolic linkage, of sexually dimorphic gene activity.

Simultaneous profiling of spatial gene expression and chromatin accessibility during mouse brain development

The brain is a complex tissue whose function relies on coordinated anatomical and molecular features. However, the molecular annotation of the spatial organization of the brain is currently insufficient. Here, we describe microfluidic indexing-based spatial assay for transposase-accessible chromatin and RNA-sequencing (MISAR-seq), a method for spatially resolved joint profiling of chromatin accessibility and gene expression. By applying MISAR-seq to the developing mouse brain, we study tissue organization and spatiotemporal regulatory logics during mouse brain development.

scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data

Single-cell technologies offer unprecedented opportunities to dissect gene regulatory mechanisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal datasets, we demonstrate scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome dataset we generated from differentiating mouse embryonic stem cells over time, we demonstrate scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.

Inflammation durably imprints memory CD4+ T cells

Adaptive immune responses are induced by vaccination and infection, yet little is known about how CD4+ T cell memory differs when primed in these two contexts. Notably, viral infection is generally associated with higher levels of systemic inflammation than is vaccination. To assess whether the inflammatory milieu at the time of CD4+ T cell priming has long-term effects on memory, we compared Spike-specific memory CD4+ T cells in 22 individuals around the time of the participants' third SARS-CoV-2 mRNA vaccination, with stratification by whether the participants' first exposure to Spike was via virus or mRNA vaccine. Multimodal single-cell profiling of Spike-specific CD4+ T cells revealed 755 differentially expressed genes that distinguished infection- and vaccine-primed memory CD4+ T cells. Spike-specific CD4+ T cells from infection-primed individuals had strong enrichment for cytotoxicity and interferon signaling genes, whereas Spike-specific CD4+ T cells from vaccine-primed individuals were enriched for proliferative pathways by gene set enrichment analysis. Moreover, Spike-specific memory CD4+ T cells established by infection had distinct epigenetic landscapes driven by enrichment of IRF-family transcription factors, relative to T cells established by mRNA vaccination. This transcriptional imprint was minimally altered following subsequent mRNA vaccination or breakthrough infection, reflecting the strong bias induced by the inflammatory environment during initial memory differentiation. Together, these data suggest that the inflammatory context during CD4+ T cell priming is durably imprinted in the memory state at transcriptional and epigenetic levels, which has implications for personalization of vaccination based on prior infection history.

A survey on algorithms to characterize transcription factor binding sites

Transcription factors (TFs) are key regulatory proteins that control the transcriptional rate of cells by binding short DNA sequences called transcription factor binding sites (TFBS) or motifs. Identifying and characterizing TFBS is fundamental to understanding the regulatory mechanisms governing the transcriptional state of cells. During the last decades, several experimental methods have been developed to recover DNA sequences containing TFBS. In parallel, computational methods have been proposed to discover and identify TFBS motifs based on these DNA sequences. This is one of the most widely investigated problems in bioinformatics and is referred to as the motif discovery problem. In this manuscript, we review classical and novel experimental and computational methods developed to discover and characterize TFBS motifs in DNA sequences, highlighting their advantages and drawbacks. We also discuss open challenges and future perspectives that could fill the remaining gaps in the field.

Homeostatic, repertoire and transcriptional relationships between colon T regulatory cell subsets

Foxp3 + regulatory T cells (Tregs) in the colon are key to promoting peaceful co-existence with symbiotic microbes. Differentiated in either thymic or peripheral locations, and modulated by microbes and other cellular influencers, colonic Treg subsets have been identified through key transcription factors (TF; Helios, Rorg, Gata3, cMaf), but their inter-relationships are unclear. Applying a multimodal array of immunologic, genomic, and microbiological assays, we find more overlap than expected between populations. The key TFs play different roles, some essential for subset identity, others driving functional gene signatures. Functional divergence was clearest under challenge. Single-cell genomics revealed a spectrum of phenotypes between the Helios+ and Rorγ+ poles, different Treg-inducing bacteria inducing the same Treg phenotypes to varying degrees, not distinct populations. TCR clonotypes in monocolonized mice revealed that Helios+ and Rorγ+ Tregs are related, and cannot be uniquely equated to tTreg and pTreg. We propose that rather than the origin of their differentiation, tissue-specific cues dictate the spectrum of colonic Treg phenotypes.

Comparative single-cell analyses identify shared and divergent features of human and mouse kidney development

Mammalian kidneys maintain fluid homeostasis through the cellular activity of nephrons and the conjoined collecting system. Each epithelial network originates from distinct progenitor cell populations that reciprocally interact during development. To extend our understanding of human and mouse kidney development, we profiled chromatin organization (ATAC-seq) and gene expression (RNA-seq) in developing human and mouse kidneys. Data were analyzed at a species level and then integrated into a common, cross-species multimodal data set. Comparative analysis of cell types and developmental trajectories identified conserved and divergent features of chromatin organization and linked gene activity, revealing species- and cell-type specific regulatory programs. Identification of human-specific enhancer regions linked through GWAS studies to kidney disease highlights the potential of developmental modeling to provide clinical insight.

Integrating single-cell transcriptomes, chromatin accessibility, and multiomics analysis of mesoderm-induced embryonic stem cells

Here, we present workflows for integrating independent transcriptomic and chromatin accessibility datasets and analyzing multiomics. First, we describe steps for integrating independent transcriptomic and chromatin accessibility measurements. Next, we detail multimodal analysis of transcriptomes and chromatin accessibility performed in the same sample. We demonstrate their use by analyzing datasets obtained from mouse embryonic stem cells induced to differentiate toward mesoderm-like, myogenic, or neurogenic phenotypes. For complete details on the use and execution of this protocol, please refer to Khateb et al.¹.

Enhlink infers distal and context-specific enhancer-promoter linkages

Enhancers play a crucial role in regulating gene expression and their functional status can be queried with cell type precision using using single-cell (sc)ATAC-seq. To facilitate analysis of such data, we developed Enhlink, a novel computational approach that leverages single-cell signals to infer linkages between regulatory DNA sequences, such as enhancers and promoters. Enhlink uses an ensemble strategy that integrates cell-level technical covariates to control for batch effects and biological covariates to infer robust condition-specific links and their associated p-values. It can integrate simultaneous gene expression and chromatin accessibility measurements of individual cells profiled by multi-omic experiments for increased specificity. We evaluated Enhlink using simulated and real scATAC-seq data, including those paired with physical enhancer-promoter links enumerated by promoter capture Hi-C and with multi-omic scATAC-/RNA-seq data we generated from the mouse striatum. These examples demonstrated that our method outperforms popular alternative strategies. In conjunction with eQTL analysis, Enhlink revealed a putative super-enhancer regulating key cell type-specific markers of striatal neurons. Taken together, our analyses demonstrate that Enhlink is accurate, powerful, and provides features that can lead to novel biological insights.

Single-cell multiomic analysis identifies a HOX-PBX gene network regulating the survival of lymphangioleiomyomatosis cells

Lymphangioleiomyomatosis (LAM) is a rare, progressive lung disease that predominantly affects women. LAM cells carry TSC1/TSC2 mutations, causing mTORC1 hyperactivation and uncontrolled cell growth. mTORC1 inhibitors stabilize lung function; however, sustained efficacy requires long-term administration, and some patients fail to tolerate or respond to therapy. Although the genetic basis of LAM is known, mechanisms underlying LAM pathogenesis remain elusive. We integrated single-cell RNA sequencing and single-nuclei ATAC-seq of LAM lungs to construct a gene regulatory network controlling the transcriptional program of LAM cells. We identified activation of uterine-specific HOX-PBX transcriptional programs in pulmonary LAMCORE cells as regulators of cell survival depending upon HOXD11-PBX1 dimerization. Accordingly, blockage of HOXD11-PBX1 dimerization by HXR9 suppressed LAM cell survival in vitro and in vivo. PBX1 regulated STAT1/3, increased the expression of antiapoptotic genes, and promoted LAM cell survival in vitro. The HOX-PBX gene network provides promising targets for treatment of LAM/TSC mTORC1-hyperactive cancers.

GTAC enables parallel genotyping of multiple genomic loci with chromatin accessibility profiling in single cells

Understanding clonal evolution and cancer development requires experimental approaches for characterizing the consequences of somatic mutations on gene regulation. However, no methods currently exist that efficiently link high-content chromatin accessibility with high-confidence genotyping in single cells. To address this, we developed Genotyping with the Assay for Transposase-Accessible Chromatin (GTAC), enabling accurate mutation detection at multiple amplified loci, coupled with robust chromatin accessibility readout. We applied GTAC to primary acute myeloid leukemia, obtaining high-quality chromatin accessibility profiles and clonal identities for multiple mutations in 88% of cells. We traced chromatin variation throughout clonal evolution, showing the restriction of different clones to distinct differentiation stages. Furthermore, we identified switches in transcription factor motif accessibility associated with a specific combination of driver mutations, which biased transformed progenitors toward a leukemia stem cell-like chromatin state. GTAC is a powerful tool to study clonal heterogeneity across a wide spectrum of pre-malignant and neoplastic conditions.

InferLoop: leveraging single-cell chromatin accessibility for the signal of chromatin loop

Deciphering cell-type-specific 3D structures of chromatin is challenging. Here, we present InferLoop, a novel method for inferring the strength of chromatin interaction using single-cell chromatin accessibility data. The workflow of InferLoop is, first, to conduct signal enhancement by grouping nearby cells into bins, and then, for each bin, leverage accessibility signals for loop signals using a newly constructed metric that is similar to the perturbation of the Pearson correlation coefficient. In this study, we have described three application scenarios of InferLoop, including the inference of cell-type-specific loop signals, the prediction of gene expression levels and the interpretation of intergenic loci. The effectiveness and superiority of InferLoop over other methods in those three scenarios are rigorously validated by using the single-cell 3D genome structure data of human brain cortex and human blood, the single-cell multi-omics data of human blood and mouse brain cortex, and the intergenic loci in the GWAS Catalog database as well as the GTEx database, respectively. In addition, InferLoop can be applied to predict loop signals of individual spots using the spatial chromatin accessibility data of mouse embryo. InferLoop is available at https://github.com/jumphone/inferloop.

Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.

Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace

Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative method to identify spatially variable cell subpopulations by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We benchmark scSpace with both simulated and biological datasets, and demonstrate that scSpace can accurately and robustly identify spatially variated cell subpopulations. When employed to reconstruct the spatial architectures of complex tissue such as the brain cortex, the small intestinal villus, the liver lobule, the kidney, the embryonic heart, and others, scSpace shows promising performance on revealing the pairwise cellular spatial association within single-cell data. The application of scSpace in melanoma and COVID-19 exhibits a broad prospect in the discovery of spatial therapeutic markers.

Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning

Recent advances in single-cell sequencing technology have made it possible to measure multiple paired omics simultaneously in a single cell such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-nucleus chromatin accessibility and mRNA expression sequencing (SNARE-seq). However, the widespread application of these single-cell multiomics profiling technologies has been limited by their experimental complexity, noise in nature, and high cost. In addition, single-omics sequencing technologies have generated tremendous and high-quality single-cell datasets but have yet to be fully utilized. Here, single-cell multiomics generation (scMOG), a deep learning-based framework to generate single-cell assay for transposase-accessible chromatin (ATAC) data in silico is developed from experimentally available single-cell RNA-seq measurements and vice versa. The results demonstrate that scMOG can accurately perform cross-omics generation between RNA and ATAC, and generate paired multiomics data with biological meanings when one omics is experimentally unavailable and out of training datasets. The generated ATAC, either alone or in combination with measured RNA, exhibits equivalent or superior performance to that of the experimentally measured counterparts throughout multiple downstream analyses. scMOG is also applied to human lymphoma data, which proves to be more effective in identifying tumor samples than the experimentally measured ATAC data. Finally, the performance of scMOG is investigated in other omics such as proteomics and it still shows robust performance on surface protein generation.

An optimized approach for multiplexing single-nuclear ATAC-seq using oligonucleotide-conjugated antibodies

BACKGROUND

Single-cell technologies to analyze transcription and chromatin structure have been widely used in many research areas to reveal the functions and molecular properties of cells at single-cell resolution. Sample multiplexing techniques are valuable when performing single-cell analysis, reducing technical variation and permitting cost efficiencies. Several commercially available methods have been used in many scRNA-seq studies. On the other hand, while several methods have been published, multiplexing techniques for single nuclear assay for transposase-accessible chromatin (snATAC)-seq assays remain under development. We developed a simple nucleus hashing method using oligonucleotide-conjugated antibodies recognizing nuclear pore complex proteins, NuHash, to perform snATAC-seq library preparations by multiplexing.

RESULTS

We performed multiplexing snATAC-seq analyses on a mixture of human and mouse cell samples (two samples, 2-plex, and four samples, 4-plex) using NuHash. The analyses on nuclei with at least 10,000 read counts showed that the demultiplexing accuracy of NuHash was high, and only ten out of 9144 nuclei (2-plex) and 150 of 12,208 nuclei (4-plex) had discordant classifications between NuHash demultiplexing and discrimination using reference genome alignments. The differential open chromatin region (OCR) analysis between female and male samples revealed that male-specific OCRs were enriched in chromosome Y (four out of nine). We also found that five female-specific OCRs (20 OCRs) were on chromosome X. A comparative analysis between snATAC-seq and deeply sequenced bulk ATAC-seq on the same samples revealed that the bulk ATAC-seq signal intensity was positively correlated with the number of cell clusters detected in snATAC-seq. Moreover, when we categorized snATAC-seq peaks based on the number of cell clusters in which the peak was present, we observed different distributions over different genomic features between the groups. This result suggests that the peak intensities of bulk ATAC-seq can be used to identify different types of functional loci.

CONCLUSIONS

Our multiplexing method using oligo-conjugated anti-nuclear pore complex proteins, NuHash, permits high-accuracy demultiplexing of samples. The NuHash protocol is straightforward, works on frozen samples, and requires no modifications for snATAC-seq library preparation.

ALS is imprinted in the chromatin accessibility of blood cells

Amyotrophic Lateral Sclerosis (ALS) is a complex and incurable neurodegenerative disorder in which genetic and epigenetic factors contribute to the pathogenesis of all forms of ALS. The interplay of genetic predisposition and environmental footprints generates epigenetic signatures in the cells of affected tissues, which then alter transcriptional programs. Epigenetic modifications that arise from genetic predisposition and systemic environmental footprints should in theory be detectable not only in affected CNS tissue but also in the periphery. Here, we identify an ALS-associated epigenetic signature ('epiChromALS') by chromatin accessibility analysis of blood cells of ALS patients. In contrast to the blood transcriptome signature, epiChromALS includes also genes that are not expressed in blood cells; it is enriched in CNS neuronal pathways and it is present in the ALS motor cortex. By combining simultaneous ATAC-seq and RNA-seq with single-cell sequencing in PBMCs and motor cortex from ALS patients, we demonstrate that epigenetic changes associated with the neurodegenerative disease can be found in the periphery, thus strongly suggesting a mechanistic link between the epigenetic regulation and disease pathogenesis.

Tbx5 maintains atrial identity by regulating an atrial enhancer network

Understanding how the atrial and ventricular chambers of the heart maintain their distinct identity is a prerequisite for treating chamber-specific diseases. Here, we selectively inactivated the transcription factor Tbx5 in the atrial working myocardium of the neonatal mouse heart to show that it is required to maintain atrial identity. Atrial Tbx5 inactivation downregulated highly chamber specific genes such as Myl7 and Nppa , and conversely, increased the expression of ventricular identity genes including Myl2 . Using combined single nucleus transcriptome and open chromatin profiling, we assessed genomic accessibility changes underlying the altered atrial identity expression program, identifying 1846 genomic loci with greater accessibility in control atrial cardiomyocytes compared to KO aCMs. 69% of the control-enriched ATAC regions were bound by TBX5, demonstrating a role for TBX5 in maintaining atrial genomic accessibility. These regions were associated with genes that had higher expression in control aCMs compared to KO aCMs, suggesting they act as TBX5-dependent enhancers. We tested this hypothesis by analyzing enhancer chromatin looping using HiChIP and found 510 chromatin loops that were sensitive to TBX5 dosage. Of the loops enriched in control aCMs, 73.7% contained anchors in control-enriched ATAC regions. Together, these data demonstrate a genomic role for TBX5 in maintaining the atrial gene expression program by binding to atrial enhancers and preserving tissue-specific chromatin architecture of atrial enhancers.

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brain's 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brain's cellular-spatial and regulatory genome diversity.

TEAD1 trapping by the Q353R-Lamin A/C causes dilated cardiomyopathy

Mutations in the LMNA gene encoding Lamin A and C (Lamin A/C), major components of the nuclear lamina, cause laminopathies including dilated cardiomyopathy (DCM), but the underlying molecular mechanisms have not been fully elucidated. Here, by leveraging single-cell RNA sequencing (RNA-seq), assay for transposase-accessible chromatin using sequencing (ATAC-seq), protein array, and electron microscopy analysis, we show that insufficient structural maturation of cardiomyocytes owing to trapping of transcription factor TEA domain transcription factor 1 (TEAD1) by mutant Lamin A/C at the nuclear membrane underlies the pathogenesis of Q353R-LMNA-related DCM. Inhibition of the Hippo pathway rescued the dysregulation of cardiac developmental genes by TEAD1 in LMNA mutant cardiomyocytes. Single-cell RNA-seq of cardiac tissues from patients with DCM with the LMNA mutation confirmed the dysregulated expression of TEAD1 target genes. Our results propose an intervention for transcriptional dysregulation as a potential treatment of LMNA-related DCM.

Characterization of altered molecular mechanisms in Parkinson's disease through cell type-resolved multiomics analyses

Parkinson's disease (PD) is a progressive neurodegenerative disorder. However, cell type-dependent transcriptional regulatory programs responsible for PD pathogenesis remain elusive. Here, we establish transcriptomic and epigenomic landscapes of the substantia nigra by profiling 113,207 nuclei obtained from healthy controls and patients with PD. Our multiomics data integration provides cell type annotation of 128,724 cis-regulatory elements (cREs) and uncovers cell type-specific dysregulations in cREs with a strong transcriptional influence on genes implicated in PD. The establishment of high-resolution three-dimensional chromatin contact maps identifies 656 target genes of dysregulated cREs and genetic risk loci, uncovering both potential and known PD risk genes. Notably, these candidate genes exhibit modular gene expression patterns with unique molecular signatures in distinct cell types, highlighting altered molecular mechanisms in dopaminergic neurons and glial cells including oligodendrocytes and microglia. Together, our single-cell transcriptome and epigenome reveal cell type-specific disruption in transcriptional regulations related to PD.

Novel insights into Hodgkin lymphoma biology by single-cell analysis

The emergence and rapid development of single-cell technologies mark a paradigm shift in cancer research. Various technology implementations represent powerful tools to understand cellular heterogeneity, identify minor cell populations that were previously hard to detect and define, and make inferences about cell-to-cell interactions at single-cell resolution. Applied to lymphoma, recent advances in single-cell RNA sequencing have broadened opportunities to delineate previously underappreciated heterogeneity of malignant cell differentiation states and presumed cell of origin, and to describe the composition and cellular subsets in the ecosystem of the tumor microenvironment (TME). Clinical deployment of an expanding armamentarium of immunotherapy options that rely on targets and immune cell interactions in the TME emphasizes the requirement for a deeper understanding of immune biology in lymphoma. In particular, classic Hodgkin lymphoma (CHL) can serve as a study paradigm because of its unique TME, featuring infrequent tumor cells among numerous nonmalignant immune cells with significant interpatient and intrapatient variability. Synergistic to advances in single-cell sequencing, multiplexed imaging techniques have added a new dimension to describing cellular cross talk in various lymphoma entities. Here, we comprehensively review recent progress using novel single-cell technologies with an emphasis on the TME biology of CHL as an application field. The described technologies, which are applicable to peripheral blood, fresh tissues, and formalin-fixed samples, hold the promise to accelerate biomarker discovery for novel immunotherapeutic approaches and to serve as future assay platforms for biomarker-informed treatment selection, including immunotherapies.

Integrating multiple single-cell multi-omics samples with Smmit

Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells and in multiple samples, facilitate the study of gene expression and gene regulatory activities on a population scale. Existing integration methods can integrate either multiple samples or multiple modalities, but not both simultaneously. To address this limitation, we developed Smmit, a computational pipeline that leverages existing integration methods to simultaneously integrate both samples and modalities and produces a unified representation of reduced dimensions. We demonstrate Smmit's capability to integrate information across samples and modalities while preserving cell type differences in two real datasets. Smmit is an R software package that is freely available at Github: https://github.com/zji90/Smmit.

Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics

Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are 'tagged' with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.

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/ .

Structural and functional properties of mSWI/SNF chromatin remodeling complexes revealed through single-cell perturbation screens

The mammalian SWI/SNF (mSWI/SNF or BAF) family of chromatin remodeling complexes play critical roles in regulating DNA accessibility and gene expression. The three final-form subcomplexes-cBAF, PBAF, and ncBAF-are distinct in biochemical componentry, chromatin targeting, and roles in disease; however, the contributions of their constituent subunits to gene expression remain incompletely defined. Here, we performed Perturb-seq-based CRISPR-Cas9 knockout screens targeting mSWI/SNF subunits individually and in select combinations, followed by single-cell RNA-seq and SHARE-seq. We uncovered complex-, module-, and subunit-specific contributions to distinct regulatory networks and defined paralog subunit relationships and shifted subcomplex functions upon perturbations. Synergistic, intra-complex genetic interactions between subunits reveal functional redundancy and modularity. Importantly, single-cell subunit perturbation signatures mapped across bulk primary human tumor expression profiles both mirror and predict cBAF loss-of-function status in cancer. Our findings highlight the utility of Perturb-seq to dissect disease-relevant gene regulatory impacts of heterogeneous, multi-component master regulatory complexes.

Spatial epigenome-transcriptome co-profiling of mammalian tissues

Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1-5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.

Lineage Tracing and Single-Nucleus Multiomics Reveal Novel Features of Adaptive and Maladaptive Repair after Acute Kidney Injury

SIGNIFICANCE STATEMENT

Understanding the mechanisms underlying adaptive and maladaptive renal repair after AKI and their long-term consequences is critical to kidney health. The authors used lineage tracing of cycling cells and single-nucleus multiomics (profiling transcriptome and chromatin accessibility) after AKI. They demonstrated that AKI triggers a cell-cycle response in most epithelial and nonepithelial kidney cell types. They also showed that maladaptive proinflammatory proximal tubule cells (PTCs) persist until 6 months post-AKI, although they decreased in abundance over time, in part, through cell death. Single-nucleus multiomics of lineage-traced cells revealed regulatory features of adaptive and maladaptive repair. These included activation of cell state-specific transcription factors and cis-regulatory elements, and effects in PTCs even after adaptive repair, weeks after the injury event.

BACKGROUND

AKI triggers a proliferative response as part of an intrinsic cellular repair program, which can lead to adaptive renal repair, restoring kidney structure and function, or maladaptive repair with the persistence of injured proximal tubule cells (PTCs) and an altered kidney structure. However, the cellular and molecular understanding of these repair programs is limited.

METHODS

To examine chromatin and transcriptional responses in the same cell upon ischemia-reperfusion injury (IRI), we combined genetic fate mapping of cycling ( Ki67+ ) cells labeled early after IRI with single-nucleus multiomics-profiling transcriptome and chromatin accessibility in the same nucleus-and generated a dataset of 83,315 nuclei.

RESULTS

AKI triggered a broad cell cycle response preceded by cell type-specific and global transcriptional changes in the nephron, the collecting and vascular systems, and stromal and immune cell types. We observed a heterogeneous population of maladaptive PTCs throughout proximal tubule segments 6 months post-AKI, with a marked loss of maladaptive cells from 4 weeks to 6 months. Gene expression and chromatin accessibility profiling in the same nuclei highlighted differences between adaptive and maladaptive PTCs in the activity of cis-regulatory elements and transcription factors, accompanied by corresponding changes in target gene expression. Adaptive repair was associated with reduced expression of genes encoding transmembrane transport proteins essential to kidney function.

CONCLUSIONS

Analysis of genome organization and gene activity with single-cell resolution using lineage tracing and single-nucleus multiomics offers new insight into the regulation of renal injury repair. Weeks to months after mild-to-moderate IRI, maladaptive PTCs persist with an aberrant epigenetic landscape, and PTCs exhibit an altered transcriptional profile even following adaptive repair.

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.

Transcriptional Activation of Regenerative Hematopoiesis via Vascular Niche Sensing

Transition between activation and quiescence programs in hematopoietic stem and progenitor cells (HSC/HSPCs) is perceived to be governed intrinsically and by microenvironmental co-adaptation. However, HSC programs dictating both transition and adaptability, remain poorly defined. Single cell multiome analysis divulging differential transcriptional activity between distinct HSPC states, indicated for the exclusive absence of Fli-1 motif from quiescent HSCs. We reveal that Fli-1 activity is essential for HSCs during regenerative hematopoiesis. Fli-1 directs activation programs while manipulating cellular sensory and output machineries, enabling HSPCs co-adoptability with a stimulated vascular niche. During regenerative conditions, Fli-1 presets and enables propagation of niche-derived Notch1 signaling. Constitutively induced Notch1 signaling is sufficient to recuperate functional HSC impairments in the absence of Fli-1. Applying FLI-1 modified-mRNA transduction into lethargic adult human mobilized HSPCs, enables their vigorous niche-mediated expansion along with superior engraftment capacities. Thus, decryption of stem cell activation programs offers valuable insights for immune regenerative medicine.

A T follicular helper cell origin for T regulatory type 1 cells

Chronic antigenic stimulation can trigger the differentiation of antigen-experienced CD4+ T cells into T regulatory type 1 (TR1) cells, a subset of interleukin-10-producing Treg cells that do not express FOXP3. The identities of the progenitor(s) and transcriptional regulators of this T-cell subset remain unclear. Here, we show that the peptide-major histocompatibility complex class II (pMHCII) monospecific immunoregulatory T-cell pools that arise in vivo in different genetic backgrounds in response to pMHCII-coated nanoparticles (pMHCII-NPs) are invariably comprised of oligoclonal subpools of T follicular helper (TFH) and TR1 cells with a nearly identical clonotypic composition but different functional properties and transcription factor expression profiles. Pseudotime analyses of scRNAseq data and multidimensional mass cytometry revealed progressive downregulation and upregulation of TFH and TR1 markers, respectively. Furthermore, pMHCII-NPs trigger cognate TR1 cell formation in TFH cell-transfused immunodeficient hosts, and T-cell-specific deletion of Bcl6 or Irf4 blunts both the TFH expansion and TR1 formation induced by pMHCII-NPs. In contrast, deletion of Prdm1 selectively abrogates the TFH-to-TR1 conversion. Bcl6 and Prdm1 are also necessary for anti-CD3 mAb-induced TR1 formation. Thus, TFH cells can differentiate into TR1 cells in vivo, and BLIMP1 is a gatekeeper of this cellular reprogramming event.

Nuclear receptor Nr5a2 promotes diverse connective tissue fates in the jaw

Organ development involves the sustained production of diverse cell types with spatiotemporal precision. In the vertebrate jaw, neural-crest-derived progenitors produce not only skeletal tissues but also later-forming tendons and salivary glands. Here we identify the pluripotency factor Nr5a2 as essential for cell-fate decisions in the jaw. In zebrafish and mice, we observe transient expression of Nr5a2 in a subset of mandibular postmigratory neural-crest-derived cells. In zebrafish nr5a2 mutants, nr5a2-expressing cells that would normally form tendons generate excess jaw cartilage. In mice, neural-crest-specific Nr5a2 loss results in analogous skeletal and tendon defects in the jaw and middle ear, as well as salivary gland loss. Single-cell profiling shows that Nr5a2, distinct from its roles in pluripotency, promotes jaw-specific chromatin accessibility and gene expression that is essential for tendon and gland fates. Thus, repurposing of Nr5a2 promotes connective tissue fates to generate the full repertoire of derivatives required for jaw and middle ear function.

Single-cell multiomic analysis reveals the involvement of Type I interferon-responsive CD8+ T cells in amyloid beta-associated memory loss

Alzheimer's disease (AD) is the leading cause of dementia worldwide, but there are limited therapeutic options and no current cure. While the involvement of microglia in AD has been highly appreciated, the role of other innate and adaptive immune cells remains largely unknown, partly due to their scarcity and heterogeneity. This study aimed to study non-microglial immune cells in wild type and AD-transgenic mouse brains across different ages. Our results uncovered the presence of a unique CD8+ T cell population that were selectively increased in aging AD mouse brains, here referred to as "disease-associated T cells (DATs)". These DATs were found to express an elevated tissue-resident memory and Type I interferon-responsive gene signature. Further analysis of aged AD mouse brains showed that these CD8+ T cells were not present in peripheral or meningeal tissues. Preventing CD8+ T cell development in AD-transgenic mice via genetic deletion of beta-2 microglobulin ( B2m ) led to a reduction of amyloid-β plaque formation in aged mice, and improved memory in AD-transgenic mice as early as four months of age. The integration of transcriptomic and epigenomic profiles at the single-cell level revealed potential transcription factors that reshape the regulomes of CD8+ T cells. These findings highlight a critical role for DATs in the progression of AD and provide a new avenue for treatment.

Single substitution in H3.3G34 alters DNMT3A recruitment to cause progressive neurodegeneration

Germline histone H3.3 amino acid substitutions, including H3.3G34R/V, cause severe neurodevelopmental syndromes. To understand how these mutations impact brain development, we generated H3.3G34R/V/W knock-in mice and identified strikingly distinct developmental defects for each mutation. H3.3G34R-mutants exhibited progressive microcephaly and neurodegeneration, with abnormal accumulation of disease-associated microglia and concurrent neuronal depletion. G34R severely decreased H3K36me2 on the mutant H3.3 tail, impairing recruitment of DNA methyltransferase DNMT3A and its redistribution on chromatin. These changes were concurrent with sustained expression of complement and other innate immune genes possibly through loss of non-CG (CH) methylation and silencing of neuronal gene promoters through aberrant CG methylation. Complement expression in G34R brains may lead to neuroinflammation possibly accounting for progressive neurodegeneration. Our study reveals that H3.3G34-substitutions have differential impact on the epigenome, which underlie the diverse phenotypes observed, and uncovers potential roles for H3K36me2 and DNMT3A-dependent CH-methylation in modulating synaptic pruning and neuroinflammation in post-natal brains.

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.

Major cell-types in multiomic single-nucleus datasets impact statistical modeling of links between regulatory sequences and target genes

Epigenomic profiling, including ATACseq, is one of the main tools used to define enhancers. Because enhancers are overwhelmingly cell-type specific, inference of their activity is greatly limited in complex tissues. Multiomic assays that probe in the same nucleus both the open chromatin landscape and gene expression levels enable the study of correlations (links) between these two modalities. Current best practices to infer the regulatory effect of candidate cis-regulatory elements (cCREs) in multiomic data involve removing biases associated with GC content by generating null distributions of matched ATACseq peaks drawn from different chromosomes. This strategy has been broadly adopted by popular single-nucleus multiomic workflows such as Signac. Here, we uncovered limitations and confounders of this approach. We found a strong loss of power to detect a regulatory effect for cCREs with high read counts in the dominant cell-type. We showed that this is largely due to cell-type-specific trans-ATACseq peak correlations creating bimodal null distributions. We tested alternative models and concluded that physical distance and/or the raw Pearson correlation coefficients are the best predictors for peak-gene links when compared to predictions from Epimap (e.g. CD14 area under the curve [AUC] = 0.51 with the method implemented in Signac vs. 0.71 with the Pearson correlation coefficients) or validation by CRISPR perturbations (AUC = 0.63 vs. 0.73).

Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements

Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidate regulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factors playing important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.

Lineage Commitment of Dermal Fibroblast Progenitors is Mediated by Chromatin De-repression

Dermal Fibroblast Progenitors (DFPs) differentiate into distinct fibroblast lineages during skin development. However, the mechanisms that regulate lineage commitment of naive dermal progenitors to form niches around the hair follicle, dermis, and hypodermis, are unknown. In our study, we used multimodal single-cell approaches, epigenetic assays, and allografting techniques to define a DFP state and the mechanisms that govern its differentiation potential. Our results indicate that the overall chromatin profile of DFPs is repressed by H3K27me3 and has inaccessible chromatin at lineage specific genes. Surprisingly, the repressed chromatin profile of DFPs renders them unable to reform skin in allograft assays despite their multipotent potential. Distinct fibroblast lineages, such as the dermal papilla and adipocytes contained specific chromatin profiles that were de-repressed during late embryogenesis by the H3K27-me3 demethylase, Kdm6b/Jmjd3. Tissue-specific deletion of Kdm6b/Jmjd3 resulted in ablating the adipocyte compartment and inhibiting mature dermal papilla functions in single-cell-RNA-seq, ChIPseq, and allografting assays. Altogether our studies reveal a mechanistic multimodal understanding of how DFPs differentiate into distinct fibroblast lineages, and we provide a novel multiomic search-tool within skinregeneration.org.

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.

Multi-omic single-cell velocity models epigenome-transcriptome interactions and improves cell fate prediction

Multi-omic single-cell datasets, in which multiple molecular modalities are profiled within the same cell, offer an opportunity to understand the temporal relationship between epigenome and transcriptome. To realize this potential, we developed MultiVelo, a differential equation model of gene expression that extends the RNA velocity framework to incorporate epigenomic data. MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression and improves the accuracy of cell fate prediction compared to velocity estimates from RNA only. Application to multi-omic single-cell datasets from brain, skin and blood cells reveals two distinct classes of genes distinguished by whether chromatin closes before or after transcription ceases. We also find four types of cell states: two states in which epigenome and transcriptome are coupled and two distinct decoupled states. Finally, we identify time lags between transcription factor expression and binding site accessibility and between disease-associated SNP accessibility and expression of the linked genes. MultiVelo is available on PyPI, Bioconda and GitHub ( https://github.com/welch-lab/MultiVelo ).

Cerebellar Granule Cells Develop Non-neuronal 3D Genome Architecture over the Lifespan

The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells-the most abundant neuron type-develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.