Transcriptome changes of tomato internode elongation induced by far-red light 3 73 3.2.10 Utilizing WGCNA to illuminate the transcriptome dynamics in SAS In order to explore the multi-factorial RNAseq data in more depth, we wanted to look for expression pattern trends. Therefore, we continued with WGCNA (Weighted Gene Coexpression Network Analysis) to identify interesting modules, functions and genes. To filter the input data to WGCNA, we selected the DEGs from any comparison previously tested (p<0.05) and used the quantile normalized expression data in WGCNA analysis. We used undirected analysis to identify the expression patterns among the genes. In total we were able to characterize 43 modules based on gene expression (Tables S3.1, S3.3 in the digital supplement). We conducted a GO enrichment on all these modules to infer their functions (Figure S3.3). We also visualized the gene expression patterns of these modules (Figures 3.12-3.14). In Figure 3.13, we constructed a heatmap based on the average normalized expression fold change comparing WL+FR vs WL in each tissue and treatment. Several modules consistently exhibited upregulation in response to FR: darkred, greenyellow, mediumpurplegrey3, red, and royal blue. These modules represent clusters of nodes that have grouped together due to shared attributes or connectivity patterns within the network (Figure 3.13). In Figure 3.13 we illustrate the modules in the network topology, denoted by different colors; the main modules that are clearly visible are the blue, green, grey, pink, orange, red, and yellow modules. Then, in Figure 3.14 we combined the log fold change data with the topology of gene modules to visualize the change over time across the network. From these approaches, a number of modules stood out. The mediumpurplegrey3 module showed an increasing, high degree of upregulation over time, where the expression in the pith was significantly elevated. This module is primarily associated with chloroplast and translation activities (as shown in Figure S3.3), indicating a potential role in enhancing photosynthetic and protein synthesis processes. Conversely, salmon and lightsteelblue1 modules demonstrated downregulation over time. The top function associated with the salmon module is the methionine metabolic process and methylenetetrahydrofolate reductase (NAD(P)H) activity, suggesting a potential shift in metabolic priorities. Meanwhile, the lightsteelblue1 module is related to vascular transfer processes, implying adjustments in the plant’s transport mechanisms to adapt to changing environmental conditions. These findings collectively provide insights into the dynamic regulatory responses of different modules to FR light exposure and their functional implications in plant acclimation.
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