Germline mutations can affect future generations, while somatic mutations cannot. This germline-soma distinction does not seem to make sense for unicellular organisms. We challenge this view, arguing that baker's yeast (Saccharomyces cerevisiae) has a germline. Under aerobic conditions yeast cells use mainly fermentation of glucose to produce ethanol. Only when glucose is exhausted, cells switch to full respiration of the produced ethanol. We hypothesize that only a subset of the cells continue dividing and switch to respiration. A change from exponential to linear growth is consistent with asymmetrical cell division, where a senescing mother cell produces quiescent daughter cells. We thus propose that most cells produced during fermentation are "somatic," that is, they rapidly lose reproductive capacity, while the cells continuing to divide constitute the germline, as they exclusively produce rejuvenated quiescent cells. We discuss biased DNA-template strand inheritance by the mother cell as a potential adaptive explanation for germline sequestration to reduce the mutation rate.

Out-of-hospital cardiac arrest (OHCA) affects over 360,000 adults in the United States each year with a 50-80% mortality. Despite aggressive supportive care and use of targeted temperature management, half of adults do not live to hospital discharge and nearly one-third of survivors have significant neurologic injury. Development of neuroprotective therapeutics is critical to improving outcomes. One promising readily available agent that has shown benefit is carbon monoxide (CO).

We utilize a swine model of ventricular fibrillation (VF) arrest to assess the therapeutic effect of CO on cellular measures. All animals underwent VF arrest followed by cardiopulmonary resuscitation until achievement of return of spontaneous circulation (ROSC) or the 20 min mark. One hour following ROSC, animals were randomized to the Cardiac Arrest group (VF alone) versus the CO group (VF treated with CO). Animals in the CO group were administered low dose CO of 200 ppm for two hours. At three hours post-ROSC period, all animals were euthanized for tissue and blood collection for mitochondrial respiration (cortical and hippocampal tissue) and the downstream biomolecular analysis.

The primary findings were an overall improvement in mitochondrial respiration and ATP concentrations in the brain from animals in the Carbon Monoxide group. In addition, we also report the use of cell-free DNA as a biomarker to localize the site of tissue injury and our non-invasive optical measuring device to assess cerebral metabolism.

CO may be a potential therapeutic to attenuate cellular injury in post-arrest.

Despite decades of research, impaired extremity wound healing in type 2 diabetes remains a significant driver of patient morbidity, mortality, and health care costs. Advances in surgical and medical therapies, including the advent of endovascular interventions for peripheral artery disease and topical therapies developed to promote wound healing, have not reduced the frequency of lower leg amputations for nonhealing wounds in type 2 diabetes. This brief report is aimed at reviewing the roles of various cell types in tissue repair and summarizing the known dysfunctions of these cell types in diabetic foot ulcers. Recent advances in our understanding of the epigenetic regulation in immune cells identified to be altered in type 2 diabetes are summarized, and particular attention is paid to the developing research defining the epigenetic regulation of structural cells, including keratinocytes, fibroblasts, and endothelial cells. Gaps in knowledge are highlighted, and potential future directions are suggested based on the current state of the field.

In this mini-review, we explore the advancements in genome-wide DNA methylation profiling, tracing the evolution from traditional methods such as methylation arrays and whole-genome bisulfite sequencing to the cutting-edge single-molecule profiling enabled by long-read sequencing (LRS) technologies. We highlight how LRS is transforming clinical and translational research, particularly by its ability to simultaneously measure genetic and epigenetic information, providing a more comprehensive understanding of complex disease mechanisms. We discuss current challenges and future directions in the field, emphasizing the need for innovative computational tools and robust, reproducible approaches to fully harness the capabilities of LRS in molecular diagnostics.

Cardiac development is a precisely regulated process governed by both genetic and epigenetic mechanisms. Among these, DNA methylation is one mode of epigenetic regulation that plays a crucial role in controlling gene expression at various stages of heart development and maturation. Understanding stage-specific DNA methylation dynamics is critical for unraveling the molecular processes underlying heart development from specification of early progenitors, formation of a primitive and growing heart tube from heart fields, heart morphogenesis, organ function, and response to developmental and physiological signals. This review highlights research that has explored profiles of DNA methylation that are highly dynamic during cardiac development and maturation, exploring stage-specific roles and the key molecular players involved. By exploring recent insights into the changing methylation landscape, we aim to highlight the complex interplay between DNA methylation and stage-specific cardiac gene expression, differentiation, and maturation.

Technological advances such as next-generation sequencing (NGS) have enabled high-throughput assessment of the human genome, supporting the usage of genetic testing as a first-line tool across clinical medicine. Although individually rare, genetic causes account for end-stage renal disease in 10% to 15% of adults and 70% of children, and in many of these individuals, genetic testing can identify a specific etiology and meaningfully impact management. However, with numerous options for genetic testing available, nephrologists may feel uncomfortable integrating genetics into their clinical practice. Here, we aim to demystify the process of genetic test selection and highlight the opportunities for interdisciplinary collaboration between nephrologists and genetics professionals, thereby supporting precision medicine for patients with kidney disease. We first detail the various clinical genetic testing modalities, highlighting their technical advantages and limitations, and then discuss indications for their usage. Next, we provide a generalized workflow for genetic test selection among individuals with kidney disease and illustrate how this workflow can be applied to genetic test selection across diverse clinical contexts. We then discuss key areas related to the usage of genetic testing in clinical nephrology that merit further research and approaches to investigate them.

Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells' epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Male infertility represents a complex clinical condition that often challenges the ability of reproductive specialists to find its etiology and then propose an adequate treatment. The unexplained decline in sperm count, as well as the association between male infertility and mortality, morbidity, and cancer, has prompted researchers toward an urgent need to better understand the causes of male infertility. Therefore, molecular biologists are increasingly trying to study whether sperm epigenetic alterations may be involved in male infertility and embryo developmental abnormalities. In this context, research is also trying to uncover the hidden role of sperm RNAs, both coding and non-coding. This narrative review aims to thoroughly and comprehensively present the relationship between sperm epigenetics, sperm RNAs, and human fertility. We first focused on the technological aspects of studying sperm epigenetics and RNAs, relating to the complex role(s) played in sperm maturation, fertilization, and embryo development. Then, we examined the intricate connections between epigenetics and RNAs with fertility measures, namely sperm concentration, embryo growth and development, and live birth rate, in both animal and human studies. A better understanding of the molecular mechanisms involved in sperm epigenetic regulation, as well as the impact of RNA players, will help to tackle infertility.

Cancer stem cells (CSCs) have a crucial function in the initiation, advancement, and resistance to therapy of tumors. Recent findings indicate that non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), play a complex role in controlling the features of cancer stem cells (CSCs). Non-coding RNAs (ncRNAs) play a crucial role in controlling important characteristics of stem cells, such as their ability to renew themselves, differentiate into distinct cell types, and resist therapy. This article provides an overview of the current understanding of the complex relationship between non-coding RNAs (ncRNAs), namely microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), and cancer stem cells (CSCs). Particular microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are involved in regulating important signaling pathways like as Wnt, Notch, and Hedgehog, which control stem cell-like characteristics. The miR-34, miR-200, and let-7 families specifically aim at inhibiting the process of self-renewal and epithelial-to-mesenchymal transition. On the other hand, long non-coding RNAs (lncRNAs) such as H19, HOTAIR, and MALAT1 play a role in modifying the epigenetic landscape, hence enhancing the characteristics of stemness. This article also offers a thorough examination of the role of non-coding RNAs (ncRNAs) in regulating cancer stemness, emphasizing their impact on crucial biochemical pathways, epigenetic changes, and therapeutic implications. Comprehending the interaction between non-coding RNAs (ncRNAs) and cancer stem cells (CSCs) provides fresh perspectives on possible focused treatments for fighting aggressive and resistant malignancies. Gaining a comprehensive understanding of the connection between non-coding RNA (ncRNA) and cancer stem cells (CSC) offers valuable insights for the development of novel and precise treatments to combat aggressive cancers that are resistant to conventional therapies. In addition, the combination of ncRNA therapies with conventional methods like as chemotherapy or epigenetic medicines could result in synergistic effects. Nevertheless, there are still obstacles to overcome in terms of delivery, effectiveness, and safety. In summary, the interaction between non-coding RNA and cancer stemness shows potential as a targeted treatment approach in the field of precision oncology. This calls for additional investigation and use in clinical settings.

edgeR is an R/Bioconductor software package for differential analyses of sequencing data in the form of read counts for genes or genomic features. Over the past 15 years, edgeR has been a popular choice for statistical analysis of data from sequencing technologies such as RNA-seq or ChIP-seq. edgeR pioneered the use of the negative binomial distribution to model read count data with replicates and the use of generalized linear models to analyze complex experimental designs. edgeR implements empirical Bayes moderation methods to allow reliable inference when the number of replicates is small. This article announces edgeR version 4, which includes new developments across a range of application areas. Infrastructure improvements include support for fractional counts, implementation of model fitting in C and a new statistical treatment of the quasi-likelihood pipeline that improves accuracy for small counts. The revised package has new functionality for differential methylation analysis, differential transcript expression, differential transcript and exon usage, testing relative to a fold-change threshold and pathway analysis. This article reviews the statistical framework and computational implementation of edgeR, briefly summarizing all the existing features and functionalities but with special attention to new features and those that have not been described previously.

The advent of single-molecule, long-read sequencing (LRS) technologies by Oxford Nanopore Technologies and Pacific Biosciences has revolutionized genomics, transcriptomics and, more recently, epigenomics research. These technologies offer distinct advantages, including the direct detection of methylated DNA and simultaneous assessment of DNA sequences spanning multiple kilobases along with their modifications at the single-molecule level. This has enabled the development of new assays for analyzing chromatin states and made it possible to integrate data for DNA methylation, chromatin accessibility, transcription factor binding and histone modifications, thereby facilitating comprehensive epigenomic profiling. Owing to recent advancements, alternative, nascent and translating transcripts can be detected using LRS approaches. This Review discusses LRS-based experimental and computational strategies for characterizing chromatin states and highlights their advantages over short-read sequencing methods. Furthermore, we demonstrate how various long-read methods can be integrated to design multi-omics studies to investigate the relationship between chromatin states and transcriptional dynamics.

Epigenetic modifications are chemical groups in our DNA (and chromatin) that determine which genes are active and which are shut off. Importantly, they integrate environmental signals to direct cellular function. Upon chronic environmental exposures, the epigenetic signature of lung cells gets altered, triggering aberrant gene expression programs that can lead to the development of chronic lung diseases. In addition to driving disease, epigenetic marks can serve as attractive lung disease biomarkers, due to early onset, disease specificity, and stability, warranting the need for more epigenetic research in the lung field. Despite substantial progress in mapping epigenetic alterations (mostly DNA methylation) in chronic lung diseases, the molecular mechanisms leading to their establishment are largely unknown. This review is meant as a guide for clinicians and lung researchers interested in epigenetic regulation with a focus on DNA methylation. It provides a short introduction to the main epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNA) and the machinery responsible for their establishment and removal. It presents examples of epigenetic dysregulation across a spectrum of chronic lung diseases and discusses the current state of epigenetic therapies. Finally, it introduces the concept of epigenetic editing, an exciting novel approach to dissecting the functional role of epigenetic modifications. The promise of this emerging technology for the functional study of epigenetic mechanisms in cells and its potential future use in the clinic is further discussed.

N4-methylcytosine (4mC) is a chemical modification that occurs on one of the four nucleotide bases in DNA and plays a vital role in DNA expression, repair, and replication. It also actively participates in the regulation of cell differentiation and gene expression. Consequently, it is important to comprehend the role of 4mC in the epigenetic regulation for revealing the complications of the gene expression and their associated governing cellular operations. However, the inherent resource requirements and time constraints of the experimental procedure, present challenges to the cellular culture process. While data-driven methodologies present promising solutions to mitigate the demand for extensive experimental efforts, their performance relies on the suitability and existence of high-quality data. This study presents a multi-model framework that integrates convolutional neural network (CNN) with the distributed k-mer and embedding feature extraction techniques to enhance the identification of 4mC sites in DNA sequences. The integration of k-mers ensures the effective representation of the local sequence patterns, while the utilization of embedding enables a more holistic encoding by considering the broader context and semantics of the sequence data. Following the initial step, the obtained distributed representation of the DNA sequence seamlessly enters the CNN, triggering a crucial convolution operation wherein a set of adaptable filters systematically convolves across the sequence to detect vital local patterns. The proposed integrated multi-model framework was applied to six publicly available datasets and evaluated against the cutting-edge 4mCPred, 4mCCNN, iDNA4mC, Meta-4mCpred, DeepTorrent, 4mCPred-SVM, and DMKL-HFIS methods. The evaluation was based on accuracy, specificity, sensitivity, and Matthews Correlation Coefficient. The results demonstrated that the proposed multi-model framework outperformed the state-of-the-art methods, as well as one-hot encoding and the hybrid of one-hot & TNC features, in accurately identifying 4mC sites.

Molecular alterations in cancerous tissues exhibit intercellular genetic and epigenetic heterogeneity, complicating the performance of diagnostic assays, particularly for early cancer detection. Conventional liquid biopsy methods have limited sensitivity and/or ability to assess epigenetic heterogeneity of rare epiallelic variants cost-effectively. We report an approach, named REM-DREAMing (Ratiometric-Encoded Multiplex Discrimination of Rare EpiAlleles by Melt), which leverages a digital microfluidic platform that incorporates a ratiometric fluorescence multiplex detection scheme and precise digital high-resolution melt analysis to enable low-cost, parallelized analysis of heterogeneous methylation patterns on a molecule-by-molecule basis for the detection of cancer in liquid biopsies. We applied the platform to simultaneously assess intermolecular epigenetic heterogeneity in five methylation biomarkers for improved, blood-based screening for early-stage non-small cell lung cancer. In a cohort of 48 low-volume liquid biopsy specimens from patients with indeterminant pulmonary nodules, we show that assessment of intermolecular methylation density distributions can notably improve the performance of multigene methylation biomarker panels for the early detection of cancer.

Polymerase chain reaction - Restriction Fragment Length Polymorphism (PCR-RFLP) is an established molecular biology technique leveraging DNA sequence variability for organism identification, genetic disease detection, biodiversity analysis, etc. Traditional PCR-RFLP requires wet-laboratory procedures that can result in technical errors, procedural challenges, and financial costs. With the aim of providing an accessible and efficient PCR-RFLP technique complement, we introduce RFLP-inator. This is a comprehensive web-based platform developed in R using the package Shiny, which simulates the PCR-RFLP technique, integrates analysis capabilities, and offers complementary tools for both pre- and post-evaluation of in vitro results. We developed the RFLP-inator's algorithm independently and our platform offers seven dynamic tools: RFLP simulator, Pattern identifier, Enzyme selector, RFLP analyzer, Multiplex PCR, Restriction map maker, and Gel plotter. Moreover, the software includes a restriction pattern database of more than 250,000 sequences of the bacterial 16S rRNA gene. We successfully validated the core tools against published research findings. This new platform is open access and user-friendly, offering a valuable resource for researchers, educators, and students specializing in molecular genetics. RFLP-inator not only streamlines RFLP technique application but also supports pedagogical efforts in genetics, illustrating its utility and reliability.

Since the mid-1970s, increasingly innovative methods to detect DNA methylation provided detailed information about its distribution, functions, and dynamics. As a result, new concepts were formulated and older ones were revised, transforming our understanding of the associated biology and catalyzing unprecedented advances in biomedical research, drug development, anthropology, and evolutionary biology. In this review, we discuss a few of the most notable advances, which are intimately intertwined with the study of DNA methylation, with a particular emphasis on the past three decades. Examples of these strides include elucidating the intricacies of 5-methylcytosine (5-mC) oxidation, which are at the core of the reversibility of this epigenetic modification; the three-dimensional structural characterization of eukaryotic DNA methyltransferases, which offered insights into the mechanisms that explain several disease-associated mutations; a more in-depth understanding of DNA methylation in development and disease; the possibility to learn about the biology of extinct species; the development of epigenetic clocks and their use to interrogate aging and disease; and the emergence of epigenetic biomarkers and therapies.

Sepsis is a severe disease that occurs when the body's immune system reacts excessively to infection. The body's response, which includes an intense antibacterial reaction, can damage its tissues and organs. Neutrophils are the major components of white blood cells in circulation, play a vital role in innate immunity while fighting against infections, and are considered a feature determining sepsis classification. There is a plethora of basic research detailing neutrophil functioning, among which, the study of neutrophil extracellular traps is providing novel insights into mechanisms and treatments of sepsis. This review explores their functions, dysfunctions, and influences in the context of sepsis. The interplay between neutrophils and the human microbiome and the impact of DNA methylation on neutrophil function in sepsis are crucial areas of study. The interaction between neutrophils and the human microbiome is complex, particularly in the context of sepsis, where dysbiosis may occur. We highlight the importance of deciphering neutrophils' functional alterations and their epigenetic features in sepsis because it is critical for defining sepsis endotypes and opening up the possibility for novel diagnostic methods and therapy. Specifically, epigenetic signatures are pivotal since they will provide a novel implication for a sepsis diagnostic method when used in combination with the cell-free DNA. Research is exploring how specific patterns of DNA methylation in neutrophils, detectable in cell-free DNA, could serve as biomarkers for the early detection of sepsis.

Air pollution is one of the leading causes of early deaths worldwide, with particulate matter (PM) as an emerging factor contributing to this trend. PM is classified based on its physical size, which ranges from PM10 (diameter ≤10 μm) to PM2.5 (≤2.5 μm) and PM0.5 (≤0.5 μm). Smaller-sized PM can move freely through the air and readily infiltrate deep into the lungs, intensifying existing health issues and exacerbating complications. Lung complications are the most common issues arising from PM exposure due to the primary site of deposition in the respiratory system. Conditions such as asthma, COPD, idiopathic pulmonary fibrosis, lung cancer and various lung infections are all susceptible to worsening due to PM exposure. PM can epigenetically modify specific target sites, further complicating its impact on these conditions. Understanding these epigenetic mechanisms holds promise for addressing these complications in cases of PM exposure. This involves studying the effect of PM on different gene expressions and regulation through epigenetic modifications, including DNA methylation, histone modifications and microRNAs. Targeting and manipulating these epigenetic modifications and their mechanisms could be promising strategies for future treatments of lung complications. This review mainly focuses on different epigenetic modifications due to PM2.5 exposure in the various lung complications mentioned above.

Genomic imprinting results in parent-of-origin-specific gene expression and, among vertebrates, is found only in therian mammals: marsupials and eutherians. A differentially methylated region (DMR), in which the methylation status of CpG dinucleotides differs between the two alleles, can mark the parental identity of imprinted genes. We developed a computational pipeline that detected CpG islands (CGIs) marked by both methylated and unmethylated signals in whole genome bisulfite sequencing data. This approach identified candidate marsupial DMRs in a publicly available koala methylome. One of these candidate DMRs was associated with PRKACB, a gene encoding the protein kinase A catalytic subunit beta. Nothing is known about the imprinting status of PRKACB in eutherian mammals although mutations of this gene are associated with endocrine neoplasia and other developmental disorders.

In the tammar wallaby and brushtail possum there was parent-of-origin-specific DNA methylation in the PRKACB DMR in which the maternal allele was methylated and the paternal allele was unmethylated. There were multiple RNAs transcribed from this locus. Allele-specific expression analysis identified paternal expression of a PRKACB lncRNA and an mRNA isoform. Comparison of the PRKACB gene start site between marsupials and eutherians demonstrated that the CGI is longer in marsupials. The PRKACB gene product functions in the same signalling pathway as the guanine nucleotide-binding protein alpha subunit encoded at the GNAS locus, a known eutherian imprinted gene. In a mouse methylome Gnas had three differentially methylated CGIs, while in the koala methylome the GNAS locus had two unmethylated CGIs.

We conclude that PRKACB is a novel, DMR-associated marsupial imprinted gene. Imprinting of PRKACB in marsupials and GNAS in eutherians may indicate a conserved selection pressure for imprinting of the protein kinase A signalling pathway in therians with the two lineages adapting by imprinting different genes.

As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.

Cardiovascular diseases (CVD) affect over half a billion people worldwide and are the leading cause of global deaths. In particular, due to population aging and worldwide spreading of risk factors, the prevalence of heart failure (HF) is also increasing. HF accounts for approximately 36% of all CVD-related deaths and stands as the foremost cause of hospitalization. Patients affected by CVD or HF experience a substantial decrease in health-related quality of life compared to healthy subjects or affected by other diffused chronic diseases.

For both CVD and HF, prediction models have been developed, which utilize patient data, routine laboratory and further diagnostic tests. While some of these scores are currently used in clinical practice, there still is a need for innovative approaches to optimize CVD and HF prediction and to reduce the impact of these conditions on the global population. Epigenetic biomarkers, particularly DNA methylation (DNAm) changes, offer valuable insight for predicting risk, disease diagnosis and prognosis, and for monitoring treatment. The present work reviews current information relating DNAm, CVD and HF and discusses the use of DNAm in improving clinical risk prediction of CVD and HF as well as that of DNAm age as a proxy for cardiac aging.

DNAm biomarkers offer a valuable contribution to improving the accuracy of CV risk models. Many CpG sites have been adopted to develop specific prediction scores for CVD and HF with similar or enhanced performance on the top of existing risk measures. In the near future, integrating data from DNA methylome and other sources and advancements in new machine learning algorithms will help develop more precise and personalized risk prediction methods for CVD and HF.

Deoxyribonucleic acid (DNA) methylation plays a key role in gene regulation and is critical for development and human disease. Techniques such as whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) allow DNA methylation analysis at the genome scale, with Illumina NovaSeq 6000 and MGI Tech DNBSEQ-T7 being popular due to their efficiency and affordability. However, detailed comparative studies of their performance are not available. In this study, we constructed 60 WGBS and RRBS libraries for two platforms using different types of clinical samples and generated approximately 2.8 terabases of sequencing data. We systematically compared quality control metrics, genomic coverage, CpG methylation levels, intra- and interplatform correlations, and performance in detecting differentially methylated positions. Our results revealed that the DNBSEQ platform exhibited better raw read quality, although base quality recalibration indicated potential overestimation of base quality. The DNBSEQ platform also showed lower sequencing depth and less coverage uniformity in GC-rich regions than did the NovaSeq platform and tended to enrich methylated regions. Overall, both platforms demonstrated robust intra- and interplatform reproducibility for RRBS and WGBS, with NovaSeq performing better for WGBS, highlighting the importance of considering these factors when selecting a platform for bisulfite sequencing.

Aberrant DNA methylation has been identified as biomarkers for breast cancer detection. Coiled-coil domain containing 12 gene (CCDC12) implicated in tumorigenesis. This study aims to investigate the potential of blood-based CCDC12 methylation for breast cancer detection.

DNA methylation level of CpG sites (Cytosine-phosphate Guanine dinucleotides) in CCDC12 gene was measured by mass spectrometry in 255 breast cancer patients, 155 patients with benign breast nodules and 302 healthy controls. The association between CCDC12 methylation and breast cancer risk was evaluated by logistic regression and receiver operating characteristic curve analysis.

A total of eleven CpG sites were analyzed. The CCDC12 methylation levels were higher in breast cancer patients. Compared to the lowest tertile of methylation level in CpG_6,7, CpG_10 and CpG_11, the highest quartile was associated with 82, 91 and 95% increased breast cancer risk, respectively. The CCDC12 methylation levels were associated with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) status. In ER-negative and HER2-positive (ER-/HER2+) breast cancer subtype, the combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer from the controls (AUC = 0.727).

The hypermethylation levels of CCDC12 in peripheral blood could be used for breast cancer detection.

The pioneering work of Dr Lewis K. Dahl established a relationship between kidney, salt, and high blood pressure (BP), which led to the major genetic-based experimental model of hypertension. BP, a heritable quantitative trait affected by numerous biological and environmental stimuli, is a major cause of morbidity and mortality worldwide and is considered to be a primary modifiable factor in renal, cardiovascular, and cerebrovascular diseases. Genome-wide association studies have identified monogenic and polygenic variants affecting BP in humans. Single nucleotide polymorphisms identified in genome-wide association studies have quantified the heritability of BP and the effect of genetics on hypertensive phenotype. Changes in the transcriptional program of genes may represent consequential determinants of BP, so understanding the mechanisms of the disease process has become a priority in the field. At the molecular level, the onset of hypertension is associated with reprogramming of gene expression influenced by epigenomics. This review highlights the specific genetic variants, mutations, and epigenetic factors associated with high BP and how these mechanisms affect the regulation of hypertension and kidney dysfunction.

A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences in probe spacing between Illumina's Infinium 450K and EPIC bead array respectively. We also study the asymptotic results of our proposed statistic. We compare our approach with a popular DMR detection method via simulation studies under large and small treatment effect settings. We also discuss the susceptibility of our method in detecting the true length of the DMRs under these two settings. Lastly, we demonstrate the biological usefulness of our method when combined with pathway analysis methods on oral cancer data. We have created an R package called idDMR, downloadable from GitHub repository with link: https://github.com/DanielAlhassan/idDMR, that allows for the convenient implementation of our array-adaptive DMR method.

Parkinson's disease is a progressive neurodegenerative disorder, predominantly of the motor system. Although some genetic components and cellular mechanisms of Parkinson's have been identified, much is still unknown. In recent years, emerging evidence has indicated that non-DNA-sequence variation (in particular epigenetic mechanisms) is likely to play a crucial role in the development and progression of the disease. Here, we present an up-to-date overview of epigenetic processes including DNA methylation, DNA hydroxymethylation, histone modifications and non-coding RNAs implicated in the brain of those with Parkinson's disease. We will also discuss the limitations of current epigenetic research in Parkinson's disease, the advantages of simultaneously studying genetics and epigenetics, and putative novel epigenetic therapies.

Huntington's disease (HD) is an inherited, autosomal, neurodegenerative ailment that affects the striatum of the brain. Despite its debilitating effect on its patients, there is no proven cure for HD management as of yet. Neuroinflammation, excitotoxicity, and environmental factors have been reported to influence the regulation of gene expression by modifying epigenetic mechanisms. Aside focusing on the etiology, changes in epigenetic mechanisms have become a crucial factor influencing the interaction between HTT protein and epigenetically transcribed genes involved in neuroinflammation and HD. This review presents relevant literature on epigenetics with special emphasis on neuroinflammation and HD. It summarizes pertinent research on the role of neuroinflammation and post-translational modifications of chromatin, including DNA methylation, histone modification, and miRNAs. To achieve this about 1500 articles were reviewed via databases like PubMed, ScienceDirect, Google Scholar, and Web of Science. They were reduced to 534 using MeSH words like 'epigenetics, neuroinflammation, and HD' coupled with Boolean operators. Results indicated that major contributing factors to the development of HD such as mitochondrial dysfunction, excitotoxicity, neuroinflammation, and apoptosis are affected by epigenetic alterations. However, the association between neuroinflammation-altered epigenetics and the reported transcriptional changes in HD is unknown. Also, the link between epigenetically dysregulated genomic regions and specific DNA sequences suggests the likelihood that transcription factors, chromatin-remodeling proteins, and enzymes that affect gene expression are all disrupted simultaneously. Hence, therapies that target pathogenic pathways in HD, including neuroinflammation, transcriptional dysregulation, triplet instability, vesicle trafficking dysfunction, and protein degradation, need to be developed.

Gravity is one of the most constant environmental factors across Earth's evolution and all organisms are adapted to it. Consequently, spatial exploration has captured the interest in studying the biological changes that physiological alterations are caused by gravity. In the last two decades, epigenetics has explained how environmental cues can alter gene functions in organisms. Although many studies addressed gravity, the underlying biological and molecular mechanisms that occur in altered gravity for those epigenetics-related mechanisms, are mostly inexistent. The present study addressed the effects of hypergravity on development, behavior, gene expression, and most importantly, on the epigenetic changes in a worldwide animal model, the zebrafish (Danio rerio). To perform hypergravity experiments, a custom-centrifuge simulating the large diameter centrifuge (100 rpm ~ 3 g) was designed and zebrafish embryos were exposed during 5 days post fertilization (dpf). Results showed a significant decrease in survival at 2 dpf but no significance in the hatching rate. Physiological and morphological alterations including fish position, movement frequency, and swimming behavior showed significant changes due to hypergravity. Epigenetic studies showed significant hypermethylation of the genome of the zebrafish larvae subjected to 5 days of hypergravity. Downregulation of the gene expression of three epigenetic-related genes (dnmt1, dnmt3, and tet1), although not significant, was further observed. Taken altogether, gravity alterations affected biological responses including epigenetics in fish, providing a valuable roadmap of the putative hazards of living beyond Earth.

Upon encountering pathogens, the immune system typically responds by initiating an acute and self-limiting reaction, with symptoms subsiding after the pathogen has been cleared. However, long-term post-infectious clinical symptoms can manifest months or even years after the initial infection. 'Trained immunity', the functional reprogramming of innate immune cells through epigenetic and metabolic rewiring, has been proposed as a key concept for understanding these long-term effects. Although trained immunity can result in enhanced protection against reinfection with heterologous pathogens, it can also contribute to detrimental outcomes. Persisting and excessive inflammation can cause tissue damage and aggravate immune-mediated conditions and cardiovascular complications. On the other hand, suppression of immune cell effector functions by long-lasting epigenetic changes can result in post-infectious immune paralysis. Distinct stimuli can evoke different trained immunity programs, potentially resulting in different consequences for the host. In this review, we provide an overview of both the adaptive and maladaptive consequences of infectious diseases. We discuss how long-term immune dysregulation in patients can be addressed by tailoring host-directed interventions and identify areas of scientific and therapeutic potential to advance further.

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

In this study, a very sensitive fluorescence nano-biosensor was developed using CeO2 nanoparticles for the rapid detection of DNA methylation. The characteristics of CeO2 nanoparticles were determined by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) spectroscopy, UV-visible spectroscopy, and fluorescence spectroscopy. The CeO2 nanoparticles were reacted with a single-stranded DNA (ssDNA) probe, and then methylated and unmethylated target DNAs hybridized with an ssDNA probe, and the fluorescence emission was measured. Upon adding the target unmethylated and methylated ssDNA, the fluorescence intensity increased in the linear range of concentration from 2 × 10-13 - 10-18 M. The limit of detection (LOD) was 1.597 × 10-6 M for methylated DNA and 1.043 × 10-6 M for unmethylated DNA. The fluorescence emission intensity of methylated sequences was higher than of that unmethylated sequences. The fabricated DNA nanobiosensor showed a fluorescence emission at 420 nm with an excitation wavelength of 280 nm. The impact of CeO2 binding on methylated and unmethylated DNA was further demonstrated by agarose gel electrophoresis. Finally, the actual sample analysis suggested that the nanobiosensor could have practical applications for detecting methylation in the human plasma samples.

Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.

DNA methylation is the dominant epigenetic mechanism for regulating gene expression in mammals, playing crucial roles in development, differentiation, and tissue homeostasis. Aberrations in DNA methylation are closely associated with the potential onset of various diseases. Consequently, numerous DNA methylation detection techniques have been successively developed. These methods not only facilitate the exploration of disease mechanisms but also hold significant promise for the development of diagnostic and prognostic strategies. In this Perspective, we present a comprehensive overview of commonly employed DNA methylation detection techniques as well as biosensing based on their underlying analytical techniques. For its medical applications, we begin by examining the pathogenesis of different diseases and then proceed to discuss how relevant technologies are applied in the context of these specific medical conditions. Additionally, we briefly discuss the current limitations of these techniques and highlight future challenges in advancing methylation detection and analysis methodologies.

Bisulfite sequencing detects and quantifies DNA methylation patterns, contributing to our understanding of gene expression regulation, genome stability maintenance, conservation of epigenetic mechanisms across divergent taxa, epigenetic inheritance and, eventually, phenotypic variation. Graphical representation of methylation data is crucial in exploring epigenetic regulation on a genome-wide scale in both plants and animals. This is especially relevant for non-model organisms with poorly annotated genomes and/or organisms where genome sequences are not yet assembled on chromosome level. Despite being a technology of choice to profile DNA methylation for many years now there are surprisingly few lightweight and robust standalone tools available for efficient graphical analysis of data in non-model systems. This significantly limits evolutionary studies and agrigenomics research. BSXplorer is a tool specifically developed to fill this gap and assist researchers in explorative data analysis and in visualising and interpreting bisulfite sequencing data more easily.

BSXplorer provides in-depth graphical analysis of sequencing data encompassing (a) profiling of methylation levels in metagenes or in user-defined regions using line plots and heatmaps, generation of summary statistics charts, (b) enabling comparative analyses of methylation patterns across experimental samples, methylation contexts and species, and (c) identification of modules sharing similar methylation signatures at functional genomic elements. The tool processes methylation data quickly and offers API and CLI capabilities, along with the ability to create high-quality figures suitable for publication.

BSXplorer facilitates efficient methylation data mining, contrasting and visualization, making it an easy-to-use package that is highly useful for epigenetic research.

Recurrence and extraocular metastasis in advanced intraocular retinoblastoma (RB) are still major obstacles for successful treatment of Chinese children. Tuberous sclerosis complex (TSC) is a very rare, multisystemic genetic disorder characterized by hamartomatous growth. In this study, we aimed to compare genomic and epigenomic profiles with human RB or TSC using recently developed nanopore sequencing, and to identify disease-associated variations or genes. Peripheral blood samples were collected from either RB or RB/TSC patients plus their normal siblings, followed by nanopore sequencing and identification of disease-specific structural variations (SVs) and differentially methylated regions (DMRs) by a systematic biology strategy named as multiomics-based joint screening framework. In total, 316 RB- and 1295 TSC-unique SVs were identified, as well as 1072 RB- and 1114 TSC-associated DMRs, respectively. We eventually identified 6 key genes for RB for further functional validation. Knockdown of CDK19 with specific siRNAs significantly inhibited Y79 cellular proliferation and increased sensitivity to carboplatin, whereas downregulation of AHNAK2 promoted the cell growth as well as drug resistance. Those two genes might serve as potential diagnostic markers or therapeutic targets of RB. The systematic biology strategy combined with functional validation might be an effective approach for rare pediatric malignances with limited samples and challenging collection process.

Iridoviruses are nucleocytoplasmic large dsDNA viruses that infect invertebrates and ectothermic vertebrates. The hypermethylated genome of vertebrate iridoviruses is unique among animal viruses. However, the map and function of iridovirus genomic methylation remain unknown. Herein, the methylated genome of Infectious spleen and kidney necrosis virus (ISKNV, a fish iridovirus), and its role in viral infection, are investigated. The methylation level of ISKNV is 23.44%. The hypermethylated genome is essential for ISKNV amplification, but there is no correlation between hypermethylation and viral gene expression. The hypomethylated ISKNV (obtained via 5-Azacytidine) activates a strong immunoreaction in vitro and reduces its pathogenicity in vivo. The unmethylated viral DNA can induce a stronger immunoreaction in vitro, whereas inactivated hypomethylated ISKNV can induce a stronger immunoreaction in vivo, suggesting ISKNV may evade from immune system by increasing its genome methylation level. Our work provides new insights into the role of genome methylation in viral infection.

Introduction: As the evaluation indices, cancer grading and subtyping have diverse clinical, pathological, and molecular characteristics with prognostic and therapeutic implications. Although researchers have begun to study cancer differentiation and subtype prediction, most of relevant methods are based on traditional machine learning and rely on single omics data. It is necessary to explore a deep learning algorithm that integrates multi-omics data to achieve classification prediction of cancer differentiation and subtypes. Methods: This paper proposes a multi-omics data fusion algorithm based on a multi-view graph neural network (MVGNN) for predicting cancer differentiation and subtype classification. The model framework consists of a graph convolutional network (GCN) module for learning features from different omics data and an attention module for integrating multi-omics data. Three different types of omics data are used. For each type of omics data, feature selection is performed using methods such as the chi-square test and minimum redundancy maximum relevance (mRMR). Weighted patient similarity networks are constructed based on the selected omics features, and GCN is trained using omics features and corresponding similarity networks. Finally, an attention module integrates different types of omics features and performs the final cancer classification prediction. Results: To validate the cancer classification predictive performance of the MVGNN model, we conducted experimental comparisons with traditional machine learning models and currently popular methods based on integrating multi-omics data using 5-fold cross-validation. Additionally, we performed comparative experiments on cancer differentiation and its subtypes based on single omics data, two omics data, and three omics data. Discussion: This paper proposed the MVGNN model and it performed well in cancer classification prediction based on multiple omics data.

N6-Methyladenine (6mdA) and N4-methylcytosine (4mdC) are the two most dominant DNA modifications in both prokaryotes and eukaryotes, but standard hybridization-based techniques cannot be applied for the 6mdA/4mdC assay. Herein, we demonstrate the silver-coordinated Watson-Crick pairing-driven three-dimensional (3D) DNA walker for locus-specific detection of genomic 6mdA/4mdC at the single-molecule level. 6mdA-DNA and 4mdC-DNA can selectively hybridize with the binding probes (BP1 and BP2) to form 6mdA-DNA-BP1 and 4mdC-DNA-BP2 duplexes. The 6mdA-C/4mdC-A mismatches cannot be stabilized by AgI, and thus, 18-nt BP1/BP2 cannot be extended by the catalysis of KF exonuclease. Through toehold-mediated strand displacement (TMSD), the signal probe (SP1/SP2) functionalized on the gold nanoparticles (AuNPs) can competitively bind to BP1/BP2 in 6mdA-DNA-BP1/4mdC-DNA-BP2 duplex to obtain SP1-18-nt BP1 and SP2-18-nt BP2 duplexes. The resulting DNA duplexes can act as the substrates of lambda exonuclease, leading to the cleavage of SP1/SP2 and the release of Cy3/Cy5 and 18-nt BP1/BP2. The released 18-nt BP1/BP2 can subsequently serve as the walker DNA, moving along the surface of the AuNP to activate dynamic 3D DNA walking and releasing abundant Cy3/Cy5. The released Cy3/Cy5 can be quantified by single-molecule imaging. This nanosensor exhibits high sensitivity with a limit of detection (LOD) of 9.80 × 10-15 M for 6mdA-DNA and 9.97 × 10-15 M for 4mdC-DNA. It can discriminate 6mdA-/4mdC-DNA from unmodified genomic DNAs, distinguish 0.01% 6mdA-/4mdC-DNA from excess unmethylated DNAs, and quantify 6mdA-/4mdC-DNA at specific sites in genomic DNAs of liver cancer cells and Escherichia coli plasmid cloning vector, providing a new platform for locus-specific analysis of 6mdA/4mdC in genomic DNAs.

Beyond storage and transmission of genetic information in cellular life, nucleic acids can perform diverse interesting functions, including specific target recognition and biochemical reaction acceleration; the versatile biopolymers, however, are acutely vulnerable to hydrolysis-driven degradation. Here, we demonstrate that the cage effect of choline dihydrogen phosphate permits active folding of nucleic acids like water, but prevents their phosphodiester hydrolysis unlike water. The choline-based ionic liquid not only serves as a universal inhibitor of nucleases, exceptionally extending half-lives of nucleic acids up to 6 500 000 times, but highly useful tasks of nucleic acids (e.g. mRNA detection of molecular beacons, ligand recognition of aptamers, and transesterification reaction of ribozymes) can be also conducted with well-conserved affinities and specificities. As liberated from the function loss and degradation risk, the presence of undesired and unknown nucleases does not undermine desired molecular functions of nucleic acids without hydrolysis artifacts even in nuclease cocktails and human saliva.

Epigenetic modifications, particularly DNA methylation, have emerged as regulators of gene expression and are implicated in various biological processes and disease states. Understanding the factors influencing the epigenome is essential for unraveling its complexity. In this study, we aimed to identify how the methylome of buccal epithelial cells, a noninvasive and easily accessible tissue, is associated with demographic and health-related variables commonly used in clinical settings, such as age, sex, blood immune composition, hemoglobin levels, and others. We developed a model to assess the association of multiple factors with the human methylome and identify the genomic loci significantly impacted by each trait. We demonstrated that DNA methylation variation is accurately modeled by several factors. We confirmed the well-known impact of age and sex and unveiled novel clinical factors associated with DNA methylation, such as blood neutrophils, hemoglobin, red blood cell distribution width, high-density lipoprotein cholesterol, and urea. Genomic regions significantly associated with these traits were enriched in relevant transcription factors, drugs, and diseases. Among our findings, we showed that neutrophil-impacted loci were involved in neutrophil functionality and maturation. Similarly, hemoglobin-influenced sites were associated with several diseases, including aplastic anemia, and the genomic loci affected by urea were related to congenital anomalies of the kidney and urinary tract. Our findings contribute to a better understanding of the human methylome plasticity and provide insights into novel factors shaping DNA methylation patterns, highlighting their potential clinical implications as biomarkers and the importance of considering these physiological traits in future medical epigenomic investigations.NEW & NOTEWORTHY We have developed a quantitative model to assess how the human methylome is associated with several factors and to identify the genomic loci significantly impacted by each trait. We reported novel health-related factors driving DNA methylation patterns and new site-specific regulations that further elucidate methylome dynamics. Our study contributes to a better understanding of the plasticity of the human methylome and unveils novel physiological traits with a potential role in future medical epigenomic investigations.

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Accumulation of deoxyribonucleic acid (DNA) damage diminishes cellular health, increases risk of developmental and degenerative diseases, and accelerates aging. Optimizing nutrient intake can minimize accrual of DNA damage. The objectives of this review are to: 1) assemble and systematically analyze high-level evidence for the effect of supplementation with micronutrients and phytochemicals on baseline levels of DNA damage in humans, and 2) use this knowledge to identify which of these essential micronutrients or nonessential phytochemicals promote DNA integrity in vivo in humans. We conducted systematic literature searches of the PubMed database to identify interventional, prospective, cross-sectional, or in vitro studies that explored the association between nutrients and established biomarkers of DNA damage associated with developmental and degenerative disease risk. Biomarkers included lymphocyte chromosome aberrations, lymphocyte and buccal cell micronuclei, DNA methylation, lymphocyte/leukocyte DNA strand breaks, DNA oxidation, telomere length, telomerase activity, and mitochondrial DNA mutations. Only randomized, controlled interventions and uncontrolled longitudinal intervention studies conducted in humans were selected for evaluation and data extraction. These studies were ranked for the quality of their study design. In all, 96 of the 124 articles identified reported studies that achieved a quality assessment score ≥ 5 (from a maximum score of 7) and were included in the final review. Based on these studies, nutrients associated with protective effects included vitamin A and its precursor β-carotene, vitamins C, E, B1, B12, folate, minerals selenium and zinc, and phytochemicals such as curcumin (with piperine), lycopene, and proanthocyanidins. These findings highlight the importance of nutrients involved in (i) DNA metabolism and repair (folate, vitamin B12, and zinc) and (ii) prevention of oxidative stress and inflammation (vitamins A, C, E, lycopene, curcumin, proanthocyanidins, selenium, and zinc). Supplementation with certain micronutrients and their combinations may reduce DNA damage and promote cellular health by improving the maintenance of genome integrity.