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Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits

BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used...

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Autores principales: Piaskowski, Julia, Hardner, Craig, Cai, Lichun, Zhao, Yunyang, Iezzoni, Amy, Peace, Cameron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5894190/
https://www.ncbi.nlm.nih.gov/pubmed/29636022
http://dx.doi.org/10.1186/s12863-018-0609-8
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author Piaskowski, Julia
Hardner, Craig
Cai, Lichun
Zhao, Yunyang
Iezzoni, Amy
Peace, Cameron
author_facet Piaskowski, Julia
Hardner, Craig
Cai, Lichun
Zhao, Yunyang
Iezzoni, Amy
Peace, Cameron
author_sort Piaskowski, Julia
collection PubMed
description BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS: High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS: Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12863-018-0609-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-58941902018-04-12 Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits Piaskowski, Julia Hardner, Craig Cai, Lichun Zhao, Yunyang Iezzoni, Amy Peace, Cameron BMC Genet Research Article BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS: High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS: Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12863-018-0609-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-10 /pmc/articles/PMC5894190/ /pubmed/29636022 http://dx.doi.org/10.1186/s12863-018-0609-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Piaskowski, Julia
Hardner, Craig
Cai, Lichun
Zhao, Yunyang
Iezzoni, Amy
Peace, Cameron
Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title_full Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title_fullStr Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title_full_unstemmed Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title_short Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
title_sort genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5894190/
https://www.ncbi.nlm.nih.gov/pubmed/29636022
http://dx.doi.org/10.1186/s12863-018-0609-8
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