Molecular Plant Breeding 2025, Vol.16, No.2, 105-118 http://genbreedpublisher.com/index.php/mpb 113 conditions, the expression of certain genes in the GA signaling pathway is suppressed, thus slowing down plant growth to conserve energy and water resources. ETH production increases under drought conditions, and it regulates plant defense responses by activating a series of TFs, such as ERF family members. These TFs can initiate the expression of a series of downstream genes, thereby enhancing plant drought tolerance (Kumar et al., 2023). Furthermore, research also indicates that there are complex interactions and cross-regulatory networks among these hormones. For instance, ABA and GAs can exhibit antagonistic effects in certain situations, with GAs inhibiting ABA-induced stomatal closure, while ABA can inhibit GA-promoted cell elongation. This interaction between hormones is crucial for plant adaptation under different environmental conditions (Wang et al., 2018). Through these studies, we can not only better understand the role of plant hormones in gene regulation but also provide a theoretical basis for cultivating drought-resistant crop varieties. 7 Advances in Genomics and Transcriptomics Technologies 7.1 High-throughput sequencing technologies High-throughput sequencing technologies have revolutionized the field of genomics and transcriptomics, enabling comprehensive analysis of genetic and transcriptomic data at an unprecedented scale. Next-generation sequencing (NGS) platforms have facilitated the generation of vast amounts of data, which are crucial for understanding the complex regulatory networks in rice under water deficit conditions. For instance, the integration of time-series transcriptome data with patterns of nucleosome-free chromatin and cis-regulatory elements has allowed the inference of EGRINs in rice, which coordinate gene expression in response to environmental stress (Ahn et al., 2017). Additionally, GWAS have identified significant MTAs in rice under different water management systems, providing insights into the genetic basis of traits related to water deficit adaptation (Wang et al., 2022). Utilizing RNA-seq technology in conjunction with epigenetic markers such as DNA methylation and histone modification data provides a more comprehensive understanding of the gene expression regulatory mechanisms in rice under water deficit conditions. High-throughput sequencing technology has also facilitated the application of gene-editing tools like CRISPR/Cas9 in rice breeding. By precisely modifying specific genes in the rice genome, scientists can develope rice varieties with enhanced drought resistance. In summary, high-throughput sequencing technology has become an indispensable tool in studying rice drought resistance. 7.2 Bioinformatics tools for data analysis The explosion of multi-omics data necessitates advanced bioinformatics tools for effective data analysis and integration. Various computational methods and platforms have been developed to manage and analyze these large datasets. For example, bioinformatics pipelines have been employed to analyze multi-omics data in transgenic rice, revealing how specific TFs like OsERF71 regulate global gene expression to confer drought resistance (McDaniel et al., 2021). Tools such as Anvio offer advanced analysis and visualization capabilities, enabling researchers to interactively organize and explore complex omics data (Eren et al., 2015). Moreover, the integration of multi-omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, has been instrumental in elucidating the molecular mechanisms underlying stress responses in crops (Liu et al., 2020; Yang et al., 2021). 7.3 Challenges and future directions in omics research Despite the significant advancements, several challenges remain in the field of omics research. One major challenge is the integration and interpretation of multi-omics data, which requires sophisticated computational tools and expertise. The rapid pace of technological development can be daunting for researchers new to the field, highlighting the need for user-friendly platforms and comprehensive training (McDaniel et al., 2021). Additionally, the complexity of regulatory networks and the dynamic nature of gene expression under stress conditions necessitate continuous improvement in data analysis methods. Future research should focus on developing more robust and integrative bioinformatics tools to enhance our understanding of gene networks and transcriptional regulation in crops. The integration of systems biology approaches with multi-omics data holds promise for predicting complex traits and improving crop resilience under environmental stresses (Yang et al., 2021; Zemlyanskaya et al., 2021).
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