1. The FORGENIUS genomic resources : new genotyping tools and genomic data for 23 forest tree species and their genetic conservation unitsSara Pinosio, Francesca Bagnoli, Camilla Avanzi, Maria Beatrice Castellani, Arcangela Frascella, Susan McEvoy, Sanna Olsson, Ilaria Spanu, Elia Vajana, Marko Bajc, Gregor Božič, Rok Damjanić, Natalija Dovč, Luka Krajnc, Marija Kravanja, Gal Oblišar, Gregor Skoberne, Marjana Westergren, 2026, original scientific article Abstract: Genetic diversity is a critical but often overlooked component of biological diversity. The European H2020 FORGENIUS project is aimed at increasing the quality and quantity of genetic data to start monitoring the European network of forest Genetic Conservation Units (GCUs). A first step in this direction was developing standardised genomic resources for 23 forest tree species, spanning from rare and scattered (e.g., Abies nebrodensis and Torminalis glaberrima) to widespread and stand-forming, economically relevant ones (e.g., Fagus sylvatica, Picea abies and Pinus sylvestris). Here, we describe the development and application of targeted genotyping tools, primarily based on Single Primer Enrichment Technology (SPET), along with existing SNP arrays for the selected species. The SPET panels developed in FORGENIUS were designed to capture ⁓10,000 loci per species, balancing species-specific and randomly distributed regions to ensure broad genome coverage and minimise ascertainment bias. Across 7220 genotyped trees, we identified over 1.8 million single nucleotide polymorphisms (SNPs) covering approximately 50 Mb of DNA sequence. SPET panels demonstrated high genotyping efficiency and cross-species transferability, especially within genera such as Quercus and Abies. They represent a cost-effective, flexible, and scalable solution for population-level genetic assessments across diverse taxa, enabling standardised, genome-wide characterisation of the GCU network. These resources not only promote the establishment of genetic monitoring, support genetically informed conservation strategies and improve our understanding of adaptive responses in European forests, but also enhance species delimitation and hybrid detection, and enable the characterisation of phylogenetically related but previously underexplored species.
Keywords: forest tree species, genetic conservation units, genetic diversity, genetic monitoring, single primer enrichment technology, targetedgenotyping, SNP, SPET
Published in DiRROS: 06.03.2026; Views: 238; Downloads: 196
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2. Genetic assignment at different geographical levels : a case study in a forest tree species (Pinus pinaster Ait.) using SNP markersSanna Olsson, Delphine Grivet, Marjana Westergren, Santiago C. González-Martínez, Ricardo Alía, Juan José Robledo-Arnuncio, 2025, original scientific article Abstract: Genetic markers can assist in the identification of the stock origin in different organisms. Comparative studies of forest tree provenances have demonstrated that forest tree populations differ in performance across environments and at multiple geographic levels: populations nested within regions nested within gene pools. These levels are critical for conservation and sustainable use of genetic resources: regions of provenance are key units for seed marketing, while populations guide reproductive material collection under most seed regulations. Despite their potential, genetic methods have rarely been applied to identify forest tree origins due to methodological (sufficient number of highly discriminatory markers) and practical (construction of a baseline composed of a representative selection of samples) challenges. In our study, we analyzed a genomic dataset comprising 10,185 SNPs from 1579 samples of Pinus pinaster, a species with strong population structure, across 86 populations, 45 regions of provenance, and 10 gene pools, to discriminate among these hierarchical levels and assign individuals to them. We used two software packages to evaluate the reliability of our baseline dataset (i.e., reference data) for genetic discrimination and assignment: RUBIAS, which performs genetic stock identification and associated tasks, and assignPOP, implementing a supervised machine-learning genetic-assignment framework. Using numerical validation analyses, we assessed their suitability and limitations for origin inference at each geographical level. Our results indicate that origin assignment is reliable in P. pinaster at the gene pool and region of provenance levels, but less so at the population level, provided that the 10 K SNP markers and a comprehensive genetic baseline are used. Incomplete baselines may result in wrong assignments at any hierarchical level, irrespective of sampling intensity for sampled candidate origins. We provide an extensive and publicly available baseline for P. pinaster, offering a useful tool for the management of forest genetic resources of this economically and ecologically important tree species.
Keywords: gene pool, genetic assignment, maritime pine, origin identification, region of provenance, SNP marker
Published in DiRROS: 03.12.2025; Views: 440; Downloads: 246
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3. Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms : Application to European autochthonous and cosmopolitan pig breedsGiuseppina Schiavo, Francesca Bertolini, Samuele Bovo, Giuliano Galimberti, Maria Muñoz, Riccardo Bozzi, Marjeta Čandek-Potokar, Cristina Ovilo, Luca Fontanesi, 2024, original scientific article Keywords: genome, population genomics, random forest, signatures of selection, SNP
Published in DiRROS: 31.12.2024; Views: 933; Downloads: 327
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