Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine
Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engel...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
| Published: |
BMC
2023
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.12123/14342 https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08747-7 https://doi.org/10.1186/s12864-022-08747-7 |
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| author | Cappa, Eduardo Pablo Chen, Charles Klutsch, Jennifer G. Sebastian-Azcona, Jaime Ratcliffe, Blaise Wei, Xiaojing Da Ros, Letitia Ullan, Aziz Liu, Yang Bernowicz, Andy Sadoway, Shane Mansfield, Shawn D. Erbilgin, Nadir Thomas, Barb R. El-Kassaby, Yousry A. |
| author_browse | Bernowicz, Andy Cappa, Eduardo Pablo Chen, Charles Da Ros, Letitia El-Kassaby, Yousry A. Erbilgin, Nadir Klutsch, Jennifer G. Liu, Yang Mansfield, Shawn D. Ratcliffe, Blaise Sadoway, Shane Sebastian-Azcona, Jaime Thomas, Barb R. Ullan, Aziz Wei, Xiaojing |
| author_facet | Cappa, Eduardo Pablo Chen, Charles Klutsch, Jennifer G. Sebastian-Azcona, Jaime Ratcliffe, Blaise Wei, Xiaojing Da Ros, Letitia Ullan, Aziz Liu, Yang Bernowicz, Andy Sadoway, Shane Mansfield, Shawn D. Erbilgin, Nadir Thomas, Barb R. El-Kassaby, Yousry A. |
| author_sort | Cappa, Eduardo Pablo |
| collection | INTA Digital |
| description | Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP
methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values fromn the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias. |
| format | Artículo |
| id | INTA14342 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | BMC |
| publisherStr | BMC |
| record_format | dspace |
| spelling | INTA143422024-03-21T13:46:54Z Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine Cappa, Eduardo Pablo Chen, Charles Klutsch, Jennifer G. Sebastian-Azcona, Jaime Ratcliffe, Blaise Wei, Xiaojing Da Ros, Letitia Ullan, Aziz Liu, Yang Bernowicz, Andy Sadoway, Shane Mansfield, Shawn D. Erbilgin, Nadir Thomas, Barb R. El-Kassaby, Yousry A. Quantitative Genetics Marker-assisted Selection Genome-wide Association Studies Parameters Genética Quantitativa Selección Asistida por Marcadores Estudios de Asociación del Genoma Completo Pinus contorta Parámetros Genomic Prediction Single and Multiple Trait Mixed Models Predicción Genómica Modelos Mixtos de Rasgos Unicos y Múltiples Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values fromn the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias. Instituto de Recursos Biológicos Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina Fil: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados Unidos Fil: Klutsch, Jennifer G. University of Alberta. Department of Renewable Resources; Canadá Fil: Sebastian-Azcona, Jaime. University of Alberta. Department of Renewable Resources; Canadá Fil: Ratchiffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá Fil: Wei, Xiaojing. 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: Ullah, Aziz. University of Alberta. Department of Renewable Resources; Canadá Fil: Liu, Yang. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canadá 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; Canadá 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 2023-03-28T18:14:33Z 2023-03-28T18:14:33Z 2022-07-23 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/14342 https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08747-7 1976-9571 2092-9293 https://doi.org/10.1186/s12864-022-08747-7 eng 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) application/pdf BMC BMC Genomics 23 : Article number: 536 (2022) |
| spellingShingle | Quantitative Genetics Marker-assisted Selection Genome-wide Association Studies Parameters Genética Quantitativa Selección Asistida por Marcadores Estudios de Asociación del Genoma Completo Pinus contorta Parámetros Genomic Prediction Single and Multiple Trait Mixed Models Predicción Genómica Modelos Mixtos de Rasgos Unicos y Múltiples Cappa, Eduardo Pablo Chen, Charles Klutsch, Jennifer G. Sebastian-Azcona, Jaime Ratcliffe, Blaise Wei, Xiaojing Da Ros, Letitia Ullan, Aziz Liu, Yang Bernowicz, Andy Sadoway, Shane Mansfield, Shawn D. Erbilgin, Nadir Thomas, Barb R. El-Kassaby, Yousry A. Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title | Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title_full | Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title_fullStr | Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title_full_unstemmed | Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title_short | Multiple‑trait analyses improved the accuracy of genomic prediction and the power of genome‑wide association of productivity and climate change‑adaptive traits in lodgepole pine |
| title_sort | multiple trait analyses improved the accuracy of genomic prediction and the power of genome wide association of productivity and climate change adaptive traits in lodgepole pine |
| topic | Quantitative Genetics Marker-assisted Selection Genome-wide Association Studies Parameters Genética Quantitativa Selección Asistida por Marcadores Estudios de Asociación del Genoma Completo Pinus contorta Parámetros Genomic Prediction Single and Multiple Trait Mixed Models Predicción Genómica Modelos Mixtos de Rasgos Unicos y Múltiples |
| url | http://hdl.handle.net/20.500.12123/14342 https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08747-7 https://doi.org/10.1186/s12864-022-08747-7 |
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