Drought stress responses deconstructed: A comprehensive approach for Norway spruce seedlings using high-throughput phenotyping with integrated metabolomics and transcriptomics.

Abstract

Karst L.) is one of the most ecologically and economically significant tree species in Europe, accounting for nearly half of the continent's forest economic value. However, drought is a significant stress factor associated with increasing Norway spruce mortality across Europe. Provenance trials, a traditional approach to assess adaptive variation, face limitations stemming from the finite number of sites, seed sources involved, and their required labor-intensive nature. In response, we developed a comprehensive multisensor high-throughput phenotyping method and integrated it with metabolomics, transcriptomics, and anatomical analyses to study the drought stress responses in two climatically contrasting but geographically proximal provenances at the seedling stage by exposing them to drought stress for a period of 21 days. Based on more than 50 physiological and growth-related traits assessed by the phenotyping platform, it was possible to characterize early and late drought stress responses. Consistent with phenotypic data, mRNA-seq, and metabolic profiles revealed apparent differences between treatments. While during the drought stress the metabolic data indicated an increased production of ABA, α-tocopherol, zeaxanthin, lutein, and phenolics, mRNA-seq showed modulation of related pathways and downregulation of photosystem transcripts. Although drought responses were largely conserved between the two provenances, they differed phenotypically in traits related to the activation of re-oxidation of the plastoquinone pool, and molecularly in transcriptional and phenolic profiles. In conclusion, our study demonstrates the potential of the high-throughput phenotyping approach for evaluating drought stress adaptation in Norway spruce thus accelerating the screening and selection of best adapted provenances.

Code and data availability

The article describes multisensor HTPP phenotyping of Norway spruce seedlings with integrated metabolomics and transcriptomics, but no public phenotype/trait dataset, plant images, analysis code, or trained models are deposited. The only data availability statement concerns RNA-seq (PRJNA1043659), which is a molecular-

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