Abstract

BackgroundThe increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Plant breeding has the potential to deliver new cultivars with stable yield and quality under warmer climate conditions, but this requires the identification of stable genetic determinants. This study tested the potentialities of the microvine to boost genetics in grapevine. A mapping population of 129 microvines derived from Picovine x Ugni Blanc flb, was genotyped with the Illumina® 18 K SNP (Single Nucleotide Polymorphism) chip. Forty-three vegetative and reproductive traits were phenotyped outdoors over four cropping cycles, and a subset of 22 traits over two cropping cycles in growth rooms with two contrasted temperatures, in order to map stable QTLs (Quantitative Trait Loci).ResultsTen stable QTLs for berry development and quality or leaf area were identified on the parental maps. A new major QTL explaining up to 44 % of total variance of berry weight was identified on chromosome 7 in Ugni Blanc flb, and co-localized with QTLs for seed number (up to 76 % total variance), major berry acids at green lag phase (up to 35 %), and other yield components (up to 25 %). In addition, a minor QTL for leaf area was found on chromosome 4 of the same parent. In contrast, only minor QTLs for berry acidity and leaf area could be found as moderately stable in Picovine. None of the transporters recently identified as mutated in low acidity apples or Cucurbits were included in the several hundreds of candidate genes underlying the above berry QTLs, which could be reduced to a few dozen candidate genes when a priori pertinent biological functions and organ specific expression were considered.ConclusionsThis study combining the use of microvine and a high throughput genotyping technology was innovative for grapevine genetics. It allowed the identification of 10 stable QTLs, including the first berry acidity QTLs reported so far in a Vitis vinifera intra-specific cross. Robustness of a set of QTLs was assessed with respect to temperature variation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0588-0) contains supplementary material, which is available to authorized users.

Highlights

  • The increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition

  • The population showed a large segregation of the phenotypes, e.g.: phyllochron (PHY; 15 to 120 growing degree-day (GDD)/leaf), leaf area (LA; 10 to 290 cm2/ leaf), number of pre-formed inflorescences in winter buds per plant (NBI; 0.25 to 3.8), number of berries per cluster (NB; 5 to 75), berry weight at green lag phase (BWG; 0.2 to 2.2 g), berry weight at maturity (BWM; 0.5 to 3.2 g), total berry acidity at green lag phase (ToAG; 220 to 780 mEq/kg.FW), malate/tartrate ratio at green lag phase (MTG; 0.75 to 5.2), total sugars at green lag phase (ToSG; 5 to 120 mM/kg.FW), total sugars at maturity (ToSM; 350 to 1200 mM/kg.FW), potassium content at green lag phase (KG; 15 to 120 mM/kg.FW)

  • quantitative trait loci (QTL) stability assessment was expanded towards an unprecedented temperature variation range thanks to the possibility to grow the microvine progeny in tightly controlled conditions, which is almost impossible with standard nondwarf vines

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Summary

Introduction

The increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Warmer climate in the past resulted in higher sugar level and lower contents of organic acids, phenolics and aroma [9,10,11,12,13] Such alterations of berry composition directly impair the organoleptic quality and the stability of wines [14]. The development of new cultivars appears to be the best long-term solution for a sustainable viticulture maintaining premium wine production under global warming. It requires improving the knowledge on the genetics of key grapevine functions under various environments

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