Dataset Information

The Draft Genome of a Flat Peach (Prunus persica L. cv. '124 Pan') Provides Insights into Its Good Fruit Flavor Traits.

ABSTRACT: The flat peach has become more and more popular worldwide for its fruit quality with relatively low acidity, high sugar content and rich flavor. However, the draft genome assembly of flat peach is still unavailable and the genetic basis for its fruit flavor remains unclear. In this study, the draft genome of a flat peach cultivar '124 Pan' was assembled by using a hybrid assembly algorithm. The final assembly resulted in a total size of 206 Mb with a N50 of 26.3 Mb containing eight chromosomes and seven scaffolds. Genome annotation revealed that a total of 25,233 protein-coding genes were predicted with comparable gene abundance among the sequenced peach species. The phylogenetic tree and divergence times inferred from 572 single copy genes of 13 plant species confirmed that Prunus ferganensis was the ancestor of the domesticated peach. By comparing with the genomes of Prunus persica (Lovell) and Prunus ferganensis, the expansion of genes encoding enzymes involved in terpene biosynthesis was found, which might contribute to the good fruit flavor traits of '124 Pan'. The flat peach draft genome assembly obtained in this study will provide a valuable genomic resource for peach improvement and molecular breeding.

SUBMITTER: Zhang A

PROVIDER: S-EPMC7998450 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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The Draft Genome of a Flat Peach (<i>Prunus persica</i> L. cv. '124 Pan') Provides Insights into Its Good Fruit Flavor Traits.

Zhang Aidi A Zhou Hui H Jiang Xiaohan X Han Yuepeng Y Zhang Xiujun X

Plants (Basel, Switzerland) 20210312 3

The flat peach has become more and more popular worldwide for its fruit quality with relatively low acidity, high sugar content and rich flavor. However, the draft genome assembly of flat peach is still unavailable and the genetic basis for its fruit flavor remains unclear. In this study, the draft genome of a flat peach cultivar '124 Pan' was assembled by using a hybrid assembly algorithm. The final assembly resulted in a total size of 206 Mb with a N50 of 26.3 Mb containing eight chromosomes a ...[more]

PMID: 33809190

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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

The Draft Genome of a Flat Peach (Prunus persica L. cv. '124 Pan') Provides Insights into Its Good Fruit Flavor Traits.

Publications

The Draft Genome of a Flat Peach (<i>Prunus persica</i> L. cv. '124 Pan') Provides Insights into Its Good Fruit Flavor Traits.

Similar Datasets

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