Unknown

Dataset Information

0

Isolation and characterization of microsatellite loci for Prunus mongolica (Rosaceae).


ABSTRACT: Premise of the Study:Microsatellite primers were developed in Prunus mongolica (Rosaceae), a relict flora endemic in arid areas of the Asian interior, to investigate the genetic diversity, phylogeography, population structure, and history of the species. Methods and Results:Fifty-one microsatellite loci, including di-, tri-, and tetranucelotide repeats, were identified using transcriptome sequencing and bioinformatic screening. The number of alleles ranged from seven to 11 and the levels of observed and expected heterozygosity ranged from 0.545 to 1.000 and 0.600 to 0.989, respectively. Most of the primers also amplified in a group of congeneric species (P. triloba, P. davidiana, P. persica, P. cerasifera, and P. serrulata). Conclusions:This set of microsatellite loci is useful for studying the genetic diversity of P. mongolica. In addition, they can also be used to investigate the population structure, phylogeography, and landscape genetic patterns of congeneric species.

SUBMITTER: Cheng YC 

PROVIDER: S-EPMC6025809 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Isolation and characterization of microsatellite loci for <i>Prunus mongolica</i> (Rosaceae).

Cheng Yu-Chen YC   Zhang De-Jian DJ   Lu Zhan-Yuan ZY   Ye Xue-Song XS   Wang Jian-Guo JG   Sun Ping P   Zhang Bao-Wei BW  

Applications in plant sciences 20180626 6


<h4>Premise of the study</h4>Microsatellite primers were developed in <i>Prunus mongolica</i> (Rosaceae), a relict flora endemic in arid areas of the Asian interior, to investigate the genetic diversity, phylogeography, population structure, and history of the species.<h4>Methods and results</h4>Fifty-one microsatellite loci, including di-, tri-, and tetranucelotide repeats, were identified using transcriptome sequencing and bioinformatic screening. The number of alleles ranged from seven to 11  ...[more]

Similar Datasets

| S-EPMC4105279 | biostudies-literature
| S-EPMC4332147 | biostudies-literature
| S-EPMC6055551 | biostudies-literature
| S-EPMC4103144 | biostudies-literature
| S-EPMC6384321 | biostudies-literature
| S-EPMC5357126 | biostudies-literature
| S-EPMC3233440 | biostudies-literature
| S-EPMC5584818 | biostudies-literature