Inferring gene regulatory networks using Kendall’s tau correlation coefficient and identification of salinity stress responsive genes in rice

Abstract

Salinity is one of the most common abiotic stresses that limit the production of rice. Since salinity stress tolerance is controlled by many genes, identification of these stress responsive genes as well as to understand the underlying mechanisms is of importance from breeding point of view. In this direction, the reverse engineering of gene regulatory networks has proven to be successful. In this study, we construct the gene regulatory network using Kendall’s tau correlation coefficient, in order to identify the stress responsive genes. The proposed approach was tested on a rice microarray dataset and 18 key genes were identified. Most of these key genes were found to be involved directly or indirectly in salinity stress, as evidenced from the published literature. Gene ontology analysis further confirmed the involvement of the selected genes in ion binding, oxidation-reduction and phosphorylation activities. These identified genes can be targeted for breeding salt-tolerant varieties of rice.