Comparative transcriptome and metabolome analysis reveal glutathione metabolic network and functional genes underlying blue and red-light mediation in maize seedling leaf

Light quality severely affects biosynthesis and metabolism-associated process of glutathione. However, the role of specific light is still unclear on the glutathione metabolism. In this article, comparatively transcriptome and metabolome

Compared to red light, blue light remarkably changed the transcription signal transduction and metabolism of glutathione metabolism. Differently expressed genes and metabolic mapped to the glutathione metabolism signaling pathways. In total, we obtained three unidentified genes, and two of them were predicted in current glutathione metabolism network. This result will contribute to the research of glutathione metabolism of maize.

There are 20 differently expressed genes and 4 differently expressed metabolites in KEGG pathway of glutathione metabolism. Among them, 12 genes belong to the glutathione S-transferase family, 3 genes belong to the ascorbate peroxidase gene family and 2 genes belong to the ribonucleoside-diphosphate reductase gene family. Three genes, G6PD, SPDS1, and GPX1 belong to the gene family of glucose 6-phosphate dehydrogenase, spermidine synthase, and glutathione peroxidase, respectively. Four differently expressed metabolites are identified. Three of them, Glutathione disulfide, Glutathione, and l-γ-Glutamyl-L-amino acid are decreased while L-Glutamate is increased. In addition, Through PPI analysis, two annotated genes gst16 and DAAT, and 3 unidentified genes 100381533, pco105094 and umc2770, identified as RPP13-like3, BCAT-like1and GMPS, were obtained. By the analysis of protein sequence and PPI network, we predict that pco105094 and umc2770 were involved in the GSSG-GSH and AsA-GSH cycle in the network of glutathione metabolism. Conclusions: Compared to red light, blue light remarkably changed the transcription signal transduction and metabolism of glutathione metabolism. Differently expressed genes and metabolic mapped to the glutathione metabolism signaling pathways. In total, we obtained three unidentified genes, and two of them were predicted in current glutathione metabolism network. This result will contribute to the research of glutathione metabolism of maize.