Hybrid necrosis is a well-known reproductive isolation mechanism in plant species, and an autoimmune response is generally considered to trigger hybrid necrosis through epistatic interaction between disease resistance-related genes in hybrids. In common wheat, the complementary Ne1 and Ne2 genes control hybrid necrosis, defined as type I necrosis. Two other types of hybrid necrosis (type II and type III) have been observed in interspecific hybrids between tetraploid wheat and Aegilops tauschii. Another type of hybrid necrosis, defined here as type IV necrosis, has been reported in F1 hybrids between Triticum urartu and some accessions of Triticum monococcum ssp. aegilopoides. In types I, III and IV, cell death occurs gradually starting in older tissues, whereas type II necrosis symptoms occur only under low temperature. To compare comprehensive gene expression patterns of hybrids showing growth abnormalities, transcriptome analysis of type I and type IV necrosis was performed using a wheat 38k oligo-DNA microarray. Defense-related genes including many WRKY transcription factor genes were dramatically up-regulated in plants showing type I and type IV necrosis, similarly to other known hybrid abnormalities, suggesting an association with an autoimmune response. Reactive oxygen species generation and necrotic cell death were effectively inhibited by ZnCl2 treatment in types I, III and IV necrosis, suggesting a significant association of Ca(2+) influx in upstream signaling of necrotic cell death in wheat hybrid necrosis.

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Potato (Solanum tuberosum L.) tubers are usually harvested once a year; thus, long-term storage is required to supply quality-assured tubers throughout the year. Further, an applicable method to predict tuber quality during storage is needed. In this study, gas chromatography-mass spectrometry (GC/MS) metabolomics was applied to identify applicable biomarkers for prediction of potato chip color based on 3 years’ field-grown tubers. The projections to latent structures (PLS) prediction model, calculated from a metabolome data set obtained before storage, was consistent with actual measured chip color values. Additionally, GC with frame ionization detector (GC/FID) metabolite fingerprinting simultaneously re-constructed more reliable and relevant prediction models for chip color quality compared to GC/MS. Moreover, nine metabolites detected by GC/MS analysis were further validated as applicable prediction markers. This strategy will provide a practical and cost-effective quality-control tool for potato processing manufacturers on an industrial scale.