Oocytes, a single cell and a tissue

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. To confirm the ERCC normalization, we performed mouse single oocyte RNA-seq with different amplification cycles during library preparation and also different fractions of GV oocytes (1/2, 1/4, 1/8).单细胞测序技术的进步，使得精细化解析单个卵母细胞的转录组成为可能。本研究针对单个及混合小鼠卵母细胞的多套RNA测序（RNA-seq）数据集开展对比分析，结果表明采用单个卵母细胞进行RNA-seq可获得更高的实验重现性。本研究进一步证实，基于唯一分子标识符（unique molecular identifiers, UMI）的去重方法与其他去重手段，在提升此类数据集精度方面存在一定局限。最后，针对跨阶段比对中样本差异的标准化问题，本研究提出：外源spike-in分子可与卵母细胞成熟过程中稳定表达的内源基因等效，用作标准化参照。实现单细胞间数据标准化的能力，可为解析小鼠卵母细胞的异质性提供重要视角。为验证ERCC标准化方法的有效性，本研究开展了两组实验：分别在文库构建过程中设置不同扩增循环数，以及选取不同比例的GV期卵母细胞（1/2、1/4、1/8）进行小鼠单个卵母细胞RNA-seq。