Molecular Genetics and Genomics

, Volume 282, Issue 3, pp 273–281 | Cite as

Mapping SNP-anchored genes using high-resolution melting analysis in almond

  • Shu-Biao Wu
  • Iraj Tavassolian
  • Gholamreza Rabiei
  • Peter Hunt
  • Michelle Wirthensohn
  • John P. Gibson
  • Christopher M. Ford
  • Margaret Sedgley
Original Paper

Abstract

Peach and almond have been considered as model species for the family Rosaceae and other woody plants. Consequently, mapping and characterisation of genes in these species has important implications. High-resolution melting (HRM) analysis is a recent development in the detection of SNPs and other markers, and proved to be an efficient and cost-effective approach. In this study, we aimed to map genes corresponding to known proteins in other species using the HRM approach. Prunus unigenes were searched and compared with known proteins in the public databases. We developed single-nucleotide polymorphism (SNP) markers, polymorphic in a mapping population produced from a cross between the cloned cultivars Nonpareil and Lauranne. A total of 12 SNP-anchored putative genes were genotyped in the population using HRM, and mapped to an existing linkage map. These genes were mapped on six linkage groups, and the predicted proteins were compared to putative orthologs in other species. Amongst those genes, four were abiotic stress-responsive genes, which can provide a starting point for construction of an abiotic resistance map. Two allergy and detoxification related genes, respectively, were also mapped and analysed. Most of the investigated genes had high similarities to sequences from closely related species such as apricot, apple and other eudicots, and these are putatively orthologous. In addition, it was shown that HRM can be an effective means of genotyping populations for the purpose of constructing a linkage map. Our work provides basic genomic information for the 12 genes, which can be used for further genetic and functional studies.

Keywords

Almond SNP Mapping HRM Protein similarity 

Notes

Acknowledgments

This research was funded by the Australian Research Council Grant No. DP0556459.

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Shu-Biao Wu
    • 1
  • Iraj Tavassolian
    • 2
    • 5
  • Gholamreza Rabiei
    • 1
  • Peter Hunt
    • 3
  • Michelle Wirthensohn
    • 2
  • John P. Gibson
    • 1
  • Christopher M. Ford
    • 2
  • 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
  5. 5.Plant Production, Faculty of AgricultureUniversity of Shahid BahonarKermanIran

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