Dataset Information

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

ABSTRACT: The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G?×?E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G?×?E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G?×?E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.

SUBMITTER: Hardner CM

PROVIDER: S-EPMC6312542 | biostudies-other | 2019

REPOSITORIES: biostudies-other

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Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

Hardner Craig M CM Hayes Ben J BJ Kumar Satish S Vanderzande Stijn S Cai Lichun L Piaskowski Julia J Quero-Garcia José J Campoy José Antonio JA Barreneche Teresa T Giovannini Daniela D Liverani Alessandro A Charlot Gérard G Villamil-Castro Miguel M Oraguzie Nnadozie N Peace Cameron P CP

Horticulture research 20190101

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome ...[more]

PMID: 30603092

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Project description:High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n?=?269) and sour (n?=?330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group.

Project description:Mason bees (Osmia spp.) are efficient fruit tree pollinators that can be encouraged to occupy and breed in artificial nesting material. In sweet cherry orchards, they are occasionally used as an alternative managed pollinator as a replacement for or in addition to honey bees (Apis mellifera). Yet, the lack of practical guidelines on management practices, for example optimal stocking rates, for both mason bee nesting material and honey bees might compromise pollination service provision. In this study, we assessed the relationship between stocking rates (honey bee hives and mason bee nesting material) and the abundance of honey bees and mason bees in 17 sweet cherry (Prunus avium) orchards in Central Germany. We furthermore performed a pollination experiment to explore the interactive effect of mason bees and honey bees on sweet cherry fruit set. In the orchards, both honey bee and mason bee abundance increased with increasing stocking rates of hives or nesting material, respectively. Honey bee abundance increased linearly with stocking rates. In contrast, mason bee abundance asymptoted at 2-3 nesting boxes per ha, beyond which more boxes resulted in little increase in visitation rate. Our pollination experiment demonstrated that orchards were pollen limited, with only 28% of insect-pollinated flowers setting fruit versus 39% of optimally hand-pollinated flowers. Honey bees and mason bees enhanced sweet cherry fruit set, but only when both were present and not when either was present alone in an orchard. Our findings demonstrate that offering nesting material for mason bees and employing honey bee hives can enhance bee abundance in sweet cherry orchards. By increasing honey bee abundance in combination with enhanced mason bee abundance, farmers can substantially boost fruit set and potentially sweet cherry yield. To enhance pollination services, farmers should consider the benefits of increasing pollinator biodiversity as an immediate benefit to improve crop yields.

Dataset Information

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

Publications

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

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