Abiotic Stress-Responsive miRNA and Transcription Factor-Mediated Gene Regulatory Network in Oryza sativa: Construction and Structural Measure Study

Abstract

Climate changes and environmental stresses have a consequential association with crop plant growth and yield, meaning it is necessary to cultivate crops that have tolerance toward the changing climate and environmental disturbances such as water stress, temperature fluctuation, and salt toxicity. Recent studies have shown that trans-acting regulatory elements, including microRNAs (miRNAs) and transcription factors (TFs), are emerging as promising tools for engineering naive improved crop varieties with tolerance for multiple environmental stresses and enhanced quality as well as yield. However, the interwoven complex regulatory function of TFs and miRNAs at transcriptional and post-transcriptional levels is unexplored in Oryza sativa. To this end, we have constructed a multiple abiotic stress responsive TF-miRNA-gene regulatory network for O. sativa using a transcriptome and degradome sequencing data meta-analysis approach. The theoretical network approach has shown the networks to be dense, scale-free, and small-world, which makes the network stable. They are also invariant to scale change where an efficient, quick transmission of biological signals occurs within the network on extrinsic hindrance. The analysis also deciphered the existence of communities (cluster of TF, miRNA, and genes) working together to help plants in acclimatizing to multiple stresses. It highlighted that genes, TFs, and miRNAs shared by multiple stress conditions that work as hubs or bottlenecks for signal propagation, for example, during the interaction between stress-responsive genes (TFs/miRNAs/other genes) and genes involved in floral development pathways under multiple environmental stresses. This study further highlights how the fine-tuning feedback mechanism works for balancing stress tolerance and how timely flowering enable crops to survive in adverse conditions. This study developed the abiotic stress-responsive regulatory network, APRegNet database (http://lms.snu.edu.in/APRegNet), which may help researchers studying the roles of miRNAs and TFs. Furthermore, it advances current understanding of multiple abiotic stress tolerance mechanisms.

Cold-responsive transcription factors in Arabidopsis and rice: A regulatory network analysis using array data and gene co-expression network

“…In addition to TFs, microRNAs (miRNAs) next to other means such as circular RNAs, long non-coding RNAs, and microproteins are the other regulatory factors [ 20 ]. Different findings indicate the common roles of many miRNAs regulatory elements to be responsive in multiple stress conditions [ 21 ].…”

Evolution of miRNA-Binding Sites and Regulatory Networks in Cichlids

“…Nonetheless, by studying the impact of miRNA regulation in three-node motifs, this work extends the first genome-wide exploration of GRN evolution in cichlids ( Mehta et al 2021 ). In a wider context, as the individual regulatory hallmarks of TFs and miRNAs start to become characterized in disease, for example, forms of cancer ( Plaisier et al 2016 ; Mullany et al 2018 ; Nersisyan et al 2021 ), congenital heart disease ( You et al 2020 ), neuromuscular disorders ( Bo et al 2021 ), as well as related to gene expression in human tissues ( Minchington et al 2020 ) and plant stress response ( Sharma et al 2020 , 2021 ), the computational framework we applied here could be used to study the evolution of characterized regulatory edges and GRNs in the aforementioned, and other systems and phylogenies. However, the combined framework could be extended further by (1) analyzing the impact of either more, or all of the 104 three-node motif models ( Ahnert and Fink 2016 ) through the integration of epigenetic and co-immunoprecipitation assay data to gain regulatory directionality; and (2) including relevant data sets to study the regulatory effect of other mechanisms, for example, lncRNAs and enhancers on network topology, that could also contribute toward the evolution of cichlid phenotypic diversity ( Brawand et al 2014 ; Salzburger 2018 ).…”

Evolution of miRNA binding sites and regulatory networks in cichlids

“…In a wider context, as the individual regulatory hallmarks of TFs and miRNAs start to become characterised in disease e.g. forms of cancer (Plaisier et al 2016; Mullany et al 2018; Nersisyan et al 2021), congenital heart disease (You et al 2020), neuromuscular disorders (Bo et al 2021), as well as related to gene expression in human tissues (Minchington et al 2020) and plant stress response (Sharma et al 2020; Sharma et al 2021), the computational framework we applied here could be used to study the evolution of characterised regulatory edges and GRNs in the aforementioned, and other systems and phylogenies. However, the combined framework could be extended further by 1) analysing the impact of either more, or all of the 104 three-node motif models (Ahnert and Fink 2016) through the integration of epigenetic and co-immunoprecipitation assay data to gain regulatory directionality; and 2) including relevant datasets to study the regulatory effect of other mechanisms e.g.…”