Agroécologie, CNRS, INRAE, Institut Agro, Université de Bourgogne, Université Bourgogne Franche-Comté, Dijon, France.
Sci Rep. 2022 Nov 8;12(1):18988. doi: 10.1038/s41598-022-23783-9.
Microalgae have recently emerged as a key research topic, especially as biological models. Among them, the green alga Klebsormidium nitens, thanks to its particular adaptation to environmental stresses, represents an interesting photosynthetic eukaryote for studying the transition stages leading to the colonization of terrestrial life. The tolerance to different stresses is manifested by changes in gene expression, which can be monitored by quantifying the amounts of transcripts by RT-qPCR. The identification of optimal reference genes for experiment normalization was therefore necessary. In this study, using four statistical algorithms followed by the RankAggreg package, we determined the best reference gene pairs suitable for normalizing RT-qPCR data in K. nitens in response to three abiotic stresses: high salinity, PEG-induced dehydration and heat shock. Based on these reference genes, we were able to identify marker genes in response to the three abiotic stresses in K. nitens.
微藻最近成为一个重要的研究课题，特别是作为生物模型。其中，绿藻 Klebsormidium nitens 由于其对环境胁迫的特殊适应能力，是研究向陆地生命殖民过渡阶段的有趣光合真核生物。对不同胁迫的耐受性表现为基因表达的变化，可以通过 RT-qPCR 定量转录本的量来监测。因此，有必要确定用于实验归一化的最佳参考基因。在这项研究中，我们使用了四个统计算法，然后使用 RankAggreg 包，确定了最适合在 K. nitens 中归一化 RT-qPCR 数据的最佳参考基因对，以响应三种非生物胁迫：高盐、PEG 诱导的脱水和热休克。基于这些参考基因，我们能够鉴定出 K. nitens 对三种非生物胁迫的标记基因。
