Tracing the color: quantitative trait loci analysis reveals new insights into red-flesh pigmentation in apple (Malus domestica)

Abstract

Red-flesh color development in apple fruit is known to depend upon a particular allele of the MdMYB10 gene. While the anthocyanin metabolic pathway is well characterized, current genetic models do not explain the observed variations in red-flesh pigmentation intensity. Previous studies focused on total anthocyanin content as a phenotypic trait to characterize overall flesh color. While this approach led to a global understanding of the genetic mechanisms involved in color expression, it is essential to adopt a more quantitative approach, by analyzing the variations of other phenolic compound classes, in order to better understand the molecular mechanisms involved in the subtle flesh color variation and distribution. In this study, we performed pedigree-based quantitative trait loci (QTL) mapping, using the FlexQTL™software, to decipher the genetic determinism of red-flesh color in five F1 inter-connected families segregating for the red-flesh trait. A total of 452 genotypes were evaluated for flesh color and phenolic profiles during 3 years (2021-2023). We identified a total of 24 QTLs for flesh color intensity and phenolic compound profiles. Six QTLs were detected for red-flesh color on LG1, LG2, LG8, LG9, LG11, and LG16. Several genes identified in QTL confidence intervals were related to anthocyanin metabolism. Further analyses allowed us to propose a model in which the competition between anthocyanins and flavan-3-ols (monomer and oligomer) end-products is decisive for red-flesh color development. In this model, alleles favorable to high red-flesh color intensity can be inherited from both white-flesh and red-flesh parents.

Acknowledgements

The authors thank the PTM PHYTO platform (SFR QUASAV) for the instruments used for determination of phenolic content. The authors would like to thank Maryline Cournol for her help in DNA extraction and Caroline Denancé for her help with DNA extraction, SNP curation, and pedigree reconstruction. Finally, the authors thank the IFO team for their support and contribution to this study. This material is based upon work supported by the ANRT (Association nationale de la recherche et de la technologie) with a CIFRE fellowship granted to Pierre Bouillon (convention N° 2021/0182), supported by IFO and IRHS.

Author contributions

P. Bouillon performed analysis, analyzed the results, and wrote the manuscript. S. Hanteville and P. Bouillon carried out fruit harvest, sampling, and image analysis. H. Muranty helped in pedigree reconstruction. H. Muranty, A-L. Fanciullino, E. Belin, F. Bernard, and J-M. Celton provided feedbacks on the analysis and contributed to reviewing and refining the manuscript. J-M Celton and F. Bernard supervised the project.

Data availability

The data underlying this article cannot be shared publicly due to privacy of pedigree and genotyping data. The data will be shared on reasonable request to the corresponding author.

Conflict of interest

No competing interest is declared.

Supplementary information

Supplementary data is available at Horticulture Research online.

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