Transcriptome Profiles Reveal Key Regulatory Networks during Single and Multifactorial Stresses Coupled with Melatonin Treatment in Pitaya (Selenicereus undatus L.)

Abstract

In response to evolving climatic conditions, plants frequently confront multiple abiotic stresses, necessitating robust adaptive mechanisms. This study focuses on the responses of Selenicereus undatus L. to both individual stresses (cadmium; Cd, salt; S, and drought; D) and their combined applications, with an emphasis on evaluating the mitigating effects of (M) melatonin. Through transcriptome analysis, this study identifies significant gene expression changes and regulatory network activations. The results show that stress decreases pitaya growth rates by 30%, reduces stem and cladode development by 40%, and increases Cd uptake under single and combined stresses by 50% and 70%, respectively. Under stress conditions, enhanced activities of H₂O₂, POD, CAT, APX, and SOD and elevated proline content indicate strong antioxidant defenses. We identified 141 common DEGs related to stress tolerance, most of which were related to AtCBP, ALA, and CBP pathways. Interestingly, the production of genes related to signal transduction and hormones, including abscisic acid and auxin, was also significantly induced. Several calcium-dependent protein kinase genes were regulated during M and stress treatments. Functional enrichment analysis showed that most of the DEGs were enriched during metabolism, MAPK signaling, and photosynthesis. In addition, weighted gene co-expression network analysis (WGCNA) identified critical transcription factors (WRKYs, MYBs, bZIPs, bHLHs, and NACs) associated with antioxidant activities, particularly within the salmon module. This study provides morpho-physiological and transcriptome insights into pitaya's stress responses and suggests molecular breeding techniques with which to enhance plant resistance.

Keywords: Selenicereus undatus L.; TFs; WGCNA; single and combined stresses; transcriptome analysis.

Figure 1

The morpho−physiological response of pitaya in under single-, double-, and multifactorial stress combinations: (A) The effect of single and combined stresses on the growth of pitaya plants. (B) Phenotypic measurements, including root length (RL), root weight (RW), shoot length (SL), shoot weight (SW), cladode length (CL), and cladode diameter (CD). The treatments were compared using one-way ANOVA at a 5% (p ≤ 0.05) probability level, and means were compared using the Duncan test. The different letters display statistically significant differences among cultivars; similar letters depict statistically non-significant values, while bars show standard errors. (C) Cadmium quantification across treatments, with error bars representing standard deviation. (D) A correlation matrix showing significant relationships among RL (cm), RW (g), SL (cm), SW (g), CL (cm), and CD (mm). Significant and highly significant correlations are represented by * (p < 0.05), ** (p < 0.01), *** (p < 0.001). Abbreviations: control (Ck); melatonin (M); salinity (S); drought (D); cadmium (Cd); cadmium + salinity (CdS); cadmium + drought (CdD); cadmium + salinity + drought (CdSD); cadmium + salinity + melatonin (CdSM); cadmium + drought + melatonin (CdDM); cadmium + drought + salinity + melatonin (CdDSM).

Figure 2

Physiological response of pitaya in response to single, double, and multifactorial stresses at seedling stage. (A) H₂O₂ concentration (µmol/g); (B) ascorbate peroxidase (APX) activity (mmol/min/g); (C) peroxidase (POD) activity (U/g); (D) catalase (CAT) activity (µmol/min/g); (E) superoxide dismutase (SOD) activity (U/g WST-8); and (F) proline (PRO) content (µg/g). Each bar represents mean ± standard deviation (n = 3), and different letters above bars indicate significant differences among treatments at p ≤ 0.01. Abbreviations: control (Ck); melatonin (M); salinity (S); drought (D); cadmium (Cd); cadmium + salinity (CdS); cadmium + drought (CdD); cadmium + salinity + drought (CdSD); cadmium + salinity + melatonin (CdSM); cadmium + drought + melatonin (CdDM); cadmium + drought + salinity + melatonin (CdDSM).

Figure 3

Identification of total and common differentially expressed genes (DEGs) in response to single-, double-, and multifactorial stress treatments (A,B). Common upregulated and downregulated DEGs for single-stress treatments: drought vs. control (D-vs-Ck), melatonin vs. control (M-vs-Ck), salinity vs. control (S-vs-Ck), cadmium vs. control (Cd-vs-Ck); (C,D) DEGs for double-stress treatments: cadmium + salinity vs. control (CdS-vs-Ck), cadmium + drought vs. control (CdD-vs-Ck); (E,F) DEGs for multifactorial treatments: cadmium + salinity + drought vs. cadmium + drought + salinity + melatonin (CdSD-vs-CdDSM), cadmium + drought vs. cadmium + drought + melatonin (CdD-vs-CdDM), cadmium + salinity vs. cadmium + salinity + melatonin (CdS-vs-CdSM).

Figure 4

Weighted gene co-expression network analysis (WGCNA). (A) Module−trait relationship: each column represents different processing conditions. Each row corresponds to characteristic gene of module. Correlation between two is indicated in each cell by Pearson correlation coefficient and p-value in parentheses. Cell color ranges from red (indicating high positive correlation) to green (indicating high negative correlation). Number of genes contained in each module is displayed in parentheses on left side. (B) Module level clustering diagram. (C) Network heatmap plot.

Figure 5

The expression pattern of the co-expressed genes in the representative module. (A) Salmon module; (B) black module; (C) yellow module; (D) pink module; (E) blue module; (F) purple module. Abbreviations: control (Ck); melatonin (M); salinity (S); drought (D); cadmium (Cd); cadmium + salinity (CdS); cadmium + drought (CdD); cadmium + salinity + drought (CdSD); cadmium + salinity + melatonin (CdSM); cadmium + drought + melatonin (CdDM); cadmium + drought + salinity + melatonin (CdDSM).

Figure 6

Analysis of differentially expressed genes (DEGs) in the salmon module based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). (A) The top 20 GO enrichments; (B) the top 20 KEGG enrichments. (Note: The q-value ranges from 0 to 0.05, with closer values indicating higher significance. The number of genes enriched in pathways is provided).

Figure 7

Identification and selection of hub transcription factors (TFs) in salmon and blue modules. (A) Network analysis of TFs in the salmon module; (B) network of top 17 hub TFs and related genes in salmon module; (C) network analysis of hub TFs in blue module. Abbreviations: control (Ck); melatonin (M); salinity (S); drought (DA); cadmium (Cd); cadmium + salinity (CdS); cadmium + drought (CdD); cadmium + salinity + drought (CdSD); cadmium + salinity + melatonin (CdSM); cadmium + drought + melatonin (CdDM); cadmium + drought + salinity + melatonin (CdDSM). WRKY TF (WRKY); myeloblastosis TF (MYB); basic-helix–loop-helix TF (bHLH); basic leucine zipper (bZIP); NAM, ATAF, and CUC (NAC).

Figure 8

Gene expression validation of five selected genes under various treatments such as Ck, M, S, D, Cd, CdS, CdD, CdSD, CdSM, CdDM, and CdDSM. Each plot shows a strong correlation with respective regression equations and R-squared values: HU02G02539_WRKY (y = 0.7173x + 2.1388, R² = 0.8350), HU01G05984_WRKY (y = 0.9507x + 1.0864, R² = 0.8026), HU07G00854_NAC (y = 0.9849x + 1.0367, R² = 0.9711), HU03G00886_MYB (y = 0.9814x + 0.7484, R² = 0.9545), and HU01G00293_bHLH (y = 0.9793x + 1.1094, R² = 0.9277). The graph compares log2 fold changes in RNA-seq and qRT-PCR analyses for five genes. Abbreviations: control (Ck); melatonin (M); salinity (S); drought (D); cadmium (Cd); cadmium + salinity (CdS); cadmium + drought (CdD); cadmium + salinity + drought (CdSD); cadmium + salinity + melatonin (CdSM); cadmium + drought + melatonin (CdDM); cadmium + drought + salinity + melatonin (CdDSM).