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Overexpression of chalcone isomerase in apple reduces phloridzin accumulation and increases susceptibility to herbivory by two-spotted mites.

Andrew P DareSumathi TomesTony K McGhieJohn W van KlinkManoharie SandanayakaIan C HallettRoss G Atkinson
Published in: The Plant journal : for cell and molecular biology (2020)
Apples (Malus spp.) accumulate significant quantities of the dihydrochalcone glycoside, phloridzin, whilst pears (Pyrus spp.) do not. To explain this difference, we hypothesized that a metabolic bottleneck in the phenylpropanoid pathway might exist in apple. Expression analysis indicated that transcript levels of early phenylpropanoid pathway genes in apple and pear leaves were similar, except for chalcone isomerase (CHI), which was much lower in apple. Apples also showed very low CHI activity compared with pear. To relieve the bottleneck at CHI, transgenic apple plants overexpressing the Arabidopsis AtCHI gene were produced. Unlike other transgenic apples where phenylpropanoid flux was manipulated, AtCHI overexpression (CHIox) plants were phenotypically indistinguishable from wild-type, except for an increase in red pigmentation in expanding leaves. CHIox plants accumulated slightly increased levels of flavanols and flavan-3-ols in the leaves, but the major change was a 2.8- to 19-fold drop in phloridzin concentrations compared with wild-type. The impact of these phytochemical changes on insect preference was studied using a two-choice leaf assay with the polyphagous apple pest, the two-spotted spider mite (Tetranychus urticae Koch). Transgenic CHIox leaves were more susceptible to herbivory, an effect that could be reversed (complemented) by application of phloridzin to transgenic leaves. Taken together, these findings shed new light on phenylpropanoid biosynthesis in apple and suggest a new physiological role for phloridzin as an antifeedant in leaves.
Keyphrases
  • wild type
  • essential oil
  • transcription factor
  • genome wide identification
  • cell proliferation
  • genome wide
  • high throughput
  • decision making
  • bioinformatics analysis
  • genome wide analysis