Epigenetic Profiles Research Articles

Evaluating the Cellular Roles of the Lysine Acetyltransferase Tip60 in Cancer: A Multi-Action Molecular Target for Precision Oncology.

Precision (individualized) medicine relies on the molecular profiling of tumors' dysregulated characteristics (genomic, epigenetic, transcriptomic) to identify the reliance on key pathways (including genome stability and epigenetic gene regulation) for viability or growth, and then utilises targeted therapeutics to disrupt these survival-dependent pathways. Non-mutational epigenetic changes alter cells' transcriptional profile and are a key feature found in many tumors. In contrast to genetic mutations, epigenetic changes are reversable, and restoring a normal epigenetic profile can inhibit tumor growth and progression. Lysine acetyltransferases (KATs or HATs) protect genome stability and integrity, and Tip60 is an essential acetyltransferase due to its roles as an epigenetic and transcriptional regulator, and as master regulator of the DNA double-strand break response. Tip60 is commonly downregulated and mislocalized in many cancers, and the roles that mislocalized Tip60 plays in cancer are not well understood. Here we categorize and discuss Tip60-regulated genes, evaluate Tip60-interacting proteins based on cellular localization, and explore the therapeutic potential of Tip60-targeting compounds as epigenetic inhibitors. Understanding the multiple roles Tip60 plays in tumorigenesis will improve our understanding of tumor progression and will inform therapeutic options, including informing potential combinatorial regimes with current chemotherapeutics, leading to improvements in patient outcomes.

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects.

Recent advancements in high-throughput sequencing technologies have significantly enhanced our ability to unravel the intricacies of gene regulatory processes. A critical challenge in this endeavor is the identification of variant effects, a key factor in comprehending the mechanisms underlying gene regulation. Non-coding variants, constituting over 90% of all variants, have garnered increasing attention in recent years. The exploration of gene variant impacts and regulatory mechanisms has spurred the development of various deep learning approaches, providing new insights into the global regulatory landscape through the analysis of extensive genetic data. Here, we provide a comprehensive overview of the development of the non-coding variants models based on bulk and single-cell sequencing data and their model-based interpretation and downstream tasks. This review delineates the popular sequencing technologies for epigenetic profiling and deep learning approaches for discerning the effects of non-coding variants. Additionally, we summarize the limitations of current approaches in variant effect prediction research and outline opportunities for improvement. We anticipate that our study will offer a practical and useful guide for the bioinformatic community to further advance the unraveling of genetic variant effects.

Autotaxin Inhibition Reduces Post-Ischemic Myocardial Inflammation via Epigenetic Gene Modifications.

Myocardial infarction (MI) triggers a complex inflammatory response that is essential for cardiac repair but can also lead to adverse outcomes if left uncontrolled. Recent studies have highlighted the importance of epigenetic modifications in regulating post-MI inflammation. This study investigated the role of the autotaxin (ATX)/lysophosphatidic acid (LPA) signaling axis in modulating myocardial inflammation through epigenetic pathways in a mouse model of MI. C57BL/6J mice underwent left anterior descending coronary artery ligation to induce MI and were treated with the ATX inhibitor, PF-8380, or vehicle. Cardiac tissue from the border zone was collected at 6h, 1, 3, and 7days post-MI for epigenetic gene profiling using RT2 Profiler PCR Arrays. The results revealed distinct gene expression patterns across sham, MI + Vehicle, and MI + PF-8380 groups. PF-8380 treatment significantly altered the expression of genes involved in inflammation, stress response, and epigenetic regulation compared to the vehicle group. Notably, PF-8380 downregulated Hdac5, Prmt5, and Prmt6, which are linked to exacerbated inflammatory responses, as early as 6h post-MI. Furthermore, PF-8380 attenuated the reduction of Smyd1, a gene important in myogenic differentiation, at 7days post-MI. This study demonstrates that the ATX/LPA signaling axis plays a pivotal role in modulating post-MI inflammation via epigenetic pathways. Targeting ATX/LPA signaling may represent a novel therapeutic strategy to control inflammation and improve outcomes after MI. Further research is needed to validate these findings in preclinical and clinical settings and to elucidate the complex interplay between epigenetic mechanisms and ATX/LPA signaling in the context of MI.

Epigenetic alterations affecting hematopoietic regulatory networks as drivers of mixed myeloid/lymphoid leukemia

Leukemias with ambiguous lineage comprise several loosely defined entities, often without a clear mechanistic basis. Here, we extensively profile the epigenome and transcriptome of a subgroup of such leukemias with CpG Island Methylator Phenotype. These leukemias exhibit comparable hybrid myeloid/lymphoid epigenetic landscapes, yet heterogeneous genetic alterations, suggesting they are defined by their shared epigenetic profile rather than common genetic lesions. Gene expression enrichment reveals similarity with early T-cell precursor acute lymphoblastic leukemia and a lymphoid progenitor cell of origin. In line with this, integration of differential DNA methylation and gene expression shows widespread silencing of myeloid transcription factors. Moreover, binding sites for hematopoietic transcription factors, including CEBPA, SPI1 and LEF1, are uniquely inaccessible in these leukemias. Hypermethylation also results in loss of CTCF binding, accompanied by changes in chromatin interactions involving key transcription factors. In conclusion, epigenetic dysregulation, and not genetic lesions, explains the mixed phenotype of this group of leukemias with ambiguous lineage. The data collected here constitute a useful and comprehensive epigenomic reference for subsequent studies of acute myeloid leukemias, T-cell acute lymphoblastic leukemias and mixed-phenotype leukemias.

Coding and Non-Coding Transcriptomic Landscape of Aortic Complications in Marfan Syndrome.

Marfan syndrome (MFS) is a rare congenital disorder of the connective tissue, leading to thoracic aortic aneurysms (TAA) and dissection, among other complications. Currently, the most efficient strategy to prevent life-threatening dissection is preventive surgery. Periodic imaging applying complex techniques is required to monitor TAA progression and to guide the timing of surgical intervention. Thus, there is an acute demand for non-invasive biomarkers for diagnosis and prognosis, as well as for innovative therapeutic targets of MFS. Unraveling the intricate pathomolecular mechanisms underlying the syndrome is vital to address these needs. High-throughput platforms are particularly well-suited for this purpose, as they enable the integration of different datasets, such as transcriptomic and epigenetic profiles. In this narrative review, we summarize relevant studies investigating changes in both the coding and non-coding transcriptome and epigenome in MFS-induced TAA. The collective findings highlight the implicated pathways, such as TGF-β signaling, extracellular matrix structure, inflammation, and mitochondrial dysfunction. Potential candidates as biomarkers, such as miR-200c, as well as therapeutic targets emerged, like Tfam, associated with mitochondrial respiration, or miR-632, stimulating endothelial-to-mesenchymal transition. While these discoveries are promising, rigorous and extensive validation in large patient cohorts is indispensable to confirm their clinical relevance and therapeutic potential.

Comprehensive analysis of distinct circadian clock subtypes of adult diffuse glioma and their associations with clinicopathological, genetic, and epigenetic profiles.

The circadian clock (CC) has biological and clinical implications in gliomas. Most studies focused on CC effects on the tumor microenvironment and the application of chronotherapy. The present study focused on CC gene expression patterns and intracellular oncogenic activities. Glioma gene expression data were collected from The Human Cancer Genome Atlas (TCGA) project. After applying inclusion and exclusion criteria, we selected 666 patients from TCGA-GBM and TCGA-LGG projects and included important clinicopathological variables. The entire cohort was subjected to clustering analysis and divided into CC1 and CC2 subtypes based on statistical, biological, and clinical criteria. CC2 gliomas showed higher expression of BMAL1 and CRY1 and lower expression of CRY2 and PER2 (adjusted P < .001). CC2 gliomas had q higher activity of cell proliferation, metabolic reprogramming, angiogenesis, hypoxia, and many oncogenic signals (P < .001). The CC2 subtype contained a higher proportion of glioblastomas (P < .001) and had a worse prognosis (P < .001). Stratified Kaplan-Meier and multivariable Cox analyses illustrated that the CC subtype is an independent prognostic factor to clinicopathological characteristics (P < .001), genetic aberrations (P = .006), and biological processes (P < .001). Thus, this study shows statistical evidence of CC subtypes and their biological, and clinicopathological significance in adult gliomas.

Respiratory infection- and asthma-prone, low vaccine responder children demonstrate distinct mononuclear cell DNA methylation pathways

BackgroundInfants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunizations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripheral blood mononuclear cells from respiratory infection allergy/asthma-prone (IAP) infants and non-infection allergy/asthma prone (NIAP) were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fisher's exact p-value = 0.02).ResultsAn endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPL), a TLR agonist, partially reversed this signature at a subset of CpGs, suggesting the potential for epigenetic remodeling.ConclusionsThis proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for future investigation.

Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees.

Despite significant advances in our understanding of genetic cancer susceptibility, known inherited cancer predisposition syndromes explain at most 20% of early-onset cancers. As early-onset cancer prevalence continues to increase, the need to assess previously inaccessible areas of the human genome, harnessing a trio or quad family-based architecture for variant filtration, may reveal further insights into cancer susceptibility. To assess a broader spectrum of variation than can be ascertained by multi-gene panel sequencing, or even whole genome sequencing with short reads, we employed long read whole genome sequencing using an Oxford Nanopore Technology (ONT) PromethION of 3 families containing an early-onset cancer proband using a trio or quad family architecture. Analysis included 2 early-onset colorectal cancer family trios and one quad consisting of two siblings with testicular cancer, all with unaffected parents. Structural variants (SVs), epigenetic profiles and single nucleotide variants (SNVs) were determined for each individual, and a filtering strategy was employed to refine and prioritize candidate variants based on the family architecture. The family architecture enabled us to focus on inapposite variants while filtering variants shared with the unaffected parents, significantly decreasing background variation that can hamper identification of potentially disease causing differences. Candidate d e novo and compound heterozygous variants were identified in this way. Gene expression, in matched neoplastic and pre-neoplastic lesions, was assessed for one trio. Our study demonstrates the feasibility of a streamlined analysis of genomic variants from long read ONT whole genome sequencing and a way to prioritize key variants for further evaluation of pathogenicity, while revealing what may be missing from panel based analyses.

A single-cell chromatin accessibility dataset of human primed and naïve pluripotent stem cell-derived teratoma

Teratoma, due to its remarkable ability to differentiate into multiple cell lineages, is a valuable model for studying human embryonic development. The similarity of the gene expression and chromatin accessibility patterns in these cells to those observed in vivo further underscores its potential as a research tool. Notably, teratomas derived from human naïve (pre-implantation epiblast-like) pluripotent stem cells (PSCs) have larger embryonic cell diversity and contain extraembryonic lineages, making them more suitable to study developmental processes. However, the cell type-specific epigenetic profiles of naïve PSC teratomas have not been yet characterized. Using single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), we analyzed 66,384 cell profiles from five teratomas derived from human naïve PSCs and their post-implantation epiblast-like (primed) counterparts. We observed 17 distinct cell types from both embryonic and extraembryonic lineages, resembling the corresponding cell types in human fetal tissues. Additionally, we identified key transcription factors specific to different cell types. Our dataset provides a resource for investigating gene regulatory programs in a relevant model of human embryonic development.

Novel bioinformatic analyses of somatic cell contamination in sperm samples

The assessment of epigenetic profiles in sperm is sensitive to somatic cell contamination, which can influence methylation signals at gene promoters. This contamination is particularly problematic in the assessment of DNA methylation in samples with low sperm counts, where fractional amounts of somatic cell DNA can lead to significant shifts in measured methylation state. In this study, a new method of detecting possible somatic cell contamination is proposed through two multi-region bioinformatic models: a traditional differential methylation analysis and a machine learning logistic regression model. These models were trained on publicly available sperm (n = 489) and blood (n = 1029) DNA methylation array data and tested on a contamination set, wherein the sperm of four donors with normal sperm counts were run on a 450k methylation array with four permutations each, including pure blood, half blood and half sperm by DNA concentration, half blood and half sperm by cell count, and pure sperm (n = 16). The DMR and logistic regression model classified the contamination testing set with 100% and 94% accuracy, respectively. These new methods of detecting the effects of somatic cell contamination allow for more accurate differentiation between epigenetic profiles that contain a biological somatic-like shift and those that have somatic-like signatures because of contamination.

Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma

Mutations in DNA regulatory regions are increasingly being recognized as important drivers of cancer and other complex diseases. These mutations can regulate gene expression by affecting DNA-protein binding and epigenetic profiles, such as DNA methylation in genome regulatory elements. However, identifying mutation hotspots associated with expression regulation and disease progression in non-coding DNA remains a challenge. Unlike most existing approaches that assign a mutation score to individual single nucleotide polymorphisms (SNP), a mutation block (MB)-based approach was introduced in this study to assess the collective impact of a cluster of SNPs on transcription factor-DNA binding affinity, differential gene expression (DEG), and nearby DNA methylation. Moreover, the long-distance target genes of functional MBs were identified using a new permutation-based algorithm that assessed the significance of correlations between DNA methylation at regulatory regions and target gene expression. Two new Python packages were developed. The Differential Methylation Region (DMR-analysis) analysis tool was used to detect DMR and map them to regulatory elements. The second tool, an integrated DMR, DEG, and SNP analysis tool (DDS-analysis), was used to combine the omics data to identify functional MBs and long-distance target genes. Both tools were validated in follicular lymphoma (FL) cohorts, where not only known functional MBs and their target genes (BCL2 and BCL6) were recovered, but also novel genes were found, including CDCA4 and JAG2, which may be associated with FL development. These genes are linked to target gene expression and are significantly correlated with the methylation of nearby DNA sequences in FL. The proposed computational integrative analysis of multiomics data holds promise for identifying regulatory mutations in cancer and other complex diseases.

PATH-04. OPTIMIZING CELL-FREE DNA ASSAYS FOR LOW INPUT LIQUID BIOPSY SAMPLES FROM PEDIATRIC BRAIN TUMOR PATIENTS

Abstract BACKGROUND Genetic and epigenetic profiling have transformed biological understanding, diagnostics, and therapeutic approaches for pediatric central nervous system (CNS) tumors. Obtaining tumor tissue may be associated with neurosurgical risk, may not be feasible in some cases, and is not routinely performed during follow-up or at relapse. Liquid biopsies (LBs) have emerged as a minimally invasive, serially collectable source of tumor-derived DNA. Here, we collected cerebrospinal fluid (CSF) and serum LBs from a large, unselected, cross-entity pediatric CNS tumor cohort (n=55 patients) for method optimization. METHODS Cell-free DNA (cfDNA) isolated from CSF and serum samples was analyzed 1) by low-coverage whole genome sequencing for copy number variation (CNV)-based tumor detection and 2) by enzymatic conversion (EC)-based DNA methylation profiling using the EPIC DNA methylation array and the Heidelberg Brain Tumor Classifier. All library protocols were optimized for LB samples with low cfDNA amounts in the picogram range. Matched tumor samples were used as reference. RESULTS Our lcWGS-based cfDNA profiling protocol had a high technical success rate across the whole cohort (&amp;gt;95%), despite very low cfDNA amounts for most CSF samples. The majority of CSF LBs captured tumor-derived CNVs and displayed a high fraction of tumor-derived cfDNA (&amp;gt;5%, range 0-78%). For serum LBs, only few samples showed detectable CNVs. Proof-of-concept methylation analyses leveraging a new EC-based workflow allowed molecular classification using CSF, particularly for embryonal brain tumors (11/15 samples). Clinical workup of selected cases illustrates the potential of LBs to aid as diagnostic tool, monitor disease, and characterize tumor evolution. CONCLUSIONS Tackling a major roadblock of clinical translation of LBs, this study delineates new methods tailored to low input cfDNA samples. Results highlight the clinical utility of LBs for the management of brain tumor patients, providing a strong rationale for prospective validation within pediatric neuro-oncology trials.

ATRT-12. EXPLORING FGFR INHIBITION AND COMBINATION THERAPIES FOR ATYPICAL TERATOID/RHABDOID TUMORS

Abstract BACKGROUND Atypical teratoid/rhabdoid tumors (ATRTs) are aggressive pediatric brain neoplasms characterized by an inactivation of the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. Based on epigenetic profiling ATRTs can be divided into four different molecular subgroups. Despite improvements in treatment strategies, the prognosis for ATRT patients remains dismal. The FGF/FGFR signaling pathway plays a crucial role in many physiological processes, including embryonic development, tissue repair, angiogenesis. Dysregulation of the signaling axis is driving tumorigenesis. Targeted therapeutic approaches, particularly FGFR inhibitors, have demonstrated potential in enhancing treatment outcomes for various tumors, including pediatric brain tumors. METHODS We used bulk and single-cell RNA sequencing (scRNA-seq) data to examine the expression patterns of FGF family members in ATRTs. Subsequently, we conducted in vitro analysis on a panel of FGFR inhibitors and combination treatments. RESULTS Transcriptomic analysis of more than 130 ATRT tissues samples, revealed a widespread expression of FGFR1 and FGFR2 across all ATRT subtypes. Notably, FGFR1 displayed distinctly elevated expression in ATRT-SHH, surpassing levels seen in other ATRT subtypes and brain tumor types. Utilizing scRNA-seq data of murine ATRT models, we elucidated an autocrine FGFR signaling loop. To assess the therapeutic feasibility of targeting FGFR, we evaluated a panel of FGFR inhibitors, currently in clinical development, across 10 in house established patient-derived cell models (6 ATRT-MYC, 3 ATRT-SHH, 1 ATRT-TYR), revealing sensitivity in a nanomolar to a low-micromolar range. We further explored combination therapies, demonstrating that Erdafitinib, the most effective inhibitor when combined with Abemaciclib and radiation, exhibited enhanced synergistic effects in 2D as well as in 3D tumoroid models. Investigations towards testing these combinations in an organoid co-culture system, along with in vivo models are ongoing. CONCLUSIONS This study emphasizes the prospect of combining FGFR inhibition with radiation and CDK4/6 inhibition as a therapeutic target for ATRTs.

DIPG-24. COMBINED EPIGENETIC THERAPY WITH FACT AND BET INHIBITORS REMODELS CHROMATIN AND DISRUPTS ONCOGENIC TRANSCRIPTION IN DIFFUSE MIDLINE GLIOMA

Abstract BACKGROUND Aberrant epigenetic regulation is a hallmark of Diffuse Midline Glioma (DMG), an incurable pediatric brain tumor. The H3K27M driver histone mutation leads to transcriptional dysregulation, indicating that targeting the epigenome and transcription may be a key therapeutic strategy against this aggressive cancer. One such target is the Facilitates Chromatin Transcription (FACT) histone chaperone. FACT is targeted by the curaxin compound CBL0137 which is currently in Phase I/II Children’s Oncology Group clinical trial as a single agent for pediatric cancer patients (NCT04870944). METHODS We applied a multi-omics approach by integrating epigenetic profiling with transcriptomics (CUT&amp;RUN, ATAC-seq and RNA-seq) to interrogate the role of FACT in DMG. We then employed in vitro cytotoxicity assays and in vivo orthotopic patient-derived xenograft (PDX) pre-clinical models to test a novel, mechanistic-anchored epigenetic combination therapy. RESULTS We found FACT to be enriched at developmental gene promoters, coinciding with regions of open chromatin and binding motifs of core DMG regulatory transcription factors (OLIG2, TCF12, and SNAI1). FACT interacted and co-localized with the Bromodomain and Extra-Terminal Domain (BET) protein BRD4 at active promoters and enhancers, suggesting functional cooperation between FACT and BRD4 in DMG. Investigating the combination of CBL0137 with two BET inhibitors (JQ1 and trotabresib) revealed potent cytotoxicity in vitro, particularly against H3K27M-mutant cells. Furthermore, this approach was recapitulated in vivo, significantly extending the survival of three independent orthotopic PDX models of DMG. Mechanistically, CBL0137 decreased chromatin accessibility, synergising with BET inhibition to disrupt transcription, leading to transcriptional silencing of several key oncogenes (MYC, PDGFRA and MDM4) as well as causing alterations to the splicing landscape. CONCLUSIONS This study highlights the therapeutic promise of simultaneously targeting FACT and BRD4 in DMG, and provides the rationale for a combination clinical trial, currently in development.

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

Long-Read Structural and Epigenetic Profiling of a Kidney Tumor-Matched Sample with Nanopore Sequencing and Optical Genome Mapping.

Carcinogenesis often involves significant alterations in the cancer genome architecture, marked by large structural and copy number variations (SVs and CNVs) that are difficult to capture with short-read sequencing. Traditionally, cytogenetic techniques are applied to detect such aberrations, but they are limited in resolution and do not cover features smaller than several hundred kilobases. Optical genome mapping and nanopore sequencing are attractive technologies that bridge this resolution gap and offer enhanced performance for cytogenetic applications. These methods profile native, individual DNA molecules, thus capturing epigenetic information. We applied both techniques to characterize a clear cell renal cell carcinoma (ccRCC) tumor's structural and copy number landscape, highlighting the relative strengths of each method in the context of variant size and average read length. Additionally, we assessed their utility for methylome and hydroxymethylome profiling, emphasizing differences in epigenetic analysis applicability.

Disease activity drives divergent epigenetic and transcriptomic reprogramming of monocyte subpopulations in systemic lupus erythematosus

ObjectivesSystemic lupus erythematosus (SLE) is characterised by systemic inflammation involving various immune cell types. Monocytes, pivotal in promoting and regulating inflammation in SLE, differentiate from classic monocytes into intermediate and...

Conserved epigenetic hallmarks of T cell aging during immunity and malignancy

Chronological aging correlates with epigenetic modifications at specific loci, calibrated to species lifespan. Such ‘epigenetic clocks’ appear conserved among mammals, but whether they are cell autonomous and restricted by maximal organismal lifespan remains unknown. We used a multilifetime murine model of repeat vaccination and memory T cell transplantation to test whether epigenetic aging tracks with cellular replication and if such clocks continue ‘counting’ beyond species lifespan. Here we found that memory T cell epigenetic clocks tick independently of host age and continue through four lifetimes. Instead of recording chronological time, T cells recorded proliferative experience through modification of cell cycle regulatory genes. Applying this epigenetic profile across a range of human T cell contexts, we found that naive T cells appeared ‘young’ regardless of organism age, while in pediatric patients, T cell acute lymphoblastic leukemia appeared to have epigenetically aged for up to 200 years. Thus, T cell epigenetic clocks measure replicative history and can continue to accumulate well-beyond organismal lifespan.

PR-SET7 epigenetically restrains uterine interferon response and cell death governing proper postnatal stromal development

The differentiation of the stroma is a hallmark event during postnatal uterine development. However, the spatiotemporal changes that occur during this process and the underlying regulatory mechanisms remain elusive. Here, we comprehensively delineated the dynamic development of the neonatal uterus at single-cell resolution and characterized two distinct stromal subpopulations, inner and outer stroma. Furthermore, single-cell RNA sequencing revealed that uterine ablation of Pr-set7, the sole methyltransferase catalyzing H4K20me1, led to a reduced proportion of the inner stroma due to massive cell death, thus impeding uterine development. By combining RNA sequencing and epigenetic profiling of H4K20me1, we demonstrated that PR-SET7-H4K20me1 either directly repressed the transcription of interferon stimulated genes or indirectly restricted the interferon response via silencing endogenous retroviruses. Declined H4K20me1 level caused viral mimicry responses and ZBP1-mediated apoptosis and necroptosis in stromal cells. Collectively, our study provides insight into the epigenetic machinery governing postnatal uterine stromal development mediated by PR-SET7.

Bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data

BackgroundBisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges.ResultsWe introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility.ConclusionsWe introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at https://github.com/hippo-yf/bsgenova under license GPL-3.0.