A metabolomics and transcriptomics resource for the identification of candidate genes in the biosynthesis of specialized metabolites in Populus tremula
Aims: Plants produce a diversity of specialized metabolites that can have substantial impacts on plant function, their interaction with other organisms, beneficial properties and uses e.g. for human health, bioenergy and pharmaceutical applications. Despite their importance, the biosynthetic pathways and associated enzymes for most specialized metabolites have not been identified. The integration of multi-omic data represents a powerful approach to link genes encoding enzymes and their regulatory factors to metabolite biosynthesis. However, suitable multi-omics data resources for this approach are largely lacking.    Data resource: We present a comprehensive dataset comprising matched samples assayed using untargeted Liquid Chromatography Mass Spectrometry (LC-MS) and mRNA-Sequencing data from various organs of Populus tremula L. to enable integrated data analysis approaches to link among-sample variation in metabolite abundance to correlated gene expression profiles. The resource comprises dual-omics profiling of samples in a collection of genotypes known to produce contrasting sets of salicinoid phenolic glucoside (SPGs), specialized metabolites involved in plant defense.   Key results: We implemented a reproducible pipeline for analysis of the LC-MS data including identification and predicted annotation of novel SPGs. We demonstrate utility of the resource by identifying candidate genes for the production of SPGs with a cinnamoyl moiety. Our approach integrated gene and metabolite differential analyses with a gene co-expression network. The network modules with the highest correlation to cinnamoyl-SPGs also contained the greatest proportion of differentially expressed genes between genotypes with contrasting SPG occurrence. Among the up-regulated genes within these modules, two HXXXD-type acyltransferases and one UDP-glucosyltransferase represented particularly compelling candidate genes for downstream characterization.    Community access: The combined gene expression and LC-MS resource is integrated into the PlantGenIE.org resource to facilitate community access and reuse and all raw and processed data is available to facilitate reuse