Scientia Agricultura Sinica ›› 2019, Vol. 52 ›› Issue (22): 4100-4109.doi: 10.3864/j.issn.0578-1752.2019.22.014

• GERMPLASM RESOURCES • Previous Articles     Next Articles

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

SHI TianTian1,HE JieLi2,GAO ZhiJun3,CHEN Ling4,WANG HaiGang4,QIAO ZhiJun4(),WANG RuiYun1,4()   

  1. 1 College of Agriculture, Shanxi Agricultural University, Taigu 030801, Shanxi
    2 College of Arts and Sciences, Shanxi Agricultural University, Taigu 030801, Shanxi
    3 Erdos Institute of Agriculture and Animal Husbandry, Erdos 017000, Inner Mongolia
    4 Institute of Crop Germplasms Resources of Shanxi Academy of Agricultural Sciences/Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau, Ministry of Agriculture, Taiyuan 030031
  • Received:2019-06-13 Accepted:2019-08-17 Online:2019-11-16 Published:2019-11-16
  • Contact: ZhiJun QIAO,RuiYun WANG E-mail:nkypzs@126.com;wry925@126.com

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

Table 1

Ecotope distribution of common millet accessions in this study"

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
波兰Poland 3
合计Total 96

Table 2

Parameters of genetic diversity of common millet populations"

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

Table 3

Genetic distance and genetic identity of common millet resources with different population"

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

Fig. 1

Cluster diagram of 96 accessions of common millet"

Fig. 2

Modelling genepools’ number in common millet accessions by Structure"

Fig. 3

Population genetic structure graph of common millet germplasm resources (K=4) Numbers in the horizontal axis represent serial number of accession"

Table 4

Genetic diversity parameters of different common millet structure cluster"

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
26 2.4931±0.5017 2.2437±0.3440 0.8281±0.1632 0.8251±0.1352 0.5554±0.0676 0.4052
12 2.4931±0.5017 2.2379±0.3710 0.8285±0.1717 0.7677±0.1929 0.5663 ±0.0777 0.4606
18 2.5347±0.5005 2.2271±0.3292 0.8292±0.1563 0.8181±0.1429 0.5576±0.0663 0.4165
40 2.5069±0.5017 2.2264±0.2962 0.8256±0.1484 0.4495±0.1167 0.5434±0.0577 0.3539

Fig. 4

Principle component analysis of 96 common millet accessions"

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