%A XUE Yan-Tao,LU Ping,SHI Meng-Sha,SUN Hao-Yue,LIU Min-Xuan,WANG Rui-Yun %T Genetic diversity and population genetic structure of broomcorn millet accessions in Xinjiang and Gansu %0 Journal Article %D 2019 %J Acta Agronomica Sinica %R 10.3724/SP.J.1006.2019.84174 %P 1511-1521 %V 45 %N 10 %U {https://zwxb.chinacrops.org/CN/abstract/article_6785.shtml} %8 2019-10-12 %X

Xinjiang and Gansu, are the critical junctures for the ancient Silk Road of China as well as the main cultivation areas of broomcorn millet. In this study, a total of 103 SSR primers and 216 millets were used to analyze the genetic diversity and population genetic structure which promotes the study on origin evolution and propagation path of broomcorn millet. The 299 alleles were detected with an average of 2.9 for each SSR. The mean values of Shannon-Weaver index, Ne, Nei were 0.7360, 0.6298, and 0.5497 respectively, and the range of PIC value was 0.0688-0.7786 with a mean of 0.4714, indicating the moderate polymorphism of these SSRs. The genetic differentiation was very small in terms of the inbreeding line number and genetic differentiation coefficient which were 0.5870 and 0.0383, respectively. The values of Na, Shannon-Weaver index, Nei, PIC of broomcorn millet accessions in Gansu were 2.8252, 0.7347, 0.4501, and 0.4674, respectively, which were higher than those in Xinjiang, indicating more abundant genetic diversity in Gansu. Two hundred and sixteen broomcorn millet accessions could be divided into five groups based on cluster analysis of genetic distance. Group I-IV had seven accessions with a distant genetic relationship with other samples. Ninety-six percent of accessions were distributed in group V, which were further divided into four subgroups at a genetic distance of 0.38. The main accessions of subgroups A and D came from Gansu, those of subgroups B and C were from Xinjiang, indicating that the accessions between Xinjiang and Gansu are obviously separated and permeated with each other. The result of genetic structure analysis was similar to that of UPGMA clustering, both of them related to their geographical distribution.