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Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies
BACKGROUND: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The ava...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460546/ https://www.ncbi.nlm.nih.gov/pubmed/28583089 http://dx.doi.org/10.1186/s12864-017-3781-8 |
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author | Biscarini, Filippo Nazzicari, Nelson Bink, Marco Arús, Pere Aranzana, Maria José Verde, Ignazio Micali, Sabrina Pascal, Thierry Quilot-Turion, Benedicte Lambert, Patrick da Silva Linge, Cassia Pacheco, Igor Bassi, Daniele Stella, Alessandra Rossini, Laura |
author_facet | Biscarini, Filippo Nazzicari, Nelson Bink, Marco Arús, Pere Aranzana, Maria José Verde, Ignazio Micali, Sabrina Pascal, Thierry Quilot-Turion, Benedicte Lambert, Patrick da Silva Linge, Cassia Pacheco, Igor Bassi, Daniele Stella, Alessandra Rossini, Laura |
author_sort | Biscarini, Filippo |
collection | PubMed |
description | BACKGROUND: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach. RESULTS: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3–5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average). CONCLUSIONS: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3781-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5460546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54605462017-06-07 Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies Biscarini, Filippo Nazzicari, Nelson Bink, Marco Arús, Pere Aranzana, Maria José Verde, Ignazio Micali, Sabrina Pascal, Thierry Quilot-Turion, Benedicte Lambert, Patrick da Silva Linge, Cassia Pacheco, Igor Bassi, Daniele Stella, Alessandra Rossini, Laura BMC Genomics Research Article BACKGROUND: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach. RESULTS: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3–5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average). CONCLUSIONS: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3781-8) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-06 /pmc/articles/PMC5460546/ /pubmed/28583089 http://dx.doi.org/10.1186/s12864-017-3781-8 Text en © The Author(s) 2017 Open Access This 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 Biscarini, Filippo Nazzicari, Nelson Bink, Marco Arús, Pere Aranzana, Maria José Verde, Ignazio Micali, Sabrina Pascal, Thierry Quilot-Turion, Benedicte Lambert, Patrick da Silva Linge, Cassia Pacheco, Igor Bassi, Daniele Stella, Alessandra Rossini, Laura Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title | Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title_full | Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title_fullStr | Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title_full_unstemmed | Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title_short | Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies |
title_sort | genome-enabled predictions for fruit weight and quality from repeated records in european peach progenies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460546/ https://www.ncbi.nlm.nih.gov/pubmed/28583089 http://dx.doi.org/10.1186/s12864-017-3781-8 |
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