Deciphering transcriptomic signatures explaining the phenotypic plasticity of non-heading lettuce genotypes under artificial light conditions

Author:

Yamashita HirotoORCID,Wada Kaede C.,Inagaki NoritoshiORCID,Fujimoto Zui,Yonemaru Jun-ichi,Itoh HironoriORCID

Abstract

AbstractElucidating the mechanisms and pathways involved in genotype–environment (G×E) interactions and phenotypic plasticity is critical for improving plant growth. Controlled environment agricultural systems allow growers to modulate the environment for particular genotypes. In this study, we evaluated the effects of interactions among 14 genotypes and four artificial light environments on leaf lettuce phenotypes and dissected the underlying molecular mechanism via transcriptome-based modeling. Variations in morphological traits and phytochemical contents in response to artificial light treatments revealed significant G×E interactions. The appropriate genotype and artificial light combinations for maximizing phenotypic expression were determined on the basis of a joint regression analysis and the additive main effect and multiplicative interaction model for these G×E interactions. Transcriptome-based regression modeling explained approximately 50%–90% of the G×E variations. Further analyzes indicatedRed Lettuce Leaves 4 (RLL4) regulates UV-B and blue light signaling through the effects of the HY5–MBW pathway on flavonoid biosynthesis and contributes to natural variations in the light-responsive plasticity of lettuce traits. Our study represents an important step toward elucidating the phenotypic variations due to G×E interactions in non-heading lettuce under artificial light conditions.HighlightsSeveral morphological characteristics of lettuce genotypes were altered by different light wavelengths.A defectiveRLL4allele (rll4) induces the expression of downstream genes related to UV-B and blue light signaling through activation of the HY5–MBW pathway, which enhances phytochemical accumulation in lettuce.G×E analyzes identified the ideal genotype and artificial light combinations for individual phenotypes.Transcriptome-based modeling explained approximately 50%–90% of the G×E variations.

Publisher

Cold Spring Harbor Laboratory

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