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3. The GenTree Platform: growth traits and tree-level environmental data in 12 European forest tree species

Author

Opgenoorth, Lars, Dauphin, Benjamin, Benavides, Raquel, Heer, Katrin, Alizoti, Paraskevi, Martínez-Sancho, Elisabet, Alía, Ricardo, Ambrosio, Olivier, Audrey, Albet, Auñón, Francisco, Avanzi, Camilla, Avramidou, Evangelia, Bagnoli, Francesca, Barbas, Evangelos, Bastias, Cristina C, Bastien, Catherine, Ballesteros, Eduardo, Beffa, Giorgia, Bernier, Frédéric, Bignalet, Henri, Bodineau, Guillaume, Bouic, Damien, Brodbeck, Sabine, Brunetto, William, Buchovska, Jurata, Buy, Melanie, Cabanillas-Saldaña, Ana M, Carvalho, Bárbara, Cheval, Nicolas, Climent, José M, Correard, Marianne, Cremer, Eva, Danusevičius, Darius, Del Caño, Fernando, Denou, Jean-Luc, Di Gerardi, Nicolas, Dokhelar, Bernard, Ducousso, Alexis, Nilsen, Anne Eskild, Farsakoglou, Anna-Maria, Fonti, Patrick, Ganopoulos, Ioannis, García Del Barrio, José M, Gilg, Olivier, González-Martínez, Santiago C, Graf, René, Gray, Alan, Grivet, Delphine, Gugerli, Felix, Hartleitner, Christoph, Hollenbach, Enja, Hurel, Agathe, Issehut, Bernard, Jean, Florence, Jorge, Veronique, Jouineau, Arnaud, Kappner, Jan-Philipp, Kärkkäinen, Katri, Kesälahti, Robert, Knutzen, Florian, Kujala, Sonja T, Kumpula, Timo A, Labriola, Mariaceleste, Lalanne, Celine, Lambertz, Johannes, Lascoux, Martin, Lejeune, Vincent, Le-Provost, Gregoire, Levillain, Joseph, Liesebach, Mirko, López-Quiroga, David, Meier, Benjamin, Malliarou, Ermioni, Marchon, Jérémy, Mariotte, Nicolas, Mas, Antonio, Matesanz, Silvia, Meischner, Helge, Michotey, Célia, Milesi, Pascal, Morganti, Sandro, Nievergelt, Daniel, Notivol, Eduardo, Østreng, Geir, Pakull, Birte, Perry, Annika, Piotti, Andrea, Plomion, Christophe, Poinot, Nicolas, Pringarbe, Mehdi, Puzos, Luc, Pyhäjärvi, Tanja, Raffin, Annie, Ramírez-Valiente, José A, Rellstab, Christian, Remi, Dourthe, Richter, Sebastian, Robledo-Arnuncio, Juan J, San Segundo, Sergio, Savolainen, Outi, Schueler, Silvio, Schneck, Volker, Scotti, Ivan, Semerikov, Vladimir, Slámová, Lenka, Sønstebø, Jørn Henrik, Spanu, Ilaria, Thevenet, Jean, Tollefsrud, Mari Mette, Turion, Norbert, Vendramin, Giovanni Giuseppe, Villar, Marc, von Arx, Georg, Westin, Johan, Fady, Bruno, Myking, Tor, Valladares, Fernando, Aravanopoulos, Filippos A, Cavers, Stephen, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Philipps Universität Marburg = Philipps University of Marburg, Department of Biogeography and Global Change, Museo Nacional de Ciencias Naturales [Madrid] (MNCN), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Aristotle University of Thessaloniki, Department of Forest Ecology and Genetics, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria = National Institute for Agricultural and Food Research and Technology (INIA), Ecologie des Forêts Méditerranéennes (URFM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité expérimentale Forêt Pierroton (UEFP), Istituto di Bioscienze e BioRisorse [Palermo] (IBBR), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Biologie intégrée pour la valorisation de la diversité des Arbres et de la Forêt (BioForA), Office national des forêts (ONF)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique et Biomasse Forestières ORléans (GBFOR), Vytautas Magnus University - Vytauto Didziojo Universitetas (VDU), Unité de Recherche Génomique Info (URGI), Gobierno de Aragon, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Unité Expérimentale Entomologie et Forêt Méditerranéenne (UEFM), Bavarian Office for Forest Seeding and Planting, Partenaires INRAE, Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO), UK Centre for Ecology & Hydrology, Natural Environment Research Council (NERC), LIECO GmbH & Co KG, Natural Resources Institute Finland (LUKE), University of Oulu, Department of Ecology and Genetics [Uppsala] (EBC), Uppsala University, SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Thunen Institute of Forest Ecosystems, Thünen Institute, Área de Biodiversidad y Conservación, Universidad Rey Juan Carlos, Universidad Rey Juan Carlos [Madrid] (URJC), Austrian Research Centre for Forests (BFW), Institute of Plant and Animal Ecology, Ural Branch of Russian Academy of Sciences (UB RAS), Skogforsk - Swedish Forestry Research Institute, Swiss Secretariat for Education, Research and Innovation (SERI) 6.0032, European Project: 676876,H2020,H2020-SFS-2015-2,GenTree(2016), Philipps Universität Marburg, Museo Nacional de Ciencias Naturales (CSIC), Consiglio Nazionale delle Ricerche (CNR), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Office National des Forêts (ONF)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centro de Investigacion Y Tecnologia Agroalimentaria de Aragon, Norwegian Institute of Bioeconomy Research (NIBIO), and Centro de Investigacion y Tecnologia Agroalimentaria de Aragon (CITA)

Subjects
crown size, fruit number, Skogsvetenskap, bark thickness, AcademicSubjects/SCI02254, DBH, Forest Science, soil depth, forking index, Botany, Pinus sylvestris, Botanik, Forests, Data Note, stem straightness, Ecology and Environment, Trees, regeneration, branch angle, Fagus, AcademicSubjects/SCI00960, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Picea, height
Abstract

Background: Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information. Findings: The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species’ geographic ranges and reflecting local environmental gradients. Conclusion: The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available.

Published
2021

4. Estimating genomic diversity and population differentiation - an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri.

Author

Fischer, Martin C., Rellstab, Christian, Leuzinger, Marianne, Roumet, Marie, Gugerli, Felix, Shimizu, Kentaro K., Holderegger, Rolf, and Widmer, Alex

Subjects
*MICROSATELLITE repeats, *ARABIDOPSIS halleri, *SINGLE nucleotide polymorphisms, *GENOMES, *NUCLEOTIDE sequencing
Abstract

Background: Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq). Results: Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-He) was not significantly correlated with genome-wide SNP diversity estimates (SNP-He and θWatterson) in A. halleri. Instead, microsatellite allelic richness (Ar) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (FST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genomewide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation. Conclusions: We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal. [ABSTRACT FROM AUTHOR]

Published
2017
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5. Using joint multivariate analyses of leaf morphology and molecular-genetic markers for taxon identification in three hybridizing European white oak species ( Quercus spp.).

Author

Rellstab, Christian, Bühler, Andreas, Graf, René, Folly, Catherine, and Gugerli, Felix

Subjects
LEAF morphology, PLANT molecular genetics, GENETIC markers in plants, WHITE oak, PLANT hybridization, PLANT classification
Abstract

• Key message : We show that joint multivariate analyses of leaf morphological characters and molecular-genetic markers improve the taxonomic assignment in hybridizing European white oaks. However, model-based approaches using genetic data alone represent straightforward alternatives to laborious, detailed morphological assessments. • Context : In European white oaks, species delimitation is debated because of large overlap of morphological characteristics likely due to hybridization. • Aims : We tested whether joint multivariate analyses of leaf morphology and molecular markers improve the identification of three oak species ( Quercus petraea, Quercus pubescens, Quercus robur) compared to approaches using morphological or genetic variables only. • Methods : We assessed 13 leaf morphological characters and applied eight nuclear microsatellite markers in almost 1400 trees of 71 oak populations across Switzerland. We performed two multivariate approaches with three variable sets (morphology, genetics, combined) and assessed their performance in separating the taxa. We also compared the taxon assignment to a model-based clustering approach ( Structure) based on genetic data alone. • Results : A joint use of morphological and genetic variables led to an improved taxon assignment. Whereas Q. robur could clearly be separated from the two other taxa, there was a certain overlap between Q. petraea and Q. pubescens. The Structure clustering led to the same taxon assignment in 85 % of the individuals. • Conclusion : It is important to consider both morphological and genetic properties in morphologically similar and hybridizing species. However, it might be more efficient to concentrate only on genetic markers than on time-consuming morphological assessments. [ABSTRACT FROM AUTHOR]

Published
2016
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