Heritability and identification of QTLs and underlying candidate genes associated with the architecture of the grapevine cluster (Vitis vinifera L.)

Abstract

We have identified 19 QTLs for rachis architecture, a key and complex trait for grapevine production. Fifty out of 1,173 genes underlying these QTLs are candidates to be further explored. In the table grape industry, the rachis architecture has economic and management implications. Therefore, understanding the genetics of this trait is key for its breeding. The aim of this work was to identify genetic determinants of traits associated with the cluster architecture. Characterisations of eight traits was performed on a 'Ruby Seedless' × 'Sultanina' crossing (F1: n = 137) during three seasons, with and without gibberellic acid (GA3) applications. The genotypic effects and the genotype × GA3 interactions were significant for several traits. Rachis length (rl), lateral shoulder length and node number along the central axis were the most prominent traits. On average, the heritability of these traits was ~71 %, with heritability of rl being 76 % as estimated under different seasons. Quantitative trait loci (QTLs) analyses showed that linkage group 5 (LG5) and LG18 harboured the largest number of QTLs for these traits. According to the variance explained, the main QTL (corresponding to rl) was found on LG9. These QTLs were supported mainly by a paternal additive effect and revealed possible pleiotropic effects. Based on the grapevine reference genome, we identified 1,173 genes located under these QTL confidence intervals. Fifty of the 891 annotated genes of this list were selected for their further characterisation because of their possible participation in the rachis architecture. In conclusion, the QTLs detected indicate that these traits and their GA3 responsiveness have a clear genetic basis. Due to the percentage of the total variance explained, they are good candidates to participate in the genetic determination of the cluster architecture.

Multicultivar and multivariate study of the natural variation for grapevine bunch compactness

“…Shavrukov et al (2004) considered the morphological volume of the grapevine bunch as a cone, the volume of which is defined by the main axes of its architecture [V cone = (πr 2 l)/3]. Recently, the genetic variation of different attributes of the architecture of the rachis have been analysed by Correa et al (2014) in a segregating progeny derived from the crossing of two tablegrape cultivars (Ruby Seedless × Sultanina). Among other structural characteristics, the width of the bunch depends on the length of the primary ramifications, supporting the significant relationship found between this variable and the compactness of the bunch.…”

“…This abnormal pattern was mainly associated to a mutation in the gene VvTFL1A (orthologous to Arabidopsis TERMINAL FLOWER 1, TFL1), the expression of which plays an important role in the establishment of the structure of the inflorescence and, consequently, on bunch size, shape and compactness. Recently, the genetic variation of different attributes of the architecture of the rachis have been analysed by Correa et al (2014) in a segregating progeny derived from the crossing of two tablegrape cultivars (Ruby Seedless × Sultanina). The high heritability found for some of the traits analysed in such progeny (for example length of the rachis, number of ramifications of the bunch and length of the first ramifications of the rachis), together with the important role found in our work for those bunch attributes indicate that bunch compactness can be included as a target trait in breeding programs, both through traditional approaches or by marker-assisted selection (Reisch et al 2012), once its genetic basis was known.…”

Whole-genome genotyping of grape using a panel of microsatellite multiplex PCRs

“…The availability of the grapevine genome sequence combined with the advent of cheaper and high throughput single nucleotide polymorphism (SNP) genotyping strategies (Gupta et al 2008;Davey et al 2011) were expected to shift the tools of genetic studies in grapevine. However, microsatellites are still the predominant markers contributing to the current knowledge of genetic determinism of the major grapevine traits (Mejía et al 2011;Huang et al 2012;Duchêne et al 2012;Karaagac et al 2012;Doligez et al 2013;Battilana et al 2013;Grzeskowiak et al 2013;Ban et al 2014;Correa et al 2014).…”

Development and Use of Biotechnology Tools for Grape Functional Analysis

“…The study of the genetic control of major agronomic traits in grapevine using QTL analysis allowed the elucidation of traits such as seedlessness and berry weight [12,18,[21][22][23]; berry phenolic composition [24][25][26][27][28]; aroma [29,30]; berry firmness [31,32]; fertility [9,33]; flower hermaphroditism [34]; cluster architecture [35]; pathogen resistance [34,[36][37][38]; plant phenology [39,40]; and adaptation to abiotic stresses [41] and to climate change [42]. Despite several of the reports allowed the identification of candidate sequences, just few of them have finally characterized the genes responsible for a particular function or trait.…”