山西谷子核心资源群体结构及主要农艺性状关联分析

doi:10.3864/j.issn.0578-1752.2019.22.013

Abstract

Abstract:

【Objective】The objective of this study is to detect the SSR markers associated with agronomic trait and analyze genetic diversity and genetic structure of foxtail millet landrace in Shanxi province. The results will be helpful for hybridization combination of parent materials and molecular marker assisted breeding.【Method】96 SSR markers on 9 chromosomes were genome-wide screened for polymorphism in core collection of 595 accessions. PowerMarker 3.25 software was used to estimate the polymorphism information of population. Population structure was analyzed using STRUCTURE 2.3.4 software. Then the data were associated with 96 SSR markers by GLM (general linear model, Q) and MLM (mixed linear model, Q+K).【Result】Totally 828 alleles were found with 96 SSR markers and 8.6 alleles were revealed with each marker in average ranged from 2-26. The gene diversity was from 0.005 to 0.941, averagely 0.610. The polymorphism information content (PIC) value ranged from 0.005 to 0.938 with the mean of 0.577. Heterozygosity per locus on average was 0.016, ranging from 0 to 0.050. All the 595 accessions were divided into three subgroups by analysis of population genetic structure. There was linkage disequilibrium (LD) among linked loci and unlinked loci pairs, and 1 955 out of 4 560 loci pairs (42.9%) had significant LD (P < 0.01) with average D′ value of 0.23. A total of 12 locus found by GLM method significantly at the level of P<0.01 which explained 2.34%-13.94% of the phenotypic variance and the mean value was 6.33%. CAAS2050 (R ²=13.94%) and B153(R ²=11.36%) kept the max value. Meanwhile, 9 loci were found by MLM method significantly at the level of P<0.01 which explained 2.80%-9.22% of the phenotypic variance and the mean value was 5.16%. P89(R ²=9.22%) and P3*(R ²=8.28%) kept the max value. A total of 7 loci were detected in common by GLM and MLM. 【Conclusion】Genetic diversity and population structure of 595 accessions were analyzed through SSR markers. In the two association analysis models, 12 markers were associated with nine traits including stem node number, plant height, peduncle length, diameter of main stem, panicle length, panicle diameter, primary branch number per panicle, spikelet number per primary branch, protein content by GLM. Nine markers were associated with eight traits including stem node number, peduncle length, leaf width, diameter of main stem, panicle diameter, primary branch number per panicle, spikelet number per primary branch, 1000-grain weight by MLM.

Key words: foxtail millet, Shanxi, landrace, SSR, genetic diversity, linkage disequilibrium, association analysis

WANG HaiGang,WEN QiFen,MU ZhiXin,QIAO ZhiJun. Population Structure and Association Analysis of Main Agronomic Traits of Shanxi Core Collection in Foxtail Millet[J].Scientia Agricultura Sinica, 2019, 52(22): 4088-4099.

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Figures/Tables 7

Table 1

Genetic diversity at 96 SSR markers"

标记 Marker	染色体 Chromosome	基因型数 Genotype No.	等位基因数 Allele No.	基因多样性指数 Gene diversity	多态性信息含量 PIC	杂合度 Heterozygosity
In1-1	Chr.1	3	2	0.4955	0.3727	0.0183
In1-3	Chr.1	5	4	0.1810	0.1663	0.0200
In1-7	Chr.1	7	4	0.3955	0.3521	0.0267
In1-9	Chr.1	3	2	0.1113	0.1051	0.0083
CAAS1054	Chr.1	34	19	0.9051	0.8976	0.0283
P3*	Chr.1	27	15	0.8264	0.8072	0.0233
P88	Chr.1	27	14	0.8852	0.8756	0.0233
B153	Chr.1	13	10	0.7789	0.7477	0.0050
P58	Chr.1	14	8	0.7565	0.7184	0.0333
B218	Chr.1	18	9	0.8303	0.8084	0.0250
CAAS2006	Chr.2	11	5	0.7162	0.6675	0.0167
CAAS2010	Chr.2	13	6	0.6777	0.6269	0.0250
In2138	Chr.2	3	2	0.4867	0.3682	0.0267
In2184	Chr.2	4	4	0.1995	0.1815	0.0000
b242	Chr.2	10	9	0.7997	0.7730	0.0017
CAAS2050	Chr.2	11	6	0.6971	0.6435	0.0300
CAAS2030	Chr.2	6	4	0.5026	0.4165	0.0283
In2-11	Chr.2	3	2	0.0535	0.0521	0.0017
B169	Chr.2	23	18	0.9235	0.9182	0.0083
B249	Chr.2	24	22	0.9286	0.9241	0.0033
MPGD13	Chr.2	8	5	0.5607	0.4671	0.0067
b101	Chr.3	22	11	0.8607	0.8449	0.0233
B163	Chr.3	10	7	0.7193	0.6760	0.0067
B186	Chr.3	37	17	0.9182	0.9123	0.0383
P61*	Chr.3	6	4	0.6897	0.6299	0.0100
B225	Chr.3	26	16	0.8963	0.8869	0.0233
P98	Chr.3	9	6	0.5330	0.4808	0.0267
MPGD32	Chr.3	9	6	0.4217	0.3865	0.0150
MPGD44	Chr.3	8	6	0.4247	0.3914	0.0100
B224	Chr.3	47	25	0.9411	0.9379	0.0383
P78	Chr.3	14	9	0.7941	0.7657	0.0150
In4-3	Chr.4	5	4	0.4948	0.3796	0.0317
CAAS4019	Chr.4	7	5	0.4388	0.4096	0.0083
CAAS4033	Chr.4	14	8	0.8181	0.7936	0.0200
IN4-6	Chr.4	3	2	0.2608	0.2268	0.0117
IN4-7	Chr.4	6	4	0.2004	0.1909	0.0117
B109	Chr.4	38	26	0.8654	0.8533	0.0267
P2	Chr.4	28	18	0.9045	0.8970	0.0183
B247*	Chr.4	22	14	0.8866	0.8762	0.0167
P100**	Chr.4	8	7	0.5368	0.4883	0.0017
P89	Chr.4	24	17	0.8428	0.8246	0.0267
CAAS5048	Chr5	9	6	0.7318	0.6894	0.0050
In5-7	Chr.5	2	2	0.0099	0.0099	0.0000
In5-8	Chr.5	3	2	0.4382	0.3422	0.0283
CAAS5032	Chr.5	26	12	0.8911	0.8810	0.0300
b111	Chr.5	17	12	0.8842	0.8729	0.0100
P17X*	Chr.5	12	6	0.5827	0.5436	0.0200
B223	Chr.5	32	19	0.9141	0.9078	0.0317
B237	Chr.5	19	8	0.8512	0.8329	0.0267
B117	Chr.5	11	7	0.5355	0.4950	0.0233
MPGA51	Chr.5	5	4	0.2576	0.2367	0.0017
MPGD4	Chr.5	4	3	0.3705	0.3400	0.0117
In6-2	Chr.6	3	2	0.2733	0.2360	0.0133
CAAS6023	Chr.6	7	5	0.2109	0.1972	0.0067
In6-9	Chr.6	3	2	0.4986	0.3743	0.0400
In6-11	Chr.6	4	3	0.3183	0.2697	0.0017
CAAS6018	Chr.6	10	8	0.7108	0.6608	0.0117
CAAS6007	Chr.6	17	10	0.7759	0.7517	0.0183
B159	Chr.6	23	11	0.8445	0.8263	0.0233
P32	Chr.6	8	6	0.3231	0.2957	0.0050
P12X	Chr.6	18	12	0.8195	0.8004	0.0183
B250	Chr.6	35	20	0.8997	0.8917	0.0267
MPGA50	Chr.6	8	5	0.6601	0.6232	0.0150
In7-1	Chr.7	3	2	0.0050	0.0050	0.0017
CAAS7021	Chr.7	7	5	0.4033	0.3782	0.0050
SIMS14450	Chr.7	6	5	0.2846	0.2612	0.0117
CAAS7036	Chr.7	3	2	0.1569	0.1446	0.0150
In7-13	Chr.7	3	2	0.4911	0.3705	0.0500
P45	Chr.7	5	5	0.5788	0.4933	0.0000
B142	Chr.7	16	12	0.8185	0.7957	0.0100
B123	Chr.7	14	11	0.6491	0.6170	0.0083
P29	Chr.7	21	13	0.8830	0.8713	0.0150
B200	Chr.7	9	5	0.5637	0.5071	0.0083
B180	Chr.7	10	7	0.7220	0.6758	0.0067
SI 227	Chr.7	12	10	0.8304	0.8084	0.0050
In8-1	Chr.8	7	4	0.6511	0.5845	0.0183
P6	Chr.8	5	5	0.3672	0.3143	0.0000
CAAS8015	Chr.8	10	7	0.7853	0.7523	0.0100
CAAS8011	Chr.8	19	8	0.8140	0.7888	0.0250
B185	Chr.8	32	22	0.9234	0.9181	0.0183
B258	Chr.8	39	21	0.9211	0.9157	0.0300
J2（GTDZ7-1）	Chr.8	2	2	0.0099	0.0099	0.0000
P14	Chr.8	25	W	0.7974	0.7791	0.0150
B128	Chr.8	25	22	0.9309	0.9267	0.0050
b246	Chr.9	23	12	0.8797	0.8676	0.0333
CAAS9036	Chr.9	24	15	0.8811	0.8703	0.0183
b166	Chr.9	20	9	0.8320	0.8107	0.0267
CAAS9081	Chr.9	17	8	0.8058	0.7790	0.0250
CAAS9082	Chr.9	12	8	0.7926	0.7633	0.0083
CAAS9058	Chr.9	7	6	0.1620	0.1555	0.0100
P20*	Chr.9	15	11	0.7462	0.7074	0.0100
P41	Chr.9	11	9	0.7927	0.7623	0.0033
SIMS 298	Chr.9	4	3	0.4286	0.3423	0.0150
B145	Chr.9	9	6	0.5104	0.4788	0.0133
B212	Chr.9	3	3	0.0394	0.0390	0.0000
SI 110	Chr.9	5	5	0.1118	0.1093	0.0000
平均值 Mean		13	8.6	0.6097	0.5773	0.0159

Table 1

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Table 2

Table3

References 36

[1]	贾冠清, 刁现民 . 谷子(Setaria italica (L.) P. Beauv.)作为功能基因组研究模式植物的发展现状及趋势. 生命科学, 2017,29(3):292-301.
	JIA G Q, DIAO X M . Current status and perspectives of researches on foxtail millet (Setaria italica(L.) P. Beauv.): A potential model of plant functional genomics studies. Chinese Bulletin of Life Sciences, 2017,29(3):292-301. (in Chinese)
[2]	王海岗, 秦慧彬, 田翔, 吕建珍, 陈凌, 王君杰, 曹晓宁, 刘思辰, 王纶, 温淇汾, 穆志新, 乔治军 . 山西谷子地方品种表型多样性分析. 中国农学通报, 2018,34(32):19-24.
	WANG H G, QIN H B, TIAN X, LÜ J Z, CHEN L, WANG J J, CAO X N, LIU S C, WANG L, WEN Q F, MU Z X, QIAO Z J . Phenotypic diversity of local foxtail millet varieties in Shanxi. Chinese Agricultural Science Bulletin, 2018,34(32):19-24. (in Chinese)
[3]	王荣焕, 王天宇, 黎裕 . 关联分析在作物种质资源分子评价中的应用. 植物遗传资源学报, 2007,8(3):366-372.
	WANG R H, WANG T Y, LI Y . Application of association analysis in molecular evaluation of crop germplasm resources. Journal of Plant Genetic Resources, 2007,8(3):366-372. (in Chinese)
[4]	杨小红, 严建兵, 郑艳萍, 余建明, 李建生 . 植物数量性状关联分析研究进展. 作物学报, 2007,33(4):523-530.
	YANG X H, YAN J B, ZHENG Y P, YU J M, LI J S . Reviews of association analysis for quantitative traits in plants. Acta Agronomica Sinica, 2007,33(4):523-530. (in Chinese)
[5]	冯建英, 温阳俊, 张瑾, 章元明 . 植物关联分析方法的研究进展. 作物学报, 2016,42(7):945-956.
	FENG J Y, WEN Y J, ZHANG J, ZHANG Y M . Advances on methodologies for genome-wide association studies in plants. Acta Agronomica Sinica, 2016,42(7):945-956. (in Chinese)
[6]	赵宏亮, 陈凯, 张强, 徐正进, 徐建龙, 黎志康 . 基于连锁不平衡水稻源库相关性状的关联分析. 核农学报, 2015,29(4) : 674-684.
	ZHAO H L, CHEN K, ZHANG Q, XU Z J, XU J L, LI Z K . Association analysis on source sink-related traits in rice based on linkage disequilibrium. Journal of Nuclear Agricultural Sciences, 2015,29(4):674-684. (in Chinese)
[7]	孙晓棠, 卢冬冬, 欧阳林娟, 胡丽芳, 边建民, 彭小松, 陈小荣, 傅军如, 贺晓鹏, 贺浩华, 朱昌兰 . 水稻纹枯病抗性关联分析及抗性等位变异发掘. 作物学报, 2014,40(5):779-787.
	SUN X T, LU D D, OUYANG L J, HU L F, BIAN J M, PENG X S, CHEN X R, FU J R, HE X P, HE H H, ZHU C L . Association mapping and resistant alleles analysis for sheath blight resistance in rice. Acta Agronomica Sinica, 2014,40(5):779-787. (in Chinese)
[8]	魏添梅, 昌小平, 闵东红, 景蕊莲 . 小麦抗旱品种的遗传多样性分析及株高优异等位变异挖掘. 作物学报, 2010,36(6):895-904.
	WEI T M, CHANG X P, MIN D H, JING R L . Analysis of genetic diversity and tapping elite alleles for plant height in drought-tolerant wheat varieties. Acta Agronomica Sinica, 2010,36(6):895-904. (in Chinese).
[9]	张冬玲, 张洪娜, 郝晨阳, 王兰芬, 李甜, 张学勇 . 花后冠层温度对小麦产量的影响及几个关联SSR位点的效应分析. 作物学报, 2015,41(4):548-556.
	ZHANG D L, ZHANG H N, HAO C Y, WANG L F, LI T, ZHANG X Y . Influence of canopy temperature (ct) during grain-filling period on yield and effects of several ct-associated SSR loci. Acta Agronomica Sinica, 2015,41(4):548-556. (in Chinese)
[10]	朱玉磊, 王升星, 赵良侠, 张德新, 胡建帮, 曹雪连, 杨亚杰, 常成, 马传喜, 张海萍 . 以关联分析发掘小麦整穗发芽抗性基因分子标记. 作物学报, 2014,40(10):1725-1732.
	ZHU Y L, WANG S X, ZHAO L X, ZHANG D X, HU J B, CAO X L, YANG Y J, CHANG C, MA C X, ZHANG H P . Exploring molecular markers of preharvest sprouting resistance gene using wheat intact spikes by association analysis. Acta Agronomica Sinica, 2014,40(10):1725-1732. (in Chinese)
[11]	杨胜先, 牛远, 李梦, 魏世平, 刘晓芬, 吕海燕, 章元明 . 栽培大豆农艺性状的关联分析及优异等位变异挖掘. 中国农业科学, 2014,47(20):3941-3952.
	YANG S X, NIU Y, LI M, WEI S P, LIU X F, LÜ H Y, ZHANG Y M . Association mapping of agronomic traits in soybean ( Glycine max L. Merr.) and mining of novel alleles. Scientia Agricultura Sinica, 2014,47(20):3941-3952. (in Chinese)
[12]	文自翔, 赵团结, 郑永战, 刘顺湖, 王春娥, 王芳, 盖钧镒 . 中国栽培和野生大豆农艺品质性状与SSR标记的关联分析: I.群体结构及关联标记. 作物学报, 2008,34(7):1169-1178.
	WEN Z X, ZHAO T J, ZHENG Y Z, LIU S H, WANG C E, WANG F, GAI J Y . Association analysis of agronomic and quality traits with SSR markers in glycine max and glycine soja in China: I. Population structure and associated markers. Acta Agronomica Sinica, 2008,34(7):1169-1178. (in Chinese)
[13]	文自翔, 赵团结, 郑永战, 刘顺湖, 王春娥, 王芳, 盖钧镒 . 中国栽培和野生大豆农艺及品质性状与SSR标记的关联分析: Ⅱ.优异等位变异的发掘. 作物学报, 2008,34(8):1339-1349.
	WEN Z X, ZHAO T J, ZHENG Y Z, LIU S H, WANG C E, WANG F, GAI J Y . Association analysis of agronomic and quality traits with SSR markers in glycine max and glycine soja in china: ii. exploration of elite alleles. Acta Agronomica Sinica, 2008,34(8):1339-1349. (in Chinese)
[14]	范虎, 文自翔, 王春娥, 王芳, 邢光南, 赵团结, 盖钧镒 . 中国野生大豆群体农艺加工性状与SSR关联分析和特异材料的遗传构成. 作物学报, 2013,39(5):775-788.
	FAN H, WEN Z X, WANG C E, WANG F, XING G N, ZHAO T J, GAI J Y . Association analysis between agronomic-processing traits and SSR markers and genetic dissection of specific accessions in Chinese wild soybean population. Acta Agronomica Sinica, 2013,39(5):775-788. (in Chinese)
[15]	孙慧敏, 张军, 赵团结, 盖钧镒 . 亚洲地区中、外大豆品种幼苗期耐淹性与SSR标记的关联分析. 作物学报, 2010,36(10):1615-1623.
	SUN H M, ZHANG J, ZHAO T J, GAI J Y . Association analysis between submergence tolerance and SSR markers in domestic and foreign soybean cultivars in Asia. Acta Agronomica Sinica, 2010,36(10):1615-1623. (in Chinese)
[16]	聂新辉, 尤春源, 鲍健, 李晓方, 惠慧, 刘洪亮, 秦江鸿, 林忠旭 . 基于关联分析的新陆早棉花品种农艺和纤维品质性状优异等位基因挖掘. 中国农业科学, 2015,48(15):2891-2910.
	NIE X H, YOU C Y, BAO J, LI X F, HUI H, LIU H L, QIN J H, LIN Z X . Exploration of elite alleles of agronomic and fiber quality traits in Xinluzao cotton varieties by association analysis. Scientia Agricultura Sinica, 2015,48(15):2891-2910. (in Chinese)
[17]	刘其宝, 李黎贝, 张驰, 宿俊吉, 魏恒玲, 王寒涛, 喻树迅 . 陆地棉叶片叶绿素含量与SSR标记的关联分析及优异等位变异的挖掘. 中国农业科学, 2017,50(18):3439-3449.
	LIU Q B, LI L B, ZHANG C, SU J J, WEI H L, WANG H T, YU S X . Association analysis of leaf chlorophyll content with SSR markers and exploration of superior alleles in upland cotton. Scientia Agricultura Sinica, 2017,50(18):3439-3449. (in Chinese)
[18]	王娟, 董承光, 刘丽, 孔宪辉, 王旭文, 余渝 . 棉花适宜机采相关性状的SSR标记关联分析及优异等位基因挖掘. 作物学报, 2010,36(10):1615-1623.
	WANG J, DONG C G, LIU L, KONG X H, WANG X W, YU Y . Association analysis and exploration of elite alleles of mechanical harvest-related traits with SSR markers in upland cotton cultivars ( Gossypium hirsutum L.). Acta Agronomica Sinica, 2010,36(10):1615-1623. (in Chinese)
[19]	赖勇, 王鹏喜, 范贵强, 司二静, 王晋, 杨轲, 孟亚雄, 李葆春, 马小乐, 尚勋武, 王化俊 . 大麦SSR标记遗传多样性及其与农艺性状关联分析. 中国农业科学, 2013,46(2):233-242.
	LAI Y, WANG P X, FAN G Q, SI E J, WANG J, YANG K, MENG Y X, LI B C, MA X L, SHANG X W, WANG H J . Genetic diversity and association analysis using SSR markers in barley. Scientia Agricultura Sinica, 2013,46(2):233-242. (in Chinese)
[20]	姜晓东, 郭刚刚, 张京 . 中国大麦地方品种的遗传多样性及α-淀粉酶活性的全基因组关联分析. 中国农业科学, 2013,46(4):668-677.
	JIANG X D, GUO G G, ZHANG J . Analysis on the genetic diversity in Chinese barley landrace and genomic wide association of α-amylase activity genes. Scientia Agricultura Sinica, 2013,46(4):668-677. (in Chinese)
[21]	赖勇, 王鹏喜, 范贵强, 司二静, 王晋, 杨轲, 孟亚雄, 李葆春, 马小乐, 尚勋武, 王化俊 . 大麦遗传多样性及连锁不平衡分析. 作物学报, 2013,39(12):2154-2161.
	LAI Y, WANG P X, FAN G Q, SI E J, WANG J, YANG K, MENG Y X, LI B C, MA X L, SHANG X W, WANG H J . Genetic diversity and linkage disequilibrium analysis in barley. Acta Agronomica Sinica, 2013,39(12):2154-2161. (in Chinese)
[22]	WANG C F, JIA G Q, ZHI H, NIU Z G, CHAI Y, LI W, WANG Y F, LI H Q, LU P, ZHAO B H, DIAO X M . Genetic diversity and population structure of Chinese foxtail millet [Setaria italica (L.) Beauv.] landraces. Genes Genomes Genetics, 2012,7(2):769-777.
[23]	JIA G Q, LIU X T, SCHNABLE J C, NIU Z G, WANG C F, LI Y H, WANG S J, WANG S Y, LIU J R, GUO E H, ZHI H, DIAO X M . Microsatellite variations of elite Setaria varieties released during last six decades in China. PLoS ONE, 10(5):e0125688.
[24]	VETRIVENTHAN M, UPADHYAYA HARI D, ANANDAKUMAR C R, SENTHILVEL S, VARSHNEY R K, PARZIES H K . Population structure and linkage disequilibrium of ICRISAT foxtail millet (Setaria italica (L.) P. Beauv.) core collection. Euphytica, 2014,196:423-435
[25]	GUPTA S, KUMARI K, MUTHAMILARASAN M, PARIDA W K, PRASAD M . Population structure and association mapping of yield contributing agronomic traits in foxtail millet. Plant Cell Report, 2014,33:881-893
[26]	王春芳 . 利用微卫星标记分析中国谷子地方品种的群体结构与遗传多样性[D]. 石家庄: 河北师范大学, 2011.
	WANG C F . Population structure and genetic diversity of foxtail millet landraces in China assessed by microsatellites[D]. Shijiazhuang: Hebei Normal University, 2011. (in Chinese)
[27]	ZHANG S, TANG C J, ZHAO Q, LI J, YANG L F, QIE L F, FAN X K, LI L, ZHANG N, ZHAO M C, LIU X T, CHAI Y, ZHANG X, WANG H L, LI Y T, LI W, ZHI H, JIA G Q, DIAO X M . Development of highly polymorphic simple sequence repeat markers using genome- wide microsatellite variant analysis in foxtail millet [Setaria italica (L.) P. Beauv.]. BMC Genomics, 2014,15:78.
[28]	白鹏, 程须珍, 王丽侠, 王素华, 陈红霖 . 小豆遗传差异、群体结构和连锁不平衡水平的SSR分析. 作物学报, 2014,40(5):788-797.
	BAI P, CHENG X Z, WANG L X, WANG S H, CHEN H L . Genetic diversity, population structure and linkage disequilibrium in adzuki bean by using SSR markers. Acta Agronomica Sinica, 2014,40(5):788-797. (in Chinese)
[29]	熊海铮 . 豇豆遗传多样性及若干农艺性状关联分析[D]. 杭州: 浙江大学, 2016.
	XIONG H Z . Genetic diversity and association analysis of agronomic traits in Cowpea[D]. Hangzhou: Zhejiang University, 2016. (in Chinese)
[30]	王海岗, 温琪汾, 乔治军, 穆志新 . 山西谷子地方品种初选核心种质构建. 农学学报, 2019,9(4):26-31.
	WANG H G, WEN Q F, QIAO Z J, MU Z X . Construction of candidate core collection local varieties of foxtail millet in Shanxi. Journal of Agriculture, 2019,9(4):26-31. (in Chinese)
[31]	温琪汾, 王纶, 赵卫红, 畅建武 . 山西省谷子种质资源的繁种入库. 山西农业科学, 2002 , 30(4):32-34.
	WEN Q F, WANG L, ZHAO W H, CHANG J W . Reproduction and storage of foxtail millet germplasm in Shanxi. Journal of Shanxi Agricultural Sciences, 2002,30(4):32-34. (in Chinese)
[32]	温琪汾, 王纶, 王星玉 . 山西省谷子种质资源及抗旱种质的筛选利用. 山西农业科学, 2005,33(4):32-33.
	WEN Q F, WANG L, WANG X Y . The foxtail millet germplasm resources and screening and utilization of drought resistance germplasm in Shanxi. Agricultural Sciences, 2005,33(4):32-33. (in Chinese)
[33]	EVANNO G, REGNAUTS S, GOUDET J . Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Molecular Ecology, 2005,14:2611-2620.
[34]	JIA X P, ZHANG Z B, LIU Y H, ZHANG C W, SHI Y S, SONG Y C, WANG T Y, LI Y . Development and genetic mapping of SSR markers in foxtail millet [Setaria italica (L.) P. Beauv.]. Theoretical and Applied Genetics, 2009,118(4):821-829.
[35]	古兆明, 古世禄 . 山西谷子起源与发展研究. 北京: 中国农业科学技术出版社, 2007: 166-168.
	GU Z M, GU S L. Origin and Development of Shanxi Foxtail Millet. Beijing: Agricultural Science and Technology Press, 2007: 166-168. (in Chinese)
[36]	任继海, 温琪汾, 王星玉, 王纶 . 山西省谷子品种类型及其分布. 华北农学报, 1999,14(3):25-30.
	REN J H, WEN Q F, WANG X Y, WANG L . Varieties of foxtail millet and their distribution in Shanxi province. Acta Agriculturae Boreali-Sinica, 1999,14(3):25-30. (in Chinese)

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D' 值范围 D' value ranges	LD成对点数 Number of LD pairs
0—0.2	946
0.2—0.4	870
0.4—0.6	103
0.6—0.8	29
0.8—1	7

性状 Trait	位点 SSR loci	染色体 Chromosome	GLM				MLM
			2017		2018		2017		2018
			R²	P	R²	P	R²	P	R²	P
节数SN	P58	Chr.1	0.0572	6.42E-08	0.0597	1.73E-07
	B142	Chr.7							0.052	6.39E-05
株高PH	P58	Chr.1	0.0541	1.06E-07	0.0547	2.19E-07
颈长PL	CAAS6023	Chr.6	0.0558	3E-09	0.0517	1.77E-08			0.0298	8.8E-05
叶宽LW	In6-2	Chr.6							0.0444	4.34E-05
茎粗DMS	P3*	Chr.1	0.0774	1.04E-05	0.0977	4.95E-08			0.0828	3.73E-06
	In6-2	Chr.6	0.0458	2.91E-05	0.0498	8.95E-06			0.0445	5.1E-05
	P58	Chr.1					0.0522	3.73E-05
	P89	Chr.4					0.0922	1.3E-06
	B142	Chr.7							0.0628	6.19E-05
穗长PL	B153	Chr.1	0.0605	7.03E-07	0.0517	7.02E-06
	CAAS7036	Chr.7	0.0234	3.08E-05	0.0306	1.16E-06
穗粗PD	B142	Chr.7	0.068	1.37E-05	0.0646	5.05E-05
	B117	Chr.5					0.0457	6.4E-05
码数PBNP	CAAS2050	Chr.2	0.0514	3.48E-06	0.1394	3.59E-18			0.053	1.61E-06
	In2-11	Chr.2							0.028	1.82E-05
	In6-2	Chr.6	0.0258	5.04E-05	0.0277	3.55E-05
	B142	Chr.7	0.0583	9.36E-05	0.0772	1.14E-06
码粒数SNPB	B117	Chr.5	0.0559	4.73E-06	0.0439	9.4E-05	0.046	6.78E-05
千粒重GW	CAAS6023	Chr.6					0.0375	5.05E-05
蛋白含量PC	B153	Chr.1	0.1136	1.12E-12	0.1081	4.84E-11
	In1-7	Chr.1	0.0512	3.08E-07	0.0425	1.09E-05
	P14	Chr.8	0.0901	3.77E-07	0.1108	7.03E-09

Population Structure and Association Analysis of Main Agronomic Traits of Shanxi Core Collection in Foxtail Millet

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