Decoding dynamic epigenetic landscapes in human oocytes using single-cell multi-omics sequencing

Exploring the untapped potential of single-cell and spatial omics in plant biology

Advances in single-cell and spatial omics technologies have revolutionised biology by revealing the diverse molecular states of individual cells and their spatial organization within tissues. The field of plant biology has widely adopted single-cell transcriptome and chromatin accessibility profiling and spatial transcriptomics, which extend traditional cell biology and genomics analyses and provide unique opportunities to reveal molecular and cellular dynamics of tissues. Using these technologies, comprehensive cell atlases have been generated in several model plant species, providing valuable platforms for discovery and tool development. Other emerging technologies related to single-cell and spatial omics, such as multiomics, lineage tracing, molecular recording, and high-content genetic and chemical perturbation phenotyping, offer immense potential for deepening our understanding of plant biology yet remain underutilised due to unique technical challenges and resource availability. Overcoming plant-specific barriers, such as cell wall complexity and limited antibody resources, alongside community-driven efforts in developing more complete reference atlases and computational tools, will accelerate progress. The synergy between technological innovation and targeted biological questions is poised to drive significant discoveries, advancing plant science. This review highlights the current applications of single-cell and spatial omics technologies in plant research and introduces emerging approaches with the potential to transform the field.

Recent advances in multimodal approaches for investigating placental development and related diseases

The placenta is a vital organ that supports fetal growth and pregnancy maintenance. Its dysfunction is associated with severe complications, including preeclampsia, fetal growth restriction, and placenta accreta spectrum disorders. Traditional approaches to placental research have provided valuable insights but are limited in capturing the complexity of this dynamic organ. In recent years, multimodal approaches-integrating advanced imaging, single-cell and spatial omics, and artificial intelligence (AI)-have enabled comprehensive analyses of placental development and disease. These strategies offer improved diagnostic accuracy, deeper molecular understanding, and real-time assessment of placental function. This review summarizes recent advances in multimodal placental research, highlighting key technologies such as ultrasound and MRI, single-cell transcriptomics, spatial profiling, and AI-based prediction models. Particular emphasis is placed on contributions from Chinese research teams, who have developed novel platforms, atlases, and clinically relevant tools. We also discuss ongoing challenges, including data standardization, interpretability of AI models, and ethical considerations. Looking ahead, the integration of multimodal data with AI and wearable technologies holds promise for precision obstetrics and individualized pregnancy care. Together, these innovations are advancing both scientific understanding and clinical management of placenta-related disorders.

CALB1 and RPL23 Are Essential for Maintaining Oocyte Quality and Function During Aging

With advancing age, significant changes occur in the female reproductive system, the most notable of which is the decline in oocyte quality, a key factor affecting female fertility. However, the mechanisms underlying oocyte aging remain poorly understood. In this study, we obtained oocytes from aged and young female mice and performed single-cell transcriptome sequencing, comparing our findings with existing proteomic analyses. Our analysis revealed that one of the primary characteristics of aging oocytes is the disruption of calcium ion homeostasis. Specifically, we identified two key genes involved in the oocyte aging process, Calb1 and Rpl23. Experimental validation demonstrated that knockdown of CALB1 in oocytes led to reduced calcium ion levels in the endoplasmic reticulum and mitochondria, resulting in mitochondrial dysfunction and meiotic defects. Further experiments suggested that RPL23 may function as a downstream gene of CALB1, and its knockdown caused mitochondrial dysfunction, excessive accumulation of reactive oxygen species (ROS), and spindle assembly defects. Notably, overexpression of these two genes in aging oocytes partially rescued the maternal age-related defective phenotypes, underscoring their crucial roles in oocyte aging. This study provides a comprehensive understanding of the specific mechanisms underlying mouse oocyte aging at single-cell resolution, supported by experimental validation, and offers new directions and potential targets for future research into age-related reproductive health issues.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Coordinated regulation of chromatin modifiers reflects organised epigenetic programming in mouse oocytes

BACKGROUND

Epigenetic modifications provide mechanisms for influencing gene expression, regulating cell differentiation and maintaining long-term memory of cellular identity and function. As oocytes transmit epigenetic information to offspring, correct establishment of the oocyte epigenome is important for normal offspring development. Oocyte epigenetic programming is highly complex, involving a range of epigenetic modifiers which interact to establish a specific distribution of DNA methylation and histone modifications. Disruptions to oocyte epigenetic programming can alter epigenetic memory and prevent normal developmental outcomes in the next generation. Therefore, it is critical that we further our understanding of the interdependent relationships between various epigenetic modifiers and modifications during oogenesis.

RESULTS

In this study we investigated the spatial and temporal distribution of a range of epigenetic modifiers and modifications in growing oocytes of primordial to antral follicles. We provide comprehensive immunofluorescent profiles of SETD2, H3K36me3, KDM6A, RBBP7, H3K27me3, DNMT3A and DNMT3L and compare these profiles to our previously published profiles of the Polycomb Repressive Complex 2 components EED, EZH2 and SUZ12 in growing oocytes of wildtype mice. In addition, we examined the nuclear levels and spatial distribution of these epigenetic modifiers and modifications in oocytes that lacked the essential Polycomb Repressive Complex 2 subunit, EED. Notably, histone remodelling in primary-secondary follicle oocytes preceded upregulation of DNMT3A and DNMT3L in secondary-antral follicle oocytes. Moreover, loss of EED and H3K27me3 led to significantly increased levels of the H3K36me3 methyltransferase SETD2 during early-mid oocyte growth, although the average levels of H3K36me3 were unchanged.

CONCLUSIONS

Overall, these data demonstrate that oocyte epigenetic programming is a highly ordered process, with histone remodelling in early growing oocytes preceding de novo DNA methylation in secondary-antral follicle oocytes. These results indicate that tight temporal and spatial regulation of histone modifiers and modifications is essential to ensure correct establishment of the unique epigenome present in fully grown oocytes. Further understanding of the temporal and spatial relationships between different epigenetic modifications and how they interact is essential for understanding how germline epigenetic programming affects inheritance and offspring development in mammals, including humans.

Epigenome dynamics in early mammalian embryogenesis

During early embryonic development in mammals, the totipotency of the zygote - which is reprogrammed from the differentiated gametes - transitions to pluripotency by the blastocyst stage, coincident with the first cell fate decision. These changes in cellular potency are accompanied by large-scale alterations in the nucleus, including major transcriptional, epigenetic and architectural remodelling, and the establishment of the DNA replication programme. Advances in low-input genomics and loss-of-function methodologies tailored to the pre-implantation embryo now enable these processes to be studied at an unprecedented level of molecular detail in vivo. Such studies have provided new insights into the genome-wide landscape of epigenetic reprogramming and chromatin dynamics during this fundamental period of pre-implantation development.

The adult ovary at single cell resolution: an expert review

The ovaries play a crucial role in both the endocrine health and fertility of adult women. The fundamental functional units of the ovaries, primordial follicles, form during fetal development and constitute the ovarian reserve. Ovaries age prematurely in comparison to other organs, with the quality of oocytes declining steeply prior to the entire reserve becoming depleted, usually around age 50. Despite the pivotal role of ovaries in women's overall health, surprisingly little is known about the mechanisms controlling follicle dormancy, growth activation, atresia, maturation, and oocyte quality. Understanding ovarian function on a cellular and molecular level is increasingly important for several reasons. First, the global trend of women delaying childbirth creates a growing population of patients wishing to conceive when the quality and quantity of their oocytes are already critically low. Second, conditions affecting the ovaries, such as polycystic ovary syndrome and endometriosis, are widespread, yet diagnosis and treatment still present challenges. Lastly, advancements in cancer therapies have increased the number of cancer survivors who contend with late complications affecting fertility and hormonal balance. Clearly, a better understanding of diseases, aging, and toxicity in ovaries is needed for the development of novel treatments, preventive therapies, and safer pharmaceuticals. Human ovaries are notoriously difficult to obtain for research due to their pivotal role in women's health, and the highly heterogeneous distribution of follicles within the tissue combined with monthly cyclical changes present further challenges. Single-cell profiling techniques are creating new opportunities, enabling the characterization of small amounts of tissue with unprecedented resolution. Here, we review the literature on single-cell characterization of adult, reproductive-age ovaries. The majority of the 46 identified studies have focused on oocytes discarded during assisted reproduction, with only a handful focusing on ovarian tissue. The overwhelming focus of the studies is on follicles and oocytes, although the somatic cell niche in the ovary undoubtedly plays an important role in endocrine function and follicle biology. Altogether, the studies reveal unexpected diversity and heterogeneity among ovarian somatic and germ cells, highlighting the prevailing knowledge gaps in basic ovarian biology. As the most common outcome for a follicle is atresia, it is possible that part of the cell diversity relates to the biology of follicles destined to degenerate. The absence of spatial coordinates in single-cell studies further complicates the interpretation of the roles and significance of the various reported cell clusters. Accomplishing a representative ovarian single-cell atlas will require merging these studies. However, direct comparisons are challenging due to nonuniform nomenclature, differing tissue sources, varying meta-data reporting, and lack of gold standards in technical approaches. Although these reports establish a single-cell draft of adult-fertile age human ovaries, more detailed metadata and better quality reporting will be essential for the development of a robust ovarian cell atlas in health and disease.

Untargeted metabolomics reveals homogeneity and heterogeneity between physiological and pathological ovarian aging

BACKGROUND

Ovarian aging is the main cause of reduced reproductive life span, yet its metabolic profiles remain poorly understood. This study aimed to reveal the metabolic homogeneity and heterogeneity between physiological and pathological ovarian aging.

METHODS

Seventy serum samples from physiological ovarian aging participants, pathological ovarian aging participants (including diminished ovarian reserve (DOR), subclinical premature ovarian insufficiency (scPOI) and premature ovarian insufficiency (POI)), as well as healthy participants were collected and analyzed by untargeted metabolomics.

RESULTS

Five homogeneous differential metabolites (neopterin, menaquinone, sphingomyelin (SM) (d14:1/24:2), SM (d14:0/21:1) and SM (d17:0/25:1)) were found in both physiological and pathological ovarian aging. While five distinct metabolites, including phosphoglyceride (PC) (17:0/18:2), PC (18:2e/17:2), SM (d22:1/14:1), SM (d14:1/20:1) and 4-hydroxyretinoic acid were specific to pathological ovarian aging. Functional annotation of differential metabolites suggested that folate biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis pathways, were mainly involved in the ovarian aging process. Meanwhile, dopaminergic synapses pathway was strongly associated with scPOI, vitamin digestion and absorption and retinol metabolism were associated with POI. Furthermore, testosterone sulfate, SM (d14:0/28:1), PC (18:0e/4:0) and 4-hydroxyretinoic acid, were identified as potential biomarkers for diagnosing physiological ovarian aging, DOR, scPOI, and POI, respectively. Additionally, SM (d14:1/24:2) strongly correlated with both physiological and pathological ovarian aging. 4-hydroxyretinoic acid was strongly correlated with pathological ovarian aging.

CONCLUSIONS

Metabolic homogeneity of physiological and pathological ovarian aging was related to disorders of lipid, folate, ubiquinone metabolism, while metabolic heterogeneity between them was related to disorders of lipid, vitamin and retinol metabolism.

CLINICAL TRIAL NUMBER

Not applicable.

Transcriptomic analysis and epigenetic regulators in human oocytes at different stages of oocyte meiotic maturation

Human oocytes are highly specialized cells with the capacity to store and regulate mRNAs during oocyte maturation, in preparation for post-fertilization steps. Here we performed single-oocyte transcriptomic analysis of human oocytes in three meitoic maturation stages - Germinal Vesicle (GV; n = 6), Metaphase I (MI; n = 6) and Metaphase II (MII; n = 7). Single-oocyte transcriptomic analysis revealed that the total number of expressed genes progressively decreased from GV to MII stages, with 9660 genes being transcribed in GV, 8734 in MI and 5889 in MII. The same tendency was observed for the number of uniquely expressed genes, with 1328 uniquely expressed genes in GV, 401 in MI and 72 in MII. GO analysis of the uniquely expressed genes showed distinct terms in GV oocytes such as transferase activity, organonitrogen compound metabolic process and ncRNA processing. Analysis of Differentially Expressed Genes (DEGs) between the three maturation stages revealed 1165 DEGs between GV and MII oocytes, with 635 being upregulated and 528 downregulated, 42 DEGs between GV and MI, with 38 being upregulated and 4 downregulated, and no significant changes in gene expression between MI and MII oocytes. Comprehensive analysis of epigenetic regulators showed high expression of several histone-modifying enzymes, namely deacetylases, acetylases, lysine demethylases and methyltransferases, and DNA methylation regulators, namely the maintenance methyltransferase DNMT1 and its co-regulators DPPA3 and UHRF1. Some of these epigenetic regulators were differentially expressed between maturation stages, namely SIRT3, SIRT6, KDM3AP1, KMT2E, DNMT1, DPPA3 and the MEST and RASGRF1 imprinted genes. Our study contributes with important information on the transcriptional landscape of human oocytes in different stages of meiotic maturation, providing important insights into candidate biomarkers of human oocyte quality.

Defining ortholog-specific UHRF1 inhibition by STELLA for cancer therapy

UHRF1 maintains DNA methylation by recruiting DNA methyltransferases to chromatin. In mouse, these dynamics are potently antagonized by a natural UHRF1 inhibitory protein STELLA, while the comparable effects of its human ortholog are insufficiently characterized, especially in cancer cells. Herein, we demonstrate that human STELLA (hSTELLA) is inadequate, while mouse STELLA (mSTELLA) is fully proficient in inhibiting the abnormal DNA methylation and oncogenic functions of UHRF1 in human cancer cells. Structural studies reveal a region of low sequence homology between these STELLA orthologs that allows mSTELLA but not hSTELLA to bind tightly and cooperatively to the essential histone-binding, linked tandem Tudor domain and plant homeodomain (TTD-PHD) of UHRF1, thus mediating ortholog-specific UHRF1 inhibition. For translating these findings to cancer therapy, we use a lipid nanoparticle (LNP)-mediated mRNA delivery approach in which the short mSTELLA, but not hSTELLA regions are required to reverse cancer-specific DNA hypermethylation and impair colorectal cancer tumorigenicity.

TET1 overexpression affects cell proliferation and apoptosis in aging ovaries

PURPOSE

Along with the progress of society, human life expectancy has been increasing, and late marriage and late childbearing are the current trend. Since reproductive aging affects fertility, ovarian aging in women has become a major reproductive health issue in the current society. During ovarian aging, DNA methylation levels may change. The ten-eleven translocation (TET) protein family proteins TET1, TET2, and TET3 are important DNA demethylation enzymes, and differential expression of TET1, TET2, and TET3 may affect the proliferation and apoptosis of aging ovarian cells. The aim of this study was to investigate the role of TET1 in the regulation of ovarian aging.

METHODS

The expression of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) was analyzed by immunofluorescence (IF) in young and aging ovaries of six 6-8-week-old female mice and six 6-8-month-old female mice. Then, the expression pattern of the TET protein family in young and aging ovaries of mice was investigated. To determine the impact of TET1 on ovarian development, the aging of IOSE-80, KGN, and SKOV-3 cells was induced with D-galactosidase (D-gal). Cells were then transfected using the TET1 overexpression vector or si-TET1. We assessed the proliferation and apoptosis of aging cells after transfection and analyzed the regulatory effect of TET1 expression on aging cells. Additionally, we verified the Tet1 expression in Tet1-KO mice.

RESULTS

The 5mC to 5hmC transition, oocyte maturation, and blastocyst rate were reduced in aging mice compared to young mice. In aging mice ovaries, the expression levels of Tet1, Tet2, and Tet3 were reduced significantly, with Tet1 being particularly pronounced. The overexpression of TET1 promoted proliferation and inhibited apoptosis in aging human ovarian cells. Furthermore, Tet1 expression was very low in Tet1-KO C57BL/6 J mice ovaries.

CONCLUSION

This study demonstrates that the expression levels of TET family proteins are low in aging ovaries, and the overexpression of TET1 can promote proliferation and inhibit apoptosis in aging ovarian cells.

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

Integrative Omics Reveals the Metabolic Patterns During Oocyte Growth

Well-controlled metabolism is associated with high-quality oocytes and optimal development of a healthy embryo. However, the metabolic framework that controls mammalian oocyte growth remains unknown. In the present study, we comprehensively depict the temporal metabolic dynamics of mouse oocytes during in vivo growth through the integrated analysis of metabolomics and proteomics. Many novel metabolic features are discovered during this process. Of note, glycolysis is enhanced, and oxidative phosphorylation capacity is reduced in the growing oocytes, presenting a Warburg-like metabolic program. For nucleotide biosynthesis, the salvage pathway is markedly activated during oocyte growth, whereas the de novo pathway is evidently suppressed. Fatty acid synthesis and channeling into phosphoinositides are specifically elevated in oocytes accompanying primordial follicle activation; nevertheless, fatty acid oxidation is reduced in these oocytes simultaneously. Our data establish the metabolic landscape during in vivo oocyte growth and serve as a broad resource for probing mammalian oocyte metabolism.

Decoding molecular features of bovine oocyte fate during antral follicle growth via single-cell multi-omics analysis†

Antral follicle size is a useful predictive marker of the competency of enclosed oocytes for yielding an embryo following in vitro maturation and fertilization. However, the molecular mechanisms underpinning oocyte developmental potential during bovine antral follicle growth are still unclear. Here, we used a modified single-cell multi-omics approach to analyze the transcriptome, DNA methylome, and chromatin accessibility in parallel for oocytes and cumulus cells collected from bovine antral follicles of different sizes. Transcriptome profiling identified three types of oocytes (small, medium, and large) that underwent different developmental trajectories, with large oocytes exhibiting the largest average follicle size and characteristics resembling metaphase-II oocytes. Differential expression analysis and real-time polymerase chain reaction assay showed that most replication-dependent histone genes were highly expressed in large oocytes. The joint analysis of multi-omics data revealed that the transcription of 20 differentially expressed genes in large oocytes was associated with both DNA methylation and chromatin accessibility. In addition, oocyte-cumulus interaction analysis showed that inflammation, DNA damage, and p53 signaling pathways were active in small oocytes, which had the smallest average follicle sizes. We further confirmed that p53 pathway inhibition in the in vitro maturation experiments using oocytes obtained from small antral follicles could improve the quality of oocytes and increased the blastocyte rate after in vitro fertilization and culture. Our work provides new insights into the intricate orchestration of bovine oocyte fate determination during antral folliculogenesis, which is instrumental for optimizing in vitro maturation techniques to optimize oocyte quality.

The evolution of ovarian somatic cells characterized by transcriptome and chromatin accessibility across rodents, monkeys, and humans

The ovary plays a crucial role in the reproductive system of female mammals by producing mature oocytes through folliculogenesis. Non-human model organisms are extensively utilized in research on human ovarian biology, thus necessitating the investigation of conservation and divergence in molecular mechanisms across species. In this study, we employed integrative single-cell analysis of transcriptome and chromatin accessibility to identify the evolutionary conservation and divergence patterns of ovaries among humans, monkeys, mice, rats, and rabbits. Our analyses revealed that theca cells exhibited the most significant changes during evolution based on scRNA-seq and scATAC-seq datasets. Furthermore, we discovered common cis-regulatory architectures in theca cells across species by conducting joint analyses of scRNA-seq and scATAC-seq datasets. These findings have potential applications in non-human biomedical and genetic research to validate molecular mechanisms found in human organisms. Additionally, our investigation into non-coding genomic regions identified intergenic highly transcribed regions (igHTRs) that may contribute to the evolution of species-specific phenotypic traits. Overall, our study provides valuable insights into understanding the molecular characteristics of adult ovaries while offering new perspectives for studying human ovarian physiology and diseases.

SMARTdb: An Integrated Database for Exploring Single-cell Multi-omics Data of Reproductive Medicine

Single-cell multi-omics sequencing has greatly accelerated reproductive research in recent years, and the data are continually growing. However, utilizing these data resources is challenging for wet-lab researchers. A comprehensive platform for exploring single-cell multi-omics data related to reproduction is urgently needed. Here, we introduce the single-cell multi-omics atlas of reproduction (SMARTdb), an integrative and user-friendly platform for exploring molecular dynamics of reproductive development, aging, and disease, which covers multi-omics, multi-species, and multi-stage data. We curated and analyzed single-cell transcriptomic and epigenomic data of over 2.0 million cells from 6 species across the entire lifespan. A series of powerful functionalities are provided, such as "Query gene expression", "DIY expression plot", "DNA methylation plot", and "Epigenome browser". With SMARTdb, we found that the male germ cell-specific expression pattern of RPL39L and RPL10L is conserved between human and other model animals. Moreover, DNA hypomethylation and open chromatin may collectively regulate the specific expression pattern of RPL39L in both male and female germ cells. In summary, SMARTdb is a powerful platform for convenient data mining and gaining novel insights into reproductive development, aging, and disease. SMARTdb is publicly available at https://smart-db.cn.

AMAR-seq: Automated Multimodal Sequencing of DNA Methylation, Chromatin Accessibility, and RNA Expression with Single-Cell Resolution

Parallel single-cell multimodal sequencing is the most intuitive and precise tool for cellular status research. In this study, we propose AMAR-seq to automate methylation, chromatin accessibility, and RNA expression coanalysis with single-cell precision. We validated the accuracy and robustness of AMAR-seq in comparison with standard single-omics methods. The high gene detection rate and genome coverage of AMAR-seq enabled us to establish a genome-wide gene expression regulatory atlas and triple-omics landscape with single base resolution and implement single-cell copy number variation analysis. Applying AMAR-seq to investigate the process of mouse embryonic stem cell differentiation, we revealed the dynamic coupling of the epigenome and transcriptome, which may contribute to unraveling the molecular mechanisms of early embryonic development. Collectively, we propose AMAR-seq for the in-depth and accurate establishment of single-cell multiomics regulatory patterns in a cost-effective, efficient, and automated manner, paving the way for insightful dissection of complex life processes.

Distinct dynamics of parental 5-hydroxymethylcytosine during human preimplantation development regulate early lineage gene expression

The conversion of DNA 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) by TET enzymes represents a significant epigenetic modification, yet its role in early human embryos remains largely unknown. Here we showed that the early human embryo inherited a significant amount of 5hmCs from an oocyte, which unexpectedly underwent de novo hydroxymethylation during its growth. Furthermore, the generation of 5hmC in the paternal genome after fertilization roughly followed the maternal pattern, which was linked to DNA methylation dynamics and regions of sustained methylation. The 5hmCs persisted until the eight-cell stage and exhibited high enrichment at OTX2 binding sites, whereas knockdown of OTX2 in human embryos compromised the expression of early lineage genes. Specifically, the depletion of 5hmC affected the activation of embryonic genes, which was further evaluated by ectopically expressing mouse Tet3 in human early embryos. These findings revealed distinct dynamics of 5hmC and unravelled its multifaceted functions in early human embryonic development.

Pramel15 facilitates zygotic nuclear DNMT1 degradation and DNA demethylation

In mammals, global passive demethylation contributes to epigenetic reprogramming during early embryonic development. At this stage, the majority of DNA-methyltransferase 1 (DNMT1) protein is excluded from nucleus, which is considered the primary cause. However, whether the remaining nuclear activity of DNMT1 is regulated by additional mechanisms is unclear. Here, we report that nuclear DNMT1 abundance is finetuned through proteasomal degradation in mouse zygotes. We identify a maternal factor, Pramel15, which targets DNMT1 for degradation via Cullin-RING E3 ligases. Loss of Pramel15 elevates DNMT1 levels in the zygote pronuclei, impairs zygotic DNA demethylation, and causes a stochastic gain of DNA methylation in early embryos. Thus, Pramel15 can modulate the residual level of DNMT1 in the nucleus during zygotic DNA replication, thereby ensuring efficient DNA methylation reprogramming in early embryos.

scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data

The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to avoid biases towards a specific modality and overcome sparsity. Batch effects obfuscating biological signals must also be taken into account. Here, we introduce a new single-cell multiomics integration model, Single-cell Multiomics Autoencoder Integration (scMaui) based on variational product-of-experts autoencoders and adversarial learning. scMaui calculates a joint representation of multiple marginal distributions based on a product-of-experts approach which is especially effective for missing values in the modalities. Furthermore, it overcomes limitations seen in previous VAE-based integration methods with regard to batch effect correction and restricted applicable assays. It handles multiple batch effects independently accepting both discrete and continuous values, as well as provides varied reconstruction loss functions to cover all possible assays and preprocessing pipelines. We demonstrate that scMaui achieves superior performance in many tasks compared to other methods. Further downstream analyses also demonstrate its potential in identifying relations between assays and discovering hidden subpopulations.

Maternal loss-of-function of Nlrp2 results in failure of epigenetic reprogramming in mouse oocytes

Background

NLRP2 belongs to the subcortical maternal complex (SCMC) of mammalian oocytes and preimplantation embryos. This multiprotein complex, encoded by maternal-effect genes, plays a pivotal role in the zygote-to-embryo transition, early embryogenesis, and epigenetic (re)programming. The maternal inactivation of genes encoding SCMC proteins has been linked to infertility and subfertility in mice and humans. However, the underlying molecular mechanisms for the diverse functions of the SCMC, particularly how this cytoplasmic structure influences DNA methylation, which is a nuclear process, are not fully understood.

Results

We undertook joint transcriptome and DNA methylome profiling of pre-ovulatory germinal-vesicle oocytes from Nlrp2-null, heterozygous (Het), and wild-type (WT) female mice. We identified numerous differentially expressed genes (DEGs) in Het and Nlrp2-null when compared to WT oocytes. The genes for several crucial factors involved in oocyte transcriptome modulation and epigenetic reprogramming, such as DNMT1, UHRF1, KDM1B and ZFP57 were overexpressed in Het and Nlrp2-null oocytes. Absence or reduction of Nlrp2, did not alter the distinctive global DNA methylation landscape of oocytes, including the bimodal pattern of the oocyte methylome. Additionally, although the methylation profile of germline differentially methylated regions (gDMRs) of imprinted genes was preserved in oocytes of Het and Nlrp2-null mice, we found altered methylation in oocytes of both genotypes at a small percentage of the oocyte-characteristic hyper- and hypomethylated domains. Through a tiling approach, we identified specific DNA methylation differences between the genotypes, with approximately 1.3% of examined tiles exhibiting differential methylation in Het and Nlrp2-null compared to WT oocytes.

Conclusions

Surprisingly, considering the well-known correlation between transcription and DNA methylation in developing oocytes, we observed no correlation between gene expression differences and gene-body DNA methylation differences in Nlrp2-null versus WT oocytes or Het versus WT oocytes. We therefore conclude that post-transcriptional changes in the stability of transcripts rather than altered transcription is primarily responsible for transcriptome differences in Nlrp2-null and Het oocytes.

The clock-like accumulation of germline and somatic mutations can arise from the interplay of DNA damage and repair

The rates at which mutations accumulate across human cell types vary. To identify causes of this variation, mutations are often decomposed into a combination of the single-base substitution (SBS) "signatures" observed in germline, soma, and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites thought to be caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these 2 signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including postmitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.

The landscape of transcriptional profiles in human oocytes with different chromatin configurations

With increasingly used assisted reproductive technology (ART), the acquisition of high-quality oocytes and early embryos has become the focus of much attention. Studies in mice have found that the transition of chromatin conformation from non-surrounded nucleolus (NSN) to surrounded nucleolus (SN) is essential for oocyte maturation and early embryo development, and similar chromatin transition also exists in human oocytes. In this study, we collected human NSN and SN oocytes and investigated their transcriptome. The analysis of differentially expressed genes showed that epigenetic functions, cyclin-dependent kinases and transposable elements may play important roles in chromatin transition during human oocyte maturation. Our findings provide new insights into the molecular mechanism of NSN-to-SN transition of human oocyte and obtained new clues for improvement of oocyte in vitro maturation technique.

GametesOmics: A Comprehensive Multi-omics Database for Exploring the Gametogenesis in Humans and Mice

Gametogenesis plays an important role in the reproduction and evolution of species. The transcriptomic and epigenetic alterations in this process can influence the reproductive capacity, fertilization, and embryonic development. The rapidly increasing single-cell studies have provided valuable multi-omics resources. However, data from different layers and sequencing platforms have not been uniformed and integrated, which greatly limits their use for exploring the molecular mechanisms that underlie oogenesis and spermatogenesis. Here, we develop GametesOmics, a comprehensive database that integrates the data of gene expression, DNA methylation, and chromatin accessibility during oogenesis and spermatogenesis in humans and mice. GametesOmics provides a user-friendly website and various tools, including Search and Advanced Search for querying the expression and epigenetic modification(s) of each gene; Tools with Differentially expressed gene (DEG) analysis for identifying DEGs, Correlation analysis for demonstrating the genetic and epigenetic changes, Visualization for displaying single-cell clusters and screening marker genes as well as master transcription factors (TFs), and MethylView for studying the genomic distribution of epigenetic modifications. GametesOmics also provides Genome Browser and Ortholog for tracking and comparing gene expression, DNA methylation, and chromatin accessibility between humans and mice. GametesOmics offers a comprehensive resource for biologists and clinicians to decipher the cell fate transition in germ cell development, and can be accessed at http://gametesomics.cn/.

Single-cell profiling reveals transcriptome dynamics during bovine oocyte growth

BACKGROUND

Mammalian follicle development is characterized by extensive changes in morphology, endocrine responsiveness, and function, providing the optimum environment for oocyte growth, development, and resumption of meiosis. In cattle, the first signs of transcription activation in the oocyte are observed in the secondary follicle, later than during mouse and human oogenesis. While many studies have generated extensive datasets characterizing gene expression in bovine oocytes, they are mostly limited to the analysis of fully grown and matured oocytes. The aim of the present study was to apply single-cell RNA sequencing to interrogate the transcriptome of the growing bovine oocyte from the secondary follicle stage through to the mid-antral follicle stage.

RESULTS

Single-cell RNA-seq libraries were generated from oocytes of known diameters (< 60 to > 120 μm), and datasets were binned into non-overlapping size groups for downstream analysis. Combining the results of weighted gene co-expression network and Trendy analyses, and differently expressed genes (DEGs) between size groups, we identified a decrease in oxidative phosphorylation and an increase in maternal -genes and transcription regulators across the bovine oocyte growth phase. In addition, around 5,000 genes did not change in expression, revealing a cohort of stable genes. An interesting switch in gene expression profile was noted in oocytes greater than 100 μm in diameter, when the expression of genes related to cytoplasmic activities was replaced by genes related to nuclear activities (e.g., chromosome segregation). The highest number of DEGs were detected in the comparison of oocytes 100-109 versus 110-119 μm in diameter, revealing a profound change in the molecular profile of oocytes at the end of their growth phase.

CONCLUSIONS

The current study provides a unique dataset of the key genes and pathways characteristic of each stage of oocyte development, contributing an important resource for a greater understanding of bovine oogenesis.

CRL4DCAF13 E3 ubiquitin ligase targets MeCP2 for degradation to prevent DNA hypermethylation and ensure normal transcription in growing oocytes

The DNA methylation is gradually acquired during oogenesis, a process sustained by successful follicle development. However, the functional roles of methyl-CpG-binding protein 2 (MeCP2), an epigenetic regulator displaying specifical binding with methylated DNA, remains unknown in oogenesis. In this study, we found MeCP2 protein was highly expressed in primordial and primary follicle, but was almost undetectable in secondary follicles. However, in aged ovary, MeCP2 protein is significantly increased in both oocyte and granulosa cells. Overexpression of MeCP2 in growing oocyte caused transcription dysregulation, DNA hypermethylation, and genome instability, ultimately leading to follicle growth arrest and apoptosis. MeCP2 is targeted by DCAF13, a substrate recognition adaptor of the Cullin 4-RING (CRL4) E3 ligase, and polyubiquitinated for degradation in both cells and oocytes. Dcaf13-null oocyte exhibited an accumulation of MeCP2 protein, and the partial rescue of follicle growth arrest induced by Dcaf13 deletion was observed following MeCP2 knockdown. The RNA-seq results revealed that large amounts of genes were regulated by the DCAF13-MeCP2 axis in growing oocytes. Our study demonstrated that CRL4DCAF13 E3 ubiquitin ligase targets MeCP2 for degradation to ensure normal DNA methylome and transcription in growing oocytes. Moreover, in aged ovarian follicles, deceased DCAF13 and DDB1 protein were observed, indicating a potential novel mechanism that regulates ovary aging.

Integration of single-cell transcriptome and chromatin accessibility and its application on tumor investigation

The advent of single-cell sequencing techniques has not only revolutionized the investigation of biological processes but also significantly contributed to unraveling cellular heterogeneity at unprecedented levels. Among the various methods, single-cell transcriptome sequencing stands out as the best established, and has been employed in exploring many physiological and pathological activities. The recently developed single-cell epigenetic sequencing techniques, especially chromatin accessibility sequencing, have further deepened our understanding of gene regulatory networks. In this review, we summarize the recent breakthroughs in single-cell transcriptome and chromatin accessibility sequencing methodologies. Additionally, we describe current bioinformatic strategies to integrate data obtained through these single-cell sequencing methods and highlight the application of this analysis strategy on a deeper understanding of tumorigenesis and tumor progression. Finally, we also discuss the challenges and anticipated developments in this field.

moSCminer: a cell subtype classification framework based on the attention neural network integrating the single-cell multi-omics dataset on the cloud

Single-cell omics sequencing has rapidly advanced, enabling the quantification of diverse omics profiles at a single-cell resolution. To facilitate comprehensive biological insights, such as cellular differentiation trajectories, precise annotation of cell subtypes is essential. Conventional methods involve clustering cells and manually assigning subtypes based on canonical markers, a labor-intensive and expert-dependent process. Hence, an automated computational prediction framework is crucial. While several classification frameworks for predicting cell subtypes from single-cell RNA sequencing datasets exist, these methods solely rely on single-omics data, offering insights at a single molecular level. They often miss inter-omic correlations and a holistic understanding of cellular processes. To address this, the integration of multi-omics datasets from individual cells is essential for accurate subtype annotation. This article introduces moSCminer, a novel framework for classifying cell subtypes that harnesses the power of single-cell multi-omics sequencing datasets through an attention-based neural network operating at the omics level. By integrating three distinct omics datasets-gene expression, DNA methylation, and DNA accessibility-while accounting for their biological relationships, moSCminer excels at learning the relative significance of each omics feature. It then transforms this knowledge into a novel representation for cell subtype classification. Comparative evaluations against standard machine learning-based classifiers demonstrate moSCminer's superior performance, consistently achieving the highest average performance on real datasets. The efficacy of multi-omics integration is further corroborated through an in-depth analysis of the omics-level attention module, which identifies potential markers for cell subtype annotation. To enhance accessibility and scalability, moSCminer is accessible as a user-friendly web-based platform seamlessly connected to a cloud system, publicly accessible at http://203.252.206.118:5568. Notably, this study marks the pioneering integration of three single-cell multi-omics datasets for cell subtype identification.

Progress in single-cell multimodal sequencing and multi-omics data integration

With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics levels. However, single-cell mono-omics results in fragmentation of information and could not provide complete cell states. In the past several years, a variety of single-cell multimodal omics technologies have been developed to jointly profile multiple molecular modalities, including genome, transcriptome, epigenome, and proteome, from the same single cell. With the availability of single-cell multimodal omics data, we can simultaneously investigate the effects of genomic mutation or epigenetic modification on transcription and translation, and reveal the potential mechanisms underlying disease pathogenesis. Driven by the massive single-cell omics data, the integration method of single-cell multi-omics data has rapidly developed. Integration of the massive multi-omics single-cell data in public databases in the future will make it possible to construct a cell atlas of multi-omics, enabling us to comprehensively understand cell state and gene regulation at single-cell resolution. In this review, we summarized the experimental methods for single-cell multimodal omics data and computational methods for multi-omics data integration. We also discussed the future development of this field.

DIRECT: Digital Microfluidics for Isolation-Free Shared Library Construction of Single-Cell DNA Methylome and Transcriptome

Simultaneous profiling of DNA methylation and gene expression within single cells is a powerful technology to dissect complex gene regulatory network of cells. However, existing methods are based on picking a single-cell in a tube and split single-cell lysate into two parts for transcriptome and methylome library construction, respectively, which is costly and cumbersome. Here, DIRECT is proposed, a digital microfluidics-based method for high-efficiency single-cell isolation and simultaneous analysis of the methylome and transcriptome in a single library construction. The accuracy of DIRECT is demonstrated in comparison with bulk and single-omics data, and the high CpG site coverage of DIRECT allows for precise analysis of copy number variation information, enabling expansion of single cell analysis from two- to three-omics. By applying DIRECT to monitor the dynamics of mouse embryonic stem cell differentiation, the relationship between DNA methylation and changes in gene expression during differentiation is revealed. DIRECT enables accurate, robust, and reproducible single-cell DNA methylation and gene expression co-analysis in a more cost-effective, simpler library preparation and automated manner, broadening the application scenarios of single-cell multi-omics analysis and revealing a more comprehensive and fine-grained map of cellular regulatory landscapes.

Auto-suppression of Tet dioxygenases protects the mouse oocyte genome from oxidative demethylation

DNA cytosine methylation plays a vital role in repressing retrotransposons, and such derepression is linked with developmental failure, tumorigenesis and aging. DNA methylation patterns are formed by precisely regulated actions of DNA methylation writers (DNA methyltransferases) and erasers (TET, ten-eleven translocation dioxygenases). However, the mechanisms underlying target-specific oxidation of 5mC by TET dioxygenases remain largely unexplored. Here we show that a large low-complexity domain (LCD), located in the catalytic part of Tet enzymes, negatively regulates the dioxygenase activity. Recombinant Tet3 lacking LCD is shown to be hyperactive in converting 5mC into oxidized species in vitro. Endogenous expression of the hyperactive Tet3 mutant in mouse oocytes results in genome-wide 5mC oxidation. Notably, the occurrence of aberrant 5mC oxidation correlates with a consequent loss of the repressive histone mark H3K9me3 at ERVK retrotransposons. The erosion of both 5mC and H3K9me3 causes ERVK derepression along with upregulation of their neighboring genes, potentially leading to the impairment of oocyte development. These findings suggest that Tet dioxygenases use an intrinsic auto-regulatory mechanism to tightly regulate their enzymatic activity, thus achieving spatiotemporal specificity of methylome reprogramming, and highlight the importance of methylome integrity for development.

Epigenetic aging of mammalian gametes

The process of aging refers to physiological changes that occur to an organism as time progresses and involves changes to DNA, proteins, metabolism, cells, and organs. Like the rest of the cells in the body, gametes age, and it is well established that there is a decline in reproductive capabilities in females and males with aging. One of the major pathways known to be involved in aging is epigenetic changes. The epigenome is the multitude of chemical modifications performed on DNA and chromatin that affect the ability of chromatin to be transcribed. In this review, we explore the effects of aging on female and male gametes with a focus on the epigenetic changes that occur in gametes throughout aging. Quality decline in oocytes occurs at a relatively early age. Epigenetic changes constitute an important part of oocyte aging. DNA methylation is reduced with age, along with reduced expression of DNA methyltransferases (DNMTs). Histone deacetylases (HDAC) expression is also reduced, and a loss of heterochromatin marks occurs with age. As a consequence of heterochromatin loss, retrotransposon expression is elevated, and aged oocytes suffer from DNA damage. In sperm, aging affects sperm number, motility and fecundity, and epigenetic changes may constitute a part of this process. 5 methyl-cytosine (5mC) methylation is elevated in sperm from aged men, but methylation on Long interspersed nuclear elements (LINE) elements is reduced. Di and trimethylation of histone 3 lysine 9 (H3K9me2/3) is reduced in sperm from aged men and trimethylation of histone 3 lysine 27 (H3K27me3) is elevated. The protamine makeup of sperm from aged men is also changed, with reduced protamine expression and a misbalanced ratio between protamine proteins protamine P1 and protamine P2. The study of epigenetic reproductive aging is recently gaining interest. The current status of the field suggests that many aspects of gamete epigenetic aging are still open for investigation. The clinical applications of these investigations have far-reaching consequences for fertility and sociological human behavior.

The oocyte: the key player in the success of assisted reproduction technologies

The ovulation of a mature oocyte at metaphase II of meiosis, with optimal potential to undergo fertilisation by a sperm cell, complete meiosis and sustain the switch to mitotic division, and support early embryo development, involves a protracted and disrupted/delayed series of processes. Many of these are targeted for exploitation in vivo , or recapitulation in vitro , by the livestock industry. Reproductive technologies, including AI, multiple ovulation embryo transfer, ovum pick-up, in vitro embryo production, and oestrus and ovulation synchronisation, offer practitioners and producers the opportunity to produce offspring from genetically valuable dams in much greater numbers than they would normally have in their lifetime, while in vitro oocyte and follicle culture are important platforms for researchers to interrogate the physiological mechanisms driving fertility. The majority of these technologies target the ovarian follicle and the oocyte within; thus, the quality and capability of the recovered oocyte determine the success of the reproductive intervention. Molecular and microscopical technologies have grown exponentially, providing powerful platforms to interrogate the molecular mechanisms which are integral to or affected by ART. The development of the bovine oocyte from its differentiation in the ovary to ovulation is described in the light of its relevance to key aspects of individual interventions, while highlighting the historical timeline.

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.

Dissecting mammalian reproduction with spatial transcriptomics

BACKGROUND

Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction.

OBJECTIVE AND RATIONALE

We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come.

SEARCH METHODS

The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed.

OUTCOMES

First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations.

WIDER IMPLICATIONS

Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.

Agrocybe cylindracea fucoglucogalactan induced lysosome-mediated apoptosis of colorectal cancer cell through H3K27ac-regulated cathepsin D

Inducing lysosomal dysfunction is emerging as a promising means for cancer therapy. Agrocybe cylindracea fucoglucogalactan (ACP) is a bioactive ingredient with anti-tumor activity, while its mechanism remains obscure. Herein, we found that ACP visibly inhibited the proliferation of colorectal cancer cells, and the IC50 value on HCT-116 cells (HT29 cells) was 490 μg/mL (786.4 μg/mL) at 24 h. RNA-seq showed that ACP regulated mitochondria, lysosome and apoptosis-related pathways. Further experiments proved that ACP indeed promoted apoptosis and lysosomal dysfunction of HCT-116 cells. Moreover, ChIP-seq revealed that ACP increased histone-H3-lysine-27 acetylation (H3K27ac) on CTSD (cathepsin D) promoter in HCT-116 cells, thus facilitating the binding of transcription factor EB (TFEB), and resulted in ascension of CTSD expression. Additionally, ACP triggered mitochondrial-mediated apoptosis by decreasing mitochondrial membrane potential and increasing pro-apoptotic protein levels. Notably, Pepstatin A (CTSD inhibitor) availably alleviated ACP-induced apoptosis. Taken together, our results indicated that ACP induced lysosome-mitochondria mediated apoptosis via H3K27ac-regulated CTSD in HCT-116 cells. This study indicates that ACP has anti-cancer potential in the treatment of colorectal cancer.

Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity

BACKGROUND

Previous studies have traditionally attributed the initiation of cancer cells to genetic mutations, considering them as the fundamental drivers of carcinogenesis. However, recent research has shed light on the crucial role of epigenomic alterations in various cell types present within the tumor microenvironment, suggesting their potential contribution to tumor formation and progression. Despite these significant findings, the progress in understanding the epigenetic mechanisms regulating tumor heterogeneity has been impeded over the past few years due to the lack of appropriate technical tools and methodologies.

RESULTS

The emergence of single-cell sequencing has enhanced our understanding of the epigenetic mechanisms governing tumor heterogeneity by revealing the distinct epigenetic layers of individual cells (chromatin accessibility, DNA/RNA methylation, histone modifications, nucleosome localization) and the diverse omics (transcriptomics, genomics, multi-omics) at the single-cell level. These technologies provide us with new insights into the molecular basis of intratumoral heterogeneity and help uncover key molecular events and driving mechanisms in tumor development.

CONCLUSION

This paper provides a comprehensive review of the emerging analytical and experimental approaches of single-cell sequencing in various omics, focusing specifically on epigenomics. These approaches have the potential to capture and integrate multiple dimensions of individual cancer cells, thereby revealing tumor heterogeneity and epigenetic features. Additionally, this paper outlines the future trends of these technologies and their current technical limitations.

Single-cell multi-omics sequencing of human spermatogenesis reveals a DNA demethylation event associated with male meiotic recombination

Human spermatogenesis is a highly ordered process; however, the roles of DNA methylation and chromatin accessibility in this process remain largely unknown. Here by simultaneously investigating the chromatin accessibility, DNA methylome and transcriptome landscapes using the modified single-cell chromatin overall omic-scale landscape sequencing approach, we revealed that the transcriptional changes throughout human spermatogenesis were correlated with chromatin accessibility changes. In particular, we identified a set of transcription factors and cis elements with potential functions. A round of DNA demethylation was uncovered upon meiosis initiation in human spermatogenesis, which was associated with male meiotic recombination and conserved between human and mouse. Aberrant DNA hypermethylation could be detected in leptotene spermatocytes of certain nonobstructive azoospermia patients. Functionally, the intervention of DNA demethylation affected male meiotic recombination and fertility. Our work provides multi-omics landscapes of human spermatogenesis at single-cell resolution and offers insights into the association between DNA demethylation and male meiotic recombination.

Omics Views of Mechanisms for Cell Fate Determination in Early Mammalian Development

During mammalian preimplantation development, a totipotent zygote undergoes several cell cleavages and two rounds of cell fate determination, ultimately forming a mature blastocyst. Along with compaction, the establishment of apicobasal cell polarity breaks the symmetry of an embryo and guides subsequent cell fate choice. Although the lineage segregation of the inner cell mass (ICM) and trophectoderm (TE) is the first symbol of cell differentiation, several molecules have been shown to bias the early cell fate through their inter-cellular variations at much earlier stages, including the 2- and 4-cell stages. The underlying mechanisms of early cell fate determination have long been an important research topic. In this review, we summarize the molecular events that occur during early embryogenesis, as well as the current understanding of their regulatory roles in cell fate decisions. Moreover, as powerful tools for early embryogenesis research, single-cell omics techniques have been applied to both mouse and human preimplantation embryos and have contributed to the discovery of cell fate regulators. Here, we summarize their applications in the research of preimplantation embryos, and provide new insights and perspectives on cell fate regulation.

Decoding Human Biology and Disease Using Single-cell Omics Technologies

Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.

The role of DNA methylation in personalized medicine for immune-related diseases

Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed.

Disentangling sources of clock-like mutations in germline and soma

The rates of mutations vary across cell types. To identify causes of this variation, mutations are often decomposed into a combination of the single base substitution (SBS) "signatures" observed in germline, soma and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these two signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly-dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including post-mitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.

Loss of the Maternal Effect Gene Nlrp2 Alters the Transcriptome of Ovulated Mouse Oocytes and Impacts Expression of Histone Demethylase KDM1B

The subcortical maternal complex (SCMC) is a multiprotein complex in oocytes and preimplantation embryos that is encoded by maternal effect genes. The SCMC is essential for zygote-to-embryo transition, early embryogenesis, and critical zygotic cellular processes, including spindle positioning and symmetric division. Maternal deletion of Nlrp2, which encodes an SCMC protein, results in increased early embryonic loss and abnormal DNA methylation in embryos. We performed RNA sequencing on pools of meiosis II (MII) oocytes from wild-type and Nlrp2-null female mice that were isolated from cumulus-oocyte complexes (COCs) after ovarian stimulation. Using a mouse reference genome-based analysis, we found 231 differentially expressed genes (DEGs) in Nlrp2-null compared to WT oocytes (123 up- and 108 downregulated; adjusted p < 0.05). The upregulated genes include Kdm1b, a H3K4 histone demethylase required during oocyte development for the establishment of DNA methylation marks at CpG islands, including those at imprinted genes. The identified DEGs are enriched for processes involved in neurogenesis, gland morphogenesis, and protein metabolism and for post-translationally methylated proteins. When we compared our RNA sequencing data to an oocyte-specific reference transcriptome that contains many previously unannotated transcripts, we found 228 DEGs, including genes not identified with the first analysis. Interestingly, 68% and 56% of DEGs from the first and second analyses, respectively, overlap with oocyte-specific hyper- and hypomethylated domains. This study shows that there are substantial changes in the transcriptome of mouse MII oocytes from female mice with loss of function of Nlrp2, a maternal effect gene that encodes a member of the SCMC.

Probabilistic tensor decomposition extracts better latent embeddings from single-cell multiomic data

Single-cell sequencing technology enables the simultaneous capture of multiomic data from multiple cells. The captured data can be represented by tensors, i.e. the higher-rank matrices. However, the existing analysis tools often take the data as a collection of two-order matrices, renouncing the correspondences among the features. Consequently, we propose a probabilistic tensor decomposition framework, SCOIT, to extract embeddings from single-cell multiomic data. SCOIT incorporates various distributions, including Gaussian, Poisson, and negative binomial distributions, to deal with sparse, noisy, and heterogeneous single-cell data. Our framework can decompose a multiomic tensor into a cell embedding matrix, a gene embedding matrix, and an omic embedding matrix, allowing for various downstream analyses. We applied SCOIT to eight single-cell multiomic datasets from different sequencing protocols. With cell embeddings, SCOIT achieves superior performance for cell clustering compared to nine state-of-the-art tools under various metrics, demonstrating its ability to dissect cellular heterogeneity. With the gene embeddings, SCOIT enables cross-omics gene expression analysis and integrative gene regulatory network study. Furthermore, the embeddings allow cross-omics imputation simultaneously, outperforming current imputation methods with the Pearson correlation coefficient increased by 3.38-39.26%; moreover, SCOIT accommodates the scenario that subsets of the cells are with merely one omic profile available.

Methods and applications for single-cell and spatial multi-omics

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.

Neurulation of the cynomolgus monkey embryo achieved from 3D blastocyst culture

Neural tube (NT) defects arise from abnormal neurulation and result in the most common birth defects worldwide. Yet, mechanisms of primate neurulation remain largely unknown due to prohibitions on human embryo research and limitations of available model systems. Here, we establish a three-dimensional (3D) prolonged in vitro culture (pIVC) system supporting cynomolgus monkey embryo development from 7 to 25 days post-fertilization. Through single-cell multi-omics analyses, we demonstrate that pIVC embryos form three germ layers, including primordial germ cells, and establish proper DNA methylation and chromatin accessibility through advanced gastrulation stages. In addition, pIVC embryo immunofluorescence confirms neural crest formation, NT closure, and neural progenitor regionalization. Finally, we demonstrate that the transcriptional profiles and morphogenetics of pIVC embryos resemble key features of similarly staged in vivo cynomolgus and human embryos. This work therefore describes a system to study non-human primate embryogenesis through advanced gastrulation and early neurulation.

The impact of epigenetic landscape on ovarian cells in infertile older women undergoing IVF procedures

The constant decline in fertility and older reproductive age is the major cause of low clinical pregnancy rates in industrialised countries. Epigenetic mechanisms impact on proper embryonic development in women undergoing in vitro fertilisation (IVF) protocols. Here, we describe the main epigenetic modifications that may influence female reproduction and could affect IVF success.

A novel DNA methylation-related gene signature for the prediction of overall survival and immune characteristics of ovarian cancer patients

BACKGROUND

Ovarian cancer (OC) is one of the most life-threatening cancers affecting women worldwide. Recent studies have shown that the DNA methylation state can be used in the diagnosis, treatment and prognosis prediction of diseases. Meanwhile, it has been reported that the DNA methylation state can affect the function of immune cells. However, whether DNA methylation-related genes can be used for prognosis and immune response prediction in OC remains unclear.

METHODS

In this study, DNA methylation-related genes in OC were identified by an integrated analysis of DNA methylation and transcriptome data. Prognostic values of the DNA methylation-related genes were investigated through least absolute shrinkage and selection operator (LASSO) and Cox progression analyses. Immune characteristics were investigated by CIBERSORT, correlation analysis and weighted gene co-expression network analysis (WGCNA).

RESULTS

Twelve prognostic genes (CA2, CD3G, HABP2, KCTD14, PI3, SERPINB5, SLAMF7, SLC9A2, STC2, TBP, TREML2 and TRIM27) were identified and a risk score signature and a nomogram based on prognostic genes and clinicopathological features were constructed for the survival prediction of OC patients in the training and two validation cohorts. Subsequently, the differences in the immune landscape between the high- and low-risk score groups were systematically investigated.

CONCLUSIONS

Taken together, our study explored a novel efficient risk score signature and a nomogram for the survival prediction of OC patients. In addition, the differences of the immune characteristics between the two risk groups were clarified preliminarily, which will guide the further exploration of synergistic targets to improve the efficacy of immunotherapy in OC patients.

Tn5 DNA Transposase in Multi-Omics Research

Tn5 transposase use in biotechnology has substantially advanced the sequencing applications of genome-wide analysis of cells. This is mainly due to the ability of Tn5 transposase to efficiently transpose DNA essentially randomly into any target DNA without the aid of other factors. This concise review is focused on the advances in Tn5 applications in multi-omics technologies, genome-wide profiling, and Tn5 hybrid molecule creation. The possibilities of other transposase uses are also discussed.