Temporal transcriptomic landscape of postnatal mouse ovaries reveals dynamic gene signatures associated with ovarian aging

Abstract

The ovary is the most important organ for maintaining female reproductive health, but it fails before most other organs. Aging-associated alterations in gene expression patterns in mammalian ovaries remain largely unknown. In this study, the transcriptomic landscape of postnatal mouse ovaries over the reproductive lifespan was investigated using bulk RNA sequencing in C57BL/6 mice. Gene expression dynamics revealed that the lifespan of postnatal mouse ovaries comprised four sequential stages, during which 2517 genes were identified as differentially enriched. Notably, the DNA repair pathway was found to make a considerable and specific contribution to the process of ovarian aging. Temporal gene expression patterns were dissected to identify differences in gene expression trajectories over the lifespan. In addition to DNA repair, distinct biological functions (including hypoxia response, epigenetic modification, fertilization, mitochondrial function, etc.) were overrepresented in particular clusters. Association studies were further performed to explore the relationships between known genes responsible for ovarian function and differentially expressed genes identified in this work. We found that the causative genes of human premature ovarian insufficiency were specifically enriched in distinct gene clusters. Taken together, our findings reveal a comprehensive transcriptomic landscape of the mouse ovary over the lifespan, providing insights into the molecular mechanisms underlying mammalian ovarian aging and supporting future etiological studies of aging-associated ovarian disorders.

Estropausal gut microbiota transplant improves ovarian function in adult mice

“…Based on our GSEA results which indicated down-regulation of inflammatory pathways in the ovaries of the FMT-EF group, we next asked whether changes in the ovarian transcriptome upon FMT-EF could represent a more general trend of transcriptional rejuvenation. For this purpose, we analyzed two publicly available bulk RNA-seq datasets profiling ovaries from young (2-3-months) and aged/estropausal (12-months) wild-type female mice 60,61 to identify gene sets that are either up- or down-regulated with ovarian aging (Figure 3A). To evaluate whether the genes identified from publicly available RNA-seq datasets on ovarian aging (“UP with ovarian aging” and “DOWN with ovarian aging”) were significantly regulated in response to FMT-EF, we conducted GSEA using significant age-regulated genes as input gene sets.…”

“…To evaluate the correlation between ovarian aging and FMT gene expression profiles of the ovaries, we pre-processed and analyzed two publicly available ovarian aging datasets (2-3-month-old vs. 12-month-old female mice; BioProject dataset PRJNA100222 and GSA dataset CRA003645) 60,61 . For each dataset, reads were pre-processed and aligned to the mm39 genome reference using the same methods as for the FMT cohort ovarian RNA-seq dataset.…”

Cocktails of NSAIDs and 17α Ethinylestradiol at Environmentally Relevant Doses in Drinking Water Alter Puberty Onset in Mice Intergenerationally

“…In addition, the deregulation of GSTM2 (DNA damage), SFRP1 , and BMPR2 (involved in folliculogenesis) has been described in ovarian diseases [ 105 ] ( Supplementary Table S10 ). Among these genes, ZP1 , WT1 , and BMPR2 are premature ovarian insufficiency (POI) genes in humans [ 106 ]. Moreover, besides Bmpr2 , Fst , and Tcf21 are deregulated in an AMH-induced mouse model of polycystic ovarian syndrome (PCOS) [ 107 ] ( Supplementary Table S10 ).…”

Identification of lncRNA expression profiles associated with ovarian development and ageing process in mice

“…RNA samples were extracted from ovaries of C57BL/6 mice at different developmental stages in the previous work (Zhou et al 2021). Ovaries were collected at each time point, and three high-quality RNA samples were selected for sequencing.…”

“…Cluster-cluster correlation between lncRNA modules and mRNA clusters A cluster-cluster correlation was calculated to describe the similar expression pattern between groups of lncRNAs and mRNAs. The Pearson correlation coe cient was calculated by the eigengene of each WGCNA module and mean gene expression of previously de ned mRNA clusters (Zhou et al 2021) along with time. A heatmap with hierarchical clustering was applied to visualize the correlation coe cient.…”