College of Resources and Environment, Henan Institute of Science and Technology, Xinxiang, P.R. China.
The Museum of Chinese Gardens and Landscape Architecture, Beijing, P.R. China.
PLoS One. 2020 Feb 4;15(2):e0226668. doi: 10.1371/journal.pone.0226668. eCollection 2020.
To accurately evaluate expression levels of target genes, stable internal reference genes is required for normalization of quantitative real-time PCR (qRT-PCR) data. However, there have been no systematical investigation on the stability of reference genes used in the bedstraw weed, Galium aparine L. (BGA). In this study, the expression profiles of seven traditionally used reference genes, namely 18S, 28S, ACT, GAPDH, EF1α, RPL7 and TBP in BGA were assessed under both biotic (developmental time and tissue), and abiotic (temperature, regions and herbicide) conditions. Four analytical algorithms (geNorm, Normfinder, BestKeeper and the ΔCt method) were used to analyze the suitability of these genes as internal reference genes. RefFinder, a comprehensive analytical software, was used to rank the overall stability of the candidate genes. The optimal normalization internal control genes were ranked as: 28S and RPL7 were best for all the different experimental conditions (developmental stages, tissues, temperature, regions and herbicide treatment); 28S and RPL7 for developmental stages; TBP and GAPDH for different tissues; 28S and GAPDH were relatively stable for different temperature; 28S and TBP were suitable for herbicide treatment. A specific set of reference genes were recommended for each experimental condition in BGA.
为了准确评估靶基因的表达水平,定量实时 PCR(qRT-PCR)数据的归一化需要稳定的内参基因。然而,对于拉拉藤(Galium aparine L.,BGA)中使用的参考基因的稳定性,还没有进行系统的研究。在本研究中,评估了七种传统内参基因(18S、28S、ACT、GAPDH、EF1α、RPL7 和 TBP)在生物(发育时间和组织)和非生物(温度、地区和除草剂)条件下的表达谱。使用了四种分析算法(geNorm、Normfinder、BestKeeper 和 ΔCt 方法)来分析这些基因作为内参基因的适用性。RefFinder 是一种综合性分析软件,用于对候选基因的整体稳定性进行排名。最佳的归一化内参基因的排名为:28S 和 RPL7 最适合所有不同的实验条件(发育阶段、组织、温度、地区和除草剂处理);28S 和 RPL7 最适合发育阶段;TBP 和 GAPDH 最适合不同的组织;28S 和 GAPDH 对不同的温度相对稳定;28S 和 TBP 适合除草剂处理。为 BGA 中的每个实验条件推荐了一组特定的参考基因。