Metabolic profiling of maize seeds with both insect- and herbicide-resistance genes (cry1Ab and epsps), dual herbicide-resistance genes (epsps and pat), and natural genotypic varieties
Abstract Background Widely targeted metabolomics was applied to estimate the differences in the metabolite profiles of maize seeds from 3 natural genotypic varieties and 4 genetically modified (GM) lines. Results Pairwise comparison with their isogenic controls revealed 71, 121, 43 and 95 differenti...
Guardado en:
Autores principales: | , , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
SpringerOpen
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/aa8a175f8f294fb6826d5be336deced5 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: | Abstract Background Widely targeted metabolomics was applied to estimate the differences in the metabolite profiles of maize seeds from 3 natural genotypic varieties and 4 genetically modified (GM) lines. Results Pairwise comparison with their isogenic controls revealed 71, 121, 43 and 95 differentially accumulated metabolites (DAMs) in GM maize seeds of C0030.2.4, C0030.3.5, C0010.1.1 and C0010.3.1, respectively. KEGG pathway enrichment analysis showed that most of these DAMs participated in the biosynthesis of secondary metabolites and purine metabolism in GM maize C0030.2.4 and C0030.3.5, but participated in tryptophan metabolism and 2-oxocarboxylic acid metabolism in C0010.3.1 seeds and in metabolic pathways and the biosynthesis of secondary metabolites in C0010.1.1 seeds. The data also showed that the differences in metabolite accumulation, both total DAMs and co-DAMs, among the different natural genotypic varieties (418 DAMs and 39 co-DAMs) were greater than those caused by genetic modification (330 DAMs and 3 co-DAMs). Conclusions None of the DAMs were identified as new or unintended, showing only changes in abundance in the studied maize seeds. The metabolite profile differences among the 3 non-GM lines were more notable than those among GM lines. Different genetic backgrounds affect metabolite profiling more than gene modification itself. Graphic abstract |
---|