Theoretical and Applied Genetics

, Volume 118, Issue 1, pp 1–14 | Cite as

High resolution melting analysis of almond SNPs derived from ESTs

  • Shu-Biao Wu
  • Michelle G. Wirthensohn
  • Peter Hunt
  • John P. Gibson
  • Margaret Sedgley
Original Paper

Abstract

High resolution melting curve (HRM) is a recent advance for the detection of SNPs. The technique measures temperature induced strand separation of short PCR amplicons, and is able to detect variation as small as one base difference between samples. It has been applied to the analysis and scan of mutations in the genes causing human diseases. In plant species, the use of this approach is limited. We applied HRM analysis to almond SNP discovery and genotyping based on the predicted SNP information derived from the almond and peach EST database. Putative SNPs were screened from almond and peach EST contigs by HRM analysis against 25 almond cultivars. All 4 classes of SNPs, INDELs and microsatellites were discriminated, and the HRM profiles of 17 amplicons were established. The PCR amplicons containing single, double and multiple SNPs produced distinctive HRM profiles. Additionally, different genotypes of INDEL and microsatellite variations were also characterised by HRM analysis. By sequencing the PCR products, 100 SNPs were validated/revealed in the HRM amplicons and their flanking regions. The results showed that the average frequency of SNPs was 1:114 bp in the genic regions, and transition to transversion ratio was 1.16:1. Rare allele frequencies of the SNPs varied from 0.02 to 0.5, and the polymorphic information contents of the SNPs were from 0.04 to 0.53 at an average of 0.31. HRM has been demonstrated to be a fast, low cost, and efficient approach for SNP discovery and genotyping, in particular, for species without much genomic information such as almond.

Notes

Acknowledgments

We acknowledge Dr. Yizhou Chen for his helpful discussions and suggestions on HRM analysis. This research was funded by Australian Research Council Grant No. DP0556459.

References

  1. Batley J, Edwards D (2007) SNP applications in plants. In: Oraguzie N, Rikkerink E, Gardiner S, Nihal De Silva H (eds) Association mapping in plants. Springer, New York, pp 95–102CrossRefGoogle Scholar
  2. Batley J, Barker G, O’Sullivan H, Edwards KJ, Edwards D (2003) Mining for single nucleotide polymorphisms and insertions/deletions in maize expressed sequence tag data. Plant Physiol 132:84–91PubMedCrossRefGoogle Scholar
  3. Bennett CD, Campbell MN, Cook CJ, Eyre DJ, Nay LM, Nielsen DR, Rasmussen RP, Bernard PS (2003) The LightTyper™: high-throughput genotyping using fluorescent melting curve analysis. Biotechniques 34:1288–1295PubMedGoogle Scholar
  4. Bertin I, Zhu JH, Gale MD (2005) SSCP-SNP in pearl millet—a new marker system for comparative genetics. Theor Appl Genet 110:1467–1472PubMedCrossRefGoogle Scholar
  5. Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32:314–331PubMedGoogle Scholar
  6. Bowcock AM, Ruizlinares A, Tomfohrde J, Minch E, Kidd JR, Cavallisforza LL (1994) High-resolution of human evolutionary trees with polymorphic microsatellites. Nature 368:455–457PubMedCrossRefGoogle Scholar
  7. Ching A, Caldwell KS, Jung M, Dolan M, Smith OS, Tingey S, Morgante M, Rafalski AJ (2002) SNP frequency, haplotype structure and linkage disequilibrium in elite maize inbred lines. BMC Genet 3:19PubMedCrossRefGoogle Scholar
  8. CorbettResearch (2006) High resolution melt assay design and analysis CorProtocol™. Corbett Research, SydneyGoogle Scholar
  9. Fang J, Devanand PS, Chao CT (2005) Practical strategy for identification of single nucleotide polymorphisms in fruiting mei (Prunus mume Sieb. et Zucc.) from amplified fragment length polymorphism fragments. Plant Mol Biol Rep 23:227–239CrossRefGoogle Scholar
  10. Felsenstein J (1993) PHYLIP (phylogeny inference package) version 3.6a2. Department of Genetics, University of Washington, SeattleGoogle Scholar
  11. Flot JF (2007) Champuru 1.0: a computer software for unraveling mixtures of two DNA sequences of unequal lengths. Mol Ecol Notes 7:974–977CrossRefGoogle Scholar
  12. Flot JF, Tillier A, Samadi S, Tillier S (2006) Phase determination from direct sequencing of length-variable DNA regions. Mol Ecol Notes 6:627–630CrossRefGoogle Scholar
  13. Griffiths AJF, Wessler SR, Lewontin RC, Carroll SB (2008) Introduction to genetic analysis, 9th edn. W.H. Freeman and Co., New YorkGoogle Scholar
  14. Gupta PK, Roy JK, Prasad M (2001) Single nucleotide polymorphisms: a new paradigm for molecular marker technology and DNA polymorphism detection with emphasis on their use in plants. Curr Sci 80:524–535Google Scholar
  15. Hayashi K, Hashimoto N, Daigen M, Ashikawa I (2004) Development of PCR-based SNP markers for rice blast resistance genes at the Piz locus. Theor Appl Genet 108:1212–1220PubMedCrossRefGoogle Scholar
  16. Herrmann MG, Durtschi JD, Bromley LK, Wittwer CT, Voelkerding KV (2006a) Amplicon DNA melting analysis for mutation scanning and genotyping: cross-platform comparison of instruments and dyes. Clin Chem 52:494–503PubMedCrossRefGoogle Scholar
  17. Herrmann MG, Durtschi JD, Voelkerding KV, Wittwer CT (2006b) Instrument comparison for DNA genotyping by amplicon melting. J Assoc Lab Automat 11:273–277CrossRefGoogle Scholar
  18. Herrmann MG, Durtschi JD, Wittwer CT, Voelkerding KV (2007) Expanded instrument comparison of amplicon DNA melting analysis for mutation scanning and genotyping. Clin Chem 53:1544–1548PubMedCrossRefGoogle Scholar
  19. Hiratsuka M, Narahara K, Kishikawa Y, Hamdy SI, Endo N, Agatsuma Y, Matsuura M, Inoue T, Tomioka Y, Mizugaki M (2002) A simultaneous LightCycler detection assay for five genetic polymorphisms influencing drug sensitivity. Clin Biochem 35:35–40PubMedCrossRefGoogle Scholar
  20. Hoffmann M, Hurlebaus J, Weilke C (2007) High-resolution melting curve analysis on the LightCycler (R) 480 PCR system. Nat Methods Suppl S:AN17–AN18Google Scholar
  21. Hung C-C, Lee C-N, Chang C-H, Jong Y-J, Chen C-P, Hsieh W-S, Su Y-N, Lin W-L (2008) Genotyping of the G1138A mutation of the FGFR3 gene in patients with achondroplasia using high-resolution melting analysis. Clin Biochem 41:162–166PubMedCrossRefGoogle Scholar
  22. Keller I, Bensasson D, Nichols RA (2007) Transition-transversion bias is not universal: a counter example from grasshopper pseudogenes. PLoS Genet 3:185–191CrossRefGoogle Scholar
  23. Kennerson L, Warburton T, Nelis E, Brewer M, Polly P, De Jonghe P, Timmerman V, Nicholson GA (2007) Mutation scanning the GJB1 gene with high-resolution melting analysis: implications for mutation scanning of genes for Charcot-Marie-Tooth disease. Clin Chem 53:349–352PubMedCrossRefGoogle Scholar
  24. Krypuy M, Ahmed A, Etemadmoghadam D, Hyland S, Australian Ovarian Cancer Study Group, deFazio A, Fox S, Brenton J, Bowtell D, Dobrovic A (2007) High resolution melting for mutation scanning of TP53 exons 5–8. BMC Cancer 7:168PubMedCrossRefGoogle Scholar
  25. Lazzari B, Caprera A, Vecchietti A, Stella A, Milanesi L, Pozzi C (2005) ESTree db: a tool for peach functional genomics. BMC Bioinformatics 6(Suppl 4):S16PubMedCrossRefGoogle Scholar
  26. Lazzari B, Caprera A, Vecchietti A, Merelli I, Barale F, Milanesi L, Stella A, Pozzi C (2008) Version VI of the ESTree db: an improved tool for peach transcriptome analysis. BMC Bioinformatics 9(Suppl 2):S9PubMedCrossRefGoogle Scholar
  27. Lehmensiek A, Sutherland MW, McNamara RB (2008) The use of high resolution melting (HRM) to map single nucleotide polymorphism markers linked to a covered smut resistance gene in barley. Theor Appl GenetGoogle Scholar
  28. Liew M, Pryor R, Palais R, Meadows C, Erali M, Lyon E, Wittwer C (2004) Genotyping of single-nucleotide polymorphisms by high-resolution melting of small amplicons. Clin Chem 50:1156–1164PubMedCrossRefGoogle Scholar
  29. Lipsky RH, Mazzanti CM, Rudolph JG, Xu K, Vyas G, Bozak D, Radel MQ, Goldman D (2001) DNA melting analysis for detection of single nucleotide polymorphisms. Clin Chem 47:635–644PubMedGoogle Scholar
  30. Mackay JF, Wright CD, Bonfiglioli RG (2008) A new approach to varietal identification in plants by microsatellite high resolution melting analysis: application to the verification of grapevine and olive cultivars. Plant Methods 4:8PubMedCrossRefGoogle Scholar
  31. Markham NR, Zuker M (2005) DINAMelt web server for nucleic acid melting prediction. Nucleic Acids Res 33:W577–W581PubMedCrossRefGoogle Scholar
  32. Martienssen RA, Colot V (2001) DNA methylation and epigenetic inheritance in plants and filamentous fungi. Science 293:1070–1074PubMedCrossRefGoogle Scholar
  33. Mekuria GT, Collins GG, Sedgley M (1999) Genetic variability between different accessions of some common commercial olive cultivars. J Hortic Sci Biotechnol 74:309–314Google Scholar
  34. Michel F, Lazowska J, Faye G, Fukuhara H, Slonimski PP (1974) Physical and genetic organization of petite and grande yeast mitochondrial DNA: III. high resolution melting and reassociation studies. J Mol Biol 85:411–431CrossRefGoogle Scholar
  35. Minch E, Ruiz-Linares A, Goldstein DB, Feldman MW, Cavalli-Sforza LL (1998) Microsat2: a computer program for calculating various statistics on microsatellite allele data. Department of Genetics. Stanford University, StanfordGoogle Scholar
  36. Nei M (1987) Molecular evolutionary genetics. Columbia University Press, New YorkGoogle Scholar
  37. Ohnishi Y, Tanaka T, Ozaki K, Yamada R, Suzuki H, Nakamura Y (2001) A high-throughput SNP typing system for genome-wide association studies. J Hum Genet 46:471–477PubMedCrossRefGoogle Scholar
  38. Page RDM (1996) TreeView: an application to display phylogenetic trees on personal computers. Comput Appl Biosci 12:357–358PubMedGoogle Scholar
  39. Rasmussen H, Werge T (2007) A closed-tube assay for genotyping of the 32-bp deletion polymorphism in the chemokine receptor 5 (CCR5) gene: dissociation analysis of amplified fragments of DNA. Mol Cell Probes 21:8–11PubMedCrossRefGoogle Scholar
  40. Reed GH, Kent JO, Wittwer CT (2007) High-resolution DNA melting analysis for simple and efficient molecular diagnostics. Pharmacogenomics 8:597–608PubMedCrossRefGoogle Scholar
  41. Ririe KM, Rasmussen RP, Wittwer CT (1997) Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem 245:154–160PubMedCrossRefGoogle Scholar
  42. Rosenberg MS, Subramanian S, Kumar S (2003) Patterns of transitional mutation biases within and among mammalian genomes. Mol Biol Evol 20:988–993PubMedCrossRefGoogle Scholar
  43. Rozen S, Skaletsky H (2000) Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 132:365–386PubMedGoogle Scholar
  44. Salisbury BA, Pungliya M, Choi JY, Jiang R, Sun XJ, Stephens JC (2003) SNP and haplotype variation in the human genome. Mutat Res 526:53–61PubMedGoogle Scholar
  45. Sambrook J, Russell DW, Cold Spring Harbor Laboratory (2001) Molecular cloning: a laboratory manual, 3rd edn. Cold Spring Harbor Laboratory, Cold Spring HarborGoogle Scholar
  46. SantaLucia J Jr (1998) A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor hermodynamics. Proc Natl Acad Sci USA 95:1460–1465PubMedCrossRefGoogle Scholar
  47. Schmid KJ, Sorensen TR, Stracke R, Torjek O, Altmann T, Mitchell-Olds T, Weisshaar B (2003) Large-scale identification and analysis of genome-wide single-nucleotide polymorphisms for mapping in Arabidopsis thaliana. Genome Res 13:1250–1257PubMedCrossRefGoogle Scholar
  48. Shen JC, Rideout WM 3rd, Jones PA (1994) The rate of hydrolytic deamination of 5-methylcytosine in double-stranded DNA. Nucleic Acids Res 22:972–976PubMedCrossRefGoogle Scholar
  49. Silva C, Garcia-Mas J, Sánchez AM, Arús P, Oliveira MM (2005) Looking into flowering time in almond (Prunus dulcis (Mill) D. A. Webb): the candidate gene approach. Theor Appl Genet 110:959–968PubMedCrossRefGoogle Scholar
  50. Steinert M, Van Assel S (1974) Base composition heterogeneity in kinetoplast DNA from four species of hemoflagellates. Biochem Biophys Res Commun 61:1249–1255PubMedCrossRefGoogle Scholar
  51. Stephens AJ, Inman-Bamber J, Giffard PM, Huygens F (2008) High-resolution melting analysis of the spa repeat region of Staphylococcus aureus. Clin Chem 54:432–436PubMedCrossRefGoogle Scholar
  52. Tatusova TA, Madden TL (1999) BLAST 2 Sequences, a new tool for comparing protein and nucleotide sequences. FEMS Microbiol Lett 174:247–250PubMedCrossRefGoogle Scholar
  53. The-International-HapMap-Consortium (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449:851–861CrossRefGoogle Scholar
  54. Toyota T, Watanabe A, Shibuya H, Nankai M, Hattori E, Yamada K, Kurumaji A, Karkera JD, Detera-Wadleigh SD, Yoshikawa T (2000) Association study on the DUSP6 gene, an affective disorder candidate gene on 12q23, performed by using fluorescence resonance energy transfer-based melting curve analysis on the LightCycler. Mol Psychiatry 5:489–494PubMedCrossRefGoogle Scholar
  55. Tsuchihashi Z, Dracopoli N (2002) Progress in high throughput SNP genotyping methods. Pharmacogenomics J 2:103–110PubMedCrossRefGoogle Scholar
  56. van Tienderen PH, de Haan AA, van der Linden CG, Vosman B (2002) Biodiversity assessment using markers for ecologically important traits. Trends Ecol Evol 17:577–582CrossRefGoogle Scholar
  57. Wakeley J (1994) Substitution-rate variation among sites and the estimation of transition bias. Mol Biol Evol 11:436–442PubMedGoogle Scholar
  58. White HE, Hall VJ, Cross NCP (2007) Methylation-sensitive high-resolution melting-curve analysis of the SNRPN gene as a diagnostic screen for Prader-Willi and Angelman syndromes. Clin Chem 53:1960–1962PubMedCrossRefGoogle Scholar
  59. Willmore-Payne C, Holden JA, Tripp S, Layfield LJ (2005) Human malignant melanoma: detection of BRAF- and c-kit-activating mutations by high-resolution amplicon melting analysis. Hum Pathol 36:486–493PubMedCrossRefGoogle Scholar
  60. Wittwer CT, Reed GH, Gundry CN, Vandersteen JG, Pryor RJ (2003) High-resolution genotyping by amplicon melting analysis using LCGreen. Clin Chem 49:853–860PubMedCrossRefGoogle Scholar
  61. Wojdacz TK, Dobrovic A (2007) Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation. Nucleic Acids Res 35:e41PubMedCrossRefGoogle Scholar
  62. Woolley FM, Collins GG, Sedgley M (2000) Application of DNA fingerprinting for the classification of selected almond [Prunus dulcis (Miller) D. A. Webb] cultivars. Aust J Exp Agric 40:995–1001CrossRefGoogle Scholar
  63. Xie H, Sui Y, Chang F-Q, Xu Y, Ma R-C (2006) SSR allelic variation in almond (Prunus dulcis Mill.). Theor Appl Genet 112:366–372PubMedCrossRefGoogle Scholar
  64. Zhou L, Vandersteen J, Wang L, Fuller T, Taylor M, Palais B, Wittwer CT (2004) High-resolution DNA melting curve analysis to establish HLA genotypic identity. Tissue Antigens 64:156–164PubMedCrossRefGoogle Scholar
  65. Zhou LM, Wang L, Palais R, Pryor R, Wittwer CT (2005) High-resolution DNA melting analysis for simultaneous mutation scanning and genotyping in solution. Clin Chem 51:1770–1777PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Shu-Biao Wu
    • 1
  • Michelle G. Wirthensohn
    • 2
  • Peter Hunt
    • 3
  • 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 Laboratory, ChiswickArmidaleAustralia
  4. 4.Faculty of Arts and SciencesThe University of New EnglandArmidaleAustralia

Personalised recommendations