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
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