New stable QTLs for berry weight do not colocalize with QTLs for seed traits in cultivated grapevine (Vitis vinifera L.)

Abstract

BackgroundIn grapevine, as in other fruit crops, fruit size and seed content are key components of yield and quality; however, very few Quantitative Trait Loci (QTLs) for berry weight and seed content (number, weight, and dry matter percentage) have been discovered so far. To identify new stable QTLs for marker-assisted selection and candidate gene identification, we performed simultaneous QTL detection in four mapping populations (seeded or seedless) with various genetic backgrounds.ResultsFor berry weight, we identified five new QTLs, on linkage groups (LGs) 1, 8, 11, 17 and 18, in addition to the known major QTL on LG 18. The QTL with the largest effect explained up to 31% of total variance and was found in two genetically distant populations on LG 17, where it colocalized with a published putative domestication locus. For seed traits, besides the major QTLs on LG 18 previously reported, we found four new QTLs explaining up to 51% of total variance, on LGs 4, 5, 12 and 14. The previously published QTL for seed number on LG 2 was found related in fact to sex. We found colocalizations between seed and berry weight QTLs only for the major QTL on LG 18 in a seedless background, and on LGs 1 and 13 in a seeded background. Candidate genes belonging to the cell number regulator CNR or cytochrome P450 families were found under the berry weight QTLs on LGs 1, 8, and 17. The involvement of these gene families in fruit weight was first described in tomato using a QTL-cloning approach. Several other interesting candidate genes related to cell wall modifications, water import, auxin and ethylene signalling, transcription control, or organ identity were also found under berry weight QTLs.ConclusionWe discovered a total of nine new QTLs for berry weight or seed traits in grapevine, thereby increasing more than twofold the number of reliable QTLs for these traits available for marker assisted selection or candidate gene studies. The lack of colocalization between berry and seed QTLs suggests that these traits may be partly dissociated.

A multivariate approach for the ampelographic discrimination of grapevine (Vitis vinifera) cultivars: application to local Syrian genetic resources

“…It is generally accepted that berry dimensions are directly affected by seed number at a intragenotypic level (Walker et al 2005), but it is not that obvious at an intergenotypic level Tello et al 2015). In this regard, Doligez et al (2013) have indicated the lack of colocalization between QTLs for berry and seed traits, suggesting that the genetic control of both traits may be partly dissociated.…”

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

“…Microsatellite and SNP markers have become in the last years the markers of choice for genetic analyses in grapevine, including genetic mapping and QTL identification (Huang et al 2012;Doligez et al 2013;Battilana et al 2013;Barba et al 2014), linkage disequilibrium and association analyses (Emanuelli et al 2010;Barnaud et al 2010;Cardoso et al 2012;Vargas et al 2013), and varietal identification (Myles et al 2010;Cabezas et al 2011;Laucou et al 2011;Migliaro et al 2012). As in many other woody plant species, genetic mapping in grapevine has been carried out using mainly the double pseudo test-cross strategy (Grattapaglia et al 1995), which is based on the study of allelic segregation of markers found in heterozygosis in one or both progenitors of an F 1 progeny.…”

“…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).…”

Genomics technologies to study structural variations in the grapevine genome

“…Comparing polymorphic regions between seedless (AR and TS) vs. seeded (It and RG) and big berry vs. small berry (TS) varieties, we were able to identify polymorphisms in genes involved in hormone responses and metabolism in berry growth as putative candidate genes. For example the gene coding for the Auxin Response Factor 5 (ARF5) showed a higher CN in the TS genome and was recently mapped to a quantitative trait locus associated to berry weight and traits [22]. Likewise we found polymorphisms specific to the seedless varieties with respect to the seeded ones in genes involved in transport overview pathways, such as PIP2B, which codes a member of the aquaporin gene family.…”