Zhang Xiaorui, Yang Jiao, Yang Wenting, Cui Nan, Duan Tingting, Li Shan, Cao Jing, Bush Stephen J, Tong Guoqing
Department of Reproductive Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
BioBank, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Mol Hum Reprod. 2025 Jul 3;31(3). doi: 10.1093/molehr/gaaf038.
While advanced maternal age is associated with significant changes in oocyte gene expression, these are not global changes but limited to a fraction of the transcriptome. However, there is little consensus on the specific genes affected, and on the transcriptomic signatures of age-related declines in oocyte quality. To characterize the effects of age on the human MII oocyte transcriptome, here we take a two-part approach. We first generated single-oocyte Smart-seq2 datasets from 10 younger (21-29 years) and 10 older (37-43 years) donors, identifying genes differentially expressed between the two groups, then cross-referenced our results with those of 12 studies (9 human, 3 mouse) performing equivalent analyses using a variety of single-cell transcriptomic or microarray platforms. Technical differences notwithstanding, we found considerable discordance between the datasets, suggesting that age-related signatures of differential gene expression are not easily reproducible. Independent corroboration of age-associated changes in expression was limited to few genes, with the vast majority only supported by one of the 13 datasets, including our own. Nevertheless, we identified 40 genes whose expression significantly altered with age in multiple studies, highlighting common processes underlying ageing, including dysregulated proteostasis. As human Smart-seq2 oocyte libraries are challenging to procure and rare in public archives, we next implemented a meta-analytic method for their re-use, combining our 20 oocytes with 130 pre-existing libraries sourced from 12 different studies and representing a continuous age range of 18-43 years. We identified 25 genes whose expression level significantly correlated with age and corroborated 14 of these genes with RT-PCR, including the proteasomal subunits PSMA1 and PSMA2, both of which were downregulated in older oocytes. Overall, our findings are consistent with both pronounced inter-oocyte heterogeneity in transcription and with oocyte ageing being a multifactorial process to which bona fide transcriptomic changes may only play a restricted role, while proteomic changes play more pronounced roles.
虽然高龄产妇与卵母细胞基因表达的显著变化有关，但这些变化并非全局性的，而是仅限于转录组的一小部分。然而，对于受影响的具体基因以及与卵母细胞质量年龄相关下降的转录组特征，人们几乎没有达成共识。为了表征年龄对人类MII期卵母细胞转录组的影响，我们采用了两部分的方法。我们首先从10名年轻（21 - 29岁）和10名年长（37 - 43岁）的捐赠者中生成了单卵母细胞Smart-seq2数据集，确定两组之间差异表达的基因，然后将我们的结果与12项研究（9项人类研究，3项小鼠研究）的结果进行交叉参考，这些研究使用各种单细胞转录组或微阵列平台进行了等效分析。尽管存在技术差异，但我们发现数据集之间存在相当大的不一致，这表明与年龄相关的差异基因表达特征不容易重现。年龄相关表达变化的独立验证仅限于少数基因，绝大多数基因仅在13个数据集中的一个得到支持，包括我们自己的数据集。尽管如此，我们在多项研究中确定了40个基因，其表达随年龄显著改变，突出了衰老背后的共同过程，包括蛋白稳态失调。由于人类Smart-seq2卵母细胞文库获取具有挑战性且在公共档案中很少见，我们接下来实施了一种元分析方法以重新利用它们，将我们的20个卵母细胞与来自12项不同研究的130个预先存在的文库相结合，这些文库代表了18 - 43岁的连续年龄范围。我们确定了25个基因，其表达水平与年龄显著相关，并用RT-PCR验证了其中14个基因，包括蛋白酶体亚基PSMA1和PSMA2，这两个亚基在年长卵母细胞中均下调。总体而言，我们的发现既与卵母细胞转录中明显的细胞间异质性一致，也与卵母细胞衰老作为一个多因素过程一致，在这个过程中，真正的转录组变化可能只起有限的作用，而蛋白质组变化起更显著的作用。
