Location: Sustainable Perennial Crops LaboratoryTitle: Cultivar identification, pedigree verification, and diversity analysis among Peach (Prunus persica L. Batsch) Cultivars based on Simple Sequence Repeat markers) Author
Submitted to: Journal of the American Society for Horticultural Science
Publication Type: Peer reviewed journal
Publication Acceptance Date: 2/13/2012
Publication Date: 4/24/2012
Citation: Sitther, V., Zhang, D., Harris, D., Okie, W.R., Dhekney, S., Yadav, A. 2012. Cultivar identification, pedigree verification, and diversity analysis among Peach (Prunus persica L. Batsch) Cultivars based on Simple Sequence Repeat markers. Journal of the American Society for Horticultural Science. 137:114-121. Interpretive Summary: Peach is an important food crop. Much is still unknown regarding peach genetics and control of important traits. Novel types of peaches such as those with dark red flesh could be useful in terms of health benefits. This research looked at a wide array of different peach types and methods to study the DNA patterns that exist among them. The techniques developed will allow the researchers to accurately identify each peach tree, understand the pedigree in the peach collection, and eventually predict important traits in breeding programs.
Technical Abstract: The genetic relationships and pedigree inferences among peach (Prunus persica (L.) Batsch) accessions and breeding lines used in genetic improvement were evaluated using 15 simple sequence repeat (SSR) markers. A total of 80 alleles were detected among the 37 peach accessions with an average of 5.53 alleles per locus. The observed mean heterozygosity was 0.219 whereas the mean inbreeding coefficient was 0.635, indicating a high degree of inbreeding among the accessions. Pairwise comparisons based on multilocus SSRs led to the identification of two synonymous groups, including five accessions. Two pairs of parent-offspring and full sibling relationships were identified using the likelihood method implemented in the CERVUS program, and model based Bayesian cluster analysis partially partitioned the accessions with the known pedigree and origin. Sibship reconstruction based on likelihood assignment was supported by clustering analysis. The 37 accessions grouped into four clusters and were largely compatible with the known pedigree and origin of these accessions. The Bayesian model differentiated the accessions in relation to white or yellow fruit flesh color. Eleven of the 15 SSR markers (73.3%) provided accurate cross-amplification in 23 accessions from 9 related Prunus species. Results of the study demonstrate that SSRs could significantly improve the assessment of genetic variation in peach germplasm and selection of cultivars among inbred progenies or siblings, thereby serving as important tool for peach breeding and improvement programs.