Molecular Breeding

, Volume 25, Issue 2, pp 351–357 | Cite as

Discrimination of SNP genotypes associated with complex haplotypes by high resolution melting analysis in almond: implications for improved marker efficiencies

  • Shu-Biao Wu
  • Tricia K. Franks
  • Peter Hunt
  • Michelle G. Wirthensohn
  • John P. Gibson
  • Margaret Sedgley
Short Communication


Developed recently, high resolution melting (HRM) analysis is an efficient, accurate and inexpensive method for distinguishing DNA polymorphisms. HRM has been used to identify mutations in human genes, and to detect SNPs, INDELs and microsatellites in plants. However, its capacity to discriminate DNA variants in the context of complex haplotypes involving INDEL as well as SNP variants has not been examined until now. In this study, we genotyped an almond (Prunus dulcis (Mill.) D. A. Webb, syn. Prunus amygdalus Batsch) pseudo-testcross mapping population that showed segregation of complex haplotypes associated with CYP79D16 promoter sequence. The 175 bp region in question included a 7 bp INDEL and 3 SNPs, and manifested as three different haplotypes in the parents. Thus, with one homozygous and one heterozygous parent, two relevant genotypes were identified in the mapping population. Although the population displayed monomorphism with respect to the INDEL and one of the SNPs, HRM was sufficiently sensitive to distinguish genotypes on the basis of the two informative SNPs, and the resulting data were used to map CYP79D16 to linkage group 6 of the almond genome. Thus the capacity of HRM to resolve genotypes arising from complex haplotypes has been demonstrated, and this has important implications for the design of efficient HRM markers for various genetic applications including mapping, population studies and biodiversity analyses.


High resolution melting analysis (HRM) SNPs INDELs Mapping CYP79 Almond 



We are grateful to Dr Jennifer Guerin for her contribution to this work by originally isolating the almond CYP79D16 promoter sequence by genomic walking. This research was funded by Australian Research Council (ARC) grant DP0556459, and ARC grant LP0560480 in conjunction with the Almond Board of Australia. Supplementary funding was also provided by The University of Adelaide through the Faculty of Sciences Research Development Scheme (2008).


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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Shu-Biao Wu
    • 1
  • Tricia K. Franks
    • 2
  • Peter Hunt
    • 3
  • Michelle G. Wirthensohn
    • 2
  • John P. Gibson
    • 1
  • Margaret Sedgley
    • 4
  1. 1.School of Environmental and Rural Science and The Institute of Genetics and BioinformaticsThe University of New EnglandArmidaleAustralia
  2. 2.School of Agriculture, Food and WineThe University of AdelaideGlen OsmondAustralia
  3. 3.CSIRO Livestock Industries, FD McMaster LaboratoryArmidaleAustralia
  4. 4.Faculty of Arts and SciencesThe University of New EnglandArmidaleAustralia

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