Molecular Plant Breeding 2025, Vol.16, No.2, 105-118 http://genbreedpublisher.com/index.php/mpb 109 4 Gene Expression Dynamics in Rice 4.1 Differential gene expression under water deficit conditions Rice exhibits significant changes in gene expression when subjected to water deficit conditions. A study using genome-wide gene expression profiling identified 5 284 genes that were differentially expressed under drought stress, with many of these genes being tissue- or stage-specific (Basu and Roychoudhury, 2021). The latest whole-genome sequencing analysis has identified 6 127 genes that change specifically under drought stress, including not only universally responding “star” genes but also many previously overlooked genes with potentially important functions (Chen et al., 2023). Another research highlighted the differential expression of genes in hybrid rice LYP9, where 595 genes were up-regulated and 25 down-regulated under stress conditions, indicating a complex regulatory network that enhances stress tolerance (Sakran et al., 2022). Additionally, a GWAS identified specific marker-trait associations (MTAs) related to drought tolerance, further elucidating the genetic basis of stress response in rice (Volante et al., 2017). Specifically, a study pointed out that in the super rice variety “Jin You”, 783 genes were significantly upregulated and 117 genes were significantly downregulated under drought conditions, revealing the differences and complexity of drought tolerance mechanisms among varieties (Li et al., 2022). 4.2 Temporal and spatial patterns of gene expression The temporal and spatial patterns of gene expression in rice under water deficit conditions are highly dynamic. For instance, the expression of drought-responsive genes varies significantly across different tissues and developmental stages. In one study, the transcriptome from leaf, root, and young panicle at three developmental stages was analyzed, revealing that most differentially expressed genes (DEGs) were regulated in a tissue- or stage-specific manner. They found that under drought conditions, the expression of OsNAC6 gene in leaves was significantly upregulated, which is a known transcription factor that positively regulates drought response, and its upregulation may have enhanced the drought tolerance of leaves. In roots, the expression of OsDREB2Agenewas more significant, which is closely related to root development and water absorption, and its upregulation may have promoted root growth and water absorption capacity under drought conditions (Yin et al., 2021). Another study on maize, which can be extrapolated to rice, showed that TFs were differentially regulated across stressed seedling tissues, indicating a complex temporal and spatial regulation of gene expression. They observed that under drought stress, the expression of ZmDREB2 gene in corn seedling leaves was upregulated, while its expression in roots remained relatively stable. This differential regulation may reflect different strategies and priorities of different tissues in coping with drought stress (Seeve et al., 2017). 4.3 Methods for studying gene expression (e.g., RNA-seq, qPCR) Several advanced methods are used to study gene expression in rice under water-scarce conditions: RNA-seq, a high-throughput sequencing technology, allows for a comprehensive analysis of the transcriptome and the identification of known and new transcripts. It has been widely used to analyze gene expression conditions in rice under various stresses (Wilkins et al., 2016). Quantitative PCR (qPCR) is used to quantify the expression level of a specific gene. It is particularly useful for validating RNA-seq results and studying the expression of key regulatory genes under stress. Gene expression sequence analysis (SAGE), a technique used to study the transcriptome of hybrid rice LYP9 and its parent varieties, provides insight into the differential expression of genes (Marcon et al., 2016). Whereas, network component analysis (NCA) integrates measurements at multiple genome scales to infer EGRINs that coordinate gene expression in response to environmental signals. 5 Regulatory Networks in Response to Water Deficit 5.1 Gene-gene interaction networks Gene-gene interaction networks play a crucial role in the response of rice to water deficit conditions. EGRINs have been identified as key players in coordinating the timing and rate of gene expression in response to environmental signals, including water deficit. EGRINs integrate multiple layers of regulation, resulting in changes in transcript levels. For instance, in tropical Asian rice cultivars, EGRINs were inferred by integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and known cis-regulatory elements, identifying 5447 putative target genes for 445 TFs (Wilkins et al., 2016; Ueda et al., 2020). Additionally, MYB
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