Reverse transcription-quantitative PCR (RT-qPCR) is a powerful tool for quantifying gene expression. However, reference genes (RGs) for gene expression analysis in peach (Prunus persica) during interactions with Monilinia laxa, a major fungal pathogen that causes brown rot, have not been established. In this study, we analysed 12 candidate RGs in this pathosystem by analysing samples from 12 to 144 HAI. The stability of the RGs was evaluated using the ΔCq method and BestKeeper, NormFinder, and geNorm algorithms. Our results identified AKT3, RNA pol II (RPII) and SNARE (using geNorm), RPII, AKT3 and TEF2 (using NormFinder), AKT3, SNARE and RPII (using BestKeeper) and RPII, MUB6 and AKT3 (using the ΔCq method) as the most stable RGs for mRNA normalisation in this pathosystem across all tested samples. The geNorm algorithm was used to determine the optimal number of suitable RGs required for proper normalisation under these experimental conditions, indicating that the three RGs were sufficient for normalisation. Analysis of the results obtained using different algorithms showed that AKT3, RPII, and SNARE were the three most stable RGs. Furthermore, to confirm the validity of the reference genes, the expression levels of six genes of interest, involved in different metabolic pathways, were normalized in inoculated and uninoculated peach fruit. These findings provide a set of RGs for accurate RT-qPCR analysis in studies involving peach and M. laxa interactions, facilitating deeper insights into the molecular mechanisms underlying this important plant–pathogen relationship.

Selection of stable reference genes in prunus persica fruit infected with monilinia laxa for normalisation of RT-qPCR gene expression data / Lizzio, Agata; Battaglia, Valerio; Lahoz, Ernesto; Reverberi, Massimo; Petriccione, Milena. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 15:1(2025). [10.1038/s41598-025-90506-1]

Selection of stable reference genes in prunus persica fruit infected with monilinia laxa for normalisation of RT-qPCR gene expression data

Lizzio, Agata
Primo
Conceptualization
;
Reverberi, Massimo
Penultimo
Writing – Review & Editing
;
2025

Abstract

Reverse transcription-quantitative PCR (RT-qPCR) is a powerful tool for quantifying gene expression. However, reference genes (RGs) for gene expression analysis in peach (Prunus persica) during interactions with Monilinia laxa, a major fungal pathogen that causes brown rot, have not been established. In this study, we analysed 12 candidate RGs in this pathosystem by analysing samples from 12 to 144 HAI. The stability of the RGs was evaluated using the ΔCq method and BestKeeper, NormFinder, and geNorm algorithms. Our results identified AKT3, RNA pol II (RPII) and SNARE (using geNorm), RPII, AKT3 and TEF2 (using NormFinder), AKT3, SNARE and RPII (using BestKeeper) and RPII, MUB6 and AKT3 (using the ΔCq method) as the most stable RGs for mRNA normalisation in this pathosystem across all tested samples. The geNorm algorithm was used to determine the optimal number of suitable RGs required for proper normalisation under these experimental conditions, indicating that the three RGs were sufficient for normalisation. Analysis of the results obtained using different algorithms showed that AKT3, RPII, and SNARE were the three most stable RGs. Furthermore, to confirm the validity of the reference genes, the expression levels of six genes of interest, involved in different metabolic pathways, were normalized in inoculated and uninoculated peach fruit. These findings provide a set of RGs for accurate RT-qPCR analysis in studies involving peach and M. laxa interactions, facilitating deeper insights into the molecular mechanisms underlying this important plant–pathogen relationship.
2025
peach; pathosystem; brown rot; RGs selection and normalisation; algorithms
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Selection of stable reference genes in prunus persica fruit infected with monilinia laxa for normalisation of RT-qPCR gene expression data / Lizzio, Agata; Battaglia, Valerio; Lahoz, Ernesto; Reverberi, Massimo; Petriccione, Milena. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 15:1(2025). [10.1038/s41598-025-90506-1]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1734861
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