Dataset Information

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.

ABSTRACT:

Background

Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach.

Results

A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3-5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average).

Conclusions

This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes.

SUBMITTER: Biscarini F

PROVIDER: S-EPMC5460546 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Publications

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.

Biscarini Filippo F Nazzicari Nelson N Bink Marco M Arús Pere P Aranzana Maria José MJ Verde Ignazio I Micali Sabrina S Pascal Thierry T Quilot-Turion Benedicte B Lambert Patrick P da Silva Linge Cassia C Pacheco Igor I Bassi Daniele D Stella Alessandra A Rossini Laura L

BMC genomics 20170606 1

<h4>Background</h4>Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach.<h4>Results</h4>A repeatability model (multiple records per individual plant ...[more]

PMID: 28583089

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Project description:BackgroundPeach (Prunus persica (L.) Batsch) is a major temperate fruit crop with an intense breeding activity. Breeding is facilitated by knowledge of the inheritance of the key traits that are often of a quantitative nature. QTLs have traditionally been studied using the phenotype of a single progeny (usually a full-sib progeny) and the correlation with a set of markers covering its genome. This approach has allowed the identification of various genes and QTLs but is limited by the small numbers of individuals used and by the narrow transect of the variability analyzed. In this article we propose the use of a multi-progeny mapping strategy that used pedigree information and Bayesian approaches that supports a more precise and complete survey of the available genetic variability.ResultsSeven key agronomic characters (data from 1 to 3 years) were analyzed in 18 progenies from crosses between occidental commercial genotypes and various exotic lines including accessions of other Prunus species. A total of 1467 plants from these progenies were genotyped with a 9 k SNP array. Forty-seven QTLs were identified, 22 coinciding with major genes and QTLs that have been consistently found in the same populations when studied individually and 25 were new. A substantial part of the QTLs observed (47%) would not have been detected in crosses between only commercial materials, showing the high value of exotic lines as a source of novel alleles for the commercial gene pool. Our strategy also provided estimations on the narrow sense heritability of each character, and the estimation of the QTL genotypes of each parent for the different QTLs and their breeding value.ConclusionsThe integrated strategy used provides a broader and more accurate picture of the variability available for peach breeding with the identification of many new QTLs, information on the sources of the alleles of interest and the breeding values of the potential donors of such valuable alleles. These results are first-hand information for breeders and a step forward towards the implementation of DNA-informed strategies to facilitate selection of new cultivars with improved productivity and quality.

Project description:Peach is one of the most important fruit crops in the world, with the global annual production about 24.6 million tons. The United States is the fourth-largest producer after China, Spain, and Italy. Peach consumption has decreased over the last decade, most likely due to inconsistent quality of the fruit on the market. Thus, marker-assisted selection for fruit quality traits is highly desired in fresh market peach breeding programs and one of the major goals of the RosBREED project. The ability to use DNA information to select for desirable traits would enable peach breeders to efficiently plan crosses and select seedlings with desired quality traits early in the selection process before fruiting. Therefore, we assembled a multi-locus genome wide association study (GWAS) of 620 individuals from three public fresh market peach breeding programs (Arkansas, Texas, and South Carolina). The material was genotyped using 9K SNP array and the traits were phenotyped for three phenological (bloom date, ripening date, and days after bloom) and 11 fruit quality-related traits (blush, fruit diameter, fruit weight, adherence, fruit firmness, redness around pit, fruit texture, pit weight, soluble solid concentration, titratable acidity, and pH) over three seasons (2010, 2011, and 2012). Multi-locus association analyses, carried out using mrMLM 4.0 and FarmCPU R packages, revealed a total of 967 and 180 quantitative trait nucleotides (QTNs), respectively. Among the 88 consistently reliable QTNs detected using multiple multi-locus GWAS methods and/or at least two seasons, 44 were detected for the first time. Fruit quality hotspots were identified on chromosomes 1, 3, 4, 5, 6, and 8. Out of 566 candidate genes detected in the genomic regions harboring the QTN clusters, 435 were functionally annotated. Gene enrichment analyses revealed 68 different gene ontology (GO) terms associated with fruit quality traits. Data reported here advance our understanding of genetic mechanisms underlying important fruit quality traits and further support the development of DNA tools for breeding.

Project description:BACKGROUND: Cold storage is used to inhibit peach fruit ripening during shipment to distant markets. However, this cold storage can negatively affect the quality of the fruit when it is ripened, resulting in disorders such as wooliness, browning or leathering. In order to understand the individual and combined biological effects that factors such as cold storage and ripening have on the fruit and fruit quality, we have taken a comparative EST transcript profiling approach to identify genes that are differentially expressed in response to these factors. RESULTS: We sequenced 50,625 Expressed Sequence Tags (ESTs) from peach mesocarp (Prunus persica O'Henry variety) stored at four different postharvest conditions. A total of 10,830 Unigenes (4,169 contigs and 6,661 singletons) were formed by assembling these ESTs. Additionally, a collection of 614 full-length and 1,109 putative full-length cDNA clones within flanking loxP recombination sites was created. Statistically analyzing the EST population, we have identified genes that are differentially expressed during ripening, in response to cold storage or the combined effects of cold storage and ripening. Pair-wise comparisons revealed 197 contigs with at least one significant difference in transcript abundance between at least two conditions. Gene expression profile analyses revealed that the contigs may be classified into 13 different clusters of gene expression patterns. These clusters include groups of contigs that increase or decrease transcript abundance during ripening, in response to cold or ripening plus cold. CONCLUSION: These analyses have enabled us to statistically identify novel genes and gene clusters that are differentially expressed in response to post-harvest factors such as long-term cold storage, ripening or a combination of these two factors. These differentially expressed genes reveal the complex biological processes that are associated with these factors, as well as a large number of putative gene families that may participate differentially in these processes. In particular, these analyzes suggest that woolly fruits lack the increased boost of metabolic processes necessary for ripening. Additionally, these results suggest that the mitochondria and plastids play a major role in these processes. The EST sequences and full-length cDNA clones developed in this work, combined with the large population of differentially expressed genes may serve as useful tools and markers that will enable the scientific community to better define the molecular processes that affect fruit quality in response to post-harvest conditions and the organelles that participate in these processes.

Project description:The peach (Prunus persica L.) is one of Tunisia's major commercial fruit crops and is considered one of the biggest water consumers of all crops. In warm and arid areas of southern Tunisia, irrigation is necessary to ensure orchard longevity and high yield and fruit quality. Nevertheless, under water-scarcity conditions and low water quality, water management should rely on efficient deficit irrigation strategies. In this study, sustained deficit irrigation (DI) and partial root-zone drying (PRD50) at 50% of crop evapotranspiration (ETc) were evaluated for their impact on the primary and secondary metabolites of the peach fruit of early cultivar Flordastar grown in the Tataouine region. A full irrigation (FI) treatment at 100%, etc., was used as a control treatment. Color, dry-matter content, firmness, organic acids, sugars, phenolic compounds, vitamin C, β-carotene and minerals were assessed on harvested mature fruits. Dry-matter content and firmness increased significantly under DI and PRD50 (13% and 15.5%). DI fruit had the highest soluble-solid content (SSC), reaching Brix values of 14.3°. Fruit sorbitol and sucrose contents were not affected by Di and PRD50. Higher glucose in fruit juice was observed in PRD50 (23%) and DI (21.5%) compared to FI, which had the highest malic acid content (33.5-37%). Quinic and citric acids decreased with DI and PRD50, while almost all individual phenolic compounds increased with deficit irrigation. Hydroxycinnamates and anthocyanins were significantly higher in fruits harvested from DI and PRD50 treatments. Proanthocyanidins (catechin and epicatechin) were only improved by DI, while flavone compounds and vitamin C were not affected by irrigation restrictions. β-carotene was higher in fruits yielded under FI (0.71 mg/100 g DM) than DI and PRD50 (0.21-0.43 mg/100 g DM). Macro- and micronutrients significantly increased in DI and PRD50 fruit. A significant difference between DI and PRD50 fruits was observed for Zn and Fe concentrations. This research highlights the positive impact of reduced irrigation on bioactive-fruit quality attributes and the suitability of PRD50 and DI as tools for irrigation management in arid areas of southern Tunisia, contributing to water-saving in orchards and the improvement of fruit commercial value.

Dataset Information

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.

Background

Results

Conclusions

Publications

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.

Similar Datasets

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