Selection and Validation of Reference Genes for RT-qPCR Analysis of Gene Expression in Nicotiana benthamiana upon Single Infections by 11 Positive-Sense Single-Stranded RNA Viruses from Four Genera.
Ge ZhangZhuo ZhangQionglian WanHuijie ZhouMengting JiaoHongying ZhengYuwen LuShaofei RaoGuanwei WuJian-Ping ChenFei YanJiejun PengJian WuPublished in: Plants (Basel, Switzerland) (2023)
Quantitative real-time PCR (RT-qPCR) is a widely used method for studying alterations in gene expression upon infections caused by diverse pathogens such as viruses. Positive-sense single-stranded (ss(+)) RNA viruses form a major part of all known plant viruses, and some of them are damaging pathogens of agriculturally important crops. Analysis of gene expression following infection by ss(+) RNA viruses is crucial for the identification of potential anti-viral factors. However, viral infections are known to globally affect gene expression and therefore selection and validation of reference genes for RT-qPCR is particularly important. In this study, the expression of commonly used reference genes for RT-qPCR was studied in Nicotiana benthamiana following single infection by 11 ss(+) RNA viruses, including five tobamoviruses, four potyviruses, one potexvirus and one polerovirus. Stability of gene expression was analyzed in parallel by four commonly used algorithms: geNorm, NormFinder, BestKeeper, and Delta CT, and RefFinder was finally used to summarize all the data. The most stably expressed reference genes differed significantly among the viruses, even when those viruses were from the same genus. Our study highlights the importance of the selection and validation of reference genes upon different viral infections.
Keyphrases
- gene expression
- dna methylation
- genome wide
- bioinformatics analysis
- sars cov
- genetic diversity
- machine learning
- nucleic acid
- high resolution
- deep learning
- genome wide analysis
- magnetic resonance
- risk assessment
- gram negative
- mass spectrometry
- antimicrobial resistance
- transcription factor
- pet ct
- artificial intelligence
- multidrug resistant