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Identifying optimal reference genes for the normalization of microRNA expression in cucumber under viral stress.

Identifying optimal reference genes for the normalization of microRNA expression in cucumber under viral stress.
Author Information (click to view)

Liang C, Hao J, Meng Y, Luo L, Li J,


Liang C, Hao J, Meng Y, Luo L, Li J, (click to view)

Liang C, Hao J, Meng Y, Luo L, Li J,

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PloS one 2018 03 1513(3) e0194436 doi 10.1371/journal.pone.0194436
Abstract

Cucumber green mottle mosaic virus (CGMMV) is an economically important pathogen and causes significant reduction of both yield and quality of cucumber (Cucumis sativus). Currently, there were no satisfied strategies for controlling the disease. A better understanding of microRNA (miRNA) expression related to the regulation of plant-virus interactions and virus resistance would be of great assistance when developing control strategies for CGMMV. However, accurate expression analysis is highly dependent on robust and reliable reference gene used as an internal control for normalization of miRNA expression. Most commonly used reference genes involved in CGMMV-infected cucumber are not universally expressed depending on tissue types and stages of plant development. It is therefore crucial to identify suitable reference genes in investigating the role of miRNA expression. In this study, seven reference genes, including Actin, Tubulin, EF-1α, 18S rRNA, Ubiquitin, GAPDH and Cyclophilin, were evaluated for the most accurate results in analyses using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Gene expression was assayed on cucumber leaves, stems and roots that were collected at different days post inoculation with CGMMV. The expression data were analyzed using algorithms including delta-Ct, geNorm, NormFinder, and BestKeeper as well as the comparative tool RefFinder. The reference genes were subsequently validated using miR159. The results showed that EF-1α and GAPDH were the most reliable reference genes for normalizing miRNA expression in leaf, root and stem samples, while Ubiquitin and EF-1α were the most suitable combination overall.

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