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Metabarcode and transcriptome datasets of Pinus sylvestris to assess fungal phyllosphere and disease dynamics

Moore, Beth; Perry, Annika ORCID: https://orcid.org/0000-0002-7889-7597; Kaur, Sundeep; Crampton, Bridget; Gurung, Amir; Beaton, Joan K.; Cottrell, Joan E.; Stockan, Jenni A.; Smith, V. Anne; Morris, Jenny; Hedley, Pete E.; Nemeth, Krisztian ORCID: https://orcid.org/0009-0009-4081-1573; Barber, Hattie; Cavers, Stephen ORCID: https://orcid.org/0000-0003-2139-9236; Jones, Susan. 2026 Metabarcode and transcriptome datasets of Pinus sylvestris to assess fungal phyllosphere and disease dynamics. Scientific Data. 10.1038/s41597-026-08035-z

Abstract

Understanding how host–microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding and transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum . We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny–provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises of ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host–microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

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