利用EST-SSR评估糜子资源遗传差异

doi:10.3864/j.issn.0578-1752.2019.22.014

Abstract

Abstract:

【Objective】The objective of this study is to analyze the genetic diversity and relationship of common millet accessions (six different ecotopes at home and abroad) by microsatellite markers, to provide available data for classification, selection and utilization of elite germplasm resources. 【Method】 One hundred and forty-four SSRs (64 high motif nucleotide sequence repeat and 80 low ones) are used to identify polymorphisms in ninety-six common millet accessions (71 home accessions and 25 abroad accessions). Genetic diversity parameters were calculated using software PowerMarker 3.25 and PopGen 1.32. Genetic distance and Structure on accessions were classified with software MEGA 5.0 and Structure 2.2, respectively. PCA (principal component analysis) was conducted by software Ntsys 2.11. 【Result】 Using 144 EST-SSR markers, a total of 368 observed alleles (Na) were detected with 2-3 alleles (mean = 2.5556) per locus. The observed heterozygosity (Ho) ranged from 0.4070 (RYW15) to 0.9789 ( RYW85) with an average of 0.8288. The expected heterozygosity (He) ranged from 0.4369 ( RYW59) to 0.6693 ( RYW58) with an average of 0.5535. The Nei's gene diversity index ranged from 0.4344 (RYW59) to 0.6653 (RYW58) with a mean of 0.5505. The polymorphism information content (PIC) ranged from 0.1811 (RYW68) to 0.7508 (RYW58) with an average of 0.4279. The Shannon diversity index (I) range was 0.6474 to 1.0956 with an average of 0.8415. In the case of genetic diversity parameters, the PIC and I of common millet accessions from Northern spring-sowing region were the most abundant than that of others. On the contrary, the accessions from Northwest spring & summer-sowing region were the lowest. For the different geographical regions accessions, the range of genetic distance was 0.0111 to 0.1425 and the scope of genetic consistency was 0.8672 to 0.9889. The genetic distance of accessions between Loess Plateau spring & summer-sowing region and Northern spring-sowing region was the least and their genetic consistency was the highest. The genetic distance between Northwest spring & summer-sowing region and North of China summer-sowing region was the largest and their genetic consistency was the lowest. UPGMA analysis divided 96 accessions into three groups (GroupⅠ, Ⅱ and Ⅲ). Group I were mainly Northern spring-sowing region common millet, Group Ⅱ were mainly foreign accessions, and Group Ⅲ were mainly Loess Plateau spring & summer-sowing region and Northern spring-sowing region accessions. Structure cluster divided resources into four groups. The red group contained Loess Plateau spring & summer-sowing region and Northern spring-sowing region accessions, which represented the gene pool of Loess Plateau and North. The green group included Northern spring-sowing region accessions, which represented the North gene pool. The blue group were Loess Plateau spring & summer-sowing region accessions, which represented the gene pool of Loess Plateau. The yellow group represented foreign gene pool. In terms of diversity parameters, the PIC value of GroupⅡwas the highest at 0.4606 and the Group Ⅳ was the lowest at 0.3539. The PCA analysis classified all accessions into six clusters, which are related to their geographical region. 【Conclusion】144 SSRs can evaluate 96 common millet resources accurately. The genetic relationships are related to their geographical region. Genetic diversity of accessions from Northern spring-sowing region are more abundant.

Key words: common millet, SSR, cluster analysis, genetic structure, principal component analysis

SHI TianTian, HE JieLi, GAO ZhiJun, CHEN Ling, WANG HaiGang, QIAO ZhiJun, WANG RuiYun. Genetic Diversity of Common Millet Resources Assessed with EST-SSR Markers[J].Scientia Agricultura Sinica, 2019, 52(22): 4100-4109.

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References 40

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生态区 Ecotope	来源 Origin	数量 Accession number
北方春糜子区 NSP	中国青海 Qinghai, China	3	30
	中国甘肃 Gansu, China	9
	中国内蒙古 Inner Mongolia, China	12
	中国山西 Shanxi, China	6
西北春夏糜子区 NWSS	中国新疆 Xinjiang, China	3	3
黄土高原春夏糜子区 LPSS	中国山西 Shanxi, China	13	26
	中国陕西 Shaanxi, China	7
	中国宁夏 Ningxia, China	6
东北春糜子区 NES	中国黑龙江 Heilongjiang, China	1	4
	中国吉林 Jilin, China	2
	中国辽宁 Liaoning, China	1
华北夏糜子区 NSU	中国河北 Hebei, China	6	8
	中国河南 Henan, China	1
	中国山东 Shandong, China	1
国外 Abroad	印度India	22	25
国外 Abroad	波兰Poland	3	25
合计Total		96

来源地 Origin	资源数 Sample	观测等位变异 Na	有效等位变异 Ne	Shannon多样性指数 I	观测杂合度 Ho	期望杂合度 He	多态性信息含量 PIC
北方春糜子区NSP	30	2.5069±0.5017	2.269±0.3391	0.8393±0.1623	0.8221±0.1358	0.5596±0.0649	0.4259
西北春夏糜子区NWSS	3	2.2778±0.4796	2.0895±0.4045	0.7530±0.1977	0.7928±0.2824	0.6097±0.1324	0.2898
黄土高原春夏糜子LPSS	26	2.5069±0.5017	2.2345±0.3050	0.8288±0.1516	0.8362±0.1255	0.5557±0.0593	0.3878
东北春糜子区NES	4	2.3333±0.5017	2.1077±0.4075	0.7657±0.2028	0.7894±0.2481	0.5824±0.1223	0.3196
华北夏糜子区NSU	8	2.4375±0.4978	2.1687±0.3530	0.7998±0.1683	0.8038±0.1752	0.5643±0.0827	0.3637
国外Abroad	25	2.5000±0.5017	2.2125±0.3135	0.8191±0.1520	0.8478±0.1320	0.5508±0.0628	0.3719

生态区 Ecotope	北方春糜子区 NSP	西北春夏糜子区 NWSS	黄土高原春夏糜子区 LPSS	东北春糜子区 NES	华北夏糜子区 NSU	国外 Abroad
北方春糜子区NSP		0.9264	0.9889	0.9420	0.9703	0.9800
西北春夏糜子区NWSS	0.0764		0.9320	0.9018	0.8983	0.9169
黄土高原春夏糜子区LPSS	0.0112	0.0704		0.9438	0.9715	0.9822
东北春糜子区NES	0.0598	0.1033	0.0578		0.9362	0.9311
华北夏糜子区NSU	0.0301	0.1072	0.0290	0.0660		0.9671
国外Abroad	0.0202	0.0867	0.0180	0.0714	0.0335

群组 Cluster	资源数 Accessions	观测等位变异 Na	有效等位变异 Ne	Shannon多样性指数 I	观测杂合度 Ho	期望杂合度 He	多样性信息含量 PIC
Ⅰ	26	2.4931±0.5017	2.2437±0.3440	0.8281±0.1632	0.8251±0.1352	0.5554±0.0676	0.4052
Ⅱ	12	2.4931±0.5017	2.2379±0.3710	0.8285±0.1717	0.7677±0.1929	0.5663 ±0.0777	0.4606
Ⅲ	18	2.5347±0.5005	2.2271±0.3292	0.8292±0.1563	0.8181±0.1429	0.5576±0.0663	0.4165
Ⅳ	40	2.5069±0.5017	2.2264±0.2962	0.8256±0.1484	0.4495±0.1167	0.5434±0.0577	0.3539

Genetic Diversity of Common Millet Resources Assessed with EST-SSR Markers

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