Dataset Information

Genetic Transformation in Peach (Prunus persica L.): Challenges and Ways Forward.

ABSTRACT: Almost 30 years have passed since the first publication reporting regeneration of transformed peach plants. Nevertheless, the general applicability of genetic transformation of this species has not yet been established. Many strategies have been tested in order to obtain an efficient peach transformation system. Despite the amount of time and the efforts invested, the lack of success has significantly limited the utility of peach as a model genetic system for trees, despite its relatively short generation time; small, high-quality genome; and well-studied genetic resources. Additionally, the absence of efficient genetic transformation protocols precludes the application of many biotechnological tools in peach breeding programs. In this review, we provide an overview of research on regeneration and genetic transformation in this species and summarize novel strategies and procedures aimed at producing transgenic peaches. Promising future approaches to develop a robust peach transformation system are discussed, focusing on the main bottlenecks to success including the low efficiency of A. tumefaciens-mediated transformation, the low level of correspondence between cells competent for transformation and those that have regenerative competence, and the high rate of chimerism in the few shoots that are produced following transformation.

SUBMITTER: Ricci A

PROVIDER: S-EPMC7465125 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Publications

Genetic Transformation in Peach (<i>Prunus persica</i> L.): Challenges and Ways Forward.

Ricci Angela A Sabbadini Silvia S Prieto Humberto H Padilla Isabel Mg IM Dardick Chris C Li Zhijian Z Scorza Ralph R Limera Cecilia C Mezzetti Bruno B Perez-Jimenez Margarita M Burgos Lorenzo L Petri Cesar C

Plants (Basel, Switzerland) 20200731 8

Almost 30 years have passed since the first publication reporting regeneration of transformed peach plants. Nevertheless, the general applicability of genetic transformation of this species has not yet been established. Many strategies have been tested in order to obtain an efficient peach transformation system. Despite the amount of time and the efforts invested, the lack of success has significantly limited the utility of peach as a model genetic system for trees, despite its relatively short ...[more]

PMID: 32752031

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Project description:Genotype-by-environment interaction (G × E) is a common phenomenon influencing genetic improvement in plants, and a good understanding of this phenomenon is important for breeding and cultivar deployment strategies. However, there is little information on G × E in horticultural tree crops, mostly due to evaluation costs, leading to a focus on the development and deployment of locally adapted germplasm. Using sweetness (measured as soluble solids content, SSC) in peach/nectarine assessed at four trials from three US peach-breeding programs as a case study, we evaluated the hypotheses that (i) complex data from multiple breeding programs can be connected using GBLUP models to improve the knowledge of G × E for breeding and deployment and (ii) accounting for a known large-effect quantitative trait locus (QTL) improves the prediction accuracy. Following a structured strategy using univariate and multivariate models containing additive and dominance genomic effects on SSC, a model that included a previously detected QTL and background genomic effects was a significantly better fit than a genome-wide model with completely anonymous markers. Estimates of an individual’s narrow-sense and broad-sense heritability for SSC were high (0.57–0.73 and 0.66–0.80, respectively), with 19–32% of total genomic variance explained by the QTL. Genome-wide dominance effects and QTL effects were stable across environments. Significant G × E was detected for background genome effects, mostly due to the low correlation of these effects across seasons within a particular trial. The expected prediction accuracy, estimated from the linear model, was higher than the realised prediction accuracy estimated by cross-validation, suggesting that these two parameters measure different qualities of the prediction models. While prediction accuracy was improved in some cases by combining data across trials, particularly when phenotypic data for untested individuals were available from other trials, this improvement was not consistent. This study confirms that complex data can be combined into a single analysis using GBLUP methods to improve understanding of G × E and also incorporate known QTL effects. In addition, the study generated baseline information to account for population structure in genomic prediction models in horticultural crop improvement.

Dataset Information

Genetic Transformation in Peach (Prunus persica L.): Challenges and Ways Forward.

Publications

Genetic Transformation in Peach (<i>Prunus persica</i> L.): Challenges and Ways Forward.

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