This work was supported by the National High-Technology Research and Development Program (863 Program) of China (No. 2012AA101801-02), the National Natural Science Foundation of China (NSFC) (No. 31201845), the spring plan of Ministry of Education, and the Sichuan Agricultural University Students Innovation Plan (No. 121062603)

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. 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 r² 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). The population structure revealed in this study will guide the design of future association studies using these switchgrass samples.