Systems Biology Institute, Yale University, West Haven, CT, USA.
Department of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT, USA.
Commun Biol. 2021 Jun 30;4(1):822. doi: 10.1038/s42003-021-02320-w.
Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.
随机基因表达即使在生长于相同环境的同基因单细胞生物中也会导致表达结果的固有可变性。Drop-Seq 技术促进了对单个哺乳动物细胞的转录组学研究，并且基于单细胞转录计数对细胞特性和功能的描述产生了变革性的影响。然而，将这项技术应用于具有不同细胞大小和形态特征的生物一直具有挑战性。在这里，我们提出了 yeastDrop-Seq，这是一种优化的酵母平台，可特异性地量化单个酵母细胞中不同 mRNA 分子的数量。使用 yeastDrop-Seq，我们测量了寿命延长化合物霉酚酸及其上位因子鸟嘌呤对转录组的影响。每个处理条件对同基因酵母细胞都有独特的转录组特征，不同组之间的聚类清晰，分离明显。yeastDrop-Seq 平台促进了酵母细胞的转录组分析，可用于基础科学和生物技术应用。
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