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Start Over Author "Kujala, Sonja T" Publisher oxford university press
5 results on '"Kujala, Sonja T"'

1. Between but not within species variation in the distribution of fitness effects

Author

James, Jennifer, Kastally, Chedly, Budde, Katharina B., González-Martínez, Santiago C., Milesi, Pascal, Pyhäjärvi, Tanja, Alizoti, Paraskevi, Alía, Ricardo, Ambrosio, Olivier, Aravanopoulos, Filippos A., von Arx, Georg, Audrey, Albet, Auñón, Francisco, Avanzi, Camilla, Avramidou, Evangelia, Bagnoli, Francesca, Bajc, Marko, Ballesteros, Eduardo, Barbas, Evangelos, del Barrio, José M. García, Bastias, Cristina C., Bastien, Catherine, Beffa, Giorgia, Benavides, Raquel, Benoit, Vanina, Bernier, Frédéric, Bignalet, Henri, Bodineau, Guillaume, Bouic, Damien, Brodbeck, Sabine, Brunetto, William, Buchovska, Jurata, Buret, Corinne, Buy, Melanie, Cabanillas-Saldaña, Ana M., Carvalho, Bárbara, Cavers, Stephen, Del Caño, Fernando, Cervantes, Sandra, Cheval, Nicolas, Climent, José M., Correard, Marianne, Cremer, Eva, Danusevičius, Darius, Dauphin, Benjamin, Denou, Jean-Luc, Dokhelar, Bernard, Ducousso, Alexis, Fady, Bruno, Faivre-Rampant, Patricia, Farsakoglou, Anna-Maria, Fonti, Patrick, Ganopoulos, Ioannis, Gilg, Olivier, De Girardi, Nicolas, Graf, René, Gray, Alan, Grivet, Delphine, Gugerli, Felix, Hartleitner, Christoph, Heer, Katrin, Hollenbach, Enja, Hurel, Agathe, Issenhuth, Bernard, Jean, Florence, Jorge, Véronique, Jouineau, Arnaud, Kappner, Jan-Philipp, Kesälahti, Robert, Knutzen, Florian, Kujala, Sonja T., Kumpula, Timo A., Kärkkäinen, Katri, Labriola, Mariaceleste, Lalanne, Celine, Lambertz, Johannes, Le-Provost, Gregoire, Lejeune, Vincent, Lesur-Kupin, Isabelle, Levillain, Joseph, Liesebach, Mirko, López-Quiroga, David, Malliarou, Ermioni, Marchon, Jérémy, Mariotte, Nicolas, Mas, Antonio, Matesanz, Silvia, Meier, Benjamin, Meischner, Helge, Michotey, Célia, Morganti, Sandro, Myking, Tor, Nievergelt, Daniel, Eskild Nilsen, Anne, Notivol, Eduardo, Ojeda, Dario I., Olsson, Sanna, Opgenoorth, Lars, Ostreng, Geir, Pakull, Birte, Perry, Annika, Pinosio, Sara, Piotti, Andrea, Plomion, Christophe, Poinot, Nicolas, Pringarbe, Mehdi, Puzos, Luc, Raffin, Annie, Ramírez-Valiente, José A., Rellstab, Christian, Remi, Dourthe, Reutimann, Oliver, Richter, Sebastian, Robledo-Arnuncio, Juan J., Rogier, Odile, Sancho, Elisabet Martínez, Savolainen, Outi, Scalabrin, Simone, Schneck, Volker, Schueler, Silvio, Scotti, Ivan, Segundo, Sergio San, Semerikov, Vladimir, Slámová, Lenka, Spanu, Ilaria, Sønstebø, Jørn Henrik, Thevenet, Jean, Tollefsrud, Mari Mette, Turion, Norbert, Valladares, Fernando, Vendramin, Giovanni G., Villar, Marc, Westergren, Marjana, Westin, Johan, Lascoux, Martin, James, Jennifer, Kastally, Chedly, Budde, Katharina B., González-Martínez, Santiago C., Milesi, Pascal, Pyhäjärvi, Tanja, Alizoti, Paraskevi, Alía, Ricardo, Ambrosio, Olivier, Aravanopoulos, Filippos A., von Arx, Georg, Audrey, Albet, Auñón, Francisco, Avanzi, Camilla, Avramidou, Evangelia, Bagnoli, Francesca, Bajc, Marko, Ballesteros, Eduardo, Barbas, Evangelos, del Barrio, José M. García, Bastias, Cristina C., Bastien, Catherine, Beffa, Giorgia, Benavides, Raquel, Benoit, Vanina, Bernier, Frédéric, Bignalet, Henri, Bodineau, Guillaume, Bouic, Damien, Brodbeck, Sabine, Brunetto, William, Buchovska, Jurata, Buret, Corinne, Buy, Melanie, Cabanillas-Saldaña, Ana M., Carvalho, Bárbara, Cavers, Stephen, Del Caño, Fernando, Cervantes, Sandra, Cheval, Nicolas, Climent, José M., Correard, Marianne, Cremer, Eva, Danusevičius, Darius, Dauphin, Benjamin, Denou, Jean-Luc, Dokhelar, Bernard, Ducousso, Alexis, Fady, Bruno, Faivre-Rampant, Patricia, Farsakoglou, Anna-Maria, Fonti, Patrick, Ganopoulos, Ioannis, Gilg, Olivier, De Girardi, Nicolas, Graf, René, Gray, Alan, Grivet, Delphine, Gugerli, Felix, Hartleitner, Christoph, Heer, Katrin, Hollenbach, Enja, Hurel, Agathe, Issenhuth, Bernard, Jean, Florence, Jorge, Véronique, Jouineau, Arnaud, Kappner, Jan-Philipp, Kesälahti, Robert, Knutzen, Florian, Kujala, Sonja T., Kumpula, Timo A., Kärkkäinen, Katri, Labriola, Mariaceleste, Lalanne, Celine, Lambertz, Johannes, Le-Provost, Gregoire, Lejeune, Vincent, Lesur-Kupin, Isabelle, Levillain, Joseph, Liesebach, Mirko, López-Quiroga, David, Malliarou, Ermioni, Marchon, Jérémy, Mariotte, Nicolas, Mas, Antonio, Matesanz, Silvia, Meier, Benjamin, Meischner, Helge, Michotey, Célia, Morganti, Sandro, Myking, Tor, Nievergelt, Daniel, Eskild Nilsen, Anne, Notivol, Eduardo, Ojeda, Dario I., Olsson, Sanna, Opgenoorth, Lars, Ostreng, Geir, Pakull, Birte, Perry, Annika, Pinosio, Sara, Piotti, Andrea, Plomion, Christophe, Poinot, Nicolas, Pringarbe, Mehdi, Puzos, Luc, Raffin, Annie, Ramírez-Valiente, José A., Rellstab, Christian, Remi, Dourthe, Reutimann, Oliver, Richter, Sebastian, Robledo-Arnuncio, Juan J., Rogier, Odile, Sancho, Elisabet Martínez, Savolainen, Outi, Scalabrin, Simone, Schneck, Volker, Schueler, Silvio, Scotti, Ivan, Segundo, Sergio San, Semerikov, Vladimir, Slámová, Lenka, Spanu, Ilaria, Sønstebø, Jørn Henrik, Thevenet, Jean, Tollefsrud, Mari Mette, Turion, Norbert, Valladares, Fernando, Vendramin, Giovanni G., Villar, Marc, Westergren, Marjana, Westin, Johan, and Lascoux, Martin

Abstract

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is therefore of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, i.e., whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterised the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence and genetic background. We find statistical support for there being variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and that evolutionarily recent events, such as demographic changes and local adaptation, have little impact.

Published
2023

2. 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, Eskild Nilsen, Anne, 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, Ostreng, 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, 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, Eskild Nilsen, Anne, 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, Ostreng, 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., and Cavers, Stephen

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

Published
2021

3. Within- and between-population comparisons suggest independently acting selection maintaining parallel clines in Scots pine ( Pinus sylvestris ).

Author

Kujala ST, Avia K, Kumpula TA, Kärkkäinen H, Heikkinen J, Kärkkäinen K, and Savolainen O

Abstract

Parallel clines in traits related to adaptation in a species can be due to independent selection on a pair of traits, or due to selection in one trait resulting in a parallel cline in a correlated trait. To distinguish between the mechanisms giving rise to parallel adaptive population divergence of multiple traits along an environmental gradient we need to study variation, correlations, and selective forces within individual populations along the gradient. In many tree species, budset timing (BST) forms a latitudinal cline, and parallel clinal variation is also found in other seedling traits, such as first-year height (FYH) and fall frost injury (FFI). In this study, we set up a common garden experiment with open pollinated progeny from natural populations of Scots pine ( Pinus sylvestris ), with one large sample from single population (500 families) and smaller samples from across a latitudinal gradient. BST, FYH and induced FFI were first measured in a greenhouse. The seedlings were then planted in the field, where survival and height were measured at the age of 9 years as fitness proxies. We compared between- and within-population variation and genetic correlations of these three seedling traits, and estimated selection gradients at the family level in our main population, taking into account the potential effects of seed weight. Between-population genetic correlations between seedling traits were high (0.76-0.95). Within-population genetic correlations in the main population were lower (0.14-0.35), as in other populations (0.10-0.39). Within population, extensive adaptive variation persists in the seedling traits, in line with rather weak selection gradients, yet maintaining the clines. Although our sampling does not cover the whole cline equally, the results suggest that the individual clines in these traits are maintained by largely independently acting selection, which results in fewer constraints in adaptation under changing climate., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEN).)

Published
2023
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4. The GenTree Platform: growth traits and tree-level environmental data in 12 European forest tree species.

Author

Opgenoorth L, Dauphin B, Benavides R, Heer K, Alizoti P, Martínez-Sancho E, Alía R, Ambrosio O, Audrey A, Auñón F, Avanzi C, Avramidou E, Bagnoli F, Barbas E, Bastias CC, Bastien C, Ballesteros E, Beffa G, Bernier F, Bignalet H, Bodineau G, Bouic D, Brodbeck S, Brunetto W, Buchovska J, Buy M, Cabanillas-Saldaña AM, Carvalho B, Cheval N, Climent JM, Correard M, Cremer E, Danusevičius D, Del Caño F, Denou JL, di Gerardi N, Dokhelar B, Ducousso A, Eskild Nilsen A, Farsakoglou AM, Fonti P, Ganopoulos I, García Del Barrio JM, Gilg O, González-Martínez SC, Graf R, Gray A, Grivet D, Gugerli F, Hartleitner C, Hollenbach E, Hurel A, Issehut B, Jean F, Jorge V, Jouineau A, Kappner JP, Kärkkäinen K, Kesälahti R, Knutzen F, Kujala ST, Kumpula TA, Labriola M, Lalanne C, Lambertz J, Lascoux M, Lejeune V, Le-Provost G, Levillain J, Liesebach M, López-Quiroga D, Meier B, Malliarou E, Marchon J, Mariotte N, Mas A, Matesanz S, Meischner H, Michotey C, Milesi P, Morganti S, Nievergelt D, Notivol E, Ostreng G, Pakull B, Perry A, Piotti A, Plomion C, Poinot N, Pringarbe M, Puzos L, Pyhäjärvi T, Raffin A, Ramírez-Valiente JA, Rellstab C, Remi D, Richter S, Robledo-Arnuncio JJ, San Segundo S, Savolainen O, Schueler S, Schneck V, Scotti I, Semerikov V, Slámová L, Sønstebø JH, Spanu I, Thevenet J, Tollefsrud MM, Turion N, Vendramin GG, Villar M, von Arx G, Westin J, Fady B, Myking T, Valladares F, Aravanopoulos FA, and Cavers S

Subjects
Forests, Trees, Fagus, Picea, Pinus sylvestris
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., (© The Author(s) 2021. Published by Oxford University Press GigaScience.)

Published
2021
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5. Utilization of Tissue Ploidy Level Variation in de Novo Transcriptome Assembly of Pinus sylvestris .

Author

Ojeda DI, Mattila TM, Ruttink T, Kujala ST, Kärkkäinen K, Verta JP, and Pyhäjärvi T

Subjects
Cluster Analysis, Molecular Sequence Annotation, Organ Specificity genetics, Ovule, Computational Biology methods, Gene Expression Profiling methods, Pinus sylvestris genetics, Ploidies, Transcriptome
Abstract

Compared to angiosperms, gymnosperms lag behind in the availability of assembled and annotated genomes. Most genomic analyses in gymnosperms, especially conifer tree species, rely on the use of de novo assembled transcriptomes. However, the level of allelic redundancy and transcript fragmentation in these assembled transcriptomes, and their effect on downstream applications have not been fully investigated. Here, we assessed three assembly strategies for short-reads data, including the utility of haploid megagametophyte tissue during de novo assembly as single-allele guides, for six individuals and five different tissues in Pinus sylvestris We then contrasted haploid and diploid tissue genotype calls obtained from the assembled transcriptomes to evaluate the extent of paralog mapping. The use of the haploid tissue during assembly increased its completeness without reducing the number of assembled transcripts. Our results suggest that current strategies that rely on available genomic resources as guidance to minimize allelic redundancy are less effective than the application of strategies that cluster redundant assembled transcripts. The strategy yielding the lowest levels of allelic redundancy among the assembled transcriptomes assessed here was the generation of SuperTranscripts with Lace followed by CD-HIT clustering. However, we still observed some levels of heterozygosity (multiple gene fragments per transcript reflecting allelic redundancy) in this assembled transcriptome on the haploid tissue, indicating that further filtering is required before using these assemblies for downstream applications. We discuss the influence of allelic redundancy when these reference transcriptomes are used to select regions for probe design of exome capture baits and for estimation of population genetic diversity., (Copyright © 2019 Ojeda et al.)

Published
2019
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