A computational system biology approach to construct gene regulatory networks for salinity response in rice (Oryza sativa)

Salinity is one of the most common abiotic stress which limits agricultural crop production. Salinity stress tolerance in rice (Oryza sativa L.) is an important trait controlled by various genes. The mechanism of salinity stress response in rice is quite complex. Modelling and construction of genetic regulatory networks is an important tool and can be used for understanding this underlying mechanism. This paper considers the problem of modeling and construction of Gene Regulatory Networks using Multiple Linear Regression and Singular Value Decomposition approach coupled with a number of computational tools. The gene networks constructed by using this approach satisfied the scale free property of biological networks and such networks can be used to extract valuable information on the transcription factors, which are salt responsive. The gene ontology enrichment analysis of selected nodes is performed. The developed model can also be used for predicting the gene responses under stress condition and the result shows that the model fits well for the given gene expression data in rice. In this paper, we have identified ten target genes and a series of potential transcription factors for each target gene in rice which are highly salt responsive.