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PubMed2005

A gene expression fingerprint of C. elegans embryonic motor neurons.

BACKGROUND: Differential gene expression specifies the highly diverse cell types that constitute the nervous system. With its sequenced genome and simple, well-defined neuroanatomy, the nematode C. elegans is a useful model system in which to correlate gene expression with neuron identity. The UNC-4 transcription factor is expressed in thirteen embryonic motor neurons where it specifies axonal morphology and synaptic function. These cells can be marked with an unc-4::GFP reporter transgene. Here we describe a powerful strategy, Micro-Array Profiling of C. elegans cells (MAPCeL), and confirm that this approach provides a comprehensive gene expression profile of unc-4::GFP motor neurons in vivo. RESULTS: Fluorescence Activated Cell Sorting (FACS) was used to isolate unc-4::GFP neurons from primary cultures of C. elegans embryonic cells. Microarray experiments detected 6,217 unique transcripts of which approximately 1,000 are enriched in unc-4::GFP neurons relative to the average nematode embryonic cell. The reliability of these data was validated by the detection of known cell-specific transcripts and by expression in UNC-4 motor neurons of GFP reporters derived from the enriched data set. In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules. The added presence of a robust array of G-protein pathway components is indicative of complex and highly integrated mechanisms for modulating motor neuron activity. Over half of the enriched genes (537) have human homologs, a finding that could reflect substantial overlap with the gene expression repertoire of mammalian motor neurons. CONCLUSION: We have described a microarray-based method, MAPCeL, for profiling gene expression in specific C. elegans motor neurons and provide evidence that this approach can reveal candidate genes for key roles in the differentiation and function of these cells. These methods can now be applied to generate a gene expression map of the C. elegans nervous system.

Animals↗

PubMed2026

CasY7: An optimized Cas12i system for enhanced genome editing in monocot crops.

The CRISPR-Cas12 family nucleases, particularly the Cas12i subtypes, are considered promising alternatives to Cas9 for genome editing in plants. We previously developed a new Cas12i variant, CasY7, which has been successfully applied in clinical trials; its performance in plants remains to be investigated. Initial testing in stable transgenic maize and rice showed that the codon-optimized CasY7 (pCasY7e1) achieved average editing efficiencies of 58.7% and 62.3% across five target sites, respectively, outperforming the typical Cpf1 (pCpf1) control that targets the same sites. To further enhance activity, we fused T5 exonuclease to CasY7 (pCasY7e2), which shifted mutation profiles toward larger deletions, and subsequently integrated an MS2 aptamer into the crRNA scaffold (pCasY7e3). The optimized pCasY7e3 system increased editing efficiencies to 87.7% in maize and 82.9% in rice-approximately 2.7-fold higher than pCpf1. We further demonstrated multiplexed editing in maize, generating biallelic dwarf mutants, and validated functionality in hexaploid wheat with editing efficiencies up to 58.8%. Overall, our comprehensive validation across 942 transgenic plants confirmed robust editing in maize, rice, and wheat, establishing CasY7 as a high-efficiency addition to the CRISPR toolkit.

Zea mays↗

PubMedDate not supplied

Clustering of molecular alterations in gastroesophageal carcinomas.

Gene expression levels are regulated at many levels. Integration of genome-wide analyses for the study of DNA and RNA provides a unique tool to detect genetic alterations in the cancer genome. In this study, we generated and integrated DNA amplification data from comparative genomic hybridization (CGH) and serial analyses of gene expression (SAGE) in order to obtain a molecular profile of gastroesophageal junction (GEJ) carcinomas. DNA amplifications mapped to specific chromosomal regions and were frequently seen at 1q, 4q, 5q, 6p, 7p, 8q, 17q, and 20q. Using SAGE, we obtained over 156,432 tags from GEJ adenocarcinomas and normal gastric mucosa. These tags were assigned to UniGene clusters. Chromosomal positions for overexpressed genes were obtained to produce a GEJ carcinoma transcriptome map. A total of 123 genes was significantly overexpressed (more than fivefold; P <.01) in one or more SAGE libraries. This gene overexpression map was integrated and compared to the chromosomal CGH ideogram. Several chromosomal arms that had frequent DNA amplifications showed frequent gene expression alterations such as chromosomes 1 (15 genes), 2 (9 genes), 6 (6 genes), 11 (6 genes), 12 (8 genes), and 17 (13 genes). Despite the relatively large DNA amplification regions, overexpressed genes frequently mapped and clustered to small chromosomal regions at early-replicating (Giemsa light) bands such as 1q21.3 (nine genes), 6p21.3 (five genes), and 17q21 (eight genes). These results provide a comprehensive tool to search for DNA amplifications and overexpressed genes in GEJ carcinoma. The observed phenomenon of the presence of large amplification areas, yet clustering of overexpressed genes to relatively small loci, may suggest a high organization of chromatin and cancer-related genes in the nucleus.

Adenocarcinoma↗

PubMed2025

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans↗

PubMed2005

The lacrimal gland transcriptome is an unusually rich source of rare and poorly characterized gene transcripts.

PURPOSE: To sequence and comprehensively analyze human and mouse lacrimal gland transcriptomes as part of the NEIBank project. METHODS: cDNA libraries generated from normal human and mouse lacrimal glands were sequenced and analyzed by PHRED, RepeatMasker, BLAST, and GRIST. Human "lacrimal-preferred genes" and putative gene regulatory elements were respectively identified in UniGene and ConSite, and gene clustering was analyzed by chromosomal mapping. "Hypothetical proteins," identified by keyword search, were verified by genomic alignment and queried in the Conserved Domain database and GEO Profiles. RESULTS: The top six transcripts in human and mouse differed, revealing a previously unappreciated molecular divergence. The human transcriptome is enriched with transcripts from 29 lacrimal-preferred genes and a content of poorly characterized hypothetical proteins, proportionally greater than in all other tissues. Only 45% of lacrimal preferred, but 71% of hypotheticals, have mouse orthologs. Many of the latter display apparently altered cancer expression in the CGAP SAGE library collection-often in keeping with predicted WD40, protein kinase, Src homology 2 and 3, RhoGEF, and pleckstrin homology domains involved in cell signaling. At the genomic level, lacrimal-expressed genes show some evidence of clustering, particularly on human chromosomes 9 and 12. Binding sites for TFAP2A, FOXC1, and other transcription factors are predicted. CONCLUSIONS: Interspecies divergence cautions against use of mouse models of human dry eye syndromes. Lacrimal preferred and hypothetical proteins, gene clustering, and putative gene regulatory elements together provide new clues for a molecular understanding of lacrimal gland function and mechanisms of coordinated tissue-specific transcriptional regulation.

Aged↗

PubMed2001

[Frequent chromosomal gain of 4q and loss of 1p in primary nasopharyngeal carcinoma].

OBJECTIVE: To reveal the genetic changes of nasopharyngeal carcinoma (NPC) in Cantonese. METHODS: Comparative genomic hybridization (CGH) was performed on 17 primary NPC biopsy specimens to find out any gain or loss of genetic material. RESULTS: A novel copy number gain on chromosome 4q and loss of chromosome 1p were found at high frequency (> 50%). The other more common genetic alterations included gain of chromosomes 4q, 12q, and 1q as well as loss of chromosomes 1p, 3p, 11q, 14q, 15q, 13q, Xq, 9q, 10p, 10q, and 16q. CONCLUSION: Current analysis has revealed a comprehensive profile of the chromosomal changes in NPC. Frequently altered loci may encode oncogenes or tumor suppressor genes involved in the development of primary NPC.

Asian People↗

PubMed2002

A database on alternative splice forms on the integrated genetic map service (IGMS).

UNLABELLED: The IGMS is a comprehensive information system that combines the knowledge from genomic sequence, genetic map and genetic disorders databases. This system is updated weekly and focuses on the analysis of EST data. The IGMS identifies UniGene clusters that are differentially expressed in different types of cancer with respect to different reference tissues. The results can be combined with clinical data to asses the potential relevance of specific genes for patient survival or metastatic spread. The second application maps EST with a specific expression profile. Our third application generates a database of alternative splice forms for nine organisms from EST and mRNA sequence data. The results can be used to find splicing patterns specific for certain tissues or tumour types. AVAILABILITY: http://www.bioinf.mdc-berlin.de/igms/.

Alternative Splicing↗

PubMed2004

Multi-tissue gene-expression analysis in a mouse model of thyroid hormone resistance.

BACKGROUND: Resistance to thyroid hormone (RTH) is caused by mutations of the thyroid hormone receptor beta (TRbeta) gene. To understand the transcriptional program underlying TRbeta mutant-induced phenotypic expression of RTH, cDNA microarrays were used to profile the expression of 11,500 genes in a mouse model of human RTH. RESULTS: We analyzed transcript levels in cerebellum, heart and white adipose tissue from a knock-in mouse (TRbetaPV/PV mouse) that harbors a human mutation (referred to as PV) and faithfully reproduces human RTH. Because TRbetaPV/PV mice have elevated thyroid hormone (T3), to define T3-responsive genes in the context of normal TRbeta, we also analyzed T3 effects in hyperthyroid wild-type gender-matched littermates. Microarray analysis revealed 163 genes responsive to T3 treatment and 187 genes differentially expressed between TRbetaPV/PV mice and wild-type littermates. Both the magnitude and gene make-up of the transcriptional response varied widely across tissues and conditions. We identified genes modulated in T3-dependent PV-independent, T3- and PV-dependent, and T3-independent PV-dependent pathways that illuminated the biological consequences of PV action in vivo. Most T3-responsive genes that were dysregulated in the heart and white adipose tissue of TRbetaPV/PV mice were repressed in T3-treated wild-type mice and upregulated in TRbetaPV/PV mice, suggesting the inappropriate activation of T3-suppressed genes in RTH. CONCLUSIONS: Comprehensive multi-tissue gene-expression analysis uncovered complex multiple signaling pathways that mediate the molecular actions of TRbeta mutants in vivo. In particular, the T3-independent mutant-dependent genomic response unveiled the contribution of a novel 'change-of-function' of TRbeta mutants to the pathogenesis of RTH. Thus, the molecular actions of TRbeta mutants are more complex than previously envisioned.

Adipose Tissue↗

PubMed2026

Myoepithelioma-like tumor of the vulvar region shows a quiet genome and heterogeneous detectable mechanisms of SMARCB1 inactivation: Integrated analysis of two cases and review of the literature.

Myoepithelioma-like tumor of the vulvar region (MELTVR) is a rare SMARCB1-deficient mesenchymal neoplasm of adult women that can mimic malignant vulvar sarcomas, particularly epithelioid sarcoma. Although loss of SMARCB1/INI1 expression is a defining feature, the comprehensive genomic landscape of MELTVR remains poorly characterized. We report two cases of MELTVR and performed integrated histopathologic, immunophenotypic, and molecular analyses, including whole-exome sequencing (WES) with copy number assessment and targeted RNA-based fusion testing using the Archer FusionPlex Sarcoma panel. Histologically, both tumors consisted of relatively uniform epithelioid to short spindle cells in solid nests and cords within focal myxoid stroma, with complete loss of INI1 and positivity for smooth muscle markers and focal ER/EMA expression. Genomic profiling demonstrated a quiet molecular background in both cases, with low tumor mutation burden (0.45 and 1.03 mut/Mb) and no pathogenic SNVs/indels in major cancer-associated genes. One case showed a focal homozygous deletion of the SMARCB1 locus at 22q11.2, whereas the other case exhibited INI1 loss without detectable SMARCB1 mutation or copy number loss, suggesting heterogeneous mechanisms of inactivation. CDKN2A copy number remained neutral in both tumors. No canonical sarcoma-associated gene rearrangements, including EWSR1, FUS, PLAG1, or NR4A3, were identified. Together with a review of previously reported cases, these findings support MELTVR as an SMARCB1-inactivated neoplasm with low genomic complexity and highlight the diagnostic value of NGS-based profiling in excluding malignant mimics and preventing overtreatment.

Humans↗

PubMed2025

Next generation sequencing analysis reveals complex genetic architecture of childhood-onset systemic lupus erythematosus.

OBJECTIVES: Our current understanding of the genetic architecture of childhood-onset SLE (cSLE) is limited by a dearth of comprehensive genomic studies in cSLE. We have quantified the number of known rare and common SLE risk variants in a diverse cSLE cohort. We characterised type I interferon (IFN) gene expression scores along with genomic data. METHODS: We performed whole genome sequencing on 83 patients with cSLE and 109 unaffected parents and analysed sequences for known common and rare SLE-associated risk variants. Type I IFN gene expression was quantified on a subset of patients. We investigated the relationship between clinical phenotype, genomic profile and type I IFN signatures in this cohort. RESULTS: Patients with cSLE were enriched for common SLE risk variants compared with unaffected parents and controls. We identified rare SLE risk variants in 11% of individuals with cSLE; those with rare variants had earlier disease onset (<12 years) than those without variants. Patients with cSLE had elevated type I IFN gene expression compared with unaffected parents and controls, even though most patients were treated with immunosuppressive therapy. CONCLUSIONS: Patients with cSLE from this ancestrally and geographically diverse cohort are enriched for common cSLE risk variants compared with controls, and 11% carry a rare variant in known monogenic SLE risk genes. The relationship between rare and common risk variant burden is more complex than previously hypothesised. Our findings indicate that studying patients with cSLE is important for understanding genetic contributions to SLE pathogenesis.

Humans↗

PubMed2006

Bioinformatics for comprehensive finding and analysis of glycosyltransferases.

Bioinformatics is a very powerful tool in the field of glycoproteomics as well as genomics and proteomics. As a part of the Glycogene Project (GG project), we have developed a novel bioinformatics system for the comprehensive identification and in silico cloning of human glycogenes. Using our system, a total of 105 candidate human glycogenes were identified and then engineered for heterologous expression. Of these candidates, 38 recombinant proteins were successfully identified for their enzyme activity and substrate specificity. We also classified 47 out of 60 carbohydrate-active enzyme glycosyltransferase families into 4 superfamilies using the profile Hidden Markov Model method. On the basis of our classification and the relationship between glycosylation pathways and superfamilies, we propose the evolution of glycosyltransferases.

Algorithms↗

PubMed2025

A Graph Contrastive Learning Method for Enhancing Genome Recovery in Complex Microbial Communities.

Accurate genome binning is essential for resolving microbial community structure and functional potential from metagenomic data. However, existing approaches-primarily reliant on tetranucleotide frequency (TNF) and abundance profiles-often perform sub-optimally in the face of complex community compositions, low-abundance taxa, and long-read sequencing datasets. To address these limitations, we present MBGCCA, a novel metagenomic binning framework that synergistically integrates graph neural networks (GNNs), contrastive learning, and information-theoretic regularization to enhance binning accuracy, robustness, and biological coherence. MBGCCA operates in two stages: (1) multimodal information integration, where TNF and abundance profiles are fused via a deep neural network trained using a multi-view contrastive loss, and (2) self-supervised graph representation learning, which leverages assembly graph topology to refine contig embeddings. The contrastive learning objective follows the InfoMax principle by maximizing mutual information across augmented views and modalities, encouraging the model to extract globally consistent and high-information representations. By aligning perturbed graph views while preserving topological structure, MBGCCA effectively captures both global genomic characteristics and local contig relationships. Comprehensive evaluations using both synthetic and real-world datasets-including wastewater and soil microbiomes-demonstrate that MBGCCA consistently outperforms state-of-the-art binning methods, particularly in challenging scenarios marked by sparse data and high community complexity. These results highlight the value of entropy-aware, topology-preserving learning for advancing metagenomic genome reconstruction.

canonical correlation analysis↗

PubMed1999

The genetics of cancer--a 3D model.

Gene expression microarrays hold great promise for studies of human disease states. There are significant technical issues specific to utilizing clinical tissue samples which have yet to be rigorously addressed and completely overcome. Precise, quantitative measurement of gene expression profiles from specific cell populations is at hand, offering the scientific community the first comprehensive view of the in vivo molecular anatomy of normal cells and their diseased counterparts. Here, we propose a model for integrating-in three dimensions-expression data obtained using the microarray.

Databases, Factual↗

PubMed2002

Gene expression analysis in microdissected renal tissue. Current challenges and strategies.

The architecture and compartmentalization of the kidney has stimulated the development of an array of microtechniques to study the functional differences between the distinct nephron segments. With the vast amounts of genomic sequence data now available, the groundwork has been laid for a comprehensive characterization of the molecular pathways defining the differences in nephron function. With the development of sensitive gene expression techniques the tools for a comprehensive molecular analysis of specific renal microenvironments have been provided: Quantitative RT-PCR technologies now allow the analysis of specific mRNAs from as little as single microdissected renal cells. A more global view of gene expression regulation is a logical development from the application of large scale profiling techniques. In this review, we will discuss the power and pitfalls of these approaches, including their potential for the functional characterization of nephron heterogeneity and diagnostic application in renal disease.

Dissection↗

PubMed2006

Array2BIO: from microarray expression data to functional annotation of co-regulated genes.

BACKGROUND: There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. RESULTS: Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1) comparative analysis of signal versus control and (2) clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. CONCLUSION: We have developed Array2BIO - a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

Algorithms↗

PubMed2026

Functional convergence of regulatory regions provides vital insights into mammalian gliding adaptation.

Uncovering the key genetic basis of complex phenotypic convergence in distantly related species has been a long-standing focus in evolutionary biology and genetics, and the convergent evolution of gliding in mammals offers a valuable opportunity to address this question. Here, we investigated the genomic basis of convergent evolution of gliding in mammals by analyzing both protein-coding genes and conserved non-coding elements (CNEs). We first de novo assembled and annotated two chromosome-level genomes of gliding mammals, the red and white giant flying squirrel (Petaurista alborufus) and sugar gliders (Petaurus breviceps), and conducted comprehensive comparative genomic analysis combined with another gliding mammal, the Sunda flying lemur (Galeopterus variegatus) and 14 background species. We found that the convergent evolution of protein-coding genes provided relatively limited but functionally relevant evidence linked to gliding phenotypes. By contrast, we found that gliding-accelerated CNEs (GACNEs) cluster near functionally equivalent genes and frequently aggregate into highly diverged yet functionally convergent hotspot regions. Across the three gliding lineages, both GACNEs and hotspot GACNEs show strong convergence in their functional enrichment profiles, suggesting a broad genetic basis underlying the convergent gliding phenotype. Furthermore, we identified 72 core transcription factors underpinning the genetic basis of gliding convergence, including EMX2 and ZFHX3, potentially involved in multiple aspects of gliding adaptation. Our study highlights the role of functional convergence in regulatory regions as a key mechanism in mammalian gliding convergence, offering valuable insights and strategies for uncovering the genetic basis of complex convergent traits, thereby advancing understanding of the molecular basis of convergent traits.

Petaurista alborufus↗

PubMed2000

Cloning and characterization of the human phosphoinositide-specific phospholipase C-beta 1 (PLC beta 1).

Phospholipase C-beta (PLC beta) catalyses the generation of inositol 1,4,5-trisphosphate (IP(3)) and diacylglycerol (DAG) from phosphatidylinositol 4,5-bisphosphate (IP(2)), a key step in the intracellular transduction of a large number of extracellular signals, including neurotransmitters and hormones modulating diverse developmental and functional aspects of the mammalian central nervous system. Four mammalian isozymes are known (PLC beta 1-4), which differ in their function and expression patterns in vivo. We have characterized the human PLC beta 1 genomic locus (PLC beta 1), cloned two distinct PLC beta 1 cDNAs (PLC beta 1a and b) and analysed their respective expression patterns in a comprehensive panel of human tissues using quantitative TaqMan technology. The two cDNAs derive from transcripts generated through alternative splicing at their 3' end, and are predicted to encode for PLC beta 1 isoforms differing at their carboxy-terminus. The human PLC beta 1 isoforms are co-expressed in the same tissues with a distinctly CNS-specific profile of expression. Quantitative differences in PLC beta 1 isoform expression levels are observed in some tissues. Transient expression of epitope-tagged versions of the two isoforms followed by immunofluorescence revealed localization of the proteins to the cytoplasm and the inner side of the cell membrane. Finally, we characterized the structure of the PLC beta 1 locus and confirmed its mapping to human chromosome 20.

Amino Acid Sequence↗

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↗