Application of Methionine Increases the Germination Rate of Maize Seeds by Triggering Multiple Phenylpropanoid Biosynthetic Genes at Transcript Levels

Abstract

Methionine is an essential amino acid that initiates protein synthesis and serves as a substrate for various chemical reactions. Methionine metabolism plays an important role in Arabidopsis seed germination, but how methionine works in seed germination of maize has not been elucidated. We compared the changes in germination rate, the contents of methionine and folates, and transcriptional levels using transcriptome analysis under water or exogenous methionine treatment. The results indicate that the application of methionine increases seed germination rate (95% versus 70%), leading to significant differences in the content of methionine at 36 h, which brought the rapid increase forward by 12 h in the embryo and endosperm. Transcriptome analysis shows that methionine mainly affects the proliferation and differentiation of cells in the embryo, and the degradation of storage substances and signal transduction in the endosperm. In particular, multiple phenylpropanoid biosynthetic genes were triggered upon methionine treatment during germination. These results provide a theoretical foundation for promoting maize seed germination and serve as a valuable theoretical resource for seed priming strategies.

Combined Analysis of Untargeted Metabolomics and Transcriptomics Revealed Seed Germination and Seedling Establishment in Zelkova schneideriana

“…The significant enrichment of numerous DEGs and DEMs in the phenylpropanoid pathway suggests that lignin biosynthesis plays a crucial role in seed germination and seeding establishment of Z. schneideriana. Previous studies on seed germination in other plants have highlighted the involvement of the phenylpropanoid pathway [25,42]. In this study, most metabolites within the phenylpropanoid pathway exhibited increased levels after stage A, indicating that phenylpropanoid metabolism may be primarily activated following dormancy release.…”

“…Gene expression levels were estimated using RSEM [40] for each sample. The sequenced reads were aligned to the unigene library using Bowtie [41], expression levels were estimated by integrating RSEM [42], and the FPKM value was utilized to quantify the expression abundance of the corresponding unigene. Differential expression analysis of the two conditions/groups was performed using the DESeq R package (1.10.1).…”