Advanced maternal age alters expression of maternal effect genes that are essential for human oocyte quality

Zhang, Jingjing; Liu, Xiaoyan; Chen, Li; Zhang, Shouxin; Zhang, Xia; Hao, Cuifang; Miao, Yi‐Liang

doi:10.18632/aging.102864

Cited by 60 publications

(49 citation statements)

References 37 publications

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“…Other examples of genes related with ageing according to the GenAge database and that we also found in our set of IVM-MII oocytes were the topoisomerase gene TOP2B and the antioxidase PRDX1. Surprisingly, TOP2B has been previously found to decrease in human oocytes with age (Zhang et al, 2020), while we observed the opposite trend. A potential origin for such a discrepancy is that Zhang and colleagues studied only 3 in vivo MII oocytes for young (<30 years old) women and 3 for older (>40 years old) women.…”

Section: Maturation Stage Is the Main Differentiator Of Oocyte Transccontrasting

confidence: 89%

“…We have used Smart-seq2 (Picelli et al 2013) single-cell RNA-Sequencing technology instead of microarrays or bulk RNA-seq protocols commonly used in previous studies. Moreover, while comparable recent studies on the impact of oocyte age on the human oocyte transcriptome analyzed only a small number of oocytes (Hendrickson et al, 2017;Reyes et al, 2017;Zhang et al, 2020), our dataset includes a large number of single oocytes (n=72) from a large cohort of women of a wide-ranging age-span (n=37, 18-43 years), thereby increasing our statistical power in comparison to those previous studies. The design of our study allowed us to compare the transcriptomes of single GV and IVM-MII oocytes obtained from women of different ages.…”

Section: Discussionmentioning

confidence: 99%

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Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

Llonch

Barragán²,

Nieto

et al. 2020

Preprint

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Study questionTo which degree does maternal age affect the transcriptome of human oocytes at the germinal vesicle (GV) stage or at metaphase II after maturation in vitro (IVM-MII)?Summary answerWhile the oocytes’ transcriptome is predominantly determined by maturation stage, transcript levels of genes related to chromosome segregation, mitochondria and RNA processing are affected by age after in vitro maturation of denuded oocytes.What is known alreadyFemale fertility is inversely correlated with maternal age due to both a depletion of the oocyte pool and a reduction in oocyte developmental competence. Few studies have addressed the effect of maternal age on the human mature oocyte (MII) transcriptome, which is established during oocyte growth and maturation, and the pathways involved remain unclear. Here, we characterize and compare the transcriptomes of a large cohort of fully grown GV and IVM-MII oocytes from women of varying reproductive age.Study design, size, durationIn this prospective molecular study, 37 women were recruited from May 2018 to June 2019. The mean age was 28.8 years (SD=7.7, range 18-43). A total of 72 oocytes were included in the study at GV stage after ovarian stimulation, and analyzed as GV (n=40) and in vitro matured oocytes (IVM-MII; n=32).Participants/materials, setting, methodsDenuded oocytes were included either as GV at the time of ovum pick-up or as IVM-MII after in vitro maturation for 30 hours in G2™ medium, and processed for transcriptomic analysis by single-cell RNA-seq using the Smart-seq2 technology. Cluster and maturation stage marker analysis were performed using the Seurat R package. Genes with an average fold change greater than 2 and a p-value < 0.01 were considered maturation stage markers. A Pearson correlation test was used to identify genes whose expression levels changed progressively with age. Those genes presenting a correlation value (R) >= |0.3| and a p-value < 0.05 were considered significant.Main results and the role of chanceFirst, by exploration of the RNA-seq data using tSNE dimensionality reduction, we identified two clusters of cells reflecting the oocyte maturation stage (GV and IVM-MII) with 4,445 and 324 putative marker genes, respectively. Next we identified genes, for which RNA levels either progressively increased or decreased with age. This analysis was performed independently for GV and IVM-MII oocytes. Our results indicate that the transcriptome is more affected by age in IVM-MII oocytes (1,219 genes) than in GV oocytes (596 genes). In particular, we found that genes involved in chromosome segregation and RNA splicing significantly increase in transcript levels with age, while genes related to mitochondrial activity present lower transcript levels with age. Gene regulatory network analysis revealed potential upstream master regulator functions for genes whose transcript levels present positive (GPBP1, RLF, SON, TTF1) or negative (BNC1, THRB) correlation with age.Limitations, reasons for cautionIVM-MII oocytes used in this study were obtained after in vitro maturation of denuded GV oocytes, therefore, their transcriptome might not be fully representative of in vivo matured MII oocytes.The Smart-seq2 methodology used in this study detects polyadenylated transcripts only and we could therefore not assess non-polyadenylated transcripts.Wider implications of the findingsOur analysis suggests that advanced maternal age does not globally affect the oocyte transcriptome at GV or IVM-MII stages. Nonetheless, hundreds of genes displayed altered transcript levels with age, particularly in IVM-MII oocytes. Especially affected by age were genes related to chromosome segregation and mitochondrial function, pathways known to be involved in oocyte ageing. Our study thereby suggests that misregulation of chromosome segregation and mitochondrial pathways also at the RNA-level might contribute to the age-related quality decline in human oocytes.Study funding/competing interest(s)This study was funded by the AXA research fund, the European commission, intramural funding of Clinica EUGIN, the Spanish Ministry of Science, Innovation and Universities, the Catalan Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) and by contributions of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership and to the “Centro de Excelencia Severo Ochoa”.The authors have no conflict of interest to declare.

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Section: Maturation Stage Is the Main Differentiator Of Oocyte Transccontrasting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

Llonch

Barragán²,

Nieto

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Whole-transcriptome analysis using expression microarrays in both human and mouse metaphase-II (MII) oocytes has shown that typically a few hundred transcripts have altered abundance in the ageing oocyte and has identified genes involved in cell-cycle regulation, spindle assembly, oxidative stress and DNA damage as being frequently affected (Barragán et al, 2017;Grøndahl et al, 2010;Hamatani et al, 2004;Pan et al, 2008;Steuerwald et al, 2007). More recent studies using single-cell RNA-seq in human MII oocytes have found similar results, although the number of differentially abundant transcripts detected varied widely between studies (Barone et al, 2020;J.-J. Zhang et al, 2020).…”

Section: Introductionmentioning

confidence: 97%

Increased transcriptome variation and localised DNA methylation changes in oocytes from aged mice revealed by parallel single‐cell analysis

et al. 2020

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“…RNA-Seq data of bovine and human oocytes were retrieved from the sequence read archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra) ( Table 1). Both bovine and human RNA-Seq data were presented in NCBI with accession numbers GSE122738 [3] and GSE125300 [26] (https://www.ncbi.nlm.nih.gov/geo/).…”

Section: Materials and Methods Revised 21 Sample Datasetsmentioning

confidence: 99%

Novel classifier orthologs of bovine and human oocytes matured in different melatonin environments

et al. 2020

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It has been demonstrated that melatonin influences the developmental competence of both in vivo and in vitro matured oocytes. It modulates oocyte-specific gene expression patterns among mammalian species. Due to differences among study systems, the identification of the classifier orthologs-the homologous genes related among mammals that could universally categorize oocytes matured in environments with varied melatonin levels is still limitedly studied. To gain insight into such orthologs, cross-species transcription profiling meta-analysis of in vitro matured bovine oocytes and in vivo matured human oocytes in low and high melatonin environments was demonstrated in the current study. RNA-Seq data of bovine and human oocytes were retrieved from the Sequence Read Archive database and pre-processed. The used datasets of bovine oocytes obtained from culturing in the absence of melatonin and human oocytes from old patients were regarded as oocytes in the low melatonin environment (Low). Datasets from bovine oocytes cultured in 10-9 M melatonin and human oocytes from young patients were considered as oocytes in the high melatonin environment (High). Candidate orthologs differentially expressed between Low and High melatonin environments were selected by a linear model, and were further verified by Zero-inflated regression analysis. Support Vector Machine (SVM) was applied to determine the potentials of the verified orthologs as classifiers of melatonin environments. According to the acquired results, linear model analysis identified 284 candidate orthologs differentially expressed between Low and High melatonin environments. Among them, only 15 candidate orthologs were verified by Zero-inflated regression analysis (FDR ≤ 0.05). Utilization of the verified orthologs as classifiers in SVM resulted in the precise classification of oocyte learning datasets according to their melatonin environments (Misclassification rates < 0.18, area under curves > 0.9). In conclusion, the cross-species RNA-Seq meta-analysis to identify novel classifier orthologs of matured oocytes under different melatonin environments was successfully demonstrated in this study-delivering candidate orthologs for future studies at biological levels. Such verified orthologs might provide valuable evidence about melatonin sufficiency in target oocytes-by which, the decision on melatonin supplementation could be implied.

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Advanced maternal age alters expression of maternal effect genes that are essential for human oocyte quality

Cited by 60 publications

References 37 publications

Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

Increased transcriptome variation and localised DNA methylation changes in oocytes from aged mice revealed by parallel single‐cell analysis

Novel classifier orthologs of bovine and human oocytes matured in different melatonin environments

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