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Aspen (Populus tremula L.) is a keystone species and a model system for forest tree genomics. We present an updated resource comprising a chromosome-scale assem- bly, population genetics and genomics data. Using the resource, we explore the genetic basis of natural variation in leaf size and shape, traits with complex genetic architecture.

We generated the genome assembly using long-read sequencing, optical and high-density genetic maps. We conducted whole-genome resequencing of the Umeå Aspen (UmAsp) collection. Using the assembly and re-sequencing data from the UmAsp, Swedish Aspen (SwAsp) and Scottish Aspen (ScotAsp) collections we performed genome-wide association analyses (GWAS) using Single Nucleotide Polymorphisms (SNPs) for 26 leaf physiognomy phenotypes. We conducted Assay of Transposase Accessible Chromatin sequencing (ATAC-Seq), identified genomic regions of accessible chromatin, and subset SNPs to these regions, improving the GWAS detection rate. We identified candidate long non-coding RNAs in leaf samples, quantified their expression in an updated co-expression network, and used this to explore the functions of candidate genes identified from the GWAS.

A GWAS found SNP associations for seven traits. The associated SNPs were in or near genes annotated with developmental functions, which represent candidates for further study. Of particular interest was a !177-kbp region harbouring associations with several leaf phenotypes in ScotAsp.

We have incorporated the assembly, population genetics, genomics, and GWAS data into the PlantGenIE.org web resource, including updating existing genomics data to the new genome version, to enable easy exploration and visualisation. We provide all raw and processed data to facilitate reuse in future studies.

This study aims to identify candidate genes involved in the biosynthesis of salicinoid phenolic glycosides (SPGs), a group of specialised metabolites characteristic of the Salicaceae family. While the integration of multi-omics data represents a powerful approach to link genes encoding enzymes and their regulatory factors to metabolite biosynthesis, suitable multi-omics data resources are scarce. We present a comprehensive dataset comprising untargeted liquid chromatography–mass spectrometry (LC–MS) and mRNA-sequencing data from various organs of European aspen (Populus tremula L.) and from genotypes that produce contrasting sets of SPGs. We present a reproducible pipeline for the analysis of the LC–MS data, including predicted annotation of potential novel SPGs. We demonstrate the utility of the resource by identifying candidate genes involved in the biosynthesis of SPGs with a cinnamoyl moiety. By integrating gene and metabolite differential analyses with a gene co-expression network, we identified two HXXXD-type acyltransferase genes and one UDP-glucosyltransferase gene as candidates for future downstream characterisation. The combined gene expression and metabolomics resource is integrated into PlantGenIE.org to facilitate easy access and data mining. All raw data are available in public databases, and all data and results files are available at an associated Figshare repository.