High-resolution genome-wide association study of a large Czech collection of sweet cherry (Prunus avium L.) on fruit maturity and quality traits

Abstract

In sweet cherry (Prunus avium L.), quantitative trait loci have been identified for fruit maturity, colour, firmness, and size to develop markers for marker-assisted selection. However, resolution is usually too low in those analyses to directly target candidate genes, and some associations are missed. In contrast, genome-wide association studies are performed on broad collections of accessions, and assemblies of reference sequences from Tieton and Satonishiki cultivars enable identification of single nucleotide polymorphisms after whole-genome sequencing, providing high marker density. Two hundred and thirty-five sweet cherry accessions were sequenced and phenotyped for harvest time and fruit colour, firmness, and size. Genome-wide association studies were used to identify single nucleotide polymorphisms associated with each trait, which were verified in breeding material consisting of 64 additional accessions. A total of 1 767 106 single nucleotide polymorphisms were identified. At that density, significant single nucleotide polymorphisms could be linked to co-inherited haplotype blocks (median size ∼10 kb). Thus, markers were tightly associated with respective phenotypes, and individual allelic combinations of particular single nucleotide polymorphisms provided links to distinct phenotypes. In addition, yellow-fruit accessions were sequenced, and a ∼90-kb-deletion on chromosome 3 that included five MYB10 transcription factors was associated with the phenotype. Overall, the study confirmed numerous quantitative trait loci from bi-parental populations using high-diversity accession populations, identified novel associations, and genome-wide association studies reduced the size of trait-associated loci from megabases to kilobases and to a few candidate genes per locus. Thus, a framework is provided to develop molecular markers and evaluate and characterize genes underlying important agronomic traits.

Acknowledgements

We thank Petra Chudobová, Lenka Křivohlávková, Lenka Tůmová, Lucie Zálesáková, and Helena Tvardíková for outstanding technical assistance. This work was supported by the Ministry of Agriculture of the Czech Republic (project QK1910290). Computational resources were supplied by the project “e-Infrastruktura CZ” (e-INFRA CZ LM2018140) supported by the Ministry of Education, Youth and Sports of the Czech Republic.

Author Contributions

J.B., J.C., L.Z., P.S., R.C. designed the research; K.H., J.C., P.S., J.S., R.C. performed the experiments; K.H., J.B., J.C., R.C. analysed and interpreted the data; K.H., J.C., J.B., P.S., J.S. wrote the manuscript; all authors revised and approved the manuscript.

Data availability

Raw data have been submitted to the Sequence Read Archive (SRA) under study number PRJNA813711.

Conflict of interests

The authors declare no conflicts of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

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