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Acta Agronomica Sinica ›› 2019, Vol. 45 ›› Issue (10): 1511-1521.doi: 10.3724/SP.J.1006.2019.84174

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Genetic diversity and population genetic structure of broomcorn millet accessions in Xinjiang and Gansu

XUE Yan-Tao1,2,LU Ping1,SHI Meng-Sha1,SUN Hao-Yue1,LIU Min-Xuan1,*(),WANG Rui-Yun2,3,*()   

  1. 1Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    2College of Agriculture, Shanxi Agricultural University, Taigu 030801, Shanxi, China
    3Institute of Crop Germplasm Resources, Shanxi Academy of Agricultural Sciences / Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau, Ministry of Agriculture / Shanxi Key Laboratory of Genetic Resources and Genetic Improvement of Minor Crops, Taiyuan 030031, Shanxi, China
  • Received:2018-12-21 Accepted:2019-05-12 Online:2019-10-12 Published:2019-09-10
  • Contact: Min-Xuan LIU,Rui-Yun WANG E-mail:liuminxuan@caas.cn;wry925@126.com
  • Supported by:
    This study was supported by the China Agriculture Research System(CARS-07-12[1].5-A1);This study was supported by the China Agriculture Research System(CARS-06-13.5-A16);the Crop Germplasm Resources Protection of Ministry of Agriculture(NB2012-2130135-25-06-1);the National Natural Science Foundation of China(31271791);the Scientific Research Foundation for Returned Scholars in Shanxi Province(2016-066);the Key Research and Development Program (Agriculture) of Shanxi Province of China(201803D221008-5)

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Abstract:

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.

Key words: broomcorn millet, Xinjiang, Gansu, SSR marker, genetic diversity

Table 1

Broomcorn millet varieties and landraces used in this study"

编号
Number		 材料来源地
Material origin		 材料数量
Number of material		 编号
Number		 材料来源地
Material origin		 材料数量
Number of material
1 新疆青河 Qinghe, Xinjiang 5 24 甘肃皋兰 Gaolan, Gansu 29
2 新疆阿勒泰 Aletai, Xinjiang 1 25 甘肃泾川 Jingchuan, Gansu 11
3 新疆哈巴河 Habahe, Xinjiang 4 26 甘肃灵台 Lingtai, Gansu 7
4 新疆吉木乃 Jeminay, Xinjiang 1 27 甘肃平凉 Pingliang, Gansu 9
5 新疆塔城 Tarbagatay, Xinjiang 12 28 甘肃华亭 Huating, Gansu 6
6 新疆额敏 Emin, Xinjiang 2 29 甘肃静宁 Jingning, Gansu 11
7 新疆伊吾 Yiwu, Xinjiang 1 30 甘肃敦煌 Dunhuang, Gansu 3
8 新疆巴里坤 Balikun, Xinjiang 2 31 甘肃金塔 Jinta, Gansu 5
9 新疆哈密 Hami, Xinjiang 1 32 甘肃酒泉 Jiuquan, Gansu 4
10 新疆乌鲁木齐 Urumqi, Xinjiang 2 33 甘肃高台 Gaotai, Gansu 1
11 新疆阜康 Fukang, Xinjiang 2 34 甘肃临泽 Linze, Gansu 2
12 新疆米泉 Miquan, Xinjiang 2 35 甘肃张掖 Zhangye, Gansu 2
13 新疆昌吉 Changji, Xinjiang 5 36 甘肃民乐 Minle, Gansu 1
14 新疆玛纳斯 Manas, Xinjiang 1 37 甘肃民勤 Minqin, Gansu 8
15 新疆沙湾 Shawan, Xinjiang 14 38 甘肃武威 Wuwei, Gansu 3
16 新疆新源 Xinyuan, Xinjiang 2 39 甘肃古浪 Gulang, Gansu 8
17 新疆特克斯 Tekes, Xinjiang 3 40 甘肃永登 Yongdeng, Gansu 5
18 新疆伊宁 Yining, Xinjiang 6 41 甘肃兰州 Lanzhou, Gansu 2
19 新疆霍城 Huocheng, Xinjiang 1 42 甘肃榆中 Yuzhong, Gansu 9
20 新疆焉耆 Yanqi, Xinjiang 2 43 甘肃崇信 Chongxin, Gansu 7
21 新疆库尔勒 Korla, Xinjiang 2 44 甘肃庄浪 Zhuanglang, Gansu 2
22 新疆拜城 Baicheng, Xinjiang 1 45 甘肃其他地区 Other regions, Gansu 4
23 新疆其他地区 Other regions, Xinjiang 5

Table 2

Genetic parameters from the 103 polymorphic SSR markers used in this study"

位点
Locus		 观测等位基因 Na 有效等位基因 Ne 多样性指数 I 观测杂合度 Ho 期望杂合度 He Nei’s期望杂
合度Nei		 多态性信息含量指数 PIC 近交系数 FIS 遗传分化系数 FST
BM5 2 1.9383 0.6772 0.8153 0.5144 0.4841 0.6726 0.6056 0.0011
BM114 2 1.8462 0.6509 0.2990 0.5405 0.4583 0.4586 -0.5072 0.0010
BM136 3 1.5378 0.6510 0.7750 0.6494 0.3497 0.5036 0.4893 0.0605
BM289 3 1.6935 0.6233 0.4865 0.5894 0.4095 0.5562 -0.2865 0.0072
BM295 3 1.6801 0.6751 0.6458 0.5942 0.4048 0.5802 0.0999 0.0248
BM306 3 1.9004 0.8133 0.8699 0.5243 0.4738 0.6085 0.7119 0.0177
BM344 2 1.9130 0.6702 0.9052 0.5216 0.4773 0.5025 0.8210 0.0060
BM374 3 2.0044 0.7710 0.9948 0.4976 0.5011 0.5255 0.9911 0.0555
BM378 4 3.1204 1.1785 0.5956 0.3180 0.6795 0.6992 0.3691 0.0330
BM396 5 3.8669 1.4184 0.4412 0.2568 0.7414 0.6216 0.1709 0.0252
位点
Locus		 观测等位基因 Na 有效等位基因 Ne 多样性指数 I 观测杂合度 Ho 期望杂合度 He Nei’s期望
杂合度Nei		 多态性信息
含量指数 PIC		 近交系数 FIS 遗传分化系数 FST
BM484 2 1.9989 0.6929 0.0330 0.4991 0.4997 0.0961 -0.9439 0.0001
BM552 2 1.4272 0.4763 0.9193 0.6998 0.2993 0.5298 0.7391 0.0001
BM637 3 1.9772 0.8574 0.9840 0.5045 0.4942 0.5729 0.9651 0.0194
BM787 2 1.6923 0.5993 0.9949 0.5899 0.4091 0.4409 0.9896 0.0212
BM994 1 1.0000 0.0000 1.0000 1.0000 0.0000 0.1345 — 0.0000
BM1303 3 2.3398 0.9215 0.1317 0.4260 0.5726 0.2976 -0.5275 0.0004
BM1332 3 2.2217 0.8677 0.1055 0.4487 0.5499 0.2960 -0.6839 0.0055
BM1419 3 2.0267 0.7383 0.1078 0.4922 0.5066 0.2653 -0.7938 0.0068
BM1477 4 1.3645 0.4784 1.0000 0.7322 0.2671 0.3471 1.0000 0.0396
BM1533 3 2.0163 0.7229 0.0632 0.4945 0.5040 0.3449 -0.8610 0.0008
BM1745 3 1.5077 0.5428 0.9888 0.6623 0.3368 0.4730 0.9449 0.0513
BM4724 2 1.4196 0.4718 0.7067 0.7037 0.2956 0.4283 -0.0304 0.0696
BM4739 1 1.0000 0.0000 1.0000 1.0000 0.0000 0.0688 — 0.0000
BM4741 2 1.9982 0.6927 0.0299 0.4992 0.4996 0.1703 -0.9493 0.0001
BM4749 2 1.9918 0.6911 0.0640 0.5008 0.4979 0.2091 -0.8783 0.0000
BM4761 2 1.9527 0.6810 0.1651 0.5110 0.4879 0.2696 -0.7295 0.0009
BM4830 2 1.9998 0.6931 0.0488 0.4988 0.5000 0.1752 -0.9021 0.0013
BM4846 2 2.0000 0.6931 0.0485 0.4985 0.5000 0.3555 -0.9108 0.0007
BM4847 3 1.2757 0.3930 1.0000 0.7833 0.2161 0.3205 1.0000 0.0018
BM4851 2 1.9979 0.6926 0.0328 0.4992 0.4995 0.2720 -0.9501 0.0007
BM4858 3 2.8140 1.0671 0.4545 0.3537 0.6446 0.6007 0.0291 0.0539
BM4871 2 1.8181 0.6422 0.3163 0.5489 0.4500 0.4527 -0.5962 0.0189
BM4877 2 2.0000 0.6931 0.0203 0.4987 0.5000 0.1811 -0.9549 0.0005
BM4882 2 1.7734 0.6278 0.3575 0.5628 0.4361 0.4110 -0.5323 0.0131
BM4947 3 2.0330 0.7408 0.0707 0.4906 0.5081 0.2495 -0.8285 0.0011
BM4954 2 1.9966 0.6923 0.0518 0.4996 0.4991 0.2503 -0.8918 0.0010
BM4956 5 3.5531 1.4317 0.7083 0.2793 0.7186 0.7786 0.5725 0.0603
BM4958 4 2.3304 0.9634 0.2062 0.4276 0.5709 0.4514 -0.4649 0.0082
BM4962 3 2.8938 1.0796 0.5833 0.3437 0.6544 0.6773 0.3670 0.0506
BM4965 2 1.6047 0.5644 0.4963 0.6218 0.3768 0.5900 -0.3359 0.0002
BM4967 3 2.5341 0.9923 0.9597 0.3926 0.6054 0.6822 0.9010 0.3009
BM4969 2 1.4404 0.4838 0.7055 0.6932 0.3058 0.5857 0.1076 0.0180
BM4973 2 1.7302 0.6130 0.3949 0.5769 0.4220 0.4811 -0.4310 0.0001
BM4997 4 1.8617 0.8692 0.8986 0.5360 0.4628 0.5248 0.7613 0.0314
BM5037 3 2.3310 0.9322 0.9845 0.4275 0.5710 0.6071 0.9675 0.0392
BM5038 4 2.4239 0.9921 0.9904 0.4112 0.5874 0.5465 0.9764 0.0497
BM5043 3 1.3924 0.4768 0.9158 0.7174 0.2818 0.4556 0.6614 0.0012
BM5181 5 4.4081 1.5426 0.9860 0.2241 0.7731 0.7603 0.9794 0.0273
BM5190 2 1.9877 0.6901 0.0890 0.5018 0.4969 0.3075 -0.8523 0.0008
BM5191 2 1.0649 0.1398 0.9510 0.9388 0.0610 0.4038 0.0714 0.0075
位点
Locus		 观测等位基因 Na 有效等位基因 Ne 多样性指数 I 观测杂合度 Ho 期望杂合度 He Nei’s期望
杂合度Nei		 多态性信息
含量指数 PIC		 近交系数 FIS 遗传分化系数 FST
BM5197 3 2.2495 0.9122 0.7278 0.4428 0.5555 0.7230 0.4842 0.0136
BM5198 4 2.3177 1.0676 0.7933 0.4301 0.5685 0.6514 0.6064 0.0402
BM5199 3 1.4330 0.5004 0.9303 0.6971 0.3022 0.4156 0.7935 0.0415
BM5200 3 2.7119 1.0473 0.9310 0.3666 0.6312 0.7036 0.8719 0.0906
BM5222 2 1.0960 0.1862 0.9855 0.9122 0.0876 0.1679 0.8169 0.0739
BM5233 3 2.3928 0.9509 0.8513 0.4164 0.5821 0.6892 0.6708 0.0568
BM5236 5 3.2999 1.3375 0.9838 0.3011 0.6970 0.7312 0.9753 0.0320
BM5255 4 2.7716 1.1500 0.9497 0.3588 0.6392 0.7069 0.9107 0.0090
BM5259 2 1.7637 0.6246 0.9150 0.5656 0.4330 0.6083 0.7945 0.0066
BM5260 4 3.1804 1.2490 0.9110 0.3126 0.6856 0.7343 0.8789 0.0037
BM5278 2 1.8589 0.6547 0.2959 0.5368 0.4620 0.4528 -0.5496 0.0017
BM5279 5 2.0148 0.8350 0.4183 0.4947 0.5037 0.6353 -0.1277 0.0191
BM5292 2 1.8111 0.6400 0.3478 0.5508 0.4478 0.5679 -0.6191 0.1899
LMX258 3 2.1885 0.8523 0.1667 0.4556 0.5431 0.3502 -0.5358 0.0006
LMX503 4 3.0753 1.1609 0.3370 0.3233 0.6748 0.5510 0.0283 0.0609
LMX515 3 1.5659 0.6700 0.8039 0.6377 0.3614 0.3719 0.4715 0.0008
LMX621 4 1.3985 0.5747 1.0000 0.7143 0.2849 0.3751 1.0000 0.0184
LMX632 3 2.0696 0.7690 0.0643 0.4817 0.5168 0.3580 -0.8255 0.0015
LMX635 1 1.0000 0.0000 1.0000 1.0000 0.0000 0.3182 — 0.0000
LMX645 4 2.8467 1.1221 0.2341 0.3497 0.6487 0.4002 -0.3148 0.0415
LMX653 2 1.9231 0.6730 0.2000 0.5184 0.4800 0.5007 -0.6887 0.0056
LMX684 2 1.8824 0.6616 0.2722 0.5299 0.4688 0.4990 -0.5866 0.0099
LMX786 2 1.5437 0.5370 0.6602 0.6469 0.3522 0.4864 -0.3160 0.1710
LMX691 2 1.8243 0.6442 0.3103 0.5470 0.4518 0.4161 -0.5112 0.0090
LMX836 4 1.5324 0.7176 0.9902 0.6517 0.3474 0.4054 0.9634 0.0443
LMX1067 5 1.8316 0.8386 0.8045 0.5447 0.4540 0.5499 0.5335 0.1305
LMX1080 5 3.4824 1.3477 0.4615 0.2850 0.7128 0.6346 0.2112 0.0044
LMX1220 4 1.3272 0.5161 0.9341 0.7528 0.2465 0.4095 0.7219 0.0555
LMX1251 4 2.5935 1.0376 0.3838 0.3840 0.6144 0.5778 -0.2001 0.0480
LMX1380 2 1.9652 0.6843 0.8032 0.5075 0.4912 0.6504 0.5540 0.2873
LMX1387 2 1.9350 0.6763 0.9895 0.5155 0.4832 0.5116 0.9653 0.3534
LMX1400 3 1.7831 0.7811 0.6970 0.5597 0.4392 0.5739 0.1793 0.0256
LMX1429 2 1.1216 0.2200 0.9950 0.8913 0.1084 0.2220 0.9556 0.0270
LMX1625 4 1.9275 0.8626 0.7027 0.5175 0.4812 0.5069 0.3871 0.0083
LMX1672 2 1.9549 0.6816 0.1899 0.5100 0.4885 0.4969 -0.6730 0.0031
LMX1760 4 1.1975 0.3842 0.9780 0.8347 0.1649 0.3505 0.8739 0.0311
LMX1749 4 2.2324 0.9120 1.0000 0.4465 0.5521 0.5729 1.0000 0.2580
LMX1761 4 1.3168 0.5155 0.8987 0.7586 0.2406 0.4564 0.5788 0.0286
LMX1959 3 2.2523 0.8898 0.9875 0.4422 0.5560 0.6362 0.9795 0.0156
LMX2175 4 3.4687 1.3006 0.6364 0.2866 0.7117 0.7296 0.4332 0.0015
LMX2410 2 1.9766 0.6872 0.1088 0.5046 0.4941 0.3185 -0.8091 0.0001
LMX1940 3 1.2271 0.3713 1.0000 0.8145 0.1851 0.2953 1.0000 0.0484
LMX2019 3 2.0034 0.7652 0.2069 0.4905 0.5082 0.3828 -0.6153 0.0087
LMX2068 4 2.6397 1.0942 1.0000 0.3773 0.6212 0.6074 1.0000 0.0130
LMX2074 2 1.0113 0.0347 0.9888 0.9888 0.0112 0.2638 -0.0076 0.0010
LMX2185 3 2.2892 0.9545 0.9899 0.4354 0.5632 0.5831 0.9854 0.0150
LMX2281 2 1.3303 0.4144 1.0000 0.7510 0.2483 0.4096 1.0000 0.0017
LMX2305 4 3.1052 1.1747 0.7943 0.3196 0.6780 0.7425 0.5881 0.1369
LMX2370 2 1.6067 0.5652 0.4947 0.6214 0.3776 0.5126 -0.3722 0.0079
位点
Locus		 观测等位基因 Na 有效等位基因 Ne 多样性指数 I 观测杂合度 Ho 期望杂合度 He Nei’s期望
杂合度Nei		 多态性信息
含量指数 PIC		 近交系数 FIS 遗传分化系数 FST
LMX2382 2 1.0937 0.1830 0.9655 0.9141 0.0856 0.4081 0.6754 0.0047
LMX2540 2 1.2207 0.3262 0.8093 0.8187 0.1808 0.3966 -0.0631 0.0030
LMX2734 4 3.0566 1.1767 0.7297 0.3241 0.6728 0.6607 0.5920 0.0151
LMX2782 3 1.4680 0.6063 0.8426 0.6804 0.3188 0.4834 0.5870 0.0185
Mean 2.9029 2.0087 0.7360 0.6298 0.5497 0.4491 0.4714 0.5870 0.0383
SD 0.9952 0.6657 0.3137 0.3517 0.1778 0.1773

Fig. 1

Dendrogram of 216 broomcorn millet accessions"

Table 3

Estimates of genetic diversity within two populations"

群体
Population		 观测等位基因 Na 有效等位基因 Ne 多样性指数
I		 观测杂合度
Ho		 期望杂合度
He		 Nei’s期望
杂合度 Nei		 多态性信息含量指数 PIC
新疆 Xinjiang 2.6117±0.8544 1.8457±0.5899 0.6517±0.3083 0.6185±0.3807 0.5937±0.1896 0.4031±0.1882 0.4123
甘肃 Gansu 2.8252±0.9643 2.0155±0.6846 0.7347±0.3196 0.6379±0.3489 0.5479±0.1780 0.4501±0.1772 0.4674

Fig. 2

Population genetic structure graph of 216 broomcorn millet accessions"

[1] 刘天鹏, 董孔军, 董喜存, 何继红, 刘敏轩, 任瑞玉, 张磊, 杨天育 . 12C 6+离子束辐照糜子诱变突变群体的构建与SSR分析 . 作物学报, 2018,44:144-156.
Liu T P, Dong K J, Dong X C, He J H, Liu M X, Ren R Y, Zhang L, Yang T Y . Pedigree construction and SSR analysis of broomcorn millet mutant by 12C 6+ ion beam irradiation . Acta Agron Sin, 2018,44:144-156 (in Chinese with English abstract).
[2] Wang R Y, Wang H G, Liu X Y, Lian S, Chen L, Qiao Z J, Mcinerney C E, Wang L . Drought-induced transcription of resistant and sensitive common millet varieties. J Animal Plant Sci, 2017,27:1303-1314.
[3] 王星玉, 王纶, 温琪汾 . 黍稷的名实考证及规范. 植物遗传资源学报, 2009,11:132-138.
Wang X Y, Wang L, Wen Q F . Textual research and standardization of Chinese name of broomcorn millet germplasm resources. J Plant Genet Resour, 2009,11:132-138 (in Chinese with English abstract).
[4] 王瑞云, 杨阳, 王海岗, 陈凌, 王纶, 陆平, 刘敏轩, 乔治军 . 糜子PmNCED1的克隆及其对PEG胁迫的响应. 核农学报, 2018,32:244-256.
Wang R Y, Yang Y, Wang H G, Chen L, Wang L, Lu P, Liu M X, Qiao Z J . Cloning of PmNCED1 and its response to PEG stress. J Nuclear Agric, 2018,32:244-256 (in Chinese with English abstract).
[5] 刁现民, 程汝宏 . 十五年区试数据分析展示谷子糜子育种现状. 中国农业科学, 2017,50:4469-4474.
Diao X M, Cheng R H . Current breeding situation of foxtail millet and common millet in China as revealed by exploitation of 15 years regional adaptation test data. Sci Agric Sin, 2017,50:4469-4474 (in Chinese with English abstract).
[6] 梁海燕, 李海, 林凤仙, 张翔宇, 张知, 宋晓强 . 不同糜子品种抗倒伏性田间鉴定及抗倒评价指标的筛选分析. 作物杂志, 2018, ( 4):37-41.
Liang H Y, Li H, Lin F X, Zhang X Y, Zhang Z, Song X Q . Analysis of lodging resistance field identification and anti- inversion evaluation indexes of different broomcorn millet accessions. Crops, 2018, ( 4):37-41 (in Chinese with English abstract).
[7] Chen L, Qiao Z J, Wang J J, Wang H G, Cao X N, Tian X, Liu S C, Qin H B, Yang G Z . Effects of different tillage techniques on yield and water use efficiency in broomcorn millet. Agric Sci Technol, 2017,18:432-437.
[8] Habiyaremye C, Matanguihan J B, D’Alpoim G J, Ganjyal G M, Whiteman M R, Kidwell K K, Murphy K M . Proso millet ( Panicum miliaceum L.) and its potential for cultivation in the Pacific Northwest, US: a review. Front Plant Sci, 2017,7:1961.
[9] 王璐琳, 王瑞云, 何杰丽, 薛延桃, 陈凌, 王海岗, 乔治军 . 糜子特异性 SSR 标记的开发. 山西农业科学, 2018,46(1):1-4.
Wang L L, Wang R Y, He J L, Xue Y T, Chen L, Wang H G, Qiao Z J . Development of broomcorn millet specific SSR marker. Shanxi Agric Sci, 2018,46(1):1-4 (in Chinese with English abstract).
[10] Manifesto M M, Schlatter A R, Hopp H E, Suárez E Y, Dubcovsky J . Quantitative evaluation of genetic diversity in wheat germplasm using molecular markers. Crop Sci, 2001,41:682-690.
[11] Hu X Y, Wang J F, Lu P, Zhang H S . Assessment of genetic diversity in broomcorn millet ( Panicum miliaceum L.) using SSR markers. J Genet Genomics, 2009,36:491-500.
[12] 王银月, 刘敏轩, 陆平, 乔治军, 杨天育, 李海, 崔喜艳 . 构建黍稷分子遗传图谱 SSR 引物的筛选. 作物杂志, 2014, ( 4):32-38.
Wang Y Y, Liu M X, Lu P, Qiao Z J, Yang T Y, Li H, Cui X Y . Construction of molecular genetic map of broomcorn millet for SSR primer screening. Crops, 2014, ( 4):32-38 (in Chinese with English abstract).
[13] Jiang Y, Li H, Zhang J, Xiang J, Cheng R, Liu G . Whole genomic EST-SSR development based on high-throughput transcript sequencing in proso millet ( Panicum miliaceum L.). Int J Agric Biol, 2018,20:617-620.
[14] 王瑞云, 刘笑瑜, 王海岗, 陆平, 刘敏轩, 陈凌, 乔治军 . 用高基元微卫星标记分析中国糜子遗传多样性. 中国农业科学, 2017,50:3848-3859.
Wang R Y, Liu X Y, Wang H G, Lu P, Liu M X, Chen L, Qiao Z J . Analysis of genetic diversity of Chinese broomcorn millet by using high elementary microsatellite markers. Sci Agric Sin, 2017,50:3848-3859 (in Chinese with English abstract).
[15] 薛延桃, 陆平, 乔治军, 刘敏轩, 王瑞云 . 基于SSR标记的黍稷种质资源遗传多样性及亲缘关系研究. 中国农业科学, 2018,51:19-39.
Xue Y T, Lu P, Qiao Z J, Liu M X, Wang R Y . Genetic diversity and genetic telationship of broomcorn millet ( Panicum miliaceum L.) germplasm based on SSR markers. Sci Agric Sin, 2018,51:19-39 (in Chinese with English abstract).
[16] 闫锋, 姜元麒, 王成, 曾玲玲, 卢环, 董扬, 赵蕾 . 20份糯性糜子品种的遗传多样性分析. 黑龙江农业科学, 2017, ( 5):18-21.
Yan F, Jiang Y Q, Wang C, Zeng L L, Lu H, Dong Y, Zhao L . Genetic diversity analysis of 20 waxy broomcorn millet. Heilongjiang Agric Sci, 2017, ( 5):18-21 (in Chinese with English abstract).
[17] 王瑞云, 季煦, 陆平, 刘敏轩, 许月, 王纶, 王海岗, 乔治军 . 利用荧光SSR分析中国糜子遗传多样性. 作物学报, 2017,43:530-548.
Wang R Y, Ji X, Lu P, Liu M X, Xu Y, Wang L, Wang H G, Qiao Z J . Analysis of genetic diversity of Chinese broomcorn millet by fluorescence SSR. Acta Agron Sin, 2017,43:530-548 (in Chinese with English abstract ).
[18] Baltensperger D D. Progress with proso, pearl and other millets. In: Janick J, Whipley A, eds, Trends in New Crops and New Uses. Alexandria: ASHS Press, 2002. pp 100-103.
[19] Obilana A B, Manyasa E. Millets. In: Pseudocereals and Less Common Cereals. Heidelberg: Springer, 2002. pp 177-217.
[20] Rajput S G, Plyler-Harveson T, Santra D K . Development and characterization of SSR markers in proso millet based on switchgrass genomics. Am J Plant Sci, 2014,5:175-186.
[21] Botstein D, White R L, Skolnick M, Davis R W . Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Human Genet, 1980,32:314-331.
[22] 束爱萍, 刘增兵, 余丽琴, 黎毛毛, 陈大洲 . 水稻SSR标记的遗传多样性研究进展. 植物资源遗传学报, 2013,14:778-783.
Shu A P, Liu Z B, Yu L Q, Li M M, Chen D Z . Advances in genetic diversity of rice based on SSR markers. J Plant Genet Resour, 2013,14:778-783 (in Chinese with English abstract).
[23] 王升星, 朱玉磊, 张海萍, 常成, 马传喜 . 小麦育种亲本材料SSR标记遗传多样性及其亲缘关系分析. 麦类作物学报, 2014,34:621-627.
Wang S X, Zhu Y L, Zhang H P, Chang C, Ma C X . Genetic diversity and genetic telationship of wheat breeding parent material based on SSR markers. J Triticeae Crops, 2014,34:621-627 (in Chinese with English abstract).
[24] Li L J, Yang K C, Pan G T, Rong T Z . Genetic diversity of maize populations developed by two kinds of recurrent selection methods investigated with SSR markers. Agric Sci China, 2008,7:1037-1045.
[25] Becher R . EST-derived microsatellites as a rich source of molecular markers for oats. Plant Breed, 2007,126:274-278.
[26] Ali A, Choi Y M, Hyun D Y, Lee S, Kim J H, Oh S, Lee M C . Development of EST-SSRs and assessment of genetic diversity in little millet ( Panicum sumatrense) germplasm. Korean J Plant Res, 2017,30:287-297.
[27] Rajput S G, Santra D K . Evaluation of genetic diversity of proso millet germplasm available in the United States using simple-sequence repeat markers. Crop Sci, 2016,56:2401-2409.
[28] Liu M X, Xu Y, He J H, Zhang S, Wang Y Y, Lu P . Genetic diversity and population structure of broomcorn millet ( Panicum miliaceum L.) cultivars and landraces in China based on microsatellite markers. Int J Mol Sci, 2016,17:370-396.
[29] 连帅, 陆平, 乔治军, 张琦, 张茜, 刘敏轩, 王瑞云 . 利用SSR分子标记研究国内外黍稷地方品种和野生资源的遗传多样性. 中国农业科学, 2016,49:3264-3275.
Lian S, Lu P, Qiao Z J, Zhang Q, Zhang Q, Liu M X, Wang R Y . Genetic diversity in broomcorn millet ( Panicum miliaceum L.) from China and abroad by using SSR markers. Sci Agric Sin, 2016,49:3264-3275 (in Chinese with English abstract).
[30] 董俊丽, 王海岗, 陈凌, 王君杰, 曹晓宁, 王纶, 乔治军 . 糜子骨干种质遗传多样性和遗传结构分析. 中国农业科学, 2015,48:3121-3131.
Dong J L, Wang H G, Chen L, Wang J J, Cao X N, Wang L, Qiao Z J . Analysis of genetic diversity and genetic structure of broomcorn millet of the Chinese. Sci Agric Sin, 2015,48:3121-3131 (in Chinese with English abstract).
[31] Hou S Y, Sun Z X, Li Y S, Wang Y, Ling H B, Xing G F, Han Y H, Li H Y . Transcriptomic analysis, genic SSR development, and genetic diversity of proso millet ( Panicum miliaceum; Poaceae). Appl Plant Sci, 2017,5:1-11.
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