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Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers
BACKGROUND: To evaluate genetic variation, population structure, and the extent of linkage disequilibrium (LD), 134 switchgrass (Panicum virgatum L.) samples were analyzed with 51 markers, including 16 ISSRs, 20 SCoTs, and 15 EST-SSRs. RESULTS: In this study, a high level of genetic variation was ob...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226102/ https://www.ncbi.nlm.nih.gov/pubmed/28096766 http://dx.doi.org/10.1186/s41065-016-0007-z |
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author | Zhang, Yu Yan, Haidong Jiang, Xiaomei Wang, Xiaoli Huang, Linkai Xu, Bin Zhang, Xinquan Zhang, Lexin |
author_facet | Zhang, Yu Yan, Haidong Jiang, Xiaomei Wang, Xiaoli Huang, Linkai Xu, Bin Zhang, Xinquan Zhang, Lexin |
author_sort | Zhang, Yu |
collection | PubMed |
description | BACKGROUND: To evaluate genetic variation, population structure, and the extent of linkage disequilibrium (LD), 134 switchgrass (Panicum virgatum L.) samples were analyzed with 51 markers, including 16 ISSRs, 20 SCoTs, and 15 EST-SSRs. RESULTS: In 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(2) of 0.035 across all 51 markers, indicating a trend of higher LD in sub-population 2 than that in sub-population 1 (P < 0.01). CONCLUSIONS: The population structure revealed in this study will guide the design of future association studies using these switchgrass samples. |
format | Online Article Text |
id | pubmed-5226102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52261022017-01-17 Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers Zhang, Yu Yan, Haidong Jiang, Xiaomei Wang, Xiaoli Huang, Linkai Xu, Bin Zhang, Xinquan Zhang, Lexin Hereditas Research BACKGROUND: To evaluate genetic variation, population structure, and the extent of linkage disequilibrium (LD), 134 switchgrass (Panicum virgatum L.) samples were analyzed with 51 markers, including 16 ISSRs, 20 SCoTs, and 15 EST-SSRs. RESULTS: In 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(2) of 0.035 across all 51 markers, indicating a trend of higher LD in sub-population 2 than that in sub-population 1 (P < 0.01). CONCLUSIONS: The population structure revealed in this study will guide the design of future association studies using these switchgrass samples. BioMed Central 2016-04-19 /pmc/articles/PMC5226102/ /pubmed/28096766 http://dx.doi.org/10.1186/s41065-016-0007-z Text en © Zhang et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zhang, Yu Yan, Haidong Jiang, Xiaomei Wang, Xiaoli Huang, Linkai Xu, Bin Zhang, Xinquan Zhang, Lexin Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title | Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title_full | Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title_fullStr | Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title_full_unstemmed | Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title_short | Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers |
title_sort | genetic variation, population structure and linkage disequilibrium in switchgrass with issr, scot and est-ssr markers |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226102/ https://www.ncbi.nlm.nih.gov/pubmed/28096766 http://dx.doi.org/10.1186/s41065-016-0007-z |
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