Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination

The utilization of genotyping has gained significant popularity in tree improvement programs, aiding in enhancing the precision of breeding values, removing pedigree errors, the assessment of genetic diversity, and evaluating pollen contamination. Our study explores the impact of utilizing 5308 SNP...

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Main Authors: Galeano, Esteban, Cappa, Eduardo Pablo, Bousquet, Jean, Thomas, Barb R.
Format: Artículo
Language:Inglés
Published: MDPI 2023
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/16244
https://www.mdpi.com/1999-4907/14/11/2212
https://doi.org/10.3390/f14112212
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author Galeano, Esteban
Cappa, Eduardo Pablo
Bousquet, Jean
Thomas, Barb R.
author_browse Bousquet, Jean
Cappa, Eduardo Pablo
Galeano, Esteban
Thomas, Barb R.
author_facet Galeano, Esteban
Cappa, Eduardo Pablo
Bousquet, Jean
Thomas, Barb R.
author_sort Galeano, Esteban
collection INTA Digital
description The utilization of genotyping has gained significant popularity in tree improvement programs, aiding in enhancing the precision of breeding values, removing pedigree errors, the assessment of genetic diversity, and evaluating pollen contamination. Our study explores the impact of utilizing 5308 SNP markers to genotype seed orchard parents (166), progeny in progeny trials (667), and seedlot orchard seedlings (780), to simultaneously enhance variance components, breeding values, genetic diversity estimates, and pollen flow in the Region I white spruce (Picea glauca) breeding program in central Alberta (Canada). We compared different individual tree mixed models, including pedigree-based (ABLUP), genomic-based (GBLUP), and single-step pedigree-genomicbased (ssGBLUP) models, to estimate variance components and predict breeding values for the height and diameter at breast height traits. The highest heritability estimates were achieved using the ssGBLUP approach, resulting in improved breeding value accuracy compared to the ABLUP and GBLUP models for the studied growth traits. In the six orchard seedlots tested, the genetic diversity of the seedlings remained stable, characterized by an average of approximately 2.00 alleles per SNP, a Shannon Index of approximately 0.44, and an expected and observed heterozygosity of approximately 0.29. The pedigree reconstruction of seed orchard seedlings successfully identified consistent parental contributions and equal genotype contributions in different years. Pollen contamination levels varied between 11% and 70% using SNP markers and 8% to 81% using pollen traps, with traps both overand under-estimating contamination. Overall, integrating genomic information from parents and offspring empowers forest geneticists and breeders in the Region I white spruce breeding program to correct errors, conduct backward and forward selections with greater precision, gain a deeper understanding of the orchard’s genetic structure, select superior seedlots, and accurately estimate the genetic worth of each orchard lot, which can ultimately result in increased and more precise estimates of genetic gain in the studied growth traits
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
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spelling INTA162442023-12-15T10:20:11Z Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination Galeano, Esteban Cappa, Eduardo Pablo Bousquet, Jean Thomas, Barb R. Genetic Markers Pollen Marcadores Genéticos Picea glauca Polen Tree Breeding Effective Population Size Pollen Flow White Spruce Mejoramiento de Arboles Tamaño Efectivo de la Población Flujo de Polen Abeto Blanco The utilization of genotyping has gained significant popularity in tree improvement programs, aiding in enhancing the precision of breeding values, removing pedigree errors, the assessment of genetic diversity, and evaluating pollen contamination. Our study explores the impact of utilizing 5308 SNP markers to genotype seed orchard parents (166), progeny in progeny trials (667), and seedlot orchard seedlings (780), to simultaneously enhance variance components, breeding values, genetic diversity estimates, and pollen flow in the Region I white spruce (Picea glauca) breeding program in central Alberta (Canada). We compared different individual tree mixed models, including pedigree-based (ABLUP), genomic-based (GBLUP), and single-step pedigree-genomicbased (ssGBLUP) models, to estimate variance components and predict breeding values for the height and diameter at breast height traits. The highest heritability estimates were achieved using the ssGBLUP approach, resulting in improved breeding value accuracy compared to the ABLUP and GBLUP models for the studied growth traits. In the six orchard seedlots tested, the genetic diversity of the seedlings remained stable, characterized by an average of approximately 2.00 alleles per SNP, a Shannon Index of approximately 0.44, and an expected and observed heterozygosity of approximately 0.29. The pedigree reconstruction of seed orchard seedlings successfully identified consistent parental contributions and equal genotype contributions in different years. Pollen contamination levels varied between 11% and 70% using SNP markers and 8% to 81% using pollen traps, with traps both overand under-estimating contamination. Overall, integrating genomic information from parents and offspring empowers forest geneticists and breeders in the Region I white spruce breeding program to correct errors, conduct backward and forward selections with greater precision, gain a deeper understanding of the orchard’s genetic structure, select superior seedlots, and accurately estimate the genetic worth of each orchard lot, which can ultimately result in increased and more precise estimates of genetic gain in the studied growth traits Instituto de Recursos Biológicos Fil: Galeano, Esteban. University of Alberta, Department of Renewable Resources; Canadá Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Bousquet, Jean. Université Laval, Department of Wood and Forest Sciences and Forest Research Centre; Canadá Fil: Thomas, Barb R. University of Alberta. Department of Renewable Resources; Canadá 2023-12-15T10:08:33Z 2023-12-15T10:08:33Z 2023-11-01 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/16244 https://www.mdpi.com/1999-4907/14/11/2212 1999-4907 https://doi.org/10.3390/f14112212 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 MDPI Forests 14 (11) : 2212 (November 2023)
spellingShingle Genetic Markers
Pollen
Marcadores Genéticos
Picea glauca
Polen
Tree Breeding
Effective Population Size
Pollen Flow
White Spruce
Mejoramiento de Arboles
Tamaño Efectivo de la Población
Flujo de Polen
Abeto Blanco
Galeano, Esteban
Cappa, Eduardo Pablo
Bousquet, Jean
Thomas, Barb R.
Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title_full Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title_fullStr Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title_full_unstemmed Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title_short Optimizing a regional white spruce tree improvement program: SNP genotyping for enhanced breeding values, genetic diversity assessment, and estimation of pollen contamination
title_sort optimizing a regional white spruce tree improvement program snp genotyping for enhanced breeding values genetic diversity assessment and estimation of pollen contamination
topic Genetic Markers
Pollen
Marcadores Genéticos
Picea glauca
Polen
Tree Breeding
Effective Population Size
Pollen Flow
White Spruce
Mejoramiento de Arboles
Tamaño Efectivo de la Población
Flujo de Polen
Abeto Blanco
url http://hdl.handle.net/20.500.12123/16244
https://www.mdpi.com/1999-4907/14/11/2212
https://doi.org/10.3390/f14112212
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