2014
DOI: 10.1007/s12155-014-9457-1
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Evaluation of Candidate Reference Genes for Normalization of Quantitative RT-PCR in Switchgrass Under Various Abiotic Stress Conditions

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Cited by 43 publications
(47 citation statements)
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“…No previous research has shown that TIP41 is the most stable RG under heat stress. ACT2 is a traditional housekeeping gene widely used in many species, such as Betula platyphylla under salt stress and Panicum virgatum L. leaves and roots [58,59]. In this study, ACT2 was an appropriate RG under heat stress, consistent with results from P. praeruptorum under heat stress [54].…”
Section: Discussionsupporting
confidence: 84%
“…No previous research has shown that TIP41 is the most stable RG under heat stress. ACT2 is a traditional housekeeping gene widely used in many species, such as Betula platyphylla under salt stress and Panicum virgatum L. leaves and roots [58,59]. In this study, ACT2 was an appropriate RG under heat stress, consistent with results from P. praeruptorum under heat stress [54].…”
Section: Discussionsupporting
confidence: 84%
“…APRT and ACT were the most variable reference genes under drought stress in our study, thereby they were considered inappropriate to use as a reference gene under this condition. Accordingly, APRT was also found unstable in sugarcane under abiotic stress conditions28, whereas ACT was selected as a suitable reference gene to switchgrass under drought and salinity treatment46, demonstrating that even phylogenetically similar species show differential responses to gene expression under the same experimental conditions.…”
Section: Discussionmentioning
confidence: 99%
“…Quantitative real-time reverse transcription PCR (qRT-PCR) is generally regarded as a convenient and efficient tool to analyse gene expression, but the RNA quantification, the reverse transcription reaction efficiency and other uncontrolled factors may limit the accuracy and stability of the final results (Huang et al 2014; Hao et al 2014). Thus, it is necessary to apply reliable reference genes to normalize the data.…”
Section: Introductionmentioning
confidence: 99%