Selection and Validation of Reference Genes for RT-qPCR in Protonemal Tissue of the Desiccation-Tolerant Moss Pseudocrossidium replicatum Under Multiple Abiotic Stress Conditions

Abstract

Plant abiotic stresses are the main cause of significant crop losses worldwide. The moss Pseudocrossidium replicatum is highly tolerant to different types of abiotic stress, such as desiccation. Our group is interested in identifying and characterising differentially expressed genes in response to abiotic stress in this species. However, a collection of validated reference genes for RT-qPCR analysis is essential to normalise the expression of genes in response to the conditions of interest. Here, we assessed 13 candidate reference genes for P. replicatum based on their expression stability across transcriptomes from six abiotic stress-related conditions using the RefFinder, BestKeeper, geNorm, and NormFinder programs. The stability and reliability of the proposed reference genes were evaluated under six experimental conditions: control, dehydration, rehydration, abscisic acid (ABA), NaCl, and sorbitol. Interestingly, most proposed reference genes exhibited high stability (low M values) across all analysed abiotic stress conditions. A pairwise variation analysis indicated that only one pair is necessary to normalise RT-qPCR experiments. Each gene was confirmed to normalise the expression of both upregulated and downregulated genes. This represents the first report of validated reference genes for RT-qPCR gene expression studies under abiotic stress in the protonemal tissue of a fully desiccation-tolerant moss.

Keywords: ABA; Pseudocrossidium replicatum; RT-qPCR; abiotic stress; bryophytes; desiccation; osmotic stress; reference genes; salinity; transcriptome.

Figure 1

Volcano plots illustrating DEGs under various abiotic stresses and abscisic acid (ABA) treatment in comparison to the control condition. The X-axis represents the log2 fold change between conditions, while the Y-axis displays the −log10 of the adjusted p < 0.05. Red dots indicate significantly upregulated genes, whereas blue dots denote significantly downregulated genes.

Figure 2

Relative expression levels of 13 candidate reference genes across various abiotic stress conditions and ABA treatment in P. replicatum protonemal tissue. Expression was assessed by RT-qPCR and plotted as quantification cycle (Cq) values. Each panel corresponds to a specific gene, with individual box plots representing expression under six conditions: control, dehydration, rehydration, ABA, NaCl, and sorbitol. Dotted lines at Cq 16 and 24 indicate the thresholds proposed for classifying high (Cq < 16), medium (Cq 16–23), and low (Cq > 23) expression levels [61].

Figure 3

Stability analysis of 13 selected reference genes under abiotic stress and ABA treatments. According to RefFinder, a low average stability value indicates a more stable expression. Genes are ranked from left to right based on their average expression stability, with the most stable genes positioned on the left and the least stable on the right.

Figure 4

Analysis of pairwise variation (V) utilising the geNorm algorithm aims to identify the optimal number of reference genes for precise normalisation. The Vn/Vn+1 values indicate enhanced expression stability with the addition of another gene.

Figure 5

Kinetics of hat5 gene expression changes under dehydration stress. Box plots represent log₂ (fold change) values obtained using the ΔΔCt method [62] at five time points: 0 h (control), 15 min, 30 min, 1 h, 3 h, and 24 h of dehydration. Each plot corresponds to a different normalisation strategy using one or two reference genes (atp6, psbB, rps1, ubq). Technical triplicates per sample were included. Statistical significance was assessed using one-way ANOVA followed by Tukey’s HSD test. Asterisks indicate significance levels: p < 0.05 (*), < 0.01 (**), < 0.001 (***); “ns” indicates no significance.

Figure 6

Kinetics of gene expression changes for erf003 under dehydration stress. Box plots represent the log₂ (fold change) values obtained using the ΔΔCt method [62] across five time points: 0 h (control), 15 min, 30 min, 1 h, 3 h, and 24 h of dehydration. Each plot corresponds to a different normalisation strategy employing one or two reference genes (petB, psbA, rps1, ubq). Technical triplicates were included for each sample. Statistical significance was assessed using one-way ANOVA followed by Tukey’s HSD test. Asterisks denote significance levels: p < 0.05 (*), < 0.01 (**), < 0.001 (***); “ns” indicates no significance.