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Multi-Omics Analyses Reveal Systemic Insights into Maize Vivipary

Maize vivipary, precocious seed germination on the ear, affects yield and seed quality. The application of multi-omics approaches, such as transcriptomics or metabolomics, to classic vivipary mutants can potentially reveal the underlying mechanism. Seven maize vivipary mutants were selected for tran...

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Detalles Bibliográficos
Autores principales: Wang, Yiru, Zhang, Junli, Sun, Minghao, He, Cheng, Yu, Ke, Zhao, Bing, Li, Rui, Li, Jian, Yang, Zongying, Wang, Xiao, Duan, Haiyang, Fu, Junjie, Liu, Sanzhen, Zhang, Xuebin, Zheng, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8618366/
https://www.ncbi.nlm.nih.gov/pubmed/34834800
http://dx.doi.org/10.3390/plants10112437
Descripción
Sumario:Maize vivipary, precocious seed germination on the ear, affects yield and seed quality. The application of multi-omics approaches, such as transcriptomics or metabolomics, to classic vivipary mutants can potentially reveal the underlying mechanism. Seven maize vivipary mutants were selected for transcriptomic and metabolomic analyses. A suite of transporters and transcription factors were found to be upregulated in all mutants, indicating that their functions are required during seed germination. Moreover, vivipary mutants exhibited a uniform expression pattern of genes related to abscisic acid (ABA) biosynthesis, gibberellin (GA) biosynthesis, and ABA core signaling. NCED4 (Zm00001d007876), which is involved in ABA biosynthesis, was markedly downregulated and GA3ox (Zm00001d039634) was upregulated in all vivipary mutants, indicating antagonism between these two phytohormones. The ABA core signaling components (PYL-ABI1-SnRK2-ABI3) were affected in most of the mutants, but the expression of these genes was not significantly different between the vp8 mutant and wild-type seeds. Metabolomics analysis integrated with co-expression network analysis identified unique metabolites, their corresponding pathways, and the gene networks affected by each individual mutation. Collectively, our multi-omics analyses characterized the transcriptional and metabolic landscape during vivipary, providing a valuable resource for improving seed quality.