Genomics and Applied Biology 2024, Vol.15, No.3, 120-131 http://bioscipublisher.com/index.php/gab 121 their expression patterns. Elucidate the regulatory networks involving miRNAs and their target genes: By integrating small RNA sequencing (sRNA-seq) and RNA sequencing (RNA-seq) data, the study aims to construct comprehensive regulatory networks that highlight the interactions between miRNAs and their target genes during cold stress. Understand the molecular mechanisms underlying cold stress response: The study seeks to uncover the pathways and processes regulated by miRNAs and their target genes, providing insights into the molecular basis of cold tolerance in rice. Identify potential genetic targets for improving cold tolerance: By pinpointing key regulatory elements and genes involved in cold stress response, the study aims to provide valuable information for breeding programs aimed at developing cold-tolerant rice varieties. This systematic review will synthesize current knowledge on the integrated regulatory networks of miRNAs and transcriptome in rice response to cold stress, offering a foundation for future research and practical applications in rice improvement. 2 Conceptual Framework of Integrated Regulatory Networks 2.1 Definition and components of regulatory networks Regulatory networks in biological systems are intricate frameworks that govern gene expression and cellular functions. These networks are composed of various elements, including transcription factors (TFs), miRNAs, and their target genes. TFs are proteins that bind to specific DNA sequences to regulate the transcription of genetic information from DNA to mRNA. MiRNAs, on the other hand, are small non-coding RNAs that post-transcriptionally regulate gene expression by binding to complementary sequences on target mRNAs, leading to their degradation or translational repression (Le et al., 2013; Guo et al., 2016; Sharma et al., 2019). The interplay between these components forms a complex regulatory network that ensures precise control over gene expression and cellular responses to environmental stimuli. 2.2 Significance of integrating MiRNAs and transcriptome data Integrating miRNA and transcriptome data is crucial for a comprehensive understanding of gene regulatory mechanisms, especially under stress conditions such as cold stress in rice. MiRNAs play a pivotal role in modulating gene expression in response to abiotic stresses by targeting specific mRNAs for degradation or translational repression (Baldrich et al., 2015; Balyan et al., 2017; Mazurier et al., 2022). By combining miRNA and transcriptome data, researchers can identify miRNA/mRNA target pairs and elucidate the regulatory networks involved in stress responses. This integrative approach allows for the identification of key regulatory nodes and pathways, providing insights into the molecular mechanisms underlying stress tolerance and enabling the development of strategies to enhance crop resilience (Gosline et al., 2015; Sharma et al., 2019; Mazurier et al., 2022). 2.3 Methodological approaches for network construction Constructing integrated regulatory networks involves several methodological approaches that leverage high-throughput sequencing technologies and computational tools. One common approach is the use of sRNA-seq and RNA-seq to profile miRNA and mRNA expression levels, respectively, under different conditions (Gosline et al., 2015; Balyan et al., 2017; Mazurier et al., 2022). Degradome sequencing is also employed to identify miRNA cleavage sites on target mRNAs, providing direct evidence of miRNA-target interactions (Meng et al., 2011; Baldrich et al., 2015). Computational methods, such as Bayesian network structure learning and network motif finding algorithms, are used to infer the regulatory relationships between miRNAs, TFs, and mRNAs from the expression data (Le et al., 2013; Guo et al., 2016). Additionally, integrating epigenetic data, such as histone modifications, can further refine the regulatory network by revealing the transcriptional and post-transcriptional regulatory layers (Gosline et al., 2015). These comprehensive approaches enable the construction of detailed and accurate regulatory networks that capture the complexity of gene regulation in response to environmental stresses. By integrating miRNA and transcriptome data, researchers can gain a holistic view of the regulatory networks that govern plant responses to cold stress, ultimately contributing to the development of stress-tolerant rice varieties.
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