ArticleHereditas2016
Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers.
Article in Hereditas, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Genetic diversity of Iranian Acanthophyllum species collection using SCoT and SRAP markers.Scientific reports · 2026Article
- Molecular Characterization ofGenes · 2022Article
- Full-length transcriptome sequencing analysis and development of EST-SSR markers for the endangered species Populus wulianensis.Scientific reports · 2020Article
- Article
- Assessment of genetic diversity inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2019Article
- Assessment of genetic diversity, population structure and sex identification in dioecious crop,Heliyon · 2019Article
- Genetic diversity and population structure of Miscanthus lutarioriparius, an endemic plant of China.PloS one · 2019Article
- Assessment of genetic diversity in Vigna unguiculata L. (Walp) accessions using inter-simple sequence repeat (ISSR) and start codon targeted (SCoT) polymorphic markers.BMC genetics · 2017Article
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Authors and funding
8 authors.
Funding
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Abstract
backgroundTo evaluate genetic variation, population structure, and the extent of linkage disequilibrium (LD), 134 switchgrass (
resultsIn this study, a high level of genetic variation was observed in the switchgrass samples and they had an average Nei's gene diversity index (H) of 0.311. A total of 793 bands were obtained, of which 708 (89.28 %) were polymorphic. Using a parameter marker index (MI), the efficiency of the three types of markers (ISSR, SCoT, and EST-SSR) in the study were compared and we found that SCoT had a higher marker efficiency than the other two markers. The 134 switchgrass samples could be divided into two sub-populations based on STRUCTURE, UPGMA clustering, and principal coordinate analyses (PCA), and upland and lowland ecotypes could be separated by UPGMA clustering and PCA analyses. Linkage disequilibrium analysis revealed an average r
conclusionsThe population structure revealed in this study will guide the design of future association studies using these switchgrass samples.
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