Selection of reference genes for expression analysis of plant-derived microRNAs in Plutella xylostella using qRT-PCR and ddPCR

Zhang, Lingling; Jing, Xiaodong; Chen, Wei; Bai, Jing; Vasseur, Liette; He, Weiyi; You, Minsheng

doi:10.1371/journal.pone.0220475

Cited by 14 publications

(17 citation statements)

References 42 publications

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“…RNA samples with a clear 18S rRNA band in the agarose gel electrophoresis and A260/A280 values within 1.9–2.1 were further used for the synthesis of first‐strand cDNA of candidate RGs (Table S1) (Zhang et al . 2019). With total RNA as a template, the reverse transcription steps were performed according to the instruction of the Mir‐X miRNA First‐Strand Synthesis Kit (TaKaRa).…”

Section: Methodsmentioning

confidence: 99%

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Evaluation of reference genes for miRNA expression analysis in Galeruca daurica (Coleoptera: Chrysomelidae) using qRT‐PCR

Wang

et al. 2021

Entomological Research

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The selection of suitable reference genes (RGs) for data normalization is a crucial step for obtaining reliable results from gene expression analysis using the quantitative real‐time polymerase chain reaction (qRT‐PCR). Expression stability of eleven putative RGs (miR‐100‐5p, miR‐92a‐3p, miR‐998‐3p, miR‐279d‐3p, miR‐305‐5p, miR‐276a‐3p, miR‐275‐3p, miR‐9a‐5p, miR‐2a‐3p, U6 snRNA and 5S rRNA) was assessed by using a web‐based tool: RefFinder, which integrates four algorithms (Delta Ct, geNorm, NormFinder, and BestKeeper), and the best combination number of RGs was calculated by geNorm. Validation of selected RGs was performed by an expression analysis of let‐7‐5p under different experimental conditions. The best combinations of RGs were shown as follows: miR‐100‐5p + miR‐275‐3p for temperature treatment, miR‐100‐5p + miR‐305‐5p for adult tissues, miR‐276a‐3p + miR‐9a‐5p for genders, miR‐2a‐3p + miR‐276a‐3p for days after eclosion, U6 snRNA + miR‐9a‐5p + miR‐2a‐3p for developmental stages, and U6 snRNA + miR‐279d‐3p for all above conditions, and there was no one RG suitable for all experimental conditions. Incorrect RG selection affected the evaluation of let‐7‐5p abundance. Our findings demonstrate that an integrated approach of multiple algorithms is necessary to identify reliable, stable RGs for miRNA evaluation, and provide a basis for further studies on expression and function analysis of miRNAs and their target genes in Galeruca daurica, a new pest with great outbreaks in Inner Mongolia since 2009.

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Section: Methodsmentioning

confidence: 99%

“…2014; Zhang et al . 2019), Helicoverpa armigera (Yang et al . 2017), Grapholita molesta (Wang et al .…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of reference genes for miRNA expression analysis in Galeruca daurica (Coleoptera: Chrysomelidae) using qRT‐PCR

Wang

et al. 2021

Entomological Research

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“…Nonetheless, many of the existing questions demand solid proofs from wet lab analyses. From the point of view of experimental design, questions related to the most appropriate techniques (deep sequencing, digital PCR, qRT-PCR) and references (samples and/or genes) to be used for crosskingdom miRNA studies still need to be addressed and uniformized accordingly (Chan and Snow, 2016;Zhang et al, 2019b). Once these issues are settled, we can then proceed to investigate other challenges; for instance, why some plant miRNAs seem to be more stable and abundant than others?…”

Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Plant miRNA Cross-Kingdom Transfer Targeting Parasitic and Mutualistic Organisms as a Tool to Advance Modern Agriculture

2020

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MicroRNAs (miRNAs), defined as small non-coding RNA molecules, are fine regulators of gene expression. In plants, miRNAs are well-known for regulating processes spanning from cell development to biotic and abiotic stress responses. Recently, miRNAs have been investigated for their potential transfer to distantly related organisms where they may exert regulatory functions in a cross-kingdom fashion. Cross-kingdom miRNA transfer has been observed in host-pathogen relations as well as symbiotic or mutualistic relations. All these can have important implications as plant miRNAs can be exploited to inhibit pathogen development or aid mutualistic relations. Similarly, miRNAs from eukaryotic organisms can be transferred to plants, thus suppressing host immunity. This two-way lane could have a significant impact on understanding inter-species relations and, more importantly, could leverage miRNA-based technologies for agricultural practices. Additionally, artificial miRNAs (amiRNAs) produced by engineered plants can be transferred to plant-feeding organisms in order to specifically regulate their crosskingdom target genes. This minireview provides a brief overview of cross-kingdom plant miRNA transfer, focusing on parasitic and mutualistic relations that can have an impact on agricultural practices and discusses some opportunities related to miRNAbased technologies. Although promising, miRNA cross-kingdom transfer remains a debated argument. Several mechanistic aspects, such as the availability, transfer, and uptake of miRNAs, as well as their potential to alter gene expression in a cross-kingdom manner, remain to be addressed.

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“…Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) has the advantages of high sensitivity, strong specificity, and high throughput, so it is widely used for the detection of gene expression levels (Nolan et al, 2006;Zhang et al, 2019). Reference genes are the relatively constant genes for expression in tissues or cells, which can calibrate the experimental errors and ensure the accuracy of the experimental results.…”

Section: Introductionmentioning

confidence: 99%

Selection and Validation of the Optimal Panel of Reference Genes for RT-qPCR Analysis in the Developing Rat Cartilage

Han

et al. 2020

Front. Genet.

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Real-time fluorescence quantitative PCR (RT-qPCR) is widely used to detect gene expression levels, and selection of reference genes is crucial to the accuracy of RT-qPCR results. Minimum Information for Publication of RT-qPCR Experiments (MIQE) proposes that using the panel of reference genes for RT-qPCR is conducive to obtaining accurate experimental results. However, the selection of the panel of reference genes for RT-qPCR in rat developing cartilage has not been well documented. In this study, we selected eight reference genes commonly used in rat cartilage from literature (GAPDH, ACTB, 18S, GUSB, HPRT1, RPL4, RPL5, and SDHA) as candidates. Then, we screened out the optimal panel of reference genes in female and male rat cartilage of fetus (GD20), juvenile (PW6), and puberty (PW12) in physiology with stability analysis software of genes expression. Finally, we verified the reliability of the selected panel of reference genes with the rat model of intrauterine growth retardation (IUGR) induced by prenatal dexamethasone exposure (PDE). The results showed that the optimal panel of reference genes in cartilage at GD20, PW6, and PW12 in physiology was RPL4 + RPL5, which was consistent with the IUGR model, and there was no significant gender difference. Further, the results of standardizing the target genes showed that RPL4 + RPL5 performed smaller intragroup differences than other panels of reference genes or single reference genes. In conclusion, we found that the optimal panel of reference genes in female and male rat developing cartilage was RPL4 + RPL5, and there was no noticeable difference before and after birth.

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Selection of reference genes for expression analysis of plant-derived microRNAs in Plutella xylostella using qRT-PCR and ddPCR

Cited by 14 publications

References 42 publications

Evaluation of reference genes for miRNA expression analysis in Galeruca daurica (Coleoptera: Chrysomelidae) using qRT‐PCR

Evaluation of reference genes for miRNA expression analysis in Galeruca daurica (Coleoptera: Chrysomelidae) using qRT‐PCR

Plant miRNA Cross-Kingdom Transfer Targeting Parasitic and Mutualistic Organisms as a Tool to Advance Modern Agriculture

Selection and Validation of the Optimal Panel of Reference Genes for RT-qPCR Analysis in the Developing Rat Cartilage

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