Discrimination of SNP genotypes associated with complex haplotypes by high resolution melting analysis in almond: implications for improved marker efficiencies |
| |
Authors: | Shu-Biao Wu Tricia K. Franks Peter Hunt Michelle G. Wirthensohn John P. Gibson Margaret Sedgley |
| |
Affiliation: | (1) School of Environmental and Rural Science and The Institute of Genetics and Bioinformatics, The University of New England, Armidale, NSW, 2351, Australia;(2) School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, SA, 5064, Australia;(3) CSIRO Livestock Industries, FD McMaster Laboratory, Chiswick, New England Highway, Armidale, NSW, 2350, Australia;(4) Faculty of Arts and Sciences, The University of New England, Armidale, NSW, 2351, Australia |
| |
Abstract: | 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. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|