Transcriptome Landscape of Human Folliculogenesis Reveals Oocyte and Granulosa Cell Interactions

Zhang, Yaoyao; Yan, Zhiqiang; Qin, Qingyuan; Nisenblat, Vicki; Chang, Hsun‐Ming; Yu, Yang; Wang, Tianren; Lu, Cuiling; Yang, Ming; Yang, Shuo; Ying, Yao; Zhu, Xiaohui; Xia, Xi; Dang, Yujiao; Ren, Yixuan; Yuan, Peng; Li, Rong; Liu, Ping; Guo, Hongyan; Han, Jiayi; He, Haojie; Zhang, Kun; Wang, Yiting; Wu, Yu-Hsueh; Li, Meng; Qiao, Jie; Yan, Jie; Yan, Liying

doi:10.1016/j.molcel.2018.10.029

Cited by 301 publications

(364 citation statements)

References 54 publications

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“…D, Relative quantification of the mean fluorescence intensity of AP2 in oocytes. Data are shown as the mean ± SEM, and different letters (a, b) represent a significant difference (P < .05) data in the existing databases (GSE107746, GSE36552), 42,43 the transcriptional expression levels of the marker genes in this study were shown to have dropped markedly in mature oocytes.…”

Section: Discussionmentioning

confidence: 62%

“…The lack of statistical significance might be attributed to transcriptional repression because as much as half of the mRNA undergoes degradation or deadenylation during meiotic maturation . By looking up the single‐cell RNA‐seq data in the existing databases (GSE107746, GSE36552), the transcriptional expression levels of the marker genes in this study were shown to have dropped markedly in mature oocytes.…”

Section: Discussionmentioning

confidence: 78%

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Melatonin promotes human oocyte maturation and early embryo development by enhancing clathrin‐mediated endocytosis

Liu

et al. 2019

Journal of Pineal Research

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Embryo development potential and reproductive clinical outcomes are all deeply rooted in oocyte maturation. Melatonin has been reported to promote oocyte maturation as an antioxidant in nonprimate species. Its antioxidative functions also help reduce plasma membrane rigidity, which facilitates clathrin‐mediated endocytosis (CME). Whether melatonin has effects on human oocyte maturation by regulating CME is worthy of exploration. In this study, we found that the optimal melatonin concentration for human oocyte maturation was 10−11 M, and the maturation rate of this group was 71.9% (P = .03). The metaphase II (MII) stage oocytes obtained by in vitro maturation with 10−11 M melatonin had a significantly higher fertilization rate (81.4% vs 61.4%, respectively, P = .017) and blastocyst rate (32.2% vs 15.8%, respectively, P = .039) compared to controls. During maturation, antioxidative melatonin greatly enhanced CME and decreased intra‐oocyte cAMP level. The former was evidenced by the increasing numbers of coated pits and vesicles, and the upregulated expression of two major CME markers—clathrin and adaptor protein‐2 (AP2). CME inhibitor dynasore increased intra‐oocyte cAMP level and blocked oocyte maturation, and melatonin could partly rescue oocyte maturation and significantly elevate the expression of clathrin and AP2 in the presence of dynasore. Therefore, we conclude that melatonin could promote human oocyte maturation and early embryo development through enhancing CME.

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Section: Discussionmentioning

confidence: 62%

Section: Discussionmentioning

confidence: 78%

Melatonin promotes human oocyte maturation and early embryo development by enhancing clathrin‐mediated endocytosis

Liu

et al. 2019

Journal of Pineal Research

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“…The canonical correlation analysis (CCA) of the expressed genes in all cell types at each developmental stage, is reported in Figures S1D and S1E. The top genes driving canonical correlation 1 (CC1) and 2 (CC2) include key genes such as Smc1b , Sycp1 , Syce2 and Sycp3 involved in germ cell meiosis (Bolcun-Filas, Costa et al, 2007, Garcia-Cruz, Brieno et al, 2010), Dazl and Xist driving germ cell transcription (Chen, Welling et al, 2014, Sado & Sakaguchi, 2013), and Sox4 and Wnt6 widely expressed in folliculogenesis (Harwood, Cross et al, 2008, Zhang, Yan et al, 2018, Zhao, Arsenault et al, 2017) (Figure S1F). A heatmap of the top ten marker genes for all six cell types is displayed in Figure S1G (Supplemental Table 1).…”

Section: Resultsmentioning

confidence: 99%

Transcriptome Landscape Reveals Underlying Mechanisms of Ovarian Cell Fate Differentiation and Primordial Follicle Assembly

Wang

Zhai

et al. 2019

Preprint

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Primordial follicle assembly in mammals occurs at perinatal ages and largely determines the ovarian reserve available to support the reproductive lifespan. The primordial follicle structure is generated by a complex network of interactions between oocytes and ovarian somatic cells that remain poorly understood. In the present research, using single-cell RNA sequencing performed over a time-series on mouse ovaries coupled with several bioinformatics analyses, the complete dynamic genetic programs of germ and granulosa cells from E16.5 to PD3 are reported for the first time. The time frame of analysis comprises the breakdown of germ cell cysts and the assembly of primordial follicles. Confirming the previously reported expression of genes by germ cells and granulosa cells, our analyses identified ten distinct gene clusters associated to germ cells and eight to granulosa cells. Consequently, several new genes expressed at significant levels at each investigated stage were assigned. Building single-cell pseudo temporal trajectories five states and two branch points of fate transition for the germ cells, and three states and one branch point for the granulosa cells were revealed. Moreover, GO and ClueGO term enrichment enabled identifying biological processes, molecular functions and cellular components more represented in germ cells and granulosa cells or common to both cell types at each specific stage. Finally, by SCENIC algorithm, we were able to establish a network of regulons that can be postulated as likely candidates for sustaining germ cell specific transcription programs throughout the investigated period.

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“…Presumably, identification of the decreased and stable RNA in this process could add understanding to the molecular regulation of oocyte development and quality control. Several RNA-seq readouts have been used to represent cross-stage differences such as FPKM (Fragments Per Kilobase Million) and RPM (Transcripts Per Kilobase Million) which are normalized by gene length and library size [10,14]. However, this library-size based quantification indicated as many genes with increased abundance as with decreased abundance which is difficult to explain biologically in the absence of transcription during oocyte maturation.…”

Section: External and Internal Normalization For Cross-stage Comparisonmentioning

confidence: 99%

“…Poly(A) RNA was isolated by oligo (dT) beads, reverse transcribed, amplified and purified [21]. Individual samples were tested for different amplification cycles (10,14,18), and different fractions of oocytes (1/8, 1/4, 1/2) were amplified for 18 cycles. After purification, cDNAs were evaluated by Bioanalyzer 2100 (Agilent).…”

Section: Rna-seq Library Preparation Of Intact and Fractions Of Mousementioning

confidence: 99%

Oocytes, a single cell and a tissue

Dean

2020

Preprint

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Development of single cell sequencing allows detailing the transcriptome of individual oocytes. Here, we compare different RNA-seq datasets from single and pooled mouse oocytes and show higher reproducibility using single oocyte RNA-seq. We further demonstrate that UMI (unique molecular identifiers) based and other deduplication methods are limited in their ability to improve the precision of these datasets. Finally, for normalization of sample differences in cross-stage comparisons, we propose that external spike-in molecules are comparable to using the endogenous genes stably expressed during oocyte maturation. The ability to normalize data among single cells provides insight into the heterogeneity of mouse oocytes. KeywordsMouse single oocyte RNA-seq; cross-stage normalization; oocyte heterogeneity (GV) stage. ConstGenes or ERCC normalization should become standards for cross-stage comparison in future single oocyte sequencing studies. Results and discussionSingle oocyte RNA-seq has high reproducibility To estimate the reproducibility of mouse oocyte RNA-seq, we obtained several published datasets from single or pooled oocytes at GV (geminal vesicle) and MII (meiosis II) stages which are the beginning and ending of oocyte maturation, respectively [6][7][8][9][10]. We processed all raw sequencing files in parallel. Due to the different distribution of transcripts from all the samples, we only took the coding reads for comparison ( Fig. 1a; Table S1). Interestingly, single oocyte RNA-seq (GSE141190, GSE96638, GSE44183) had higher correlation within the group than when compared to pooled oocytes of the same stage (Fig. 1b). In addition, MII stages exhibit higher deviation of poly(A) vs RiboMinus sequencing results, possibly due to the existence of dormant RNAs and hyper polyadenylated mRNAs being actively translated (Fig. 1b) [11]. By principal component clustering, single oocyte groups show higher similarity, though experiments/methods dominate the difference (Fig. 1c-d). Thus, we concluded that single oocyte sequencing can generate highly reproducible and consistent results. Deduplication improved the single oocyte RNA-seq limitedlySingle cell RNA-seq is susceptible to a range of biases, including gene capture, reverse transcription and cDNA amplification [12]. The incorporation of UMI (unique molecular identifiers) significantly improves single cell sequencing reproducibility by quantifying reads with more precision [3]. To test whether UMI also benefits single oocyte RNA-seq, we re-analyzed the GSE141190 RiboMinus RNA-seq results using UMI quantification ( Fig. 2a-b) which determines duplicates by both UMI and insert reads. The N8 UMI, capable of distinguishing up to 65,536 molecules, is sufficient to distinguish the ~20,000 different RNAs expressed in mouse oocytes [3,7]. On average, the number of reads of the Dedup (UMI-based) samples were 43%±15% of their Original (without deduplication) samples ( Fig. 2c-d; Table S2). After filtering out low-count genes, the linear regression of gene counts in Original a...

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Transcriptome Landscape of Human Folliculogenesis Reveals Oocyte and Granulosa Cell Interactions

Cited by 301 publications

References 54 publications

Melatonin promotes human oocyte maturation and early embryo development by enhancing clathrin‐mediated endocytosis

Melatonin promotes human oocyte maturation and early embryo development by enhancing clathrin‐mediated endocytosis

Transcriptome Landscape Reveals Underlying Mechanisms of Ovarian Cell Fate Differentiation and Primordial Follicle Assembly

Oocytes, a single cell and a tissue

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