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PubMed2004

DNA methyltransferase 1 knock down induces gene expression by a mechanism independent of DNA methylation and histone deacetylation.

DNA methyltransferase 1 (DNMT1) catalyzes the post-replication methylation of DNA and is responsible for maintaining the DNA methylation pattern during cell division. A long list of data supports a role for DNMT1 in cellular transformation and inhibitors of DNMT1 were shown to have antitumorigenic effects. It was long believed that DNMT1 promoted tumorigenesis by maintaining the hypermethylated and silenced state of tumor suppressor genes. We have previously shown that DNMT1 knock down by either antisense oligonucleotides directed at DNMT1 or expressed antisense activates a number of genes involved in stress response and cell cycle arrest by a DNA methylation-independent mechanism. In this report we demonstrate that antisense knock down of DNMT1 in human lung carcinoma A549 and embryonal kidney HEK293 cells induces gene expression by a mechanism that does not involve either of the known epigenomic mechanisms, DNA methylation, histone acetylation, or histone methylation. The mechanism of activation of the cell cycle inhibitor p21 and apoptosis inducer BIK by DNMT1 inhibition is independent of the mechanism of activation of the same genes by histone deacetylase inhibition. We determine whether DNMT1 knock down activates one of the nodal transcription activation pathways in the cell and demonstrate that DNMT1 activates Sp1 response elements. This activation of Sp1 response does not involve an increase in either Sp1 or Sp3 protein levels in the cell or the occupancy of the Sp1 elements with these proteins. The methylation-independent regulation of Sp1 elements by DNMT1 unravels a novel function for DNMT1 in gene regulation. DNA methylation was believed to be a mechanism for suppression of CG-rich Sp1-bearing promoters. Our data suggest a fundamentally different and surprising role for DNMT1 regulation of CG-rich genes by a mechanism independent of DNA methylation and histone acetylation. The implications of our data on the biological roles of DNMT1 and the therapeutic potential of DNMT1 inhibitors as anticancer agents are discussed.

Acetylation↗
PubMed2006

A trans-tail histone code defined by monomethylated H4 Lys-20 and H3 Lys-9 demarcates distinct regions of silent chromatin.

The specific post-translational modifications of the histone proteins are associated with specific DNA-templated processes, such as transcriptional activation or repression. To investigate the biological role(s) of histone H4 lysine 20 (H4 Lys-20) methylation, we created a novel panel of antibodies that specifically detected mono-, di-, or trimethylated H4 Lys-20. We report that the different methylated forms of H4 Lys-20 are compartmentalized within visually distinct, transcriptionally silent regions in the mammalian nucleus. Interestingly, direct comparison of methylated H4 Lys-20 with the different methylated states of histone H3 lysine 9 (H3 Lys-9) revealed significant overlap and exclusion between the specific groups of methyl modifications. Trimethylated H4 Lys-20 and H3 Lys-9 were both selectively enriched within pericentric heterochromatin. Similarly, monomethylated H4 Lys-20 and H3 Lys-9 partitioned together and the dimethylated forms partitioned together within the chromosome arms; however, the mono- and dimethylated modifications were virtually exclusive. These findings strongly suggest that the combinatorial presence or absence of the different methylated states of H4 Lys-20 and H3 Lys-9 define particular types of silent chromatin. Consistent with this, detailed analysis of monomethylated H4 Lys-20 and H3 Lys-9 revealed that both were preferentially and selectively enriched within the same nucleosome particle in vivo. Collectively, these findings define a novel trans-tail histone code involving monomethylated H4 Lys-20 and H3 Lys-9 that act cooperatively to mark distinct regions of silent chromatin within the mammalian epigenome.

Amino Acid Sequence↗
PubMed2004

Emerging diet-related surrogate end points for colorectal cancer: UK Food Standards Agency diet and colonic health workshop report.

The UK Food Standards Agency convened a group of expert scientists to review current research investigating emerging diet-related surrogate end points for colorectal cancer (CRC). The workshop aimed to overview current research and establish priorities for future research. The workshop considered that the validation of current putative diet-related surrogate end points for CRC and the development of novel ones, particularly in the emerging fields of proteomics, genomics and epigenomics, should be a high priority for future research.

Biomarkers, Tumor↗
PubMed2006

Perinatal maternal undernutrition programs the offspring hypothalamo-pituitary-adrenal (HPA) axis.

There is now compelling evidence, coming both from animal and human studies that an early exposure to undernutrition is frequently associated with low birth weight and programs HPA axis alterations throughout the lifespan. Although animal models have reported conflicting findings arising from differences in experimental paradigms and species, they have clearly demonstrated that such programming not only affects the brain but also the pituitary corticotrophs and the adrenal cortex. In fetuses, maternal undernutrition reduces HPA axis function and implicates a reduction of placental 11beta-HSD2 activity and a greater transplacental transfer of glucocorticoids (GRs). In young adults, usually only fine HPA axis alterations were observed, whereas in older ones, maternal undernutrition was frequently associated with chronic hyperactivity of this neuroendocrine axis. In humans, evidence of HPA axis dysregulation in people who were small at birth has recently emerged. Thus, we suggest that such alterations in adults may be implicated in the aetiology of several disorders related to the metabolic syndrome as well as to immune or inflammatory diseases. To reverse such programming, recent experimental reports have shown that postnatal environmental interventions, dietary modifications and the use of agents modulating the epigenomic state could partly restore physiological functions and thus open new therapeutic strategies.

Adrenocorticotropic Hormone↗
PubMed2026

Mapping the development pipeline of genomic point-of-care tests: a horizon scan.

INTRODUCTION: As precision medicine increasingly relies on genetic information, the development of reliable genomic point-of-care tests (POCTs) is essential. However, the number of technologies that have reached true clinical usability is limited. There is a growing need for POCTs that enable rapid, accurate analysis of human genetic variation, particularly across diverse clinical settings without requiring specialist expertise. AREAS COVERED: This horizon scan aimed to provide an overview of the development pipeline of POCTs to identify variation(s) in the genome and epigenome that enable the use of genetic information to inform diagnosis, prognosis, and treatment decisions in any clinical area. Database (Embase and MEDLINE) and clinical trial registry (ClinicalTrials.gov) searches were conducted from 2019 to 19 December 2024; 346 unique technologies were identified. EXPERT OPINION AND COMMENTARY: A range of purposes and conditions were identified; the most common being diagnosis (n = 263) and cancer (n = 237) respectively. We defined 'true POCTs' as those that were highly automated, capable of analyzing complex samples, and operable by non-specialists. Only 36 met these criteria; six are already on the market, one is in clinical trials, and the remaining 29 are at various stages of development. Overall, most technologies were in early stages of development, highlighting the need for further innovation and validation.

Point-of-care↗
PubMed2026

SNP-derived CpG variation and DNA methylation linking genetic susceptibility to metabolic disease.

DNA methylation at CpG dinucleotides represents a key epigenetic mechanism linking genetic variation to gene regulation in complex human diseases. Single-nucleotide polymorphisms (SNPs) that create or disrupt CpG sites can alter local DNA methylation and transcriptional activity, thereby influencing disease susceptibility. These CpG-modifying variants provide a functional interface between inherited genetic variation and epigenetic regulation in complex metabolic disorders. This review summarizes current evidence on SNP-derived CpG variation and its role in allele-specific DNA methylation and gene regulation in metabolically relevant tissues. By integrating findings from genome-wide association studies, epigenome-wide association studies, and multi-omics research, this review provides a mechanistic framework explaining how CpG-modifying polymorphisms influence adipogenesis, pancreatic β-cell function, inflammation, and glucose metabolism. Special emphasis is placed on South Asian populations, who exhibit early β-cell dysfunction and increased visceral adiposity. Many CpG-modifying variants act as methylation quantitative trait loci (meQTLs), influencing allele-specific methylation and gene expression. Understanding SNP-CpG-methylation interactions may improve functional interpretation of disease-associated genetic variants, enhance biomarker discovery, and support precision medicine strategies for metabolic disease.

Humans↗
PubMed2025

dbscATAC: a resource of single-cell super-enhancers/enhancers and gene markers derived from scATAC-seq data.

MOTIVATION: scATAC-seq enables high-resolution mapping of cis-regulatory elements. It has been widely applied to uncover cell-type-specific regulatory networks and complement scRNA-seq analysis in numerous studies. However, a large number of datasets generated by scATAC-seq remain underutilized due to limited exploration of super-enhancers/typical enhancers and gene markers. A comprehensive resource enabling cell-type-specific annotation of cis-regulatory elements and their dynamic enhancer-gene linkages remains an urgent unmet need for scATAC-seq. RESULTS: We present dbscATAC, a specialized single-cell database for annotating super-enhancers, gene markers, and enhancer-gene interactions derived from scATAC-seq data. Using improved machine learning algorithms, we identified 213 835 super-enhancers across 520 tissue/cell types from three species, as well as 347 484 gene markers, 13 470 526 enhancers, and 10 402 346 enhancer-gene interactions derived from 1 668 076 single cells spanning 1028 tissue/cell types in 13 species. An easy-to-use online platform with multiple analytic modules and hierarchical query options was developed for searching, browsing and visualizing single-cell super-enhancers, enhancers, and gene markers. dbscATAC provides a comprehensive resource to facilitate the exploration of enhancer landscapes, gene regulation, and cell-type-specific characteristics in single-cell epigenomics. AVAILABILITY AND IMPLEMENTATION: The database with all the super-enhancer/enhancer annotation data is available at http://singlecelldb.com/dbscATAC/index.php. And the source code of dbscATAC for prediction of SEs, enhancers, and gene markers are available at https://github.com/EvansGao/dbscATAC. The source code, tissue/cell type description, and data summary can be downloaded at DOI: 10.6084/m9.figshare.28706414.scATAC-seq, Database, Super-enhancers/enhancers, Gene markers.

Enhancer Elements, Genetic↗
PubMed2025

scPOEM: robust co-embedding of peaks and genes revealing peak-gene regulation.

MOTIVATION: Identifying regulatory elements in various chromosomal regions that influence gene expression is a fundamental challenge in epigenomics, with profound implications for understanding gene regulation and disease mechanisms. The advent of paired single-cell RNA sequencing and single-cell ATAC sequencing has created unprecedented opportunities to address this challenge by enabling simultaneous profiling of gene expression and chromatin accessibility at single-cell resolution. However, the inherent signals between them are weak due to the highly sparse and noisy nature of data. RESULTS: This article proposes single-cell meta-Path based Omics Embedding (scPOEM), a novel embedding method that jointly projects chromatin accessibility peaks and expressed genes into a shared low-dimensional space. By integrating the relationships among peak-peak, peak-gene, and gene-gene interactions, scPOEM assigns closer representations in the embedding space to related peak-gene pairs. Our experiments demonstrate that scPOEM generates stable representations of peaks and genes, outperforms existing methods in recovering biologically meaningful peak-gene regulatory relationships and enables new insights in subgroup and differential analysis of gene regulation. These results highlight its potential to uncover gene regulatory mechanisms and enhance the understanding of transcriptional regulation at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: The source code of scPOEM is available at https://github.com/Houyt23/scPOEM. The datasets can be obtained from the 10× Genomics (https://www.10xgenomics.com/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) and GEO database under access codes GSE194122 and GSE239916.

Gene Expression Regulation↗
PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗
PubMed2026

Dogme: a nextflow pipeline for reprocessing nanopore RNA and DNA modifications.

MOTIVATION: Oxford Nanopore (ONT) sequencing allows for the direct detection of RNA and DNA modifications from unamplified nucleic acids, which is a significant advantage over other platforms. However, the rapid updates to ONT basecalling models and the evolving landscape of computational tools for modification detection bring about challenges for reproducible and standardized analyses. To address these challenges, we developed Dogme to automate basecalling, alignment, modification detection, and transcript quantification. Dogme automates the reprocessing of ONT POD5 files by integrating basecalling using Dorado, read mapping using minimap2 and subsequent analysis steps such as running modkit. The pipeline supports three major types of sequencing data-direct RNA (dRNA), complementary DNA (cDNA), and genomic DNA (gDNA). Dogme facilitates detection of diverse RNA modifications supported by Dorado such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), inosine, pseudouridine, 2'-O-methylation (Nm) and DNA methylation, while concurrently quantifying full-length transcript isoforms LR-Kallisto for transcript quantification for dRNA and cDNA. RESULTS: We applied Dogme to three separate mouse C2C12 myoblast replicates using direct RNA sequencing on MinION flow cells. We detected 96 603 m6A, 43 476 m5C, 8829 inosine, 10 055 pseudouridine, and 30 320 Nm sites in three biological replicates. The pipeline produced reproducible modification profiles and transcript expression levels across replicates, demonstrating its utility for integrative long-read transcriptomic and epigenomic analyses. AVAILABILITY AND IMPLEMENTATION: Dogme is implemented in Nextflow and is freely available under the MIT license at https://github.com/mortazavilab/dogme, with documentation provided for installation and usage.

RNA↗
PubMed2004

Quantitative DNA methylation analysis based on four-dye trace data from direct sequencing of PCR amplificates.

MOTIVATION: Methylation of cytosines in DNA plays an important role in the regulation of gene expression, and the analysis of methylation patterns is fundamental for the understanding of cell differentiation, aging processes, diseases and cancer development. Such analysis has been limited, because technologies for detailed and efficient high-throughput studies have not been available. We have developed a novel quantitative methylation analysis algorithm and workflow based on direct DNA sequencing of PCR products from bisulfite-treated DNA with high-throughput sequencing machines. This technology is a prerequisite for success of the Human Epigenome Project, the first large genome-wide sequencing study for DNA methylation in many different tissues. Methylation in tissue samples which are compositions of different cells is a quantitative information represented by cytosine/thymine proportions after bisulfite conversion of unmethylated cytosines to uracil and PCR. Calculation of quantitative methylation information from base proportions represented by different dye signals in four-dye sequencing trace files needs a specific algorithm handling imbalanced and overscaled signals, incomplete conversion, quality problems and basecaller artifacts. RESULTS: The algorithm we developed has several key properties: it analyzes trace files from PCR products of bisulfite-treated DNA sequenced directly on ABI machines; it yields quantitative methylation measurements for individual cytosine positions after alignment with genomic reference sequences, signal normalization and estimation of effectiveness of bisulfite treatment; it works in a fully automated pipeline including data quality monitoring; it is efficient and avoids the usual cost of multiple sequencing runs on subclones to estimate DNA methylation. The power of our new algorithm is demonstrated with data from two test systems based on mixtures with known base compositions and defined methylation. In addition, the applicability is proven by identifying CpGs that are differentially methylated in real tissue samples.

Algorithms↗
PubMed2025

Genomic loci and molecular genetic mechanisms for hidradenitis suppurativa.

BACKGROUND: Hidradenitis suppurativa (HS) is a common, chronic and debilitating inflammatory disease that most commonly affects intertriginous skin. Despite its high heritability, the genetic underpinnings of HS remain poorly understood. OBJECTIVES: To identify genetic signals associated with HS, determine genetic relationships with other diseases and investigate potential molecular genetic mechanisms. METHODS: We performed a genome-wide association meta-analysis of six studies, totalling 4540 patients with HS and > 1 million control participants, and identified genetic correlations with other common diseases. We integrated the HS data with expression quantitative trait loci from 10 trait-relevant tissues, epigenomic and transcriptomic data from human scalp, differential expression data from HS lesions vs. adjacent skin and mesenchymal Hi-C chromatin looping data. To identify functional noncoding variants, we performed transcriptional reporter assays for signals near KLF5 and SOX9. RESULTS: We identified 11 significant HS signals across 7 loci: 4 corresponded to previously reported associations, 4 represented novel signals within known loci and 3 were signals in newly implicated loci. We identified significant genetic correlations between HS and other inflammatory conditions, particularly inflammatory bowel disease, rheumatoid arthritis, type 2 diabetes mellitus and asthma. We prioritized candidate genes for the 11 signals. The risk allele at KLF5 exhibited 10-fold greater transcriptional activity than the nonrisk allele, while risk alleles at SOX9 showed significantly reduced transcriptional activity. CONCLUSIONS: Our results provide insights into potential genetic mechanisms underlying HS and suggest potential therapeutic targets for this challenging condition.

Humans↗
PubMed2003

Human DNA methyltransferase gene DNMT1 is regulated by the APC pathway.

Epigenomic changes in DNA methylation patterns are evident in a variety of cancers, including colorectal cancer (CRC). In addition, a large proportion of CRC tumors and cell lines harbor genetic mutations in the APC/beta-catenin/TCF transcription activation pathway. While several target genes have been proposed, a causal downstream agent between APC mutation and cancer has not been fully established. Because previous work implicates DNA methyltransferase (DMNT1) as a critical point in tumorigenesis and recent studies suggest that familial CRC also exhibits epigenetic alterations, we sought to investigate whether this gene might be regulated by APC in CRC. Reconstitution of wild type APC in HT-29 CRC cell lines reduced the expression of both a reporter gene driven by the minimal DNMT1 promoter and DNMT1 mRNA that is independent of cell growth stasis. We also provide evidence for a causal role of DNMT1 in CRC by demonstrating that antisense-driven reduction of DNMT1 mRNA inhibits anchorage-independent growth, an indicator of tumorigenesis, of CRC cells. These data support future consideration of DNMT1 as a target in the treatment of CRC.

Adenomatous Polyposis Coli Protein↗
PubMed2006

Valproate induces widespread epigenetic reprogramming which involves demethylation of specific genes.

Valproate (VPA)(1) has been used for decades in the treatment of epilepsy, and is also effective as a mood stabilizer and in migraine therapy. It has been shown that VPA is also a histone deacetylase (HDAC) inhibitor. We have previously shown that VPA could trigger active demethylation of ectopically methylated transiently transfected DNA in HEK 293 cells. We therefore tested whether VPA treatment could bring about stable changes in the epigenome by causing changes in the state of DNA methylation of genomic DNA. Using a microarray gene expression analysis we identified the genes whose expression is induced by VPA treatment in HEK 293 cells. We found that a subset of these genes could also be induced by the classical DNA methylation inhibitor 5-aza-2'-deoxy-cytidine (5-aza-CdR) suggesting that VPA can alter the state of expression of genes, which are stably suppressed by DNA methylation. We mapped the state of methylation of three of these genes, MELANOMA ANTIGEN B2 GENE (MAGEB2), METALLOPROTEINASE 2 (MMP2) and WIF1, which are involved in tumor growth and metastasis. A chromatin immunoprecipitation (ChIP) assay revealed that VPA treatment caused as expected a change in the state of acetylation of these genes. Our data supports the concept that chromatin acetylation and DNA methylation are found in a dynamic interrelation and that the consequences of HDAC inhibitors are not limited to changes in histone acetylation but that they also bring about a change in the state of modification of DNA. The implications of our results on the future therapeutic utilities of VPA in cancer will be discussed.

Adaptor Proteins, Signal Transducing↗
PubMed2004

Mapping development-related and age-related chromatin remodeling by a high throughput ChIP-HPLC approach.

Common to numerous differentiation pathways in vertebrate organisms is the regulation of key genes through epigenetic mechanisms. Less well studied is to what extent cells of a given differentiation state, but examined at different points within the life history of an organism, are distinct at the level of the epigenome. A few instances of such variation have been reported, and it would be of considerable value to have at hand a means to characterize additional examples more efficiently. We describe an integrated approach to this task, and further present evidence for regions of age-related histone H4 acetylation change extending over tens to hundreds of kilobases. Broad similarity between two distinct regions of such change suggests a previously unsuspected link between developmental programs and aging.

Acetylation↗
PubMed2005

Histone modifying and chromatin remodelling enzymes in cancer and dysplastic syndromes.

Inactivation of tumour suppressor genes is central to the development of cancer. Although this inactivation was once considered to be secondary to intragenic mutations, it is now clear that silencing of these genes often occurs by epigenetic means. Hypermethylation of CpG islands associated with the tumour suppressor genes was the first manifestation of this phenomenon to be described. It is apparent, however, that this is one of a host of chromatin modifications which characterize gene silencing. Although we know little about what determines which loci are affected, our understanding of the nature of the epigenetic marks and how they are established has blossomed. There is no compelling evidence that cancer ever develops by purely epigenetic means, but it is apparent that perturbations in the apparatus which establish the epigenome may contribute to the development of cancer. This review will focus on the role of two classes of chromatin remodelling enzymes, those that alter histones by the addition or removal of acetyl and methyl groups and those of the SWI/SNF family of proteins that change the topology of the nucleosome and its DNA strand via the hydrolysis of ATP, and we shall examine the consequence of mutations in, or mis-expression of, these factors. In some cases, mutations in these factors appear to play a direct role in cancer development. However, their general role as important intermediaries involved in regulating gene expression makes them attractive therapeutic targets. In exciting developments, it has been shown that inhibition of these factors leads to the reversal of tumour suppressor gene silencing and the inhibition of cancer cell growth.

Acetyltransferases↗
PubMed2005

Cancer epigenetics.

The field of cancer epigenetics is evolving rapidly on several fronts. Advances in our understanding of chromatin structure, histone modification, transcriptional activity and DNA methylation have resulted in an increasingly integrated view of epigenetics. In response to these insights, epigenetic therapy is expanding to include combinations of histone deacetylase inhibitors and DNA methyltransferase inhibitors. Zebularine, an orally administerable DNA methyltransferase inhibitor, has been a very promising recent addition to our arsenal of potentially useful drugs for epigenetic therapy. Aberrant DNA methylation patterns provide three powerful diagnostic applications as classification markers, sensitive detection markers, and risk assessment markers. Classification studies continue to increase in marker complexity, now incorporating microarrays, high-throughput bisulfite genomic sequencing and mass spectrometry, as the field moves to human epigenome projects. Sensitive detection technology has expanded from primarily blood-based cancer detection to include applications on a wide diversity of sample sources and is now also making inroads as a molecular risk assessment tool.

Antineoplastic Agents↗
PubMed2026

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗