Molecular Breeding

, 35:29 | Cite as

Identification and validation of a QTL influencing bitter pit symptoms in apple (Malus × domestica)

  • M. Buti
  • L. Poles
  • D. Caset
  • P. Magnago
  • F. Fernandez Fernandez
  • R. J. Colgan
  • R. Velasco
  • D. J. Sargent


Bitter pit is one of the most economically important physiological disorders affecting apple fruit production, causing soft discrete pitting of the cortical flesh of the apple fruits which renders them unmarketable. The disorder is heritable; however, the environment and cultural practices play a major role in expression of symptoms. Bitter pit has been shown to be controllable to a certain extent using calcium sprays and dips; however, their use does not entirely prevent the incidence of the disorder. Previously, bitter pit has been shown to be controlled by two dominant genes, and markers on linkage group 16 of the apple genome were identified that were significantly associated with the expression of bitter pit symptoms in a genome-wide association study. In this investigation, we identified a major QTL for bitter pit defined by two microsatellite (SSR) markers. The association of the SSRs with the bitter pit locus, and their ability to predict severe symptom expression, was confirmed through screening of individuals with stable phenotypic expression from an additional mapping progeny. The data generated in this current study suggest a two gene model could account for the control of bitter pit symptom expression; however, only one of the loci was detectable, most likely due to dominance of alleles carried by both parents of the mapping progeny used. The SSR markers identified are cost-effective, robust and multi-allelic and thus should prove useful for the identification of seedlings with resistance to bitter pit using marker-assisted selection in apple breeding programs.


Marker-assisted breeding Genomics Mapping Storage disorders Calcium Fruit 

Supplementary material

11032_2015_258_MOESM1_ESM.tif (960 kb)
Supplementary Fig. 1 – Initial linkage map and QTL analysis using interval mapping for 94 individuals of R × X mapping population. Marker positions are given in cM, and accompanying graphs give LOD scores associated with bitter pit symptom expression.(TIFF 960 kb)
11032_2015_258_MOESM2_ESM.tif (59 kb)
Supplementary Fig. 2 – Schematic representation of the segregation of alleles within the R × X progeny and their associated expected phenotypes, according to the two gene model for bitter pit susceptibility of Korban and Swiader (1984). (TIFF 59 kb)
11032_2015_258_MOESM3_ESM.pdf (15 kb)
Supplementary Table 1 – Results of mapping and QTL analysis using interval mapping on a subset (n = 94) of the R × X mapping population that displayed a consistent phenotype across all three years of evaluation. The position of each of the nine markers across the linkage group is given, along with the LOD score and associated percentage variance explained for each marker. (PDF 14 kb)
11032_2015_258_MOESM4_ESM.pdf (15 kb)
Supplementary Table 2 – Results of mapping and QTL analysis using interval mapping the full mapping progeny of n = 364 individuals of the R × X mapping population across all three years of evaluation. The position of each marker across the linkage group is given, along with the LOD score and associated percentage variance explained for each of the four markers scored. (PDF 14 kb)
11032_2015_258_MOESM5_ESM.pdf (13 kb)
Supplementary Table 3 – Validation of alleles in coupling with severe bitter pit symptom expression in nine susceptible (phenotype 4) and seven resistant (phenotype 0) plants belonging to B × C progeny that gave a consistent phenotype over two years evaluation. (PDF 12 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • M. Buti
    • 1
  • L. Poles
    • 1
  • D. Caset
    • 1
  • P. Magnago
    • 1
  • F. Fernandez Fernandez
    • 2
  • R. J. Colgan
    • 3
  • R. Velasco
    • 1
  • D. J. Sargent
    • 1
  1. 1.Centre for Research and InnovationFondazione Edmund MachSan Michele all’AdigeItaly
  2. 2.East Malling ResearchEast MallingUK
  3. 3.Natural Resources InstituteUniversity of GreenwichChathamUK

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