scMethBank: a database for single-cell whole genome DNA methylation maps

Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia

Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.

S-nitrosothiol homeostasis maintained by ADH5 facilitates STING-dependent host defense against pathogens

Oxidative (or respiratory) burst confers host defense against pathogens by generating reactive species, including reactive nitrogen species (RNS). The microbial infection-induced excessive RNS damages many biological molecules via S-nitrosothiol (SNO) accumulation. However, the mechanism by which the host enables innate immunity activation during oxidative burst remains largely unknown. Here, we demonstrate that S-nitrosoglutathione (GSNO), the main endogenous SNO, attenuates innate immune responses against herpes simplex virus-1 (HSV-1) and Listeria monocytogenes infections. Mechanistically, GSNO induces the S-nitrosylation of stimulator of interferon genes (STING) at Cys257, inhibiting its binding to the second messenger cyclic guanosine monophosphate-adenosine monophosphate (cGAMP). Alcohol dehydrogenase 5 (ADH5), the key enzyme that metabolizes GSNO to decrease cellular SNOs, facilitates STING activation by inhibiting S-nitrosylation. Concordantly, Adh5 deficiency show defective STING-dependent immune responses upon microbial challenge and facilitates viral replication. Thus, cellular oxidative burst-induced RNS attenuates the STING-mediated innate immune responses to microbial infection, while ADH5 licenses STING activation by maintaining cellular SNO homeostasis.

A DNA methylation haplotype block landscape in human tissues and preimplantation embryos reveals regulatory elements defined by comethylation patterns

DNA methylation and associated regulatory elements play a crucial role in gene expression regulation. Previous studies have focused primarily on the distribution of mean methylation levels. Advances in whole-genome bisulfite sequencing (WGBS) have enabled the characterization of DNA methylation haplotypes (MHAPs), representing CpG sites from the same read fragment on a single chromosome, and the subsequent identification of methylation haplotype blocks (MHBs), in which adjacent CpGs on the same fragment are comethylated. Using our expert-curated WGBS data sets, we report comprehensive landscapes of MHBs in 17 representative normal somatic human tissues and during early human embryonic development. Integrative analysis reveals MHBs as a distinctive type of regulatory element characterized by comethylation patterns rather than mean methylation levels. We show the enrichment of MHBs in open chromatin regions, tissue-specific histone marks, and enhancers, including super-enhancers. Moreover, we find that MHBs tend to localize near tissue-specific genes and show an association with differential gene expression that is independent of mean methylation. Similar findings are observed in the context of human embryonic development, highlighting the dynamic nature of MHBs during early development. Collectively, our comprehensive MHB landscapes provide valuable insights into the tissue specificity and developmental dynamics of DNA methylation.

Decoding Aging Hallmarks at the Single-Cell Level

Organismal aging exhibits wide-ranging hallmarks in divergent cell types across tissues, organs, and systems. The advancement of single-cell technologies and generation of rich datasets have afforded the scientific community the opportunity to decode these hallmarks of aging at an unprecedented scope and resolution. In this review, we describe the technological advancements and bioinformatic methodologies enabling data interpretation at the cellular level. Then, we outline the application of such technologies for decoding aging hallmarks and potential intervention targets and summarize common themes and context-specific molecular features in representative organ systems across the body. Finally, we provide a brief summary of available databases relevant for aging research and present an outlook on the opportunities in this emerging field.

Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell-cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

Epigenetic modifications as therapeutic targets in atherosclerosis: a focus on DNA methylation and non-coding RNAs

Significant progress in the diagnosis and treatment of cardiovascular disease (CVD) has been made in the past decade, yet it remains a leading cause of morbidity and mortality globally, claiming an estimated 17.9 million deaths per year. Although encompassing any condition that affects the circulatory system, including thrombotic blockage, stenosis, aneurysms, blood clots and arteriosclerosis (general hardening of the arteries), the most prevalent underlying hallmark of CVD is atherosclerosis; the plaque-associated arterial thickening. Further, distinct CVD conditions have overlapping dysregulated molecular and cellular characteristics which underlie their development and progression, suggesting some common aetiology. The identification of heritable genetic mutations associated with the development of atherosclerotic vascular disease (AVD), in particular resulting from Genome Wide Association Studies (GWAS) studies has significantly improved the ability to identify individuals at risk. However, it is increasingly recognised that environmentally-acquired, epigenetic changes are key factors associated with atherosclerosis development. Increasing evidence suggests that these epigenetic changes, most notably DNA methylation and the misexpression of non-coding, microRNAs (miRNAs) are potentially both predictive and causal in AVD development. This, together with their reversible nature, makes them both useful biomarkers for disease and attractive therapeutic targets potentially to reverse AVD progression. We consider here the association of aberrant DNA methylation and dysregulated miRNA expression with the aetiology and progression of atherosclerosis, and the potential development of novel cell-based strategies to target these epigenetic changes therapeutically.

MST4 as a novel therapeutic target for autophagy and radiosensitivity in gastric cancer

BACKGROUND

Mammalian ste20-like kinase 4 (MST4) and autophagy have been implicated in ailments such as inflammatory and cancers.

METHODS

In this study, the expression of MST4 data was extracted from TCGA, GTEx, and GEPIA. The infiltration of immune cells and methylation level of MST4 in tumor and normal tissues were extracted from GEPIA 2021, TISIDB, UALCAN, EWAS, MethSurv, and MEXPRESS database. We also predict the efficacy of outcome prediction with receiver operating characteristic curve (ROC). All proteins expressions of MST4, P62, and LC3 were detected by immunohistochemistry (IHC) in paired Gastric cancer (GC) and para-cancerous normal tissue samples. We verify the effects of MST4 on irradiation-induced gastric death, and also investigate effects of MST4 activating autophagy in GC cell lines with various in vitro assays using western blotting.

RESULTS

We have confirmed the high transcription level of MST4 from TCGA, USLCAN, HPA, and other portals, but a rapid decrease in protein level. More, MST4 can be considered as an independent prognostic molecule, which has significant prognostic significance in tumor grade, anti-tumor treatment, histological type, and time-dependent ROC curve. The methylation degree of MST4 promoter region in tumor is much lower than that in normal tissue, which may be the main reason for the remarkably high transcription level of MST4. In addition, MST4 transcription level was significantly inversely proportional to the infiltration level of most immune cells. The MST4 up-regulation and the positive association of MST4 with autophagy expression were cross-validated in open-access datasets.

CONCLUSIONS

MST4, as an autophagy-associated protein, plays a potential role in inducing cell death by increasing protein content in radiotherapy.

Databases and prospects of dynamic gene regulation in eukaryotes: A mini review

In eukaryotes, dynamic regulation enables DNA polymerases to catalyze a variety of RNA products in spatial and temporal patterns. Dynamic gene expression is regulated by transcription factors (TFs) and epigenetics (DNA methylation and histone modification). The applications of biochemical technology and high-throughput sequencing enhance the understanding of mechanisms of these regulations and affected genomic regions. To provide a searchable platform for retrieving such metadata, numerous databases have been developed based on the integration of genome-wide maps (e.g., ChIP-seq, whole-genome bisulfite sequencing, RNA-seq, ATAC-seq, DNase-seq, and MNase-seq data) and functionally genomic annotation. In this mini review, we summarize the main functions of TF-related databases and outline the prevalent approaches used in inferring epigenetic regulations, their associated genes, and functions. We review the literature on crosstalk between TF and epigenetic regulation and the properties of non-coding RNA regulation, which are challenging topics that promise to pave the way for advances in database development.

Single-Cell DNA Methylation Analysis in Cancer

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

MethBank 4.0: an updated database of DNA methylation across a variety of species

DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution

Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.

Advances in Single-Cell Multi-Omics and Application in Cardiovascular Research

With the development of ever more powerful and versatile high-throughput sequencing techniques and innovative ways to capture single cells, mapping the multicellular tissues at the single-cell level is becoming routine practice. However, it is still challenging to depict the epigenetic landscape of a single cell, especially the genome-wide chromatin accessibility, histone modifications, and DNA methylation. We summarize the most recent methodologies to profile these epigenetic marks at the single-cell level. We also discuss the development and advancement of several multi-omics sequencing technologies from individual cells. Advantages and limitations of various methods to compare and integrate datasets obtained from different sources are also included with specific practical notes. Understanding the heart tissue at single-cell resolution and multi-modal levels will help to elucidate the cell types and states involved in physiological and pathological events during heart development and disease. The rich information produced from single-cell multi-omics studies will also promote the research of heart regeneration and precision medicine on heart diseases.

The 2022 Nucleic Acids Research database issue and the online molecular biology database collection

The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study

Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.