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

Obesity modulates cell-cell interactions during ovarian folliculogenesis

Obesity is known to affect female reproduction, as evidenced by obese patients suffering from subfertility and abnormal oogenesis. However, the underlying mechanisms by which obesity impairs folliculogenesis are poorly documented. Here, we performed comprehensive single-cell transcriptome analysis in both regular diet (RD) and obese mouse models to systematically uncover how obesity affects ovarian follicle cells and their interactions. We found an increased proportion of Inhbb highly expressed granulosa cells (GCs) among all the GC subpopulations in obese mice. Under obese conditions, excessive androgen secreted from endocrine theca cells (ETCs) may contribute to the imbalanced change of GC subtypes through ETCs-GCs interactions. This is alleviated by enzalutamide, an androgen receptor antagonist. We also identified and confirmed typical GC markers, such as Marcks and Prkar2b, for sensitive evaluation of female fertility in obesity. These data represent a resource for studying transcriptional networks and cell-cell interactions during folliculogenesis under physiological and pathological conditions.

Protocol for scChaRM-seq: Simultaneous profiling of gene expression, DNA methylation, and chromatin accessibility in single cells

Single-cell multi-omics sequencing technology can infer cell heterogeneity and reveal relationships across molecular layers. Combining single-cell RNA sequencing, DNA methylation, and chromatin accessibility allows a multimodal understanding of cell function and epigenetic regulation within individual cells. Here, we offer a protocol to perform scChaRM-seq (single-cell chromatin accessibility, RNA barcoding, and DNA methylation sequencing), which has been applied to study de novo DNA methylation and its relationship with transcription and chromatin accessibility in single human oocytes.

For complete details on the use and execution of this protocol, please refer to Yan et al. (2021).

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Protocol for sequencing library construction of scChaRM-seq

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Detailed description of single-cell RNA libraries procedures in scChaRM-seq

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Detailed TAILS procedures to construct single-cell DNA libraries in scChaRM-seq

Single-Cell Transcriptomics Analysis of Human Small Antral Follicles

Human ovarian folliculogenesis is a highly regulated and complex process. Characterization of follicular cell signatures during this dynamic process is important to understand follicle fate (to grow, become dominant, or undergo atresia). The transcriptional signature of human oocytes and granulosa cells (GCs) in early-growing and ovulatory follicles have been previously described; however, that of oocytes with surrounding GCs in small antral follicles have not been studied yet. Here, we have generated a unique dataset of single-cell transcriptomics (SmartSeq2) consisting of the oocyte with surrounding GCs from several individual (non-dominant) small antral follicles isolated from adult human ovaries. We have identified two main types of (healthy) follicles, with a distinct oocyte and GC signature. Using the CellphoneDB algorithm, we then investigated the bi-directional ligand–receptor interactions regarding the transforming growth factor-β (TGFβ)/bone morphogenetic protein (BMP), wingless-type (MMTV)-integration site (WNT), NOTCH, and receptor tyrosine kinases (RTK) signaling pathways between oocyte and GCs within each antral follicle type. Our work not only revealed the diversity of small antral follicles, but also contributes to fill the gap in mapping the molecular landscape of human folliculogenesis and oogenesis.

Tensor-Decomposition-Based Unsupervised Feature Extraction in Single-Cell Multiomics Data Analysis

Analysis of single-cell multiomics datasets is a novel topic and is considerably challenging because such datasets contain a large number of features with numerous missing values. In this study, we implemented a recently proposed tensor-decomposition (TD)-based unsupervised feature extraction (FE) technique to address this difficult problem. The technique can successfully integrate single-cell multiomics data composed of gene expression, DNA methylation, and accessibility. Although the last two have large dimensions, as many as ten million, containing only a few percentage of nonzero values, TD-based unsupervised FE can integrate three omics datasets without filling in missing values. Together with UMAP, which is used frequently when embedding single-cell measurements into two-dimensional space, TD-based unsupervised FE can produce two-dimensional embedding coincident with classification when integrating single-cell omics datasets. Genes selected based on TD-based unsupervised FE are also significantly related to reasonable biological roles.

DNA Methylation Dynamics in the Female Germline and Maternal-Effect Mutations That Disrupt Genomic Imprinting

Genomic imprinting is an epigenetic marking process that results in the monoallelic expression of a subset of genes. Many of these ‘imprinted’ genes in mice and humans are involved in embryonic and extraembryonic growth and development, and some have life-long impacts on metabolism. During mammalian development, the genome undergoes waves of (re)programming of DNA methylation and other epigenetic marks. Disturbances in these events can cause imprinting disorders and compromise development. Multi-locus imprinting disturbance (MLID) is a condition by which imprinting defects touch more than one locus. Although most cases with MLID present with clinical features characteristic of one imprinting disorder. Imprinting defects also occur in ‘molar’ pregnancies-which are characterized by highly compromised embryonic development-and in other forms of reproductive compromise presenting clinically as infertility or early pregnancy loss. Pathogenic variants in some of the genes encoding proteins of the subcortical maternal complex (SCMC), a multi-protein complex in the mammalian oocyte, are responsible for a rare subgroup of moles, biparental complete hydatidiform mole (BiCHM), and other adverse reproductive outcomes which have been associated with altered imprinting status of the oocyte, embryo and/or placenta. The finding that defects in a cytoplasmic protein complex could have severe impacts on genomic methylation at critical times in gamete or early embryo development has wider implications beyond these relatively rare disorders. It signifies a potential for adverse maternal physiology, nutrition, or assisted reproduction to cause epigenetic defects at imprinted or other genes. Here, we review key milestones in DNA methylation patterning in the female germline and the embryo focusing on humans. We provide an overview of recent findings regarding DNA methylation deficits causing BiCHM, MLID, and early embryonic arrest. We also summarize identified SCMC mutations with regard to early embryonic arrest, BiCHM, and MLID.