کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8892539 | 1628761 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Species identification, genetic diversity and population structure of sweet cherry commercial cultivars assessed by SSRs and the gametophytic self-incompatibility locus
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش باغداری
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چکیده انگلیسی
Assessing the genetic diversity and population structure of sweet cherry is essential for the efficient preservation of germplasms and exploitation of genetic resources. In this study, 10 highly polymorphic simple sequence repeat markers, combined with the gametophytic self-incompatibility locus, were used to evaluate the genetic diversity levels, phylogenetic relationships and population structure among 95 sweet cherry commercial cultivars. A total of 67 alleles were detected, with a mean of 6.09 alleles per locus. In total, five out of 10 simple sequence repeat primers chose according to their polymorphism information content values were able to completely differentiate 95 accessions based on S-genotype information. The un-weighted pair group method with arithmetic mean dendrogram and model-based structural analysis clearly divided the accessions into three distinct populations (Pop 1, 2 and 3) that were consistent with their pedigree-based relationships. Pop 1 and Pop 2 contained 82% of the analyzed accessions and some admixed accessions dispersed between the populations. Pop 3 mainly included sweet cherry cultivars from the Ukraine and their descendants. This study provides an efficient method for species identification and demonstrates its potential application in analyzing genetic fingerprints and diversity levels, as well as verifying parentage, in sweet cherry.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Scientia Horticulturae - Volume 237, 14 July 2018, Pages 28-35
Journal: Scientia Horticulturae - Volume 237, 14 July 2018, Pages 28-35
نویسندگان
Congli Liu, Xiliang Qi, Lulu Song, Yuhong Li, Ming Li,