A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs
To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258538/ https://www.ncbi.nlm.nih.gov/pubmed/35485948 http://dx.doi.org/10.1093/g3journal/jkac103 |
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author | Flutre, Timothée Le Cunff, Loïc Fodor, Agota Launay, Amandine Romieu, Charles Berger, Gilles Bertrand, Yves Terrier, Nancy Beccavin, Isabelle Bouckenooghe, Virginie Roques, Maryline Pinasseau, Lucie Verbaere, Arnaud Sommerer, Nicolas Cheynier, Véronique Bacilieri, Roberto Boursiquot, Jean-Michel Lacombe, Thierry Laucou, Valérie This, Patrice Péros, Jean-Pierre Doligez, Agnès |
author_facet | Flutre, Timothée Le Cunff, Loïc Fodor, Agota Launay, Amandine Romieu, Charles Berger, Gilles Bertrand, Yves Terrier, Nancy Beccavin, Isabelle Bouckenooghe, Virginie Roques, Maryline Pinasseau, Lucie Verbaere, Arnaud Sommerer, Nicolas Cheynier, Véronique Bacilieri, Roberto Boursiquot, Jean-Michel Lacombe, Thierry Laucou, Valérie This, Patrice Péros, Jean-Pierre Doligez, Agnès |
author_sort | Flutre, Timothée |
collection | PubMed |
description | To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed. |
format | Online Article Text |
id | pubmed-9258538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92585382022-07-07 A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs Flutre, Timothée Le Cunff, Loïc Fodor, Agota Launay, Amandine Romieu, Charles Berger, Gilles Bertrand, Yves Terrier, Nancy Beccavin, Isabelle Bouckenooghe, Virginie Roques, Maryline Pinasseau, Lucie Verbaere, Arnaud Sommerer, Nicolas Cheynier, Véronique Bacilieri, Roberto Boursiquot, Jean-Michel Lacombe, Thierry Laucou, Valérie This, Patrice Péros, Jean-Pierre Doligez, Agnès G3 (Bethesda) Investigation To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed. Oxford University Press 2022-04-29 /pmc/articles/PMC9258538/ /pubmed/35485948 http://dx.doi.org/10.1093/g3journal/jkac103 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigation Flutre, Timothée Le Cunff, Loïc Fodor, Agota Launay, Amandine Romieu, Charles Berger, Gilles Bertrand, Yves Terrier, Nancy Beccavin, Isabelle Bouckenooghe, Virginie Roques, Maryline Pinasseau, Lucie Verbaere, Arnaud Sommerer, Nicolas Cheynier, Véronique Bacilieri, Roberto Boursiquot, Jean-Michel Lacombe, Thierry Laucou, Valérie This, Patrice Péros, Jean-Pierre Doligez, Agnès A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title | A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title_full | A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title_fullStr | A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title_full_unstemmed | A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title_short | A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs |
title_sort | genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new qtls |
topic | Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258538/ https://www.ncbi.nlm.nih.gov/pubmed/35485948 http://dx.doi.org/10.1093/g3journal/jkac103 |
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