Fusarium verticillioides is the causal agent of Fusarium ear rot in maize and contaminates the grain with fumonisins, a family of mycotoxins that affects feed and food. Candidate genes for kernel resistance to F. verticillioides infection were detected through the comparison of resistant (CO441) and susceptible (CO354) maize inbred lines, through transcriptomic (RNASeq) and metabolomic analyses. We observed 2,250 and 2,442 differentially expressed genes at 72 hours post inoculation (hpi) for the resistant and susceptible maize genotypes, respectively, of which 1,028 were in common and showed 5,342 SNP variants. Our data indicated that the resistance in CO441 was based on differences in basal gene expression between the two genotypes. At 72 hpi the transcriptional modulation remained higher in the resistant line, involving the specific changes of numerous transcripts encoding components of signal transduction cascades and enzymes required for the synthesis of secondary metabolites. The metabolic profiles of the same kernel samples were investigated with Liquid Chromatography-High Resolution Mass Spectrometry. Stable isotopic labeling combined to MetExtract algorithm allowed the automatic detection and prediction of carbon atoms of biological metabolites. 830 and 1135 peaks resulted in negative and positive ionization mode, respectively. Metabolite annotation was achieved by searching accurate m/z values, carbon atom numbers and type of ion species in MaizeCyc and KEGG databases. Statistics on consistently detected metabolites (around 85%) demonstrated a clear separation between maize genotypes and treatments. A large amount of metabolites and transcripts resulted involved in defense pathways: biosynthesis of aromatic amino acids, phenylpropanoids, flavonoids and oxylipin metabolism. The identification of differentially expressed plant genes and metabolites after pathogen interaction will produce useful tools for the identification of candidate genes, the development of molecular markers and their use for selection of resistant maize genotypes by means of marker assisted selection.
Maschietto, V., Lanubile, A., Battaglia, R., Marocco, A., Breeding maize for resistance to Fusarium ear rot: a candidate gene approach from the integration of metabolomics and transcriptomics., Poster, in 56th Annual Maize Genetics ConferenceProgram and Abstracts, (Beijing, China, 13-March 16-December 2014), Maize GDB, Beijing 2014: 67-67 [http://hdl.handle.net/10807/61619]
Breeding maize for resistance to Fusarium ear rot: a candidate gene approach from the integration of metabolomics and transcriptomics.
Maschietto, Valentina;Lanubile, Alessandra;Battaglia, Raffaella;Marocco, Adriano
2014
Abstract
Fusarium verticillioides is the causal agent of Fusarium ear rot in maize and contaminates the grain with fumonisins, a family of mycotoxins that affects feed and food. Candidate genes for kernel resistance to F. verticillioides infection were detected through the comparison of resistant (CO441) and susceptible (CO354) maize inbred lines, through transcriptomic (RNASeq) and metabolomic analyses. We observed 2,250 and 2,442 differentially expressed genes at 72 hours post inoculation (hpi) for the resistant and susceptible maize genotypes, respectively, of which 1,028 were in common and showed 5,342 SNP variants. Our data indicated that the resistance in CO441 was based on differences in basal gene expression between the two genotypes. At 72 hpi the transcriptional modulation remained higher in the resistant line, involving the specific changes of numerous transcripts encoding components of signal transduction cascades and enzymes required for the synthesis of secondary metabolites. The metabolic profiles of the same kernel samples were investigated with Liquid Chromatography-High Resolution Mass Spectrometry. Stable isotopic labeling combined to MetExtract algorithm allowed the automatic detection and prediction of carbon atoms of biological metabolites. 830 and 1135 peaks resulted in negative and positive ionization mode, respectively. Metabolite annotation was achieved by searching accurate m/z values, carbon atom numbers and type of ion species in MaizeCyc and KEGG databases. Statistics on consistently detected metabolites (around 85%) demonstrated a clear separation between maize genotypes and treatments. A large amount of metabolites and transcripts resulted involved in defense pathways: biosynthesis of aromatic amino acids, phenylpropanoids, flavonoids and oxylipin metabolism. The identification of differentially expressed plant genes and metabolites after pathogen interaction will produce useful tools for the identification of candidate genes, the development of molecular markers and their use for selection of resistant maize genotypes by means of marker assisted selection.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.