Molecular Biology Reports

, Volume 37, Issue 7, pp 3413–3420

Genetic diversity of Iranian Aegilops tauschii Coss. using microsatellite molecular markers and morphological traits

Authors

    • Molecular Marker LabSeed and Plant Certification and Registration Institute
  • Mohammad Javad Zamani
    • Seed and Plant Improvement Institute
  • Mahmood Solouki
    • Department of Agronomy & Plant BreedingUniversity of Zabol
  • Mehdi Zahravi
    • National Plant Gene Bank of Iran
  • Abbas Ali Imamjomeh
    • Department of Agronomy & Plant BreedingUniversity of Zabol
  • Mohammad Jafaraghaei
    • National Plant Gene Bank of Iran
  • Mohammad Reza Bihamta
    • Department of Agronomy and Plant breeding, Agriculture CollegeTehran University
Article

DOI: 10.1007/s11033-009-9931-6

Cite this article as:
Tahernezhad, Z., Zamani, M.J., Solouki, M. et al. Mol Biol Rep (2010) 37: 3413. doi:10.1007/s11033-009-9931-6
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Abstract

Aegilops tauschii Coss. is a diploid (2n = 2x = 14,DD) goat grass species which has contributed the D genome in common wheat. Genetic variations in 28 accessions of Aegilops tauschii belonged to different provinces of Iran, were evaluated using 16 morphological traits and 19 SSR markers. In number of spikelet per spike and plant height, there was a high variation in ssp. tauschii and ssp. strangulata respectively and for days to mature a low variation in both subspecies was found. Discriminant function analysis showed that 67.9% of original grouped cases correctly classified. Factor analysis indicated that three factor explain 66.49% of total variation. The three clusters revealed by the cluster analysis were not consistent with their geographical distributions. We determined 208 alleles using 19 microsatellites. Average of alleles for every locus was 10.94. The total average of PIC was 0.267. 2261 bands produced for total of genotypes and Chinese Spring had the highest bands (95 alleles). The range of similarity coefficients was between 0.23 and 0.73. Genotypes were clustered using UPGMA method. The accessions did not match according to morphological cluster and geographical regions. 51.2% of total variations were related to 9 principle components.

Keywords

Aegilops tauschiiGenetic diversityMorphological traitMicrosatellite

Introduction

Genetic drift of germplasm in cultivated wheat is a good motivation for studying about genetic diversity in its wild relatives [1]. Goat grass Aegilopstauschii (Ae. squarrosa) is a diploid (2n = 2x = 14, DD) and self- pollinated plant that is the donor of D genome to bread wheat (Triticum aestivum). There are many causes show T. aestivum derived through hybridization of T. turgidum (AABB) and Ae. tauschii (DD) [2]. Center of the diversity is south of Caspian Sea that is limited to Turkey (West) and to Afghanistan (East). Distribution of Ae. tauschii in Iran is the north, the north-west, the north -east and the center of this country [3]. There was that the origin of bread wheat D genome is from the south -east or the south-west of the Caspian Sea in Iran [4]. Kihara and Tanaka [5] divided Ae. tauschii in two subspecies: strangulata and squarrosa. They realized three varieties in squarrosa: meyeri, typical and anathera. They also specified that there are many intermediate varieties between typical and anathera, one of them is meyeri [5]. Almost all of the researchers according to Eig [6] divided Ae. tauschii into two subspecies: the first, tauschii that has cylindrical spike and the second, strangulata that has cubic spike. It recognized that strangulata is nearer to T. aestivum in comparison of tauschii [7]. Genetic diversity in D genome of bread wheat is less than Ae. tauschii [8]. Accessions of Ae. tauschii developed for many agronomical traits, such as insect and disease resistance [9], endosperm proteins quality [10] and physiological characters [11, 12], Also Ae. tauschii is the donor of many agricultural traits like: bread making quality [13], cold resistance [12] and salt tolerance [14], therefore this species has a good potential for wheat improvement [8]. Ae. tauschii germplasm studied by using morphological traits [8, 15, 16], physiological traits [17], seed storage protein [18], Isosyme [19, 20], restriction fragment length polymorphism [2, 21], microsatellite analysis [7, 22] and SSR and AFLP methods [23]. Microsatellites (SSR) are 2–6 nucleotide sequence repeats that have high level of polymorphism in different animals and plant species. Microsatellite analysis based on polymerase chain reaction (PCR) is easier than RFLP analysis, also it has codominant and Mendelian inheritance. Microsatellites have good potential for automation, in addition this method needs few DNA for PCR. SSR used for recognition of genetic diversity successfully [24], producing wheat genome map [25] and estimate genetic relationship between Ae. tauschii accessions [7, 22]. In this study, 28 accessions of Iranian Ae. tauschii were used for studying about genetic diversity by using morphological traits, SSR molecular marker and comparison of these markers and also estimating the distance between these accessions to Triticum aestivum in order to help breeding programs in T. aestivum.

Materials and methods

Microsatellite

Twenty-Eight accessions of Ae. tauschii from various regions of Iran provided by National Plant Gene Bank of Iran (Table 1), T. turgidum (durum wheat) and Chinese Spring cultivar as a control were used in this study. From each accession, after the seed germination and growth, DNA was isolated from the plants of each accession according to Saghai maroof [26]. 19 pairs of microsatellite primers (were designed by Roder et al. [25] mapped to bread wheat D genome) were selected. PCR amplifications were performed in 20 μl with 0.31 μM of each primer, 0.9 mM dNTPs Mix, 2.5 mM Mgcl2, 1 U Taq polymerase, PCR buffer 1X and 50 ng of isolated DNA from the studied plants. 4 min at 94°C then 35 cycles were performed that included of 1 min at 94°C, 1 min at annealing temperature (49–60°C) and 1 min at 72°C. Then the final extension was 8 min at 72°C. Amplification reaction products were separated on 6% denaturing Polyacrylamide gels containing Polyacrylamide (29:1 acrylamide:Bis) 7M Urea, TBE 5X, 10% Ammonium persulphate (300 μl), 25 μl TEMED and distilled water. 10 μl (5 μl of products and 5 μl of loading buffer) of samples after denaturation at 95°C and cooling on ice were loaded. The electrophoresis ran at 80 V, after electrophoresis, staining performed by Silver Nitrate. The bands were scored by presence or absence of each single fragment as 1 and 0 respectively. Statistical analysis included: polymorphism information content, principle component analysis, cluster analysis and calculating Jaccard similarity coefficients by NTSYSpc V2.02 and Excel softwares.
Table 1

Accessions and their geographic origin of Ae. tauschii

Accessions

Subspecies

Origin

KC-50037, KC-50083

tauschii

Kermanshah

KC-50124, TN-614

tauschii

Khorasan

TN-304, TN-873, TN-308

tauschii

Azarbayjan (West)

TN-560, TN-1745, TN-562

tauschii

Semnan

TN-1747, TN-1749

strangulata

Semnan

TN-563, TN-564

tauschii

Gilan

TN-621, TN-1420

tauschii

Khorasan (North)

TN-641

tauschii

Azarbayjan (East)

TN-672

tauschii

Hamedan

TN-690, TN-697, TN-698, TN-699

tauschii

Golestan

TN-839, TN-841, TN-844, TN-846

strangulata

Mazandaran

TN-845, TN-850

tauschii

Mazandaran

Morphological traits

Twenty-Eight accessions of Ae. tauschii (collected from various regions of Iran, Table 1) were planted in this frame: 1 m long of rows, 120 cm distance of rows and 5 cm plant spacing in experimental field of Plant Gene Bank of Iran in Karaj during 2004–2005 and 16 characters were evaluated following IPGRI. The traits were: flowering date, maturity date, number of leaf, plant height, number of node per stem, stem width, spike length, spike width, number of spikelet per spike, node length of rachis, node width of rachis, number of seeds per spikelet, glume width, glume length, seed length, seed width. Then data analyzed by SPSS and SAS softwares. Statistical analysis included: simple statistics i.e.; mean, variance and C.V., factor analysis, discriminant function analysis and cluster analysis.

Results and discussion

Means, variance and C.V. for the accessions for the ssp. strangulata and ssp. tauschii are shown in Tables 2 and 3. High variation was observed for many of traits (for ssp. tauschii specially). Diversities related to plant height (16.8%) was highest and maturity date (4.1%) was lowest for ssp. strangulata. The highest diversity related to number of seed per spikelet (24.5%) and the lowest related to maturity date (7.8%) for ssp. tauschii, Therefore accessions that were studied have significant diversity in number of seed per spikelet that has effect on plant product. The ssp. tauschii accessions had high mean value for plant height, number of node per stem, spike length, number of spikelet per spike, glume length and seed length. In Naghavi and Amirian [16] study that accomplished on 55 accessions of Ae. tauschii, most of the diversity existed in many traits. In that study, between Iranian accessions, the mean and standard deviation for number of spikelet per spike (1.26 & 7.75) and spike length (1.17 & 7.17) were high. Zaharieva et al. [1] because of studying about 3 species of Aegilops, found out that plant height, thousand grain weight, grain weight per spike and earliness have the most share in accession diversity.
Table 2

Simple statistics of ssp. strangulata accessions

 

Seed width (mm)

Seed length (mm)

Glume length (mm)

Glume width (mm)

Seed number per spiklet

Nodes width of rachis (mm)

Nodes length of rachis (mm)

Number of spiklet per spike

Spike width (mm)

Spike length (cm)

Stem width (mm)

Number of node per stem

Plant heigth (cm)

Leaf number

Maturity date (day)

Flowering date (day)

Mean

2.83

5.27

7.02

4.26

2.83

2.75

9.68

8.28

4.74

7.34

1.28

3.06

45.69

4.28

91.66

57.5

Variance

0.04

0.15

0.11

0.34

0.16

0.080

0.48

0.24

0.1

0.11

0.2

0.11

59.58

0.24

14.66

16.7

C.V. (%)

7.1

7.2

4.7

13.6

14.5

10.5

7.1

5.9

6.7

4.5

10.4

10.6

16.8

11.5

4.1

6.9

Table 3

Simple statistics of ssp. tauschii accessions

 

Seed width (mm)

Seed length (mm)

Glume length (mm)

Glume width (mm)

Seed number per spiklet

Nodes width of rachis (mm)

Nodes length of rachis (mm)

Number of spiklet per spike

Spike width (mm)

Spike length (cm)

Stem width (mm)

Number of node per stem

Plant heigth (cm)

Leaf number

Maturity date (day)

Flowering date (day)

Mean

2.61

5.85

7.5

3.6

2.4

2.68

9.6

8.59

4.11

7.94

1.25

3.15

47.36

4.24

87.36

54.86

Variance

0.09

0.88

1.34

0.21

0.35

0.18

1.22

2.03

0.48

3.47

0.02

0.24

72.12

0.23

47.48

31.84

C.V. (%)

11.5

16.1

15.4

12.7

24.5

16

11.4

16.5

17

23

12

15.5

17.9

11

7.8

10

Discriminant function analysis was used to show the distance of two subspecies (strangulata and tauschii). The results showed that 19 out of the 28 accessions (67.9%) were classified correctly (Table 4). 50% of ssp. strangulata and 27.3% of ssp. tauschii were found to be misclassified in addition only glume width was effective to reclassify this subspecies by this analysis. Knaggs et al. [8] by discriminant analysis of morphological characters for Ae. tauschii, found that morphological variability can be used to subspecies and varieties.
Table 4

Classification of 28 accessions of Ae. tauschii according to discriminant function analysis

 

Name

Division by discriminant analysis

Total

 

strangulata

tauschii

 

Original

Count

strangulata

3

3

6

 

tauschii

6

16

22

%

strangulata

50

50

100

 

tauschii

27.3

72.7

100

In factor analysis (FA) between 16 traits, the first three factor explained 66.49% of total variance (Table 5). Analyzing 9 traits of Ae. tauschii by Naghavi and Amirian [16] showed that three components have 67.8% of total variance also principle component analysis caused that the germplasm of Ae. tauschii divided into different genetic groups. After rotation by varimax method, the first factor explained that 27.46% was positive relationship with glume length, spike length and node length of rachis, it is spike length factor also the second FA accounted of 21.15% that has positive relationship with flowering date and maturity date. It is grow up time factor. The third FA contributed 17.88% of total variance, it has positive relationship with glum width, spike width, seed width and number of seeds per spiklet, it is spike width factor. Consequently choosing through each factor resulted to selection of accessions based on traits collection existed in each component.
Table 5

Factor analysis for 16 traits in Ae. tauschii

Factor

Eigen value

Variance proportion (%)

Cumulative (%)

1

4.39

27.46

27.46

2

3.38

21.15

48.61

3

2.86

17.88

66.49

Through cluster analysis according to FA by Ward method, accessions divided into three groups. The accessions of group I in view of stem width, spike length, node length of rachis, node width of rachis and number of spikelet per spike were higher than the others. The group II were higher in flowering date, maturity date, spike width, glume width, number of seed per spikelet, plant height, leaf number and seed width than other groups. The group III was higher in view of number of node per stem, glume length and seed length (Table 6). Therefore in breeding programs this grouping is very useful. Also by comparison of Ward tree (Fig. 1) and origin of these accessions, according to morphological traits, accessions grouping were not conforming by geographical distribution. For example, Kermanshah accessions were in two separated groups, Therefore these accessions had the highest distance. Also in study of three species of Aegilops by Zaharieva et al. [1], there was not any relationship between morphological traits and original geographical places of them.
Table 6

Comparison of 16 traits between three groups of Ae. tauschii from cluster analysis of 28 accessions

Group

Trait

Seed width (mm)

Seed length (mm)

Glume length (mm)

Glume width (mm)

Seed number per spiklet

Nodes width of rachis (mm)

Nodes length of rachis (mm)

Number of spiklet per spike

Spike width (mm)

Spike length (cm)

Stem width (mm)

Number of node per stem

Plant heigth (cm)

Leaf number

Maturity date (day)

Flowering date (day)

Group I

2.64

5.69

7.21

3.88

2.60

2.79

9.93

8.63

4.33

8.21

1.42

3.10

45.78

4.07

89.40

54.90

GroupII

2.92

5.67

7.18

4.01

2.66

2.73

9.60

8.41

4.63

7.54

1.21

3.07

47.87

4.37

90.00

57.33

GroupIII

2.41

5.84

7.32

3.35

2.22

2.56

9.29

8.52

3.78

7.65

1.13

3.22

47.50

4.33

85.33

54.11

https://static-content.springer.com/image/art%3A10.1007%2Fs11033-009-9931-6/MediaObjects/11033_2009_9931_Fig1_HTML.gif
Fig. 1

Dendrogram of 28 accessions of Ae. tauschii using Ward method according to FA

All of 19 primer pairs from D genome of common wheat gave amplification and showed a good polymorphism in Ae. tauschii. Totally 208 alleles were recognized. Total number of bands per primers ranged from 5 to 17 polymorphic bands and the mean of the allele number in loci was 10.94 that was not conforming with the results of Pestsova et al. [7]. They got: 18.8 mean and 11–25 range, also Saeidi et al. [22] got this results: 7.3 mean and 4–12 range but obtained results was conforming with the results of Naghavi et al. [23] with 9.21 mean and 6–15 range that was achieved by SSR marker. In this study, polymorphism information content (PIC) was counted in all genotypes (Table 7) and the mean was 0.267 that this mean was lower than 0.659 [13] and 0.82 [23]. PIC is not fix and it dependent on number of allele per locus, (GT) content and type of motif [27]. The total number of bands in 28 accessions of Ae. tauschii, C.S. and durum wheat was 2261. Chinese Spring had the highest number of bands that was 95 bands. TN-641 accession had the highest number of bands (83) and TN-621 had lowest number of bands (51) between accessions. In this study, D genome specified primers could amplify some regions in durum wheat (AABB) and finally durum wheat had (63) polymorphic bands. It means that there are similar regions between D genome and A, B genome. Zhang et al. [28] studied the synthesized hexaploid wheat (was derived through hybridization of tetraploid wheat (AABB) and Ae. tauschii) using D genome specific SSR primers of common wheat, and found that some D genome primers of common wheat can amplify SSR products in tetraploid wheat with AABB genome.
Table 7

Polymorphism information content and number of allele for used primers

Primer

PIC

Number of allele

Xgwm437

0.347

13

Xgwm609

0.111

6

Xgwm428

0.430

14

Xgwm190

0.197

12

Xgwm261

0.264

15

Xgwm194

0.213

6

Xgwm608

0.234

9

Xgwm121

0.240

5

Xgwm55

0.241

14

Xgwm111

0.286

9

Xgwm314

0.284

12

Xgwm350

0.228

13

Xgwm295

0.326

17

Xgwm3

0.204

12

Xgwm102

0.396

8

Xgwm33

0.150

12

Xgwm174

0.294

13

Xgwm37

0.253

7

Xgwm106

0.397

11

Mean

0.267

10.94

Genetic similarity coefficients estimated by Jaccard method between 28 accessions of Ae. tauschii, T. turgidum and C.S. The range was from 0.23 to 0.73. The lowest similarity was between TN-697 and TN-839 (from North), also the highest similarity was between TN-846 (from Azarbaijan) and TN-873 (from Mazandaran). It means that these two accessions (TN-846 and TN-873) are far from each other geographically, but they have the highest similarity, Also ssp. tauschii had higher genetic diversity (Similarity coefficient = 0.32–0.6) than ssp. strangulata (Similarity coefficient = 0.41–0.59). Jaaska [19] mentioned that ssp. tauschii has a higher level of genetic variation than ssp. strangulata. Among studied accessions, TN-562 had the highest similarity coefficient (0.51) and TN-697 had the lowest similarity coefficient (0.29) with C.S., Also the similarity index between durum wheat and Chinese Spring was 0.5.

Cluster analysis based on Jaccard similarity coefficients and UPGMA algorithm calculated for the genotypes. In this group C.S. and durum wheat were in a separated class (Fig. 2) but ssp. strangulata and ssp. tauschii did not separate from each other. This classification was not conforming to morphological study and geographical sites of the Ae. tauschii accessions. In fact, there was not any classification based on subspecies or geographical regions. There was not any significant grouping based on geography of the accessions or subspecies. In Saeidi et al. [22], SSR marker study also there was not any significant grouping according to geographical sites or subspecies.
https://static-content.springer.com/image/art%3A10.1007%2Fs11033-009-9931-6/MediaObjects/11033_2009_9931_Fig2_HTML.gif
Fig. 2

Dendrogram of Ae. tauschii accessions and control (C.S.) based on SSR, using UPGMA method

In principle component analysis method (PCA) based on SSR data, the first nine components explained 51.2% of total variance, therefore this markers covered much amount of Ae. tauschii genome. The method of PCA could not divide Ae. tauschii accessions into genetic groups (exception of the accessions from Kermanshah and Hamedan that separated from other accessions, Fig. 3).
https://static-content.springer.com/image/art%3A10.1007%2Fs11033-009-9931-6/MediaObjects/11033_2009_9931_Fig3_HTML.gif
Fig. 3

Plot of the first and second principal components in Ae. tauschii according to SSR markers

In this study, all of 19 SSR markers of common wheat D genome amplified in this wild diploid species (Ae. tauschii) that it appearance the high ability of SSR markers transformation of common wheat D genome to Ae. tauschii genome and high level of sequence conservation in the flanking regions of SSR regions between common wheat and diploid wheat. Microsatellites from common wheat amplified in many related or alien species [28]. Also in this study, D genome microsatellites analysis, allelic extended range, showed high level of polymorphism and genetic diversity. The high level of genetic diversity in Iran had been reported by Lubbers et al. [21], Dvorak et al. [2] and Pestsova et al. [7]. Saeidi et al. [22]. The highest level of diversity in Ae. tauschii is in the North of Iran (South of Caspian Sea). Also based on morphological traits there were many genetic diversity in Ae. tauschii that can show high potential of Iran genepool for this plant.

Microsatellite data could not separate the accessions of tauschii and strangulata subspecies. Maybe this matter is because of the classification of tauschii and strangulata subspecies. In fact the possible events of migration between the two subspecies could have lead to a decrease of the genetic differentiation between them, as migration between tauschii and strangulata subspecies can occur in Iran [2] the genetic differentiation between these accessions is low. Also Kihara et al. [29] found intermediate and hybrid forms between subspecies. Kim et al. [30] did not distinguish ssp. strangulata genotype from ssp. tauschii genotype by studying of highly conserved region of ribosomal DNA in Ae. tauschii subspecies.

The classification based on morphological traits was not conforming to classification according to SSR markers and geographical regions. Vojdani and Meybodi [31] believe that there is not any relationship between morphological diversity and ecogeographic diversity. Nevo [32] believes that the locations of collecting belong the geographic regions could be grouped based on morphological diversity. Many studies showed that dividing based on morphological diversity is not conforming to genetic dividing. Semagn [33] mentioned that molecular markers cover a large proportion of the genome, including coding and noncoding regions than the morphology and molecular markers are not subjected to artificial selection compared to morphology.

The collection that studied includes of strangulata and tauschii subspecies in Iran. Strangulata subspecies scattered in North of Iran: Mazandaran, Gilan and Golestsn. tauschii subspecies scatter in North and Northeast of Alborz mountains, Center and North of Isfahan and a part of Fars province. Some of the Ae. tauschii collections in the Northeast of Iran are growing between rocks [22]. Therefore tauschii genepool exist around the strangulata genepool and classification based on genetical information is not conforming to classification basis of morphological traits. According to Jaaska [19] tauschii and strangulata subspecies in the first time that Ae. tauschii appeared and before geographical dispersion, were different from each other. It seems that intraspecies branching outs were at the same time with big changes in genetic structure of Ae. tauschii collections. Based on Hammer [15], Lubbers et al. [21] and Dvorak et al. [2] studies, one of the important origin sites for Ae. tauschii is the Southwest of Caspian Sea. Therefore studying about Iranian Ae. tauschii in South of the Caspian Sea specially and detection of genetic diversity of them is very helpful for us to do breeding programs. Because of South of the Caspian Sea is the main origin sites of Ae. tauschii, where bread wheat has evolved [2, 15], identification of genetic diversity of Ae. tauschii can help us that how to transport desirable traits to bread wheat.

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© Springer Science+Business Media B.V. 2009