植物学报 ›› 2019, Vol. 54 ›› Issue (6): 723-732.doi: 10.11983/CBB19037

• 研究报告 • 上一篇    下一篇

糜子EST-SSR分子标记的开发及种质资源遗传多样性分析

何杰丽1,石甜甜2,陈凌3,王海岗3,高志军4,杨美红1,王瑞云2,3,*(),乔治军3,*()   

  1. 1 山西农业大学文理学院, 太谷 030801
    2 山西农业大学农学院, 太谷 030801
    3 山西省农业科学院农作物品种资源研究所/农业部黄土高原作物基因资源与种质创制重点实验室/杂粮种质资源发掘与遗传改良山西省重点实验室, 太原 030031
    4 鄂尔多斯市农牧业科学研究院, 鄂尔多斯 017200
  • 收稿日期:2019-02-24 接受日期:2019-06-18 出版日期:2019-11-01 发布日期:2020-07-09
  • 通讯作者: 王瑞云,乔治军 E-mail:wry925@126.com;nkypzs@126.com
  • 基金资助:
    国家现代农业产业技术体系建设专项(No.CARS-06-13.5-A16);国家自然科学基金(No.31271791);山西省回国留学人员科研资助项目(No.2016-066);山西省重点研发计划(No.201803D221008-5)

The Genetic Diversity of Common Millet (Panicum miliaceum) Germplasm Resources Based on the EST-SSR Markers

He Jieli1,Shi Tiantian2,Chen Ling3,Wang Haigang3,Gao Zhijun4,Yang Meihong1,Wang Ruiyun2,3,*(),Qiao Zhijun3,*()   

  1. 1 College of Arts and Science, Shanxi Agricultural University, Taigu 030801, China
    2 College of Agronomy, Shanxi Agricultural University, Taigu 030801, China
    3 Shanxi Key Laboratory of Genetic Resources and Genetic Improvement of Minor Crops, Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau, Ministry of Agriculture, Institute of Crop Germplasm Resources, Shanxi Academy of Agricultural Sciences, Taiyuan 030031, China
    4 Erdos Institute of Agriculture and Animal Husbandry, Erdos 017200, China
  • Received:2019-02-24 Accepted:2019-06-18 Online:2019-11-01 Published:2020-07-09
  • Contact: Wang Ruiyun,Qiao Zhijun E-mail:wry925@126.com;nkypzs@126.com

摘要:

基于前期高通量测序结果设计EST-SSR引物, 用于评估国内外不同生态区144份糜子(Panicum miliaceum)种质资源的遗传差异。结果表明, 200对引物中80对呈多态性, 开发效率为40%; 引物分辨率(Rp)为0.67-4.67 (平均值为2.00), 扩增产物大小为50-500 bp。144份材料在80个位点共检测到206个等位变异, 每个位点为2-3个; 多样性指数(I)为0.659 3 (RYW108)-1.087 2 (RYW124), 平均为0.859 9; 多态性信息含量(PIC)为0.222 9 (RYW98)-0.717 2 (RYW124), 平均为0.457 3。基于UPGMA将144份资源划分为3个群组, 其中2个群组主要为北方春糜子区材料, 另一个群组主要为黄土高原春夏糜子区材料。基于Structure (K=4)将材料划分为4个类群, 即2个代表北方资源基因库以及代表黄土高原和国外资源基因库各1个。基于主成分分析将材料聚为7个类群, 划分结果与材料的地理来源一致。

关键词: 糜子, 遗传多样性, 主成分分析, SSR标记

Abstract:

The EST-SSR molecular markers of common millet (Panicum miliaceum) were developed by high-throughput sequencing. Using these markers, we assessed the genetic diversity in a panel of 144 common millet accessions collected from different ecotopic regions in China and abroad. It was shown that 80 pairs of these markers were polymorphic, with the efficiency of approximately 40%. The resolution power (Rp) was 0.67-4.67 (mean 2.00) and the amplified product sizes ranged from 50 to 500 bp. Among the examined 144 accessions, 206 allelic variations were identified in 80 loci, with 2-3 alleles at each locus. The Shannon’s diversity index (I) ranged from 0.659 3 (RYW108) to 1.087 2 (RYW124) with an average of 0.859 9. The range of polymorphism information content (PIC) was 0.222 9 (RYW98) -0.717 2 (RYW124) with an average of 0.457 3. Based on UPGMA, these 144 accessions were classified into 3 groups, two of which belonged to the the Northern China spring-sowing ecotopes and one group was mainly from the Loess Plateau spring-summer-sowing ecotopes. Based on Structure (K=4), all the accessions were divided into four groups, of which two groups represented the gene pool originated from the Northern China, whereas the other two groups from the Loess Plateau and abroad accessions. Based on principal component analysis (PCA), the accessions were clustered into seven groups, consistent with their geographic origins.

Key words: Panicum miliaceum, genetic diversity, PCA, EST-SSR markers

表1

国内各生态区和国外糜子资源的分布"

Ecotope/abroad Origin Number of accession Total
Northwest spring and summer-sowing ecotope (NWSS) Xinjiang 4 4
Northern spring-sowing ecotope (NSP) Qinghai 13 48
Gansu 11
Inner Mongolia 14
Shanxi 10
Loess Plateau spring and summer-sowing ecotope (LPSS) Shanxi 18 37
Shaanxi 8
Ningxia 11
Northeast spring-sowing ecotope (NES) Heilongjiang 5 9
Jilin 3
Liaoning 1
Northern summer-sowing ecotope (NSU) Hebei 9 13
Shandong 2
Anhui 1
Henan 1
Southern autumn and winter-sowing ecotope (SAW) Hainan 2 2
Abroad Former Soviet Union 2 31
Poland 2
India 27
Total 144

表2

糜子SSR引物筛选"

Number Unicode Accession name Origin
1 00000177 Hongmizi Ningan, Heilongjiang
2 00000750 Baimizi Shawan, Xinjiang
3 00006653 Jinshu Hainan
4 00007238 Dahongmizi Bameng, Inner Mongolia
5 00007478 Baigedami Huangzhong, Qinghai
6 No unicode Hongshuzi Anyang, Henan

图1

80个EST-SSR的Rp值分布频次"

表3

不同生态区糜子的遗传多样性参数"

Ecotope/ abroad Accessions Na Ne I Ho He PIC
NWSS 4 2.3375±0.5017 2.1517±0.4194 0.7644±0.2178 0.8042±0.2688 0.5944±0.1193 0.3551
NSP 48 2.5750±0.4975 2.3106±0.3211 0.8604±0.1576 0.8228±0.1308 0.5655±0.0604 0.4536
LPSS 37 2.5750±0.4975 2.2803±0.3110 0.8506±0.1534 0.8384±0.1166 0.5615±0.0595 0.4203
NES 9 2.5125±0.5030 2.2435±0.3929 0.8289±0.1823 0.7937±0.1732 0.5737±0.0909 0.4212
NSU 13 2.5625±0.4992 2.2815±0.3527 0.8496±0.1632 0.7946±0.1608 0.5712±0.0667 0.4304
SAW 2 2.2375±0.5092 2.0608±0.4387 0.7347±0.2316 0.7812±0.3265 0.6813±0.2006 0.2156
Domestic 113 2.5750 ±0.4975 2.3122±0.3086 0.8628±0.1554 0.8200±0.1188 0.5625±0.0584 0.4651
Abroad 31 2.5750±0.4975 2.2464±0.2909 0.8387±0.1449 0.8540±0.1193 0.5571±0.0561 0.3896

表4

各糜子群体间的Nei氏遗传距离与遗传一致度"

Population NWSS NSP LPSS NES NSU SAW Abroad
NWSS 0.9560 0.9614 0.9487 0.9380 0.8694 0.9477
NSP 0.0449 0.9884 0.9678 0.9794 0.9110 0.9864
LPSS 0.0394 0.0117 0.9716 0.9830 0.9116 0.9865
NES 0.0527 0.0327 0.0288 0.9675 0.8974 0.9587
NSU 0.0640 0.0208 0.0171 0.0331 0.9023 0.9762
SAW 0.1400 0.0932 0.0926 0.1083 0.1029 0.9102
Abroad 0.0537 0.0137 0.0136 0.0422 0.0240 0.0941

图2

基于UPGMA的糜子资源聚类分析 NWSS、NSP、LPSS、NES、NSU和SAW同表1。"

表5

基于UPGMA聚类分析糜子各类群的遗传多样性"

Group Accessions Na Ne I Ho He PIC
A 33 2.5750±0.4975 2.3226±0.3374 0.8654±0.1620 0.8055±0.1417 0.5696±0.0636 0.4716
B 15 2.5125±0.5030 2.2471±0.3383 0.8330±0.1627 0.8153±0.1530 0.5651±0.0686 0.3993
C 96 2.5750±0.4975 2.2922±0.2894 0.8571±0.1495 0.8363±0.1111 0.5599±0.0553 0.4380
C1 70 2.5750±0.4975 2.3136±0.3098 0.8635±0.1551 0.8291±0.1199 0.5643±0.0584 0.4531
C2 26 2.5625±0.4992 2.1912±0.2797 0.8163±0.1391 0.8555 ±0.1212 0.5477±0.0558 0.3420
C11 37 2.5750±0.4975 2.3014±0.3143 0.8589±0.1561 0.8332±0.1182 0.5664±0.0603 0.4382
C12 33 2.5750±0.4975 2.3028±0.3224 0.8583±0.1571 0.8255±0.1383 0.5654±0.0610 0.4348

图3

基于Structure对144份糜子资源群体建模"

图4

基于Structure的糜子资源遗传结构 颜色代表类群; 条形和横坐标数字分别表示资源及其编号。"

表6

遗传结构图中K=2和K=4各类群的遗传多样性分析"

Cluster Accessions Na Ne I Ho He PIC
K=2 Red 68 2.5750±0.4975 2.2446±0.2626 0.8407±0.1403 0.8602±0.1056 0.5528±0.0520 0.3773
Green 76 2.5750±0.4975 2.3396±0.3329 0.8711±0.1620 0.7975±0.1315 0.5679±0.0619 0.5031
K=4 Red 47 2.5750± 0.4975 2.3496±0.3944 0.8745±0.1768 0.7439±0.1668 0.5785±0.0743 0.5296
Green 31 2.5750± 0.4975 2.2844±0.3202 0.8516± 0.1549 0.8225±0.1399 0.5635±0.0607 0.4414
Blue 19 2.5750±0.4975 2.2973±0.3199 0.8575±0.1568 0.8190±0.1311 0.5628±0.0608 0.4450
Yellow 47 2.5750±0.4975 2.2238±0.2723 0.8312±0.1387 0.3634±0.2702 0.4984±0.1050 0.3543

图5

基于糜子资源SSR基因型的主成分分析"

[1] 董俊丽, 王海岗, 陈凌, 王君杰, 曹晓宁, 王纶, 乔治军 ( 2015). 糜子骨干种质遗传多样性和遗传结构分析. 中国农业科学 48, 3121-3131.
[2] 国家谷子糜子产业技术体系 ( 2018). 中国现代农业产业可持续发展战略研究·谷子糜子分册. 北京: 中国农业出版社. pp. 3-22.
[3] 郭琪, 郭大龙, 郭丽丽, 张琳, 侯小改 ( 2015). SSR分子标记在牡丹亲缘关系研究中的应用与研究进展. 植物学报 50, 652-664.
[4] 连帅, 陆平, 乔治军, 张琦, 张茜, 刘敏轩, 王瑞云 ( 2016). 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 49, 3264-3275.
[5] 刘笑瑜 ( 2017). 利用高基元SSR分析中国糜子资源的遗传多样性. 硕士论文. 太谷: 山西农业大学. pp. 22-41.
[6] 刘笑瑜, 王瑞云, 刘敏轩, 邱岩岩, 季煦, 连帅, 乔治军, 王纶, 王海岗 ( 2016). 利用SSR标记分析40份糜子资源的遗传多样性. 分子植物育种 14, 1624-1630.
[7] 王璐琳, 王瑞云, 何杰丽, 薛延桃, 陈凌, 王海岗, 乔治军 ( 2018). 糜子特异性SSR标记的开发. 山西农业科学 46, 1-4, 86.
[8] 王瑞云 (2017). 糜子遗传多样性及进化研究进展. 北京: 中国农业出版社. pp. 20-92.
[9] 王瑞云, 季煦, 陆平, 刘敏轩, 许月, 王纶, 王海岗, 乔治军 ( 2017a). 利用荧光SSR分析中国糜子遗传多样性. 作物学报 43, 530-548.
[10] 王瑞云, 刘笑瑜, 王海岗, 陆平, 刘敏轩, 陈凌, 乔治军 ( 2017b). 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 50, 3848-3859.
[11] 王舒婷, 何杰丽, 石甜甜, 陈凌, 王海岗, 王瑞云, 乔治军 ( 2019). 利用微卫星标记分析山西糜子的遗传多样性. 植物遗传资源学报 20, 69-78.
[12] 王银月, 刘敏轩, 陆平, 乔治军, 杨天育, 李海, 崔喜艳 ( 2014). 构建黍稷分子遗传图谱SSR引物的筛选. 作物杂志 ( 4), 32-38.
[13] 薛延桃, 陆平, 乔治军, 刘敏轩, 王瑞云 ( 2018). 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 51, 2846-2859.
[14] 朱宇佳, 焦凯丽, 罗秀俊, 冯尚国, 王慧中 ( 2018). 基于SSR分子标记的酸浆属植物亲缘关系研究. 植物学报 53, 305-312.
[15] Azevedo ALS, Costa PP, Machado JC, Machado MA, Pereira AV, da Silva Lédo FJ ( 2012). Cross species amplification of Pennisetum glaucum microsatellite markers in Pennisetum purpureum and genetic diversity of napier grass accessions. Crop Sci 52, 1776-1785.
[16] Bonman JM, Babiker EM, Cuesta-Marcos A, Esvelt-Klos K, Brown-Guedira G, Chao SM, See D, Chen JL, Akhunov E, Zhang JL, Bockelman HE, Gordon TC ( 2015). Genetic diversity among wheat accessions from the USDA national small grains collection. Crop Sci 55, 1243-1253.
[17] Changmei S, Dorothy J ( 2014). Millet—the frugal grain. Int J Sci Res Rev 3(4), 75-90.
[18] Cho Yl, Chung JW, Lee GA, Ma KH, Dixit A, Gwag JG, Park YJ ( 2010). Development and characterization of twenty-five new polymorphic microsatellite markers in proso millet ( Panicum miliaceum L.). Genes Genomics 32, 267-273.
[19] Courtois B, Frouin J, Greco R, Bruschi G, Droc G, Hamelin C, Ruiz M, Clément G, Evrard JC, Van Coppenole S, Katsantonis D, Oliveira M, Negrão S, Matos C, Cavigiolo S, Lupotto E, Piffanelli P, Ahmadi N ( 2012). Genetic diversity and population structure in a European collection of rice. Crop Sci 52, 1663-1675.
[20] Evanno G, Regnaut S, Goudet J ( 2005). Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14, 2611-2620.
[21] Falush D, Stephens M, Pritchard JK ( 2003). Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567-1587.
[22] Habiyaremye C, Matanguihan JB, Guedes JD, Ganjyal GM, Whiteman MR, Kidwell KK, Murphy KM ( 2017). Proso millet ( Panicum miliaceum L.) and its potential for cultivation in the pacific northwest, U.S: a review. Front Plant Sci 7, 1961.
[23] Hu XY, Wang JF, Lu P, Zhang HS ( 2009). Assessment of genetic diversity in broomcorn millet ( Panicum miliaceum L.) using SSR markers. J Genet Genomics 36, 491-500.
[24] Hunt HV, Campana MG, Lawes MC, Park YJ, Bower MA, Howe CJ, Jones MK ( 2011). Genetic diversity and phylogeography of broomcorn millet ( Panicum miliaceum L.) across Eurasia. Mol Ecol 20, 4756-4771.
[25] Liu KJ, Muse SV ( 2005). PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21, 2128-2129.
[26] Liu MX, Xu Y, He JH, Zhang S, Wang YY, Lu P ( 2016). Genetic diversity and population structure of broomcorn millet ( Panicum miliaceum L.) cultivars and landraces in China based on microsatellite markers. Int J Mol Sci 17, 370.
[27] Lu HY, Zhang JP, Liu KB, Wu NQ, Li YM, Zhou KS, Ye ML, Zhang TY, Zhang HJ, Yang XY, Shen LC, Xu DK, Li Q ( 2009). Earliest domestication of common millet ( Panicum miliaceum ) in East Asia extended to 10, 000 years ago. Proc Natl Acad Sci USA 106, 7367-7372.
[28] Murray MG, Thompson WF ( 1980). Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8, 4321-4325.
[29] Prevost A, Wilkinson MJ ( 1999). A new system of comparing PCR primers applied to ISSR fingerprinting of potato cultivars. Theor Appl Genet 98, 107-112.
[30] Rajput SG, Plyler-Harveson T, Santra DK ( 2014). Development and characterization of SSR markers in proso millet based on switchgrass genomics. Am J Plant Sci 5, 175-186.
[31] Rajput SG, Santra DK ( 2016). Evaluation of genetic diversity of proso millet germplasm available in the United States using simple-sequence repeat markers. Crop Sci 56, 2401-2409.
[32] Rohlf FJ (2002). NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.10. New York: Exter Publishing Ltd. Setauket.
[33] Saha D, Channabyre Gowda MV, Arya L, Verma M, Bansal KC ( 2016). Genetic and genomic resources of small millets. Crit Rev Plant Sci 35, 56-79.
[34] Satya P, Karan M, Jana S, Mitra S, Sharma A, Karmakar PG, Ray DP ( 2015). Start codon targeted (SCoT) polymorphism reveals genetic diversity in wild and domesticated populations of ramie ( Boehmeria nivea L. Gaudich.), a premium textile fiber producing species. Meta Gene 3, 62-70.
[35] Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S ( 2011). MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 665, 2731-2739.
[36] Tiwar G, Singh R, Singh N, Choudhury DR, Paliwal R, Kumar A, Gupta V ( 2016). Study of arbitrarily amplified (RAPD and ISSR) and gene targeted (SCoT and CBDP) markers for genetic diversity and population structure in kalmegh [Andrographis paniculata(Burm. f.) Nees]. Ind Crops Prod 86, 1-11.
[37] Van Inghelandt D, Melchinger AE, Lebreton C, Stich B ( 2010). Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers. Theor Appl Genet 120, 1289-1299.
[38] Wang RY, Hunt HV, Qiao ZJ, Wang L, Han YH ( 2016). Diversity and cultivation of broomcorn millet ( Panicum miliaceum L.) in China: a review. Econ Bot 70, 332-342.
[39] Wang RY, Wang HG, Liu XY, Ji X, Chen L, Lu P, Liu MX, Teng B, Qiao ZJ ( 2018). Waxy allelic diversity in common millet(Panicum miliaceum L.) in China. Crop J 6, 377-385.
[40] Yeh FC, Boyle TJB ( 1997). Population genetic analysis of codominant and dominant markers and quantitative traits. Belg J Bot 129, 157-163.
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