Triticeae Genomics and Genetics, 2025, Vol.16, No.3, 138-147 http://cropscipublisher.com/index.php/tgg 141 3.2 Temporal clustering analysis of differentially expressed genes (DEGs) Many people think that grain development is just a quantitative change, but in fact, the temporal expression changes are equally important. Transcriptome data analysis from the early to mid-stage of grouting revealed that there were tens of thousands of differentially expressed genes (DEGs), among which over 1 400 were transcription factors. These genes are not randomly "online"; they are automatically divided into different expression clusters according to their developmental stages. Between 0 and 6 days after pollination, the most active genes are those involved in cell division and hormone metabolism. However, by the 8th to 10th day, the situation changes, and genes related to starch synthesis and protein storage start to take the lead. Upon further examination through co-expression clustering analysis and WGCNA, several key modules and hub genes have emerged - such as those regulating processes like sucrose conversion to starch and hormone signaling, which control the "switch button" from the cellular activity stage to the storage and accumulation stage (Guan et al., 2022; Hou et al., 2024). 3.3 Functional prediction of tissue-specific expressed genes If it is not detailed enough from an overall perspective, then it is necessary to delve into the organizational level. Transcriptome and proteome analyses of the endosperm and embryo have revealed many genes that only "speak" in specific tissues. The genes with high expression levels in the endosperm region are mostly related to the synthesis of starch and storage proteins, while the genes that are active in the embryo are more inclined towards developmental control and stress response. Interestingly, functional prediction has identified some "seed players" - such as those that can regulate sucrose transport and enhance starch synthase activity, as well as genes linked to hormone signaling pathways (like abolic acid and ethylene). The emergence of such genes not only explains the differences in tissue functions, but also provides direct candidate resources for subsequent breeding and directed genetic engineering (Liu et al., 2023; Shi et al., 2024). 4 Functional Pathways and Molecular Network Analysis 4.1 Enrichment analysis revealing metabolic and signaling pathways During the crucial period of grain filling for wheat, it was actually quite lively inside. Whether it is starch and sucrose metabolism, or glycolysis, amino acid synthesis, photosynthesis and other pathways, they are almost all "online" - at different tissues and different time points, these metabolic pathways are not static but constantly changing (Rangan et al., 2017; Zhang et al., 2021; Li et al., 2025). However, things didn't go as smoothly as expected. Environmental stresses such as shading or high temperatures, once they occur, can easily disrupt these core pathways. For instance, the expression of photosynthetic antenna proteins, carbon fixation efficiency, and even the activity of genes related to starch synthesis will all be affected, and ultimately it may be reflected in grain size, weight, and quality (Chunduri et al., 2021; Hou et al., 2024). More systematic functional annotations and pathway analyses have revealed that there are over seventy identified metabolic and signaling pathways, including hormone synthesis (such as abscisic acid and ethylene), protein synthesis and degradation, as well as some specialized metabolic processes closely related to grout (Zhang et al., 2023). 4.2 Construction of transcription factor regulatory networks and identification of key nodes When all the regulatory factors are considered together, network construction becomes a crucial link. Using analytical methods such as WGCNA and graphic LASSO, researchers gradually pieced together the full picture of the TF network behind grouting regulation. Of course, not all transcription factors have the same "weight". Some like Q, TaTPP-7A, and members of the OsNF-Y family are basically control hubs. They do not simply activate one gene, but can mobilize multiple functional regions, involving multiple directions such as carbon and nitrogen metabolism, starch synthesis, and hormone signaling (Fang et al., 2022). For instance, the Q gene binds to the gene motifs related to photosynthesis and nitrogen metabolism, driving up both production and protein levels. TaTPP-7A is involved in the T6P-SnRK1 pathway, integrating glucose signaling and ABA hormone response to regulate sucrose distribution and starch accumulation (Liu et al., 2023). Behind the entire network lies a complex regulatory mechanism that is clearly layered yet highly interwoven.
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