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An association mapping approach to identify favourable alleles for tomato fruit quality breeding
BACKGROUND: Genome Wide Association Studies (GWAS) have been recently used to dissect complex quantitative traits and identify candidate genes affecting phenotype variation of polygenic traits. In order to map loci controlling variation in tomato marketable and nutritional fruit traits, we used a co...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266912/ https://www.ncbi.nlm.nih.gov/pubmed/25465385 http://dx.doi.org/10.1186/s12870-014-0337-9 |
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author | Ruggieri, Valentino Francese, Gianluca Sacco, Adriana D’Alessandro, Antonietta Rigano, Maria Manuela Parisi, Mario Milone, Marco Cardi, Teodoro Mennella, Giuseppe Barone, Amalia |
author_facet | Ruggieri, Valentino Francese, Gianluca Sacco, Adriana D’Alessandro, Antonietta Rigano, Maria Manuela Parisi, Mario Milone, Marco Cardi, Teodoro Mennella, Giuseppe Barone, Amalia |
author_sort | Ruggieri, Valentino |
collection | PubMed |
description | BACKGROUND: Genome Wide Association Studies (GWAS) have been recently used to dissect complex quantitative traits and identify candidate genes affecting phenotype variation of polygenic traits. In order to map loci controlling variation in tomato marketable and nutritional fruit traits, we used a collection of 96 cultivated genotypes, including Italian, Latin American, and other worldwide-spread landraces and varieties. Phenotyping was carried out by measuring ten quality traits and metabolites in red ripe fruits. In parallel, genotyping was carried out by using the Illumina Infinium SolCAP array, which allows data to be collected from 7,720 single nucleotide polymorphism (SNP) markers. RESULTS: The Mixed Linear Model used to detect associations between markers and traits allowed population structure and relatedness to be evidenced within our collection, which have been taken into consideration for association analysis. GWAS identified 20 SNPs that were significantly associated with seven out of ten traits considered. In particular, our analysis revealed two markers associated with phenolic compounds, three with ascorbic acid, β-carotene and trans-lycopene, six with titratable acidity, and only one with pH and fresh weight. Co-localization of a group of associated loci with candidate genes/QTLs previously reported in other studies validated the approach. Moreover, 19 putative genes in linkage disequilibrium with markers were found. These genes might be involved in the biosynthetic pathways of the traits analyzed or might be implied in their transcriptional regulation. Finally, favourable allelic combinations between associated loci were identified that could be pyramided to obtain new improved genotypes. CONCLUSIONS: Our results led to the identification of promising candidate loci controlling fruit quality that, in the future, might be transferred into tomato genotypes by Marker Assisted Selection or genetic engineering, and highlighted that intraspecific variability might be still exploited for enhancing tomato fruit quality. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-014-0337-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4266912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42669122014-12-16 An association mapping approach to identify favourable alleles for tomato fruit quality breeding Ruggieri, Valentino Francese, Gianluca Sacco, Adriana D’Alessandro, Antonietta Rigano, Maria Manuela Parisi, Mario Milone, Marco Cardi, Teodoro Mennella, Giuseppe Barone, Amalia BMC Plant Biol Research Article BACKGROUND: Genome Wide Association Studies (GWAS) have been recently used to dissect complex quantitative traits and identify candidate genes affecting phenotype variation of polygenic traits. In order to map loci controlling variation in tomato marketable and nutritional fruit traits, we used a collection of 96 cultivated genotypes, including Italian, Latin American, and other worldwide-spread landraces and varieties. Phenotyping was carried out by measuring ten quality traits and metabolites in red ripe fruits. In parallel, genotyping was carried out by using the Illumina Infinium SolCAP array, which allows data to be collected from 7,720 single nucleotide polymorphism (SNP) markers. RESULTS: The Mixed Linear Model used to detect associations between markers and traits allowed population structure and relatedness to be evidenced within our collection, which have been taken into consideration for association analysis. GWAS identified 20 SNPs that were significantly associated with seven out of ten traits considered. In particular, our analysis revealed two markers associated with phenolic compounds, three with ascorbic acid, β-carotene and trans-lycopene, six with titratable acidity, and only one with pH and fresh weight. Co-localization of a group of associated loci with candidate genes/QTLs previously reported in other studies validated the approach. Moreover, 19 putative genes in linkage disequilibrium with markers were found. These genes might be involved in the biosynthetic pathways of the traits analyzed or might be implied in their transcriptional regulation. Finally, favourable allelic combinations between associated loci were identified that could be pyramided to obtain new improved genotypes. CONCLUSIONS: Our results led to the identification of promising candidate loci controlling fruit quality that, in the future, might be transferred into tomato genotypes by Marker Assisted Selection or genetic engineering, and highlighted that intraspecific variability might be still exploited for enhancing tomato fruit quality. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-014-0337-9) contains supplementary material, which is available to authorized users. BioMed Central 2014-12-03 /pmc/articles/PMC4266912/ /pubmed/25465385 http://dx.doi.org/10.1186/s12870-014-0337-9 Text en © Ruggieri et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Ruggieri, Valentino Francese, Gianluca Sacco, Adriana D’Alessandro, Antonietta Rigano, Maria Manuela Parisi, Mario Milone, Marco Cardi, Teodoro Mennella, Giuseppe Barone, Amalia An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title | An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title_full | An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title_fullStr | An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title_full_unstemmed | An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title_short | An association mapping approach to identify favourable alleles for tomato fruit quality breeding |
title_sort | association mapping approach to identify favourable alleles for tomato fruit quality breeding |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266912/ https://www.ncbi.nlm.nih.gov/pubmed/25465385 http://dx.doi.org/10.1186/s12870-014-0337-9 |
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