Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program

Autores
Cappa, Eduardo Pablo; Klutsch, Jennifer G.; Sebastian-Azcona, Jaime; Ratcliffe, Blaise; Xiaojing, Wei; Da Ros, Letitia; Yang, Liu; Chen, Charles; Benowicz, Andy; Sadoway, Shane; Mansfield, Shawn D.; Erbilgin, Nadir; Thomas, Barb R.; El-Kassaby, Yousry A.
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.
Instituto de Recursos Biológicos
Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
Fil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Klutsch, Jenifer G. University of Alberta; Department of Renewable Resources; Canada
Fil: Sebastian-Azcona, Jaime. University of Alberta; Department of Renewable Resources; Canada
Fil: Ratchiffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fil: Xiaojing, Wei. University of Alberta; Department of Renewable Resources; Canada
Fil: Da Ros, Letitia. University of British Columbia. Faculty of Forestry. Department of Wood Science; Canadá
Fil: Yang, Liu. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fil: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados Unidos
Fil: Benowicz, Andy. Alberta Agriculture and Forestry. Forest Stewardship and Trade Branch; Canadá
Fil: Sadoway, Shane. Blue Ridge Lumber Inc.; Canadá
Fil: Mansfield, Shawn D. University of British Columbia. Faculty of Forestry. Department of Wood Science; Canadá
Fil: Erbilgin, Nadir. University of Alberta; Department of Renewable Resources; Canada
Fil: Thomas, Barb R. University of Alberta; Department of Renewable Resources; Canada
Fil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fuente
PLoS ONE 17 (3) : e0264549. (March 2022)
Materia
Genómica
Fitomejoramiento
Picea glauca
Clima
Cambio Climático
Productividad
Genomics
Plant Breeding
Climate
Climate Change
Productivity
Abeto Blanco
White Spruce
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/11776
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spelling Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding programCappa, Eduardo PabloKlutsch, Jennifer G.Sebastian-Azcona, JaimeRatcliffe, BlaiseXiaojing, WeiDa Ros, LetitiaYang, LiuChen, CharlesBenowicz, AndySadoway, ShaneMansfield, Shawn D.Erbilgin, NadirThomas, Barb R.El-Kassaby, Yousry A.GenómicaFitomejoramientoPicea glaucaClimaCambio ClimáticoProductividadGenomicsPlant BreedingClimateClimate ChangeProductivityAbeto BlancoWhite SpruceTree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.Instituto de Recursos BiológicosFil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Klutsch, Jenifer G. University of Alberta; Department of Renewable Resources; CanadaFil: Sebastian-Azcona, Jaime. University of Alberta; Department of Renewable Resources; CanadaFil: Ratchiffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáFil: Xiaojing, Wei. University of Alberta; Department of Renewable Resources; CanadaFil: Da Ros, Letitia. University of British Columbia. Faculty of Forestry. Department of Wood Science; CanadáFil: Yang, Liu. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáFil: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados UnidosFil: Benowicz, Andy. Alberta Agriculture and Forestry. Forest Stewardship and Trade Branch; CanadáFil: Sadoway, Shane. Blue Ridge Lumber Inc.; CanadáFil: Mansfield, Shawn D. University of British Columbia. Faculty of Forestry. Department of Wood Science; CanadáFil: Erbilgin, Nadir. University of Alberta; Department of Renewable Resources; CanadaFil: Thomas, Barb R. University of Alberta; Department of Renewable Resources; CanadaFil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáPlos ONE2022-04-29T16:31:59Z2022-04-29T16:31:59Z2022-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/11776https://journals.plos.org/plosone/article?id=10.1371/journal.pone.02645491932-6203https://doi.org/10.1371/journal.pone.0264549PLoS ONE 17 (3) : e0264549. (March 2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:45:33Zoai:localhost:20.500.12123/11776instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:45:33.359INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
title Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
spellingShingle Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
Cappa, Eduardo Pablo
Genómica
Fitomejoramiento
Picea glauca
Clima
Cambio Climático
Productividad
Genomics
Plant Breeding
Climate
Climate Change
Productivity
Abeto Blanco
White Spruce
title_short Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
title_full Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
title_fullStr Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
title_full_unstemmed Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
title_sort Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program
dc.creator.none.fl_str_mv Cappa, Eduardo Pablo
Klutsch, Jennifer G.
Sebastian-Azcona, Jaime
Ratcliffe, Blaise
Xiaojing, Wei
Da Ros, Letitia
Yang, Liu
Chen, Charles
Benowicz, Andy
Sadoway, Shane
Mansfield, Shawn D.
Erbilgin, Nadir
Thomas, Barb R.
El-Kassaby, Yousry A.
author Cappa, Eduardo Pablo
author_facet Cappa, Eduardo Pablo
Klutsch, Jennifer G.
Sebastian-Azcona, Jaime
Ratcliffe, Blaise
Xiaojing, Wei
Da Ros, Letitia
Yang, Liu
Chen, Charles
Benowicz, Andy
Sadoway, Shane
Mansfield, Shawn D.
Erbilgin, Nadir
Thomas, Barb R.
El-Kassaby, Yousry A.
author_role author
author2 Klutsch, Jennifer G.
Sebastian-Azcona, Jaime
Ratcliffe, Blaise
Xiaojing, Wei
Da Ros, Letitia
Yang, Liu
Chen, Charles
Benowicz, Andy
Sadoway, Shane
Mansfield, Shawn D.
Erbilgin, Nadir
Thomas, Barb R.
El-Kassaby, Yousry A.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Genómica
Fitomejoramiento
Picea glauca
Clima
Cambio Climático
Productividad
Genomics
Plant Breeding
Climate
Climate Change
Productivity
Abeto Blanco
White Spruce
topic Genómica
Fitomejoramiento
Picea glauca
Clima
Cambio Climático
Productividad
Genomics
Plant Breeding
Climate
Climate Change
Productivity
Abeto Blanco
White Spruce
dc.description.none.fl_txt_mv Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.
Instituto de Recursos Biológicos
Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
Fil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Klutsch, Jenifer G. University of Alberta; Department of Renewable Resources; Canada
Fil: Sebastian-Azcona, Jaime. University of Alberta; Department of Renewable Resources; Canada
Fil: Ratchiffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fil: Xiaojing, Wei. University of Alberta; Department of Renewable Resources; Canada
Fil: Da Ros, Letitia. University of British Columbia. Faculty of Forestry. Department of Wood Science; Canadá
Fil: Yang, Liu. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
Fil: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados Unidos
Fil: Benowicz, Andy. Alberta Agriculture and Forestry. Forest Stewardship and Trade Branch; Canadá
Fil: Sadoway, Shane. Blue Ridge Lumber Inc.; Canadá
Fil: Mansfield, Shawn D. University of British Columbia. Faculty of Forestry. Department of Wood Science; Canadá
Fil: Erbilgin, Nadir. University of Alberta; Department of Renewable Resources; Canada
Fil: Thomas, Barb R. University of Alberta; Department of Renewable Resources; Canada
Fil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá
description Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-29T16:31:59Z
2022-04-29T16:31:59Z
2022-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/11776
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0264549
1932-6203
https://doi.org/10.1371/journal.pone.0264549
url http://hdl.handle.net/20.500.12123/11776
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0264549
https://doi.org/10.1371/journal.pone.0264549
identifier_str_mv 1932-6203
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Plos ONE
publisher.none.fl_str_mv Plos ONE
dc.source.none.fl_str_mv PLoS ONE 17 (3) : e0264549. (March 2022)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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