Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yu, Yan, Haidong, Jiang, Xiaomei, Wang, Xiaoli, Huang, Linkai, Xu, Bin, Zhang, Xinquan, Zhang, Lexin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
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
_version_ 1782493617374363648
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
work_keys_str_mv AT zhangyu geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT yanhaidong geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT jiangxiaomei geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT wangxiaoli geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT huanglinkai geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT xubin geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT zhangxinquan geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers
AT zhanglexin geneticvariationpopulationstructureandlinkagedisequilibriuminswitchgrasswithissrscotandestssrmarkers