The Experts below are selected from a list of 3678 Experts worldwide ranked by ideXlab platform
David I Dunstan - One of the best experts on this subject based on the ideXlab platform.
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cloning and characterization of six embryogenesis associated cdnas from somatic embryos of Picea glauca and their comparative expression during zygotic embryogenesis
Plant Molecular Biology, 1999Co-Authors: Jinzhuo Dong, David I DunstanAbstract:Six somatic embryogenesis-associated cDNAs (PgEMB2, 6, 7, 8, 24 and 34) from white spruce (Picea glauca (Moench) Voss) somatic embryos have been characterized. Transcript accumulation during somatic embryo development and subsequent germination related to these genes, indicated that they were developmentally regulated. The transcripts related to clones PgEMB2, 6, 24 and 34 were also detected during zygotic embryo development, but transcripts of clones PgEMB7 and 8 were not. PgEMB24 had a similar gene expression pattern to spruce Em-like late embryo abundant (lea) gene, but other clones had no similarities in gene expression to either spruce lea-like or storage protein genes. Abscisic acid, a stimulator for spruce somatic embryo maturation, did not obviously affect gene expression corresponding to these cDNAs. The predicted proteins are distinguishable from known LEA proteins based on analyses of hydropathy plots, amino acid compositions and deduced protein structures. The similarities of the spruce cDNAs, and protein sequences predicted from these cDNAs, to other sequence data are described.
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sucrose requirements and lipid utilization during germination of interior spruce Picea glauca engelmannii complex somatic embryos
Plant Cell Reports, 1997Co-Authors: Danielle Julie Carrier, James E Cunningham, D C Taylor, David I DunstanAbstract:Both somatic and excised zygotic embryos of interior spruce (Picea glauca engelmannii complex) required exogenous sucrose in the medium for germination in vitro. Over a period of 29 days on sucrose-containing medium germinants with roots and epicotyls developed from both kinds of embryo, and their content of linolenic acid (9,12,15-18:3) increased about six- to eightfold. Without added sucrose, embryos showed retarded growth or were necrotic, and the content of linolenic acid was barely detectable in their fatty acid profiles. Through14C-sucrose uptake studies, it was determined that germinants consumed only 25% of the sucrose available in a 1% (wt/vol) sucrose-containing medium. Since no radiolabelled fatty acids were detected, it appears that externally supplied sucrose was not used in the synthesis of lipids. Although sucrose was present during plantlet development, 72% of the initial lipids were consumed. To some extent, the plantlets appeared to be obligate storage lipid utilizers.
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expression of abundant mrnas during somatic embryogenesis of white spruce Picea glauca moench voss
Planta, 1996Co-Authors: Jinzhuo Dong, David I DunstanAbstract:Embryogenic tissues of white spruce [Picea glauca (Moench) Voss] remain in an early developmental stage while cultured on 2,4-dichlorophenoxyacetic acid and N6-benzyladenine, but develop to cotyledonary embryos when these phytohormones are replaced by abscisic acid. Twenty-eight cDNAs were isolated from cotyledonary embryos by differential screening against immature embryo and non-embryonic tissues. Temporal expression patterns of these cDNAs during ABA-stimulated somatic embryo development were observed. This showed that clones could be allocated to various groups, including embryo-abundant, embryo-maturation-induced, and those whose expression was modulated during embryo development, germination or in non-embryogenic tissues. Expression corresponding to these cDNA clones showed that there were various responses to exogenous ABA or polyethylene glycol during a period of 48 h. Analyses of DNA and predicted amino acid sequence revealed that 12 of 28 cDNA clones had no known homologues, while others were predicted to encode different late-embryogenesis-abundant proteins, early methionine-labelled proteins, storage proteins, heat-shock proteins, glycine-rich cell wall protein, metallothionein-like protein and some other metabolic enzymes.
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germination of encapsulated embryos of interior spruce Picea glauca engelmannii complex and black spruce Picea mariana mill
Plant Cell Reports, 1993Co-Authors: Monika M Lulsdorf, T E Tautorus, Susan I Kikcio, Terry D Bethune, David I DunstanAbstract:Interior spruce (Picea glauca engelmannii complex) and black spruce (Picea mariana Mill.) cotyledonary somatic embryos were encapsulated in sodium alginate. Somatic embryo viability was retained, but germination occurred at a reduced frequency compared with the equivalent zygotic embryos. The addition of 0.5% (w/v) activated charcoal to the alginate capsule significantly enhanced root development and germination for somatic embryos but not for zygotic embryos. The possibility of developing an artiflcal endosperm was also investigated, by addition of Litvay (Litvay et al. 1981) nutrients with or without 90 mM sucrose to the alginate-charcoal capsule. This treatment significantly enhanced root development for all embryo categories with the exception of black spruce somatic embryos. Encapsulated and non-encapsulated somatic embryos survived one month cold storage at 4 °C without reduction in germination frequency.
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growth parameters of embryogenic suspension cultures of interior spruce Picea glauca engelmannii complex and black spruce Picea mariana mill
Plant Science, 1992Co-Authors: Monika M Lulsdorf, T E Tautorus, Susan I Kikcio, David I DunstanAbstract:Abstract Enhanced stability of conifer somatic embryo suspensions could improve their utility for mass propagation. For this purpose, growth characteristics of interior spruce ( Picea glauca-engelmannii complex) and black spruce ( Picea mariana Mill.) embryogenic lines in suspension were determined over a 21-day period as well as the characteristics of several other parameters which might be correlated with growth. Maximum growth for both species in terms of dry weight occurred between day 2 and day 8 whereas the number of embryos per ml (4000–6000) peaked on day 10 or later. Settled culture volume, packed culture volume, osmolarity and medium conductivity were closely correlated with growth. However, osmolarity was considered the best non-destructive growth parameter because only microliters of supernatant were required for its determination. Carbohydrate, nitrogen and potassium utilization were also monitored. Neither ammonium, nitrate nor potassium were found to be limiting but carbohydrate supply could be a growth restricting factor.
Jaroslav Klápště - One of the best experts on this subject based on the ideXlab platform.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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single step blup with varying genotyping effort in open pollinated Picea glauca
G3: Genes Genomes Genetics, 2017Co-Authors: Blaise Ratcliffe, Omnia Gamal Eldien, Charles Chen, Jaroslav Klápště, Ilga Porth, Eduardo P Cappa, Yousry A ElkassabyAbstract:Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Quebec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.
Omnia Gamal Eldien - One of the best experts on this subject based on the ideXlab platform.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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single step blup with varying genotyping effort in open pollinated Picea glauca
G3: Genes Genomes Genetics, 2017Co-Authors: Blaise Ratcliffe, Omnia Gamal Eldien, Charles Chen, Jaroslav Klápště, Ilga Porth, Eduardo P Cappa, Yousry A ElkassabyAbstract:Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Quebec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.
Yousry A Elkassaby - One of the best experts on this subject based on the ideXlab platform.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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single step blup with varying genotyping effort in open pollinated Picea glauca
G3: Genes Genomes Genetics, 2017Co-Authors: Blaise Ratcliffe, Omnia Gamal Eldien, Charles Chen, Jaroslav Klápště, Ilga Porth, Eduardo P Cappa, Yousry A ElkassabyAbstract:Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Quebec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.
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the role of moist chilling and thermo priming on the germination characteristics of white spruce Picea glauca seed
Seed Science and Technology, 2013Co-Authors: Yang Liu, Allison R. Kermode, Yousry A ElkassabyAbstract:The individual and combined effect of moist-chilling and thermo-priming on germination parameters (capacity, speed, lag and dormancy index) were evaluated using seed lots representing British Columbia's five white spruce (Picea glauca) seed planning zones. The combined effect of moist-chilling followed by a 3-day priming at 15 or 20°C, stimulated seed germination across all seed lots. These combined treatments resulted in substantial improvement of all germination parameters including reducing the dormancy index (14 vs. 25). Generally, three days of priming at 20°C yielded a higher percent germination than priming for the same period at 15°C, irrespective of whether or not seeds had received a previous moist-chilling treatment. Thermo-priming alone led to some improvement in germination characteristics such as reducing the time to germination onset (lag) and increasing germination speed. These results indicate that the combined application of moist-chilling and thermo-priming could improve container nursery practices for commercial seedling production of white spruce. The positive combined effect of moist-chilling and thermo-priming on seed germination offer great potential for generalised application to other conifers; however, species-specific treatment adjustment is required.
Ilga Porth - One of the best experts on this subject based on the ideXlab platform.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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multienvironment genomic variance decomposition analysis of open pollinated interior spruce Picea glauca x engelmannii
Molecular Breeding, 2018Co-Authors: Omnia Gamal Eldien, Blaise Ratcliffe, Charles Chen, Jaroslav Klápště, Ilga Porth, Yousry A ElkassabyAbstract:The advantages of open-pollinated (OP) family testing over controlled crossing (i.e., structured pedigree) are the potential to screen and rank a large number of parents and offspring with minimal cost and efforts; however, the method produces inflated genetic parameters as the actual sibling relatedness within OP families rarely meets the half-sib relatedness assumption. Here, we demonstrate the unsurpassed utility of OP testing after shifting the analytical mode from pedigree- (ABLUP) to genomic-based (GBLUP) relationship using phenotypic tree height (HT) and wood density (WD) and genotypic (30k SNPs) data for 1126 38-year-old Interior spruce (Picea glauca (Moench) Voss x P. engelmannii Parry ex Engelm.) trees, representing 25 OP families, growing on three sites in Interior British Columbia, Canada. The use of the genomic realized relationship permitted genetic variance decomposition to additive, dominance, and epistatic genetic variances, and their interactions with the environment, producing more accurate narrow-sense heritability and breeding value estimates as compared to the pedigree-based counterpart. The impact of retaining (random folding) vs. removing (family folding) genetic similarity between the training and validation populations on the predictive accuracy of genomic selection was illustrated and highlighted the former caveats and latter advantages. Moreover, GBLUP models allowed breeding value prediction for individuals from families that were not included in the developed models, which was not possible with the ABLUP. Response to selection differences between the ABLUP and GBLUP models indicated the presence of systematic genetic gain overestimation of 35 and 63% for HT and WD, respectively, mainly caused by the inflated estimates of additive genetic variance and individuals’ breeding values given by the ABLUP models. Extending the OP genomic-based models from single to multisite made the analysis applicable to existing OP testing programs.
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single step blup with varying genotyping effort in open pollinated Picea glauca
G3: Genes Genomes Genetics, 2017Co-Authors: Blaise Ratcliffe, Omnia Gamal Eldien, Charles Chen, Jaroslav Klápště, Ilga Porth, Eduardo P Cappa, Yousry A ElkassabyAbstract:Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Quebec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.