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棘阿米巴属 RT-qPCR 基因表达标准化参考基因的验证

Validation of reference genes for the normalization of RT-qPCR gene expression in Acanthamoeba spp.

机构信息

Institute of Specific Prophylaxis und Tropical Medicine, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria.

Institute of Parasitology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.

出版信息

Sci Rep. 2020 Jun 25;10(1):10362. doi: 10.1038/s41598-020-67035-0.

DOI:10.1038/s41598-020-67035-0
PMID:32587282
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7316857/
Abstract

Acanthamoebae are potentially pathogenic organisms, with a highly unique, yet still insufficiently investigated metabolism. Many open questions can be addressed by gene expression studies, however, for Acanthamoeba reliable standards have not yet been established. In this study, suitable reference genes (RGs) for RT-qPCR in Acanthamoeba were comprehensively evaluated, comparing different Acanthamoeba strains and employing four different algorithms (NormFinder, GeNorm, BestKeeper and RefFinder). Expression stability was assessed under various conditions and the potentials of the most promising RGs for accurate normalization of target genes were evaluated. Expression stability of RGs varied depending on conditions and employed algorithms, however, the genes for the 18S rRNA and the hypoxanthine phosphoribosyl transferase seem to be widely suitable RGs. Normalization with a combination of two carefully chosen RGs resulted in reliable expression data for target genes, while normalization with unsuitable RGs led to significant misinterpretation of expression profiles. Thus, a careful evaluation of RGs prior to expression studies is essential.

摘要

棘阿米巴是潜在的致病生物体,具有高度独特但研究仍不充分的代谢途径。通过基因表达研究可以解决许多悬而未决的问题,但对于棘阿米巴来说,尚未建立可靠的标准。在这项研究中,我们综合评估了用于棘阿米巴 RT-qPCR 的合适参考基因(RGs),比较了不同的棘阿米巴菌株,并采用了四种不同的算法(NormFinder、GeNorm、BestKeeper 和 RefFinder)。评估了在不同条件下 RG 的表达稳定性,并评估了最有前途的 RG 用于准确归一化靶基因的潜力。RGs 的表达稳定性取决于条件和所使用的算法,但 18S rRNA 和次黄嘌呤磷酸核糖转移酶的基因似乎是广泛适用的 RG。使用两个精心挑选的 RG 进行组合归一化可得到可靠的靶基因表达数据,而使用不合适的 RG 归一化会导致对表达谱的显著错误解释。因此,在进行表达研究之前,对 RG 进行仔细评估至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/7dfbe8707f49/41598_2020_67035_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/38d0ccaf2390/41598_2020_67035_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/acccf90d4471/41598_2020_67035_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/7c84a24dcf2d/41598_2020_67035_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/7dfbe8707f49/41598_2020_67035_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/38d0ccaf2390/41598_2020_67035_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/acccf90d4471/41598_2020_67035_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/7c84a24dcf2d/41598_2020_67035_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2da6/7316857/7dfbe8707f49/41598_2020_67035_Fig4_HTML.jpg

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