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Novel genomic approaches unravel genetic architecture of complex traits in apple

BACKGROUND: Understanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × d...

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Autores principales: Kumar, Satish, Garrick, Dorian J, Bink, Marco CAM, Whitworth, Claire, Chagné, David, Volz, Richard K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686700/
https://www.ncbi.nlm.nih.gov/pubmed/23758946
http://dx.doi.org/10.1186/1471-2164-14-393
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author Kumar, Satish
Garrick, Dorian J
Bink, Marco CAM
Whitworth, Claire
Chagné, David
Volz, Richard K
author_facet Kumar, Satish
Garrick, Dorian J
Bink, Marco CAM
Whitworth, Claire
Chagné, David
Volz, Richard K
author_sort Kumar, Satish
collection PubMed
description BACKGROUND: Understanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated. RESULTS: A high degree of LD even at longer distances between markers was observed, and the patterns of LD decay were similar across successive generations. Genomic regions were identified, some of which coincided with known candidate genes, with significant effects on various traits. Phenotypic variation explained by the loci identified through a whole-genome scan ranged from 3% to 25% across different traits, while fitting all markers simultaneously generally provided heritability estimates close to those from pedigree-based analysis. Results from ‘Q+K’ and ‘K’ models were very similar, suggesting that the SNP-based kinship matrix captures most of the underlying population structure. Correlations between allele substitution effects obtained from single-marker and all-marker analyses were about 0.90 for all traits. Use of SNP-derived realized relationships in linear mixed models provided a better goodness-of-fit than pedigree-based expected relationships. Genomic regions with probable pleiotropic effects were supported by the corresponding higher linkage group (LG) level estimated genetic correlations. CONCLUSIONS: The accuracy of artificial selection in plants species can be increased by using more precise marker-derived estimates of realized coefficients of relationships. All-marker analyses that indirectly account for population- and pedigree structure will be a credible alternative to single-SNP analyses in GWAS. This study revealed large differences in the genetic architecture of apple fruit traits, and the marker-trait associations identified here will help develop genome-based breeding methods for apple cultivar development.
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spelling pubmed-36867002013-06-25 Novel genomic approaches unravel genetic architecture of complex traits in apple Kumar, Satish Garrick, Dorian J Bink, Marco CAM Whitworth, Claire Chagné, David Volz, Richard K BMC Genomics Research Article BACKGROUND: Understanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated. RESULTS: A high degree of LD even at longer distances between markers was observed, and the patterns of LD decay were similar across successive generations. Genomic regions were identified, some of which coincided with known candidate genes, with significant effects on various traits. Phenotypic variation explained by the loci identified through a whole-genome scan ranged from 3% to 25% across different traits, while fitting all markers simultaneously generally provided heritability estimates close to those from pedigree-based analysis. Results from ‘Q+K’ and ‘K’ models were very similar, suggesting that the SNP-based kinship matrix captures most of the underlying population structure. Correlations between allele substitution effects obtained from single-marker and all-marker analyses were about 0.90 for all traits. Use of SNP-derived realized relationships in linear mixed models provided a better goodness-of-fit than pedigree-based expected relationships. Genomic regions with probable pleiotropic effects were supported by the corresponding higher linkage group (LG) level estimated genetic correlations. CONCLUSIONS: The accuracy of artificial selection in plants species can be increased by using more precise marker-derived estimates of realized coefficients of relationships. All-marker analyses that indirectly account for population- and pedigree structure will be a credible alternative to single-SNP analyses in GWAS. This study revealed large differences in the genetic architecture of apple fruit traits, and the marker-trait associations identified here will help develop genome-based breeding methods for apple cultivar development. BioMed Central 2013-06-12 /pmc/articles/PMC3686700/ /pubmed/23758946 http://dx.doi.org/10.1186/1471-2164-14-393 Text en Copyright © 2013 Kumar et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kumar, Satish
Garrick, Dorian J
Bink, Marco CAM
Whitworth, Claire
Chagné, David
Volz, Richard K
Novel genomic approaches unravel genetic architecture of complex traits in apple
title Novel genomic approaches unravel genetic architecture of complex traits in apple
title_full Novel genomic approaches unravel genetic architecture of complex traits in apple
title_fullStr Novel genomic approaches unravel genetic architecture of complex traits in apple
title_full_unstemmed Novel genomic approaches unravel genetic architecture of complex traits in apple
title_short Novel genomic approaches unravel genetic architecture of complex traits in apple
title_sort novel genomic approaches unravel genetic architecture of complex traits in apple
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686700/
https://www.ncbi.nlm.nih.gov/pubmed/23758946
http://dx.doi.org/10.1186/1471-2164-14-393
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