Heritability and identification of QTLs and underlying candidate genes associated with the architecture of the grapevine cluster (Vitis vinifera L.)
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2014Metadata
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Correa, J.
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Heritability and identification of QTLs and underlying candidate genes associated with the architecture of the grapevine cluster (Vitis vinifera L.)
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Abstract
Key message 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.
Abstract 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.
General note
Artículo de publicación ISI
Patrocinador
This work was financed by GENOMAChile
(FONDEF-CONICYT Grant G07I-1002).
Identifier
URI: https://repositorio.uchile.cl/handle/2250/120269
DOI: DOI: 10.1007/s00122-014-2286-y
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Theor Appl Genet (2014) 127:1143–1162
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