Identification of Potential Zinc Deficiency Responsive Genes and Regulatory Pathways in Rice by Weighted Gene Co-expression Network Analysis

Zinc (Zn) malnutrition is a major public health issue. Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition. Therefore, elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties. Here, a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis (WGCNA) and other in silico prediction tools to identify modules (denoting cluster of genes with related expression pattern) of co-expressed genes, modular genes which are conserved differentially expressed genes (DEGs) across independent RNA-Seq studies, and the molecular pathways of the conserved modular DEGs. WGCNA identified 16 modules of co-expressed genes. Twenty-eight and five modular DEGs were conserved in leaf and crown, and root tissues across two independent RNA-Seq studies. Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 15 Gene Ontology (GO) terms, including the substrate- specific transmembrane transporter and the small molecule metabolic process. Further, the well-studied transcription factors (OsWOX11 and OsbHLH120), protein kinase (OsCDPK20 and OsMPK17), and miRNAs (OSA-MIR397A and OSA-MIR397B) were predicted to target some of the identified conserved modular DEGs. Out of the 24 conserved and up-regulated modular DEGs, 19 were yet to be experimentally validated as Zn deficiency responsive genes. Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.