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

Yan, Rui; Gu, Chan; You, Di; Huang, Zhongying; Qian, Jingjing; Yang, Qixiang; Cheng, Xin; Zhang, Lin; Wang, Hongmei; Wang, Ping; Guo, Fan

doi:10.1016/j.stem.2021.04.012

Cited by 72 publications

(76 citation statements)

References 45 publications

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“…The timing of methylation establishment during oogenesis in humans has recently been described by Yan et al [34]. Single-cell multi-omics sequencing revealed that de novo methylation occurs in growing oocytes, similar to what has been described in the mouse.…”

Section: Primordial Germ Cells and Oocytessupporting

confidence: 56%

“…Therefore, it has been suggested that DNMT3B, or an oocyte-specific isoform of DNMT3B, may replace DNMT3L in human oocytes as a partner for DNMT3A [13,37]. In the Yan et al study, DNMT1 and DNMT3A transcripts were found in both growing and fully grown oocytes, while DNMT3B and UHRF1 were mostly expressed in mature oocytes [34].…”

Section: Primordial Germ Cells and Oocytesmentioning

confidence: 97%

“…Single-cell multi-omics sequencing revealed that de novo methylation occurs in growing oocytes, similar to what has been described in the mouse. De novo methylation correlates with chromatin accessibility and transcription [34]. Although the timing and pattern of de novo methylation during human oogenesis may be analogous to those in mice, the roles of DNMTs may differ.…”

Section: Primordial Germ Cells and Oocytesmentioning

confidence: 99%

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

Anvar

Chakchouk

Demond

et al. 2021

Genes

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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.

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Section: Primordial Germ Cells and Oocytessupporting

confidence: 56%

Section: Primordial Germ Cells and Oocytesmentioning

confidence: 97%

Section: Primordial Germ Cells and Oocytesmentioning

confidence: 99%

See 1 more Smart Citation

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

Anvar

Chakchouk

Demond

et al. 2021

Genes

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“…Second, our method can deal with massive datasets. For example, although integrated analysis of multiomics data was performed using multiomics factor analysis (MOFA) [21] in the original studies [4,7] of datasets 1 and 2, MOFA cannot accept x ijk in this study as inputs because MOFA does not implement sparse matrix architecture.…”

mentioning

confidence: 99%

“…To address this problem, especially for DNA methylation and accessibility, heavy pre-processing is usually required. For example, for dataset 1, statistical tests are applied and regions associated with significant P-values are selected[4], which reduces the number of features attributed to DNA methylation and accessibility. Because such a statistical test automatically filters out regions filled with missing values, the ratio of non-zero components is also reduced as a result.…”

mentioning

confidence: 99%

Tensor-decomposition–based unsupervised feature extraction in single-cell multiomics data analysis

Taguchi

Turki

2021

Preprint

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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 percentages of non-zero values, TD-based unsupervised FE can integrate three omics datasets without filling 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 were also significantly related to reasonable biological roles.

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The combination of DNA methylome and transcriptome revealed the intergenerational inheritance on the influence of advanced maternal age

Hua

Chen

Meng

et al. 2022

Clinical & Translational Med

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Background The number of women delivering at advanced maternal age (AMA; > = 35) continuously increases in developed and high‐income countries. Large cohort studies have associated AMA with increased risks of various pregnancy complications and adverse pregnancy outcomes, which raises great concerns about the adverse effect of AMA on the long‐term health of offspring. Specific acquired characteristics of parents can be passed on to descendants through certain molecular mechanisms, yet the underlying connection between AMA‐related alterations in parents and that in offspring remains largely uncharted. Methods We profiled the DNA methylomes of paired parental peripheral bloods and cord bloods from 20 nuclear families, including 10 AMA and 10 Young, and additional transcriptomes of 10 paired maternal peripheral bloods and cord bloods. Results We revealed that AMA induced aging‐like changes in DNA methylome and gene expression in both parents and offspring. The expression changes in several genes, such as SLC28A3, were highly relevant to the disorder in DNA methylation. In addition, AMA‐related differentially methylated regions (DMRs) identified in mother and offspring groups showed remarkable similarities in both genomic locations and biological functions, mainly involving neuron differentiation, metabolism, and histone modification pathways. AMA‐related differentially expressed genes (DEGs) shared by mother and offspring groups were highly enriched in the processes of immune cell activation and mitotic nuclear division. We further uncovered developmental‐dependent dynamics for the DNA methylation of intergenerationally correlated DMRs during pre‐implantation embryonic development, as well as diverse gene expression patterns during gametogenesis and early embryonic development for those common AMA‐related DEGs presenting intergenerational correlation, such as CD24. Moreover, some intergenerational DEGs, typified by HTRA3, also showed the same significant alterations in AMA MII oocyte or blastocyst. Conclusions Our results reveal potential intergenerational inheritance of both AMA‐related DNA methylome and transcriptome and provide new insights to understand health problems in AMA offspring.

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

Cited by 72 publications

References 45 publications

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

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

Tensor-decomposition–based unsupervised feature extraction in single-cell multiomics data analysis

The combination of DNA methylome and transcriptome revealed the intergenerational inheritance on the influence of advanced maternal age

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