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Zhou, W.

Publications and source records attributed to Zhou, W..

At least 109 records · Page 6Linked to original sources

Sparse Sequencing permits accurate and efficient quantification of genome-wide cytosine modification levels

5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) regulate gene expression and exhibit dynamic levels during development and disease. While high-depth, base-resolution studies offer the most detailed view of epigenetic landscapes, many open questions are answered by surveying changes in 5mC/5hmC levels across larger cohorts. Nonetheless, current global quantification methods, including mass spectrometry, are typically limited in accessibility, accuracy, or throughput. Here, to evaluate the viability of low-coverage sequencing as an alternative, we first computationally downsampled deeply sequenced data to resolve the three-way relationship between sequencing coverage, modification levels, and measurement error. This relationship allowed us to develop a facile online tool for error calculation and to define experimental targets: <0.24% genome coverage can quantify 5mC and low-abundance 5hmC with minimal and predictable errors (<5%). Importantly, in direct comparisons, low-depth sequencing (Sparse-Seq) demonstrated high accuracy and less variability than mass spectrometry, while distinctively preserving genomic context. Applied serially to developing mouse brains, Sparse-Seq revealed an earlier emergence of 5hmCpG compared to 5mCpH and uncovered previously overlooked, genomic feature-specific epigenetic changes. This work establishes a rigorous foundation for employing Sparse-Seq as a highly accessible approach for 5mC/5hmC quantification, enabling economical first-pass analysis of epigenetic landscapes suited for large cohort studies and new hypothesis generation.

genomics↗

Niacin protects against vascular calcification via enhanced SIRT1 and SIRT6 signaling and promoted VSMC autophagy

BackgroundVascular calcification (VC) is a common pathologic state that often accompanies calcium-phosphorus metabolism disorder and chronic kidney diseases (CKDs) in aging individuals. Vascular smooth muscle cell (VSMC) has been widely acknowledged as one of the main cell types that involved in this process. Niacin, a lipid-lowering reagent, has been demonstrated to be beneficial in atherosclerotic disease. The correlation and mechanism between niacin and vascular calcification have not been reported so far. Methods and resultsRCS analysis based on large clinical databases indicated that diet that riches in niacin can protect against abdominal artery calcification (AAC). Our data showed that niacin treatment remarkably reduced VSMC osteogenic differentiation and senescence-associated markers under osteogenic stimulation. Moreover, niacin treatment alleviated CKD and vitamin D3-induced vascular calcification in C57BL/6J mice. Mechanistically, we for the first time demonstrated that niacin supplementation inhibited vascular calcification via maintaining both Sirtuin 1 (SIRT1) and Sirtuin 6 (SIRT6) levels. Moreover, we verified that niacin activated SIRT1 and SIRT6 promoted VSMC autophagy flux. ConclusionsThese findings may help to develop novel therapeutic strategies in the treatment and prevention of vascular calcification.

cell biology↗

TGFBR2-High mesenchymal glioma stem cells phenocopy regulatory T cells to suppress CD4+ and CD8+ T cell function

Attempts to activate an anti-tumor immune response in glioblastoma (GBM) have been met with many challenges due to its inherently immunosuppressive tumor microenvironment. The degree and mechanisms by which molecularly and phenotypically diverse tumor-propagating glioma stem cells (GSCs) contribute to this state are poorly defined. In this study, our multifaceted approach combining bioinformatics analyses of clinical and experimental datasets, single-cell sequencing, and molecular and pharmacologic manipulation of patient-derived cells identified GSCs expressing immunosuppressive effectors mimicking regulatory T cells (Tregs). We show that this Immunosuppressive Treg-Like (ITL) GSC state is specific to the mesenchymal GSC subset and is associated with and driven specifically by TGF-{beta} type II receptor (TGFBR2) in contrast to TGFBR1. Transgenic TGFBR2 expression in patient-derived GBM neurospheres promoted a mesenchymal transition and induced a 6-gene ITL signature consisting of CD274 (PD-L1), NT5E (CD73), ENTPD1 (CD39), LGALS1 (galectin-1), PDCD1LG2 (PD-L2), and TGFB1. This TGFBR2-driven ITL signature was identified in clinical GBM specimens, patient-derived GSCs and systemic mesenchymal malignancies. TGFBR2High GSCs inhibited CD4+ and CD8+ T cell viability and their capacity to kill GBM cells, effects reversed by pharmacologic and shRNA-based TGFBR2 inhibition. Collectively, our data identify an immunosuppressive GSC state that is TGFBR2-dependent and susceptible to TGFBR2-targeted therapeutics.

cancer biology↗

Computational Fluid Dynamics (CFD) Modeling of Ilamycin E Production in Streptomyces atratus SCSIO ZH16 Submerged Fermentation

A computational fluid dynamics (CFD) model was developed and validated against experiments for a laboratory-scale 5-L bioreactor. Numerical simulation was performed to describe the bioreaction of Streptomyces atratus SCSIO ZH16 fermentation for ilamycin E production with the dynamic changes in viscosity of the fermentation broth due to biomass growth and decay. This model can account for the two-way coupling between the fermentation environment and medium, which allowed for the elucidation of the impact of the flow field in the bioreactor on bacterial growth and production, as well as the influence of viscosity changes on the flow field. This work represents the first integration of Streptomyces fermentation with CFD, enabling the simulation of flow field and mass transfer under varying stirring speed, aeration rate, and viscosity during Streptomyces fermentation. An optimum range of fermentation broth viscosity (10-30 mPa s) was identified for ilamycin E production by S. atratus SCSIO ZH16 fermentation. Furthermore, the addition of sorbitol to optimize the viscosity of the fermentation broth in the later stages of fermentation. The enhanced mass transfer efficiency strengthens the respiration, energy supply, and carbon source consumption in Streptomyces, thereby increasing the ilamycin E production. This research offers a practical strategy for the process intensification and industrial scale-up for such bioreactors. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/630827v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@3d463corg.highwire.dtl.DTLVardef@ce3859org.highwire.dtl.DTLVardef@d55c7forg.highwire.dtl.DTLVardef@1abaee5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Enzyme-independent functions of HDAC3 in the adult heart

The cardioprotective effects of histone deacetylase (HDAC) inhibitors (HDIs) are at odds with the deleterious effects of HDAC depletion. Here, we use HDAC3 as a prototype HDAC to address this contradiction. We show that adult-onset cardiac-specific depletion of HDAC3 in mice causes cardiac hypertrophy and contractile dysfunction on a high-fat diet (HFD), excluding developmental disruption as a major reason for the contradiction. Genetically abolishing HDAC3 enzymatic activity without affecting its protein level does not cause cardiac dysfunction on HFD. HDAC3 depletion causes robust downregulation of lipid oxidation/bioenergetic genes and upregulation of antioxidant/anti-apoptotic genes. In contrast, HDAC3 enzyme activity abolishment causes much milder changes in far fewer genes. The abnormal gene expression is cardiomyocyte-autonomous and can be rescued by an enzyme-dead HDAC3 mutant but not by an HDAC3 mutant ({Delta}33-70) that lacks interaction with the nuclear-envelope protein lamina-associated polypeptide 2{beta} (LAP2{beta}). Tethering LAP2{beta} to the HDAC3 {Delta}33-70 mutant restored its ability to rescue gene expression. Finally, HDAC3 depletion, not loss of HDAC3 enzymatic activity, exacerbates cardiac contractile functions upon aortic constriction. These results suggest that the cardiac function of HDAC3 in adults is not attributable to its enzyme activity, which has implications for understanding the cardioprotective effects of HDIs.

physiology↗

Single-cell analysis reveals distinct immune characteristics of hepatocellular carcinoma in HBV-positive versus HBV-negative cases

Infection with the Hepatitis B virus (HBV) is a key risk factor for Hepatocellular carcinoma (HCC) development and progression. It is widely recognized that immunopathological mechanisms are pivotal in developing HBV-related HCC. Nevertheless, the specific mechanisms by which HBV-induced modifications within the tumor microenvironment (TME) contribute to HCC pathogenesis are still not well understood. Here, we utilized single-cell RNA sequencing to analyze and compare the immune landscapes between HBV-positive and HBV-negative HCC. We discovered that HBV infection significantly modifies the immune cell makeup and state, and leads to the suppression and exhaustion of T cells within the TME. Specifically, an increase in SLC4A10+ CD8+ T cells and IFITM3+ macrophages was observed, along with the upregulation of the gene SLC35F1 in various immune cell subtypes. These findings offer valuable insights into the alteration of the immunological microenvironment in HCC associated with HBV infection, suggesting possible targets for immunotherapeutic intervention.

bioinformatics↗

A personalized multi-platform assessment of somatic mosaicism in the human frontal cortex

Somatic mutations in individual cells create genomic mosaicism, influencing genetic disorders and cancers. While clonal mutations in cancers are well-studied, rarer somatic variants in normal tissues remain poorly characterized. This study systematically evaluates detection methods using a personalized donor-specific assembly (DSA) from a neurotypical individuals dorsolateral prefrontal cortex assessed with Oxford Nanopore, NovaSeq, linked-read sequencing, Cas9-targeted long-read sequencing (TEnCATS), and single-neuron MALBAC amplification. The haplotype-resolved DSA improved cross-platform analysis, dramatically increasing phasing rates. Germline SNVs, structural variations (SVs), and transposable elements (TEs) were recalled with 99.4%-99.7% accuracy in bulk tissue, and phased haplotype analysis reduced false positives by 15.4%-75.1% for putative somatic candidates. Long-read single-neuron sequencing detected nine somatic SV candidates, demonstrating enhanced sensitivity for rare variants, while TEnCATS identified eight low-frequency somatic TE candidates. These findings highlight advanced methodologies for precise somatic variant detection, critical for understanding mosaicisms role in health and disease.

genomics↗

Flexibility in Gene Coexpression at Developmental and Evolutionary Timescales

The explosion of next-generation sequencing technologies has allowed researchers to move from studying single genes to thousands of genes, and thereby to also consider the relationships within gene networks. Like others, we are interested in understanding how developmental and evolutionary forces shape the expression of individual genes, as well as the interactions among genes. In pursuing these questions, we confronted the central challenge that standard approaches fail to control the Type I error and/or have low power in the presence of high dimensionality (i.e., large number of genes) and small sample size, as in many gene expression studies. To overcome these challenges, we used random projection tests and correlation network comparisons to characterize differences in network connectivity and density. We detail central challenges, discuss sample size guidelines, and provide rigorous statistical approaches for exploring coexpression differences with small sample sizes. We apply these approaches in a species known for rapid adaptation - the Trinidadian guppy (Poecilia reticulata). Our findings provide evidence for coexpression network differences at developmental and evolutionary timescales and suggest that flexibility in gene coexpression relationships could promote evolvability.

evolutionary biology↗

Gender-specific Single Transcript Level Atlas of Vasopressin and its Receptor (AVPR1a) in the Mouse Brain

Vasopressin (AVP), a nonapeptide synthesized predominantly by magnocellular hypothalamic neurons, is conveyed to the posterior pituitary via the pituitary stalk, where AVP is secreted into the circulation. Known to regulate blood pressure and water homeostasis, it also modulates diverse social behaviors, such as pair-bonding, social recognition and cognition in mammals including humans. Importantly, AVP modulates social behaviors in a sex-specific manner, perhaps, due to sex differences in the distribution in the brain of AVP and its main receptor AVPR1a. There is a corpus of integrative studies for the expression of AVP and AVPR1a in various brain regions, and their functions in modulating central and peripheral actions. In order to purposefully address sexually dimorphic and novel roles of AVP on central and peripheral functions through its AVPR1a, we utilized RNAscope to map Avp and Avpr1a single transcript expression in the mouse brain. As the most comprehensive atlas of AVP and AVPR1a in the mouse brain, this compendium highlights the importance of newly identified AVP/AVPR1a neuronal nodes that may stimulate further functional studies.

neuroscience↗

Reciprocal links between methionine metabolism, DNA repair and therapy resistance in glioblastoma

Glioblastoma (GBM) is uniformly lethal due to profound treatment resistance. Altered cellular metabolism is a key mediator of GBM treatment resistance. Uptake of the essential sulfur-containing amino acid methionine is drastically elevated in GBMs compared to normal cells, however, it is not known how this methionine is utilized or whether it relates to GBM treatment resistance. Here, we find that radiation acutely increases the levels of methionine-related metabolites in a variety of treatment-resistant GBM models. Stable isotope tracing studies further revealed that radiation acutely activates methionine to S-adenosyl methionine (SAM) conversion through an active signaling event mediated by the kinases of the DNA damage response. In vivo tumor SAM synthesis increases after radiation, while normal brain SAM production remains unchanged, indicating a tumor- specific metabolic alteration to radiation. Pharmacological and dietary strategies to block methionine to SAM conversion slowed DNA damage response and increased cell death following radiation in vitro. Mechanistically, these effects are due to depletion of DNA repair proteins and are reversed by SAM supplementation. These effects are selective to GBMs lacking the methionine salvage enzyme methylthioadenosine phosphorylase. Pharmacological inhibition of SAM synthesis hindered tumor growth in flank and orthotopic in vivo GBM models when combined with radiation. By contrast, methionine depletion does not reduce tumor SAM levels and fails to radiosensitize intracranial models, indicating depleting SAM, as opposed to simply lowering methionine, is critical for hindering tumor growth in intracranial models of GBM. These results highlight a new signaling link between DNA damage and SAM synthesis and define the metabolic fates of methionine in GBM in vivo. Inhibiting radiation-induced SAM synthesis slows DNA repair and augments radiation efficacy in GBM. Using MAT2A inhibitors to deplete SAM may selectively overcome treatment resistance in GBMs with defective methionine salvage while sparing normal brain.

cancer biology↗

Pan-cancer study on transition of signaling systems from primary to metastatic tumors

Metastatic progression is responsible for the majority of cancer-related deaths. A better understanding of the underlying molecular mechanisms driving metastasis therefore remains of utmost importance. Here we take efforts to excavate mutant driver factors of metastases in the level of signaling pathways. We introduce two models, EntCDP and ModSDP, to detect the similarity and specificity of pathways in a pan-cancer context. The simulation studies confirm their feasibility and identification accuracy. Using mutation profiles of 17 cancer types with primary and metastatic cohorts from MSK-IMPACT, we apply the two models to investigate the transition of signaling systems from primary to metastatic tumors mainly from five perspectives. 1) We initially perform a comprehensive comparison of 15 primary-metastatic cancer pairs. Nearly all shared common driver genes or pathways, while specific driver gene sets of primary or/and metastatic tumors can be seen for almost each pair, except for breast cancer. 2) We use ModSDP to identify the specificity of metastases with the same primary site and highlight calcium signaling in breast cancer with bone metastasis, FoxO signaling for melanoma/lung lymph node metastasis, etc. 3) Oppositely, we use EntCDP to identify common factors yielding three frequently metastatic sites (liver, lung and brain), and recognized cushing syndrome, microRNAs in cancer and MAPK signaling pathway, separately. 4) Regarding high-tropism metastatic patterns, we investigated the relationship between the metastatic tumor and primary tumors in both locations. In the typical pattern of colorectal cancer metastasis to the liver, we detected hepatic signals in primary colorectal cancer. 5) Finally, we focused on the common and specific characteristics of relevant cancer types, such as gender-related cancers and gastrointestinal cancers. Study on gynecologic tumors suggest endocrine hormone change and virus infection as their common risk factors, while for male we highlight hedgehog signaling and EPH-related receptors as invasive potential of prostate cancer. Multiple interesting findings revealed by this study may be helpful for the understanding of the extent of signal changes during tumor metastasis. We expect that this study will provide a valuable resource for transforming our knowledge about signals in cancer metastasis into alternative clinical practice for advanced patients.

bioinformatics↗

Assessing Conformation Validity and Rationality of Deep Learning-Generated 3D Molecules

Recent advancements in artificial intelligence (AI) have revolutionized the field of 3D molecule generation. However, the lack of effective evaluation methods for 3D conformations limits further improvements. Current techniques, in order to achieve the necessary speed for evaluating large numbers of AI-generated molecules, often rely on empirical geometric metrics that do not adequately capture various conformational anomalies, or on molecular mechanics (MM) energy metrics that exhibit low accuracy and lack atomic or torsional details. To address this gap, we propose a two-stage approach that achieves both high speed and quantum mechanical (QM) level accuracy. The first stage, termed the validity test, employs an AI-derived force field to identify atoms with elevated energy resulting from implausible neighboring environments. The second stage, known as the rationality test, utilizes a deep learning network trained on data with density functional theory (DFT) accuracy to detect rotatable bonds with high torsional energies. To demonstrate the functionality of our evaluation system, we applied our approach to five recently reported 3D molecule generation AI models across 102 targets in Directory of Useful Decoys-Enhanced (DUD-E) dataset. To facilitate accessibility for the academic community, our method is available as an open-source package.

bioinformatics↗

Quantifying Functional Conservation of Human and Mouse Regulatory Elements via FUNCODE

Evolutionary conservation is crucial for understanding genome functions and lays the foundation for using animal models in studying human diseases. However, conventional conservation scores based on DNA sequence evolution do not capture the dynamic biochemical activities of DNA elements, termed functional conservation. Quantifying functional conservation has been limited by the availability of functional genomic data matched across species. To address this, we developed FUNCODE, a framework for characterizing functional conservation through in silico sample matching. Applying FUNCODE to 2,595 uniformly processed datasets from the Encyclopedia of DNA Elements (ENCODE), we generated genome-wide FUNCODE scores for human and mouse regulatory elements, identifying 3.3 million functionally conserved human-mouse element pairs. We demonstrate FUNCODEs diverse applications, including annotating 78,501 novel regulatory elements, transferring 37,968 high-resolution human ENCODE Hi-C loops in immune lineages to mice, identifying conserved functional signals for disease modeling, and enhancing cross-species integration of single-cell omics data.

genomics↗

Orexinergic projections to substantia innominata mediate arousal and analgesia

Understanding neural circuits involved in anesthesia is crucial for improving its safety and efficacy. Hypothalamic orexin neurons (LHAOX), projecting broadly, are essential in regulating arousal and pain. However, the precise targets remain unclear. Here we investigated the orexin projections to the substantia innominata (SI). Combining optogenetics, fiber photometry, and EEG/EMG allowed us to manipulate orexin activities, while simultaneously recording local ligand release and global cortical activities during anesthesia. Brain slice electrophysiology revealed the synaptic connections in the SI, while RNAscope was employed to examine the distribution of orexin receptors and downstream neuronal types. Presynaptic vesicles were identified in the orexin terminals in the SI, where 49.16% of cells expressed OX2R and 6.8% expressed OX1R. Orexin release in the SI was reversibly suppressed by isoflurane. Optogenetic activation of the LHAOX[->]SI circuit significantly increased orexin release and promoted arousal from various anesthesia stages, including reanimation during 0.75% isoflurane (p < 0.0001), prolongation of 3% isoflurane induction (p = 0.0033), and acceleration of emergence from 2% isoflurane (p < 0.0001). Furthermore, activating this circuit induced analgesia to both thermal (p = 0.0074) and inflammatory (p = 0.0127) pain. Patch-clamp recordings revealed that optogenetic activation of orexin terminals in the SI elicited excitatory postsynaptic currents, which were blocked by the OX2R antagonist. SI contains more GABAergic (28.17%) and glutamatergic (11.96%) neurons than cholinergic neurons (4.13%), all of which expressed OX2R. Thus, LHAOX neurons innervate SI neurons to regulate both arousal and pain predominantly through OX2R.

neuroscience↗

DNA methylation memory of pancreatic acinar-ductal metaplasia transition state altering Kras-downstream PI3K and Rho GTPase signaling in the absence of Kras mutation

A critical area of recent cancer research is the emergence of transition states between normal and cancer that exhibit increased cell plasticity which underlies tumor cell heterogeneity. Pancreatic ductal adenocarcinoma (PDAC) can arise from the combination of a transition state termed acinar-to-ductal metaplasia (ADM) and a gain-of-function mutation in the proto-oncogene KRAS. During ADM, digestive enzyme-producing acinar cells acquire a transient ductal epithelium-like phenotype while maintaining their geographical acinar organization. One route of ADM initiation is the overexpression of the Kruppel-like factor 4 gene (KLF4) in the absence of oncogenic driver mutations. Here, we asked to what extent cells acquire and retain an epigenetic memory of the ADM transition state in the absence of oncogene mutation. We identified differential DNA methylation at Kras-downstream PI3K and Rho/Rac/Cdc42 GTPase pathway genes during ADM, as well as a corresponding gene expression increase in these pathways. Importantly, differential methylation persisted after gene expression returned to normal. Caerulein exposure, which induces widespread digestive system changes in addition to ADM, showed similar changes in DNA methylation in ADM cells. Regions of differential methylation were enriched for motifs of KLF and AP-1 family transcription factors, as were those of human pancreatic intraepithelial neoplasia (PanIN) samples, demonstrating the relevance of this epigenetic transition state memory in human carcinogenesis. Finally, single-cell spatial transcriptomics revealed that these ADM transition cells were enriched for PI3K pathway and AP1 family members, linking epigenetic memory to cancer cell plasticity even in the absence of oncogene mutation.

cancer biology↗

DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML

Disruption of the epigenetic landscape is of particular interest in acute myeloid leukemia (AML) due to its relatively low mutational burden and frequent occurrence of mutations in epigenetic regulators. Here, we applied an information-theoretic analysis of methylation potential energy landscapes, capturing changes in mean methylation level and methylation entropy, to comprehensively analyze DNA methylation stochasticity in subtypes of AML defined by mutually exclusive genetic mutations. We identified AML subtypes with CEBPA double mutation and those with IDH mutations as distinctly high-entropy subtypes, marked by methylation disruption over a convergent set of genes. We found a core program of epigenetic landscape disruption across all AML subtypes, with discordant methylation stochasticity and transcriptional dysregulation converging on functionally important leukemic signatures, suggesting a genotype-independent role of stochastic disruption of the epigenetic landscape in mediating leukemogenesis. We further established a relationship between methylation entropy and gene expression variability, connecting the disruption of the epigenetic landscape to transcription in AML. This approach identified a convergent program of epigenetic dysregulation in leukemia, clarifying the contribution of specific genetic mutations to stochastic disruption of the epigenetic and transcriptional landscapes of AML.

cancer biology↗

Further characterization and engineering of a 11-amino acid motif for enhancing recombinant protein expression

BackgroundRecombinant protein production in Escherichia coli (E. coli) is a widely used system in both academic and industrial research owing to its low cost and wide availability of genetic tools. Despite its advantages, this system still struggles with soluble expression of recombinant proteins. To address this, various solubility-enhancing and yield-improving methods such as the addition of fusion tags have been developed. However, traditional tags such as small ubiquitin-related modifier (SUMO) and Glutathione S-transferase (GST) can interfere with protein folding or require removal post-translation, which adds complexity and cost to production. To circumvent these issues, smaller solubility tags (<10 kDa) are preferred. This study specifically focuses on an 11-amino acid solubility-enhancing tag (NT11) derived from the N-terminal domain of a duplicated carbonic anhydrase from Dunaliella species. ResultsA comprehensive analysis was performed to improve the characteristics of the 11-amino acid tag. By investigating the alanine-scan library of NT11, we increased its activity and identified key residues for further development. Screening with the alanine mutant library consistently led to at least a two-fold improvement in protein yield for three different proteins. We also discovered that the NT11 tag is not limited to the N-terminal position and can function at either the N- or C-terminal of the protein, providing flexibility in designing protein expression constructs. With these new insights, we have successfully doubled the recombinant protein yields of valuable growth factors, such as fibroblast growth factor 2 (FGF2) and an originally low-yielding human epidermal growth factor (hEGF), in E. coli. ConclusionThe further characterisation and development of the NT11 tag have provided valuable insights into the optimization process for such small tags and expanded our understanding of its potential applications. The ability of NT11 tag to be positioned at different locations within the protein construct without compromising its effectiveness to enhance recombinant protein yields, makes it a valuable tool across a diverse range of proteins. Collectively, these findings have the potential to simplify and enhance the efficiency of recombinant protein production.

synthetic biology↗

High-coverage allele-resolved single-cell DNA methylation profiling by scDEEP-mC reveals cell lineage, X-inactivation state, and replication dynamics

DNA methylation is a relatively stable epigenetic mark with important roles in development and disease.1 Since cell-to-cell variation in epigenetic programming can reflect important differences in cell state and fate, it is clear that single-cell methods are essential to understanding this key epigenetic mark in heterogeneous tissues. Existing single-cell whole-genome bisulfite sequencing (scWGBS) methods2 have significant shortcomings, including very low CpG coverage3-7 or inefficient library generation requiring extremely deep sequencing.8 These methods offer limited insight into focal regulatory regions and generally preclude direct cell-to-cell comparisons. To address these shortcomings, we have developed an improved method, scDEEP-mC (single-cell Deep and Efficient Epigenomic Profiling of methyl-C). We show that high-coverage promoter methylation profiling by scDEEP-mC can identify multiple cell types, while allele-resolved methylation calls allow assessment of X-inactivation state in single cells and identification of transcription factor binding sites (TFBS) enriched for hemi-methylation. We also use scDEEP-mC to profile single-cell copy number alterations, identify actively replicating cells, and track DNA methylation dynamics during and after DNA replication. The high coverage of scDEEP-mC creates an exceptional opportunity to explore DNA methylation biology in individual cells.

genomics↗