Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

BMC Plant Biology

Research Article

Nancy Terrier¹  Jean-Marc Souquet¹  Véronique Cheynier¹  Frédéric Veran¹  Yves Bertrand²  Valérie Miralles²  Agnès Doligez²  Cécile Morel²  Patrice This²  Alexandre Fournier-Level³  Yung-Fen Huang⁴  Loïc Le Cunff⁵  Aurélie Canaguier⁶ 

[1] INRA, UMR1083 SPO, 2, place, Viala, 34060, Montpellier, France;UMR AGAP, INRA, 2, place Viala, 34060, Montpellier, France;UMR AGAP, INRA, 2, place Viala, 34060, Montpellier, France;Department of Ecology and Evolutionary Biology, Brown University, Box G-W, 80 Waterman Street, 02912, Providence, RI, USA;UMR AGAP, INRA, 2, place Viala, 34060, Montpellier, France;INRA, UMR1083 SPO, 2, place, Viala, 34060, Montpellier, France;UMR AGAP, INRA, 2, place Viala, 34060, Montpellier, France;UMT Geno-Vigne®, IFV, 2, place Viala, 34060, Montpellier, France;UMR Génomique Végétale, INRA UEVE ERL CNRS, 2, rue Gaston Crémieux, 91057, Evry, France;

关键词: Quantitative Trait Locus;    Catechin;    Quantitative Trait Locus Analysis;    Quantitative Trait Locus Mapping;    Grape Berry;   

DOI  :  10.1186/1471-2229-12-30

 received in 2011-07-13, accepted in 2012-02-27,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundProanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs.ResultsMultiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel.ConclusionsThis study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different genetic architectures for grape PA composition between berry skin and seeds. This work also uncovers novel genomic regions for further investigation in order to increase our knowledge of the genetic basis of PA composition.

【 授权许可】

Unknown   
© Huang et al; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. 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.