Development and characterization of microsatellite markers in Prunus sibirica (Rosaceae).

Appl Plant Sci

Center for Computational Biology, National Engineering Laboratory for Tree Breeding, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, People's Republic of China.

Published: March 2013

AI Article Synopsis

  • The study developed microsatellite loci for Prunus sibirica to explore genetic diversity, population structure, and aid in breeding late-blooming cultivars.
  • Researchers created 19 primer pairs using a magnetic bead enrichment technique, analyzing 40 individuals from three wild populations of P. sibirica and six from P. armeniaca, discovering varying levels of alleles and heterozygosity.
  • The newly developed microsatellite primer pairs can enhance population genetics research and support germplasm identification and selection in breeding P. sibirica and similar species.

Article Abstract

Premise Of The Study: Microsatellite loci were developed for Prunus sibirica to investigate genetic diversity, population genetic structure, and marker-assisted selection of late-blooming cultivars in the breeding of P. sibirica. •

Methods And Results: Using a magnetic bead enrichment strategy, 19 primer pairs were developed and characterized across 40 individuals from three P. sibirica wild populations and six individuals of P. armeniaca. The number of alleles per locus varied from three to 11 and the observed and expected heterozygosities ranged from 0.063 to 0.917 and 0.295 to 0.876, respectively, in the three P. sibirica wild populations. All primer pairs could be successfully amplified in six individuals of P. armeniaca. •

Conclusions: These microsatellite primer pairs should be useful for population genetics, germplasm identification, and marker-assisted selection in the breeding of P. sibirica and related species.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4105279PMC
http://dx.doi.org/10.3732/apps.1200074DOI Listing

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