Identification of altered metabolic pathways of γ-irradiated rice mutant via network-based transcriptome analysis
In order to develop rice mutants for crop improvement, we applied γ-irradiation mutagenesis and selected a rice seed color mutant (MT) in the M14 targeting-induced local lesions in genome lines. This mutant exhibited differences in germination rate, plant height, and root length in seedlings compared to the wild-type plants. We found 1645 different expressed probes of MT by microarray hybridization. To identify the modified metabolic pathways, we conducted integrated genomic analysis such as weighted correlation network analysis with a module detection method of differentially expressed genes (DEGs) in MT on the basis of large-scale microarray transcriptional profiling. These modules are largely divided into three subnetworks and mainly exhibit overrepresented gene ontology functions such as oxidation-related function, ion-binding, and kinase activity (phosphorylation), and the expressional coherences of module genes mainly exhibited in vegetative and maturation stages. Through a metabolic pathway analysis, we detected the significant DEGs involved in the major carbohydrate metabolism (starch degradation), protein degradation (aspartate protease), and signaling in sugars and nutrients. Furthermore, the accumulation of amino acids (asparagine and glutamic acid), sucrose, and starch in MT were affected by gamma rays. Our results provide an effective approach for identification of metabolic pathways associated with useful agronomic traits in mutation breeding.
KeywordsRice Gamma ray mutagenesis Weighted correlation network analysis (WGCNA) Microarray
This work was carried out with the support of “Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ01115201)” Rural Development Administration, Republic of Korea, and a grant from the Nuclear R&D Program by the Ministry of Science, ICT and Future Planning (MSIP), Republic of Korea, and the 2014 Research Grant from Kangwon National University (No. 120140389).
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Conflict of interest
The authors declare that they have no conflict of interest.
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