4/2015

 

УДК 575.1; 577.21

 

USE OF RETROTRANSPOSON MARKERS FOR ANALYSING THE GENETIC DIVERSITY OF WILD EMMER WHEAT (TRITICUM DICOCCOIDES)

 

Tagimanova D.S., Novakovskaya A.P., Uvashov A.O., Khapilina O.N., Kalendar R.N.
National Center for Biotechnology
13/5 Korghalzhyn Road, Astana, 010000, Kazakhstan
This email address is being protected from spambots. You need JavaScript enabled to view it.

 

ABSTRACT

The wild ancestor of all cultivated tetra- and hexaploid wheat, wild emmer wheat (Triticum dicoccoides), harbours considerable genetic diversity. This diversity might be expected to display eco-geographical patterns of variation, conflating gene flow, and local adaptation. Similarly, retrotransposons, as self-replicating entities comprising the bulk of genomic DNA in wheat, are expected to generate generally neutral variation due to their transpositional activity. Here, we examined the genetic diversity of 14 Israeli and one Turkish population of wild emmer wheat, based on the retrotransposon marker methods IRAP (Inter-Retrotransposon Amplified Polymorphism) and REMAP (Retrotransposon-Microsatellite Amplified Polymorphism). The level of genetic diversity we detected was in agreement with previous studies that have used a variety of marker systems to assay genes and other genomic components. The genetic distances failed to correlate with the geographical distances, suggesting local selection on geographically widespread haplotypes (“weak selection”). However, the proportion of polymorphic loci correlated with the latitude of the population and the genetic diversity correlated with the longitude. Principal component analysis of the marker data resulted in separation of some of the populations.

Keywords: Triticum dicoccoides, wild emmer wheat, IRAP, REMAP, genetic diversity.


 

INTRODUCTION

Wild emmer wheat, Triticum dicoccoides (Körn.) Aaronsohn, is the tetraploid progenitor of cultivated hexaploid bread wheat. Therefore, it has been used as a material for many genetic, ecological, physiological, and cytogenetic studies investigating the genus. Considerable genetic diversity has been reported among wild emmer wheat populations, which harbor a rich source for many disease resistance alleles, agronomic traits, and environmental adaptations [1, 2, 3]. Wild emmer wheat grows on the area of the Fertile Crescent in Middle East. The populations are often isolated or semi-isolated from each other, but in Israel, most of them are in close contact.

Crescent features, over its geographical range, sharp environmental gradients, even on local scales, that impose selective pressures on local plant populations. The interaction between mutation rates in various compartments of the genome, gene flow, and selection have created patterns of variation within the genome of T. dicoccoides. This variation has been interrogated by molecular markers sampling either genic, and possibly selective, allozyme markers [4].

Previously, analyzed 37 populations of wild emmer wheat using allozyme markers, neutral microsatellite markers [2], or anonymous (RAPD) markers possibly sampling both compartments [5]. These studies showed a high level of polymorphism within T. dicoccoides, with the isolated marginal populations clearly differing from the others and genetic diversity patterns reflecting soil type at each location.

Retrotransposons are ubiquitous [6] throughout the plant kingdom and they exist in a vast number of copies in any plant genome. Thus, they are a well suited source of genetic markers. A given retrotransposition is a unique phenomenon, and the same integration site is not likely to be used more than once [7]. The retrotransposons remain as a part of the chromosome and they spread by producing daughter copies, which migrate to new loci [7].

In the present study, we used retrotransposon markers to analyze the polymorphism among these populations. We used the techniques IRAP (Inter-Retrotransposon Amplified Polymorphism) and REMAP (Retrotransposon-Microsatellite Amplified Polymorphism) previously described by Kalendar et al [8, 9, 10]. In IRAP, both PCR primers are designed to find the LTR (Long Terminal Repeat) sequence of a retrotransposon. In REMAP, one primer finds the LTR sequence and the other primer finds a microsatellite. Linking retrotransposon markers to genes of interest could be useful for marker-assisted selection [11].

The adaptive pattern of retrotransposons has been studied earlier by Kalendar et al. [12]. They used the REMAP-method to investigate wild barley (Hordeum spontaneum L.) accessions from the Evolution Canyon in Lower Nahal Oren, Mount Carmel, Israel. The LTR primers were designed to face outward from the BARE-1 retrotransposon [13]. In the canyon, the microclimates differ significantly, which appeared to cause differentiation among populations. The copy number of BARE-1 was found to be higher on the stressful south-facing slope, where the radiation is strong, than on the less stressful north-facing slope.

IRAP and REMAP methods have also been used successfully to study the young allopolyploid species Spartina maritima C.E. Hubbard [14]. S-SAP (Sequence-Specific Amplification Polymorphisms) is another method in which retrotransposons are used as markers. The use of that method has been reported in investigation on polymorphisms on pea (Pisum) [15] and barley (Hordeum vulgare L.) [16, 17]. IRAP and REMAP markers were used along with other markers to create a genetic map of the genome of Aegilops tauschii (Coss.) Schmal. [18, 19, 20].

The main goal of this study was to find useful retrotransposon markers for wild emmer wheat and to assess the diversity of these markers among 150 genotypes originating from 15 populations which all differed in their ecogeographical background. Another goal was to examine the nature of retrotransposons and their adaptive pattern.

 

MATERIALS AND METHODS

Plant material and DNA extraction

Plants of T. dicoccoides from 14 Israeli and from one Turkish population, 8-10 genotypes per population, were collected randomly, at least 1-m apart. The populations and collection sites were described in earlier publications [4, 21].

The material was stored in the cereal gene bank of the Institute of Evolution, University of Haifa, from where the genotypes for this study were obtained. The locations of the populations and the ecogeographical background of them are listed in table 1. Figure 1 shows their geographical origin. The location of the Turkish Diyarbakir population is shown in Figure 1 of Nevo and Beiles [22]. The climate data for Israel is from the Atlas of Israel (1970) and publications of the Meteorological service of Israel.

One seed of each genotype was grown into a 7-day-old seedling and the leaves were collected for preparation of DNA. Total genomic DNA was extracted from leaf samples of these genotypes using a modification of the CTAB extraction protocol (http://primerdigital.com/dna.html) with RNAse A treatment. The DNA samples were diluted in 1×TE buffer and the DNA quality was checked electrophoretically and spectrophotometrically with a Nanodrop apparatus (Thermo Fisher Scientific Inc.).

 

Table 1. Geographical and climatical data for 15 populations of wild emmer wheat, Triticum dicoccoides, in Israel and Turkey

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

No.a

Population

Ln

Lt

Al

Tm

Ta

Tj

Td

Tdd

Rn

Rd

Hu14

Huan

Dw

Trd

Ev

So

Rv

Rr

1

Mt. Hermon

35.73

33.30

1300

11

21

3

18

6

1400

66

48

60

60

0

150

1

30

20

7

Yehudiyya

35.70

32.93

200

19

27

11

16

12

550

47

42

58

58

100

160

5

38

25

8

Gamla

35.74

32.88

200

19

26

9

17

12

470

50

43

58

58

60

155

5

39

26

9

Rosh Pinna

35.52

32.95

700

18

25

9

16

10

697

50

48

58

50

35

150

1

35

22

11

Tabigha

35.53

32.90

0

24

32

15

17

10

436

45

45

57

58

120

160

5

39

25

16

Mt. Gilboa

35.42

32.50

150

21

28

12

16

12

400

44

43

58

40

160

165

1

34

24

17

Mt. Gerizim

35.28

32.20

800

17

23

8

15

9

700

47

45

60

42

0

155

1

38

25

18

Gitit

35.40

32.10

300

21

29

13

16

12

360

39

39

55

25

100

170

1

38

24

19

Kokhav Hashahar

35.34

31.95

600

20

28

12

16

12

400

40

45

59

30

25

165

1

38

22

23

J’aba

35.08

31.67

660

17

25

9

15

9

500

41

49

62

57

30

155

1

35

21

24

Amirim

35.45

32.93

600

15

24

8

16

8

850

61

48

60

53

13

153

1

35

23

28

Beit-Oren

35.03

32.73

400

17

24

11

13

8

700

55

59

69

80

0

142

1

25

19

30

Bat-Shelomo

35.02

32.60

75

20

26

13

13

10

650

55

58

68

77

30

150

2

24

20

33

Givat Koach

34.92

32.03

75

20

26

12

14

12

540

46

50

64

65

105

160

1

32

26

36

W. Diyarbakir

39.63

37.89

850

13

27

2

25

-

546

65

-

46

-

-

-

5

-

-

a Population numbers are according to Nevo and Beiles (1989).
Symbols of variables:
Geographical: Ln=longtitude (decimals); Lt=latitude (decimal); Al=Altitude (m);
Temperature: Tm=mean annual temperature; Ta=mean August temperature; Tj=mean Jannuary temperature; Td=seasonal temperature difference;
Tdd = day-night temperature difference; Trd=mean number of tropical days;
Water availability: Rn=mean annual rainfall (mm); Rd=mean number of rainy days; Huan=mean annual humidity; Hu14=mean humidity at 14:00;
Dw = mean number of dew nights in summer; Ev=mean annual evaporation; Rv=mean interannual variability of rainfall; Rr=mean relative variability of rainfall;
Edaphic: So=soil type; 1=terra rossa; 2=rendzina; 5=basalt

 

Fig. 1. A map showing the geographic distribution of the 14 Israeli wild emmer wheat populations. For names of the populations, see Table 1. For a map showing, the Turkish West Diyarbakir population see Nevo and Beiles [4]
 
Fig. 1. A map showing the geographic distribution of the 14 Israeli wild emmer wheat populations. For names of the populations, see Table 1. For a map showing, the Turkish West Diyarbakir population see Nevo and Beiles [4]

 

TE sequence sources and PCR primer design

To determine the interpopulation diversity of seven LTR retrotransposons (Bare-1-WIS2, Wilma-Bagy-2, Cereba, Nikita, Sukkula, Sabrina and Daniela), IRAP analysis of the populations was performed, and the results were compared among themselves. This type of data provides insights into the dynamics of LTR retrotransposons in the genome of Triticum dicoccoides under changing environments. The sequences of transposable elements were taken from the TREP database (table 2) (http://wheat.pw.usda.gov/ggpages/ITMI/Repeats/index.shtml). Different LTRs of certain elements vary in sequence at specific locations and have point mutations, but there are places where polymorphism is reduced to a minimum. For each TE family, the sequence accessions were aligned, and the conservation was assessed with the multiple alignment procedure of MULTALIN [23].

The conserved segments of the LTR or internal domain of the retrotransposons were used for the design of PCR primers, which was carried out with the program FastPCR (http://primerdigital.com/fastpcr.html) [24, 25]. We designed several primers for each retrotransposon’s LTRs to compare the efficiency and reproducibility of amplification. The sequences of the primers are shown in table 2. None of the primer pairs chosen form dimers, and all showed high PCR efficiency. The chosen primers match motifs sufficiently conserved in the retrotransposons to allow amplification of almost all targets in the genome.

 

Table 2. The primers used for IRAP and REMAP

Primer ID

The source

Sequence (5’-3’)

Tm, °C [24]

554

BARE-1 LTR

CCAACTAGAGGCTTGCTAGGGAC

60.0

734

BARE-1 LTR

TTCCCATGCGACGTTCCCCAAC

62.6

692

Cereba LTR

GCGATTGCTAAGGCGCAACG

61.1

2110

Daniela LTR

TCGCTGCGACTGCCCGTGCACA

67.3

2113

Daniela LTR

TACGCATCCGTGCGGCCCGAAC

66.6

773

Nikita LTR

CCCTCTAGGCGACATCCACG

60.6

639

Sabrina LTR

ACACACAAAGCATTCCTCCGG

58.4

432

Sukkula LTR

GATAGGGTCGCATCTTGGGCGTGAC

64.1

678

Sukkula LTR

AAAGTTGTATCCGGGGCGTTAC

57.8

679

Sukkula LTR

GGGTCGCATATTGGGCGTGAC

62.0

2107

Wilma-Bagy-2 LTR

AGCATGATGCAAAATGGACGTATCA

56.8

2108

Wilma-Bagy-2 LTR

AGAGCCTTCTGCTCCTCGTTGGGT

63.4

455

Wis LTR

TTGAATTTCTGCTACGTTCCCC

55.8

738

Wis LTR

AATTTCTGCTACGTTCCCCTAC

55.0

2105

Wis LTR

ACTCCATAGATGGATCTTGGTGA

54.6

2106

Wis LTR

TAATTTCTGCAACGTTCCCCAACA

57.1

443

ISSR: (AC)9T

ACACACACACACACACACT

54.3

 

IRAP and REMAP analysis

IRAP analysis was conducted according to Kalendar and Schulman [9, 10] using seventeen primers from seven LTR retrotransposons (Bare-1-WIS2, Wilma-Bagy-2, Cereba, Nikita, Sukkula, Sabrina and Daniela). The PCR was performed in a 20-µl reaction mixture containing 20 ng DNA, 1x DreamTaq buffer, 200 mM dNTP, 400 nM primer and 1 U DreamTaq Taq polymerase (Thermo Scientific). The amplification was performed in the Mastercycler Gradient (Eppendorf AG, Germany). The PCR reaction program consisted of 1 cycle at 95ºC, 3 min; 31 cycles of 95ºC for 20 sec, 60ºC for 20 sec, 72ºC for 2 min; 72ºC for 5 min; maintenance at 4ºC.

In REMAP, we used one primer from WIS2 LTR (738) with ISSR primer (443), which is also shown in table 2. The same optimizations were done for REMAP resulting in the following reaction mix and amplification program.

Each LTR primer or primers combinations was tested singularly in PCR reactions using a genomic DNA mixture composed of equal amounts from all the accessions. The PCR products were separated by electrophoresis at 70 V for 8 hours in a 1.3% agarose gel (RESolute Wide Range, BIOzym) with 0.5 × TBE electrophoresis buffer. Gels were stained with EtBr and scanned using a FLA-5100 imaging system (Fuji Photo Film GmbH) with a resolution of 50 µm.

 

Data analysis

From the IRAP and REMAP profiles, all distinct bands were scored as present (1) or absent (0) at each band position for each primer in all samples. Each PCR band was treated as a single locus. The presence or absence of a fragment of a given length was recorded in binary code. The sets that contained missing values were removed from the raw scored data sets. Monomorphic bands were scored and removed from the data set before analysis.

The gels were scored for the presence and absence of bands totaling 224 polymorphic bands for the samples. Based on the primary data, the level of genetic diversity (Nei 1987) was determined using the Arlequin software [26]. The primary genetic data were bootsrapped with SEQBOOT, after which the pairwise genetic distances were calculated using GENDIST (http://www.bablokb.de/gendist/), both programs from the PHYLIP 3.696 software package (http://evolution.gs.washington.edu/phylip.html). The ability of IRAP and REMAP markers to reveal genetic relationships among all T. dicoccoides accessions was evaluated phylogenetically by Neighbor-Joining (NJ). An algorithm was constructed using PAUP software [27]. Support for the tree was determined by performing one thousand bootstrap operations on the data set generated by distance analysis. To study the partition of IRAP genetic variation to among-and within- population variance components, the analysis of molecular variance (AMOVA) was conducted with the program GenAlex 6.5 [28]. The genetic distances among groups were analyzed with the Phi statistic (Φst). The number of permutations was set at 999 for AMOVA for a test of significance of the genetic distance among groups.

Principal component analyses for the data matrix were run with the statistical software SAS (Cary, NC, USA) and the chart was visualized on SigmaPlot (Systat Software Inc., San Jose, CA, USA). SAS was used to conduct a stepwise multiple regression with all eco-geographical variables (table 1) as independent variables to find the best predictors of the proportion of polymorphic loci (P) and genetic diversity (He).

 

RESULTS

Screening for primers resulted in 15 primer for IRAP and one primer pair for REMAP (primers 738 with 443) (figure 2, 3). These primer pairs yielded 10 to 40 scorable bands and 10 to 20 of these bands were scorable. Altogether 224 polymorphic bands were scored.

Fig. 2. An IRAP gel produced with the primers 679 (Sukkula LTR). Thermo Scientific GeneRuler DNA Ladder Mix (100-10,000 bp). DNA samples of the 14 Israeli wild emmer wheat populations (Triticum dicoccoides): Mt. Hermon (1-10); Rosh-Pinna (11-20); Tabigha (21-30); Bat-Shelomo (31-40); Mt. Gilboa (41-50); Mt. Gerizim (51-60); Kokhav Hashahar (61-69); Amirim (70-79); Bet-Oren (80-89); Givat Koach (90-99); Gitit (100-109); J’aba (110-119); Gamla (120-129); Turkey (130-139); Yehudiyya (140-156)
 
Fig. 2. An IRAP gel produced with the primers 679 (Sukkula LTR). Thermo Scientific GeneRuler DNA Ladder Mix (100-10,000 bp). DNA samples of the 14 Israeli wild emmer wheat populations (Triticum dicoccoides): Mt. Hermon (1-10); Rosh-Pinna (11-20); Tabigha (21-30); Bat-Shelomo (31-40); Mt. Gilboa (41-50); Mt. Gerizim (51-60); Kokhav Hashahar (61-69); Amirim (70-79); Bet-Oren (80-89); Givat Koach (90-99); Gitit (100-109); J’aba (110-119); Gamla (120-129); Turkey (130-139); Yehudiyya (140-156)

 

Fig. 3. An IRAP gel produced with the primers 2108 (Wilma-Bagy-2 LTR). Thermo Scientific GeneRuler DNA Ladder Mix (100-10,000 bp). DNA samples of the 14 Israeli wild emmer wheat populations (Triticum dicoccoides): Mt. Hermon (1-10); Rosh-Pinna (11-20); Tabigha (21-30); Bat-Shelomo (31-40); Mt. Gilboa (41-50); Mt. Gerizim (51-60); Kokhav Hashahar (61-69); Amirim  (70-79); Bet-Oren (80-89); Givat Koach (90-99); Gitit (100-109); J’aba (110-119); Gamla (120-129); Turkey (130-139); Yehudiyya (140-156)
 
Fig. 3. An IRAP gel produced with the primers 2108 (Wilma-Bagy-2 LTR). Thermo Scientific GeneRuler DNA Ladder Mix (100-10,000 bp). DNA samples of the 14 Israeli wild emmer wheat populations (Triticum dicoccoides): Mt. Hermon (1-10); Rosh-Pinna (11-20); Tabigha (21-30); Bat-Shelomo (31-40); Mt. Gilboa (41-50); Mt. Gerizim (51-60); Kokhav Hashahar (61-69); Amirim  (70-79); Bet-Oren (80-89); Givat Koach (90-99); Gitit (100-109); J’aba (110-119); Gamla (120-129); Turkey (130-139); Yehudiyya (140-156)

 

Genetic diversity

The results concerning genetic diversity including the proportion of polymorphic loci (P-5%) and the genetic diversity (He, Nei 1987) are shown in table 3. The mean proportion of polymorphic loci and degree of genetic diversity equaled 0.360 and 0.138±0.063 (standard deviation), respectively. The He values varied between 0.002-0.204. The lowest He value (0.002±0.002) was obtained in the small, isolated population of Bet-Oren and the highest value (0.204±0.114) in Mt. Hermon, which belongs to the marginal steppic populations. Other high values were detected in the populations of Mt. Gilboa (0.201±0.108), and Rosh Pinna (0.195±0.105).

 

Table 3. Numbers of polymorphic loci and average gene diversities over loci

No

Populationa

No. loci incl.b

No. polym. loci

Prop. polym. loci

Diversity ±SD

1

Mt. Hermon

197

93

0.47

0.204±0.114

7

Yehudiyya

210

20

0.10

0.052±0.030

8

Gamla

192

77

0.40

0.118±0.065

9

Rosh Pinna

215

93

0.43

0.195±0.105

11

Tabigha

221

48

0.22

0.109±0.050

16

Mt. Gilboa

211

114

0.54

0.201±0.108

17

Mt. Gerizim

207

104

0.50

0.186±0.100

18

Gitit

214

102

0.48

0.189±0.102

19

Kokhav Hashahar

201

78

0.39

0.157±0.086

23

J’aba

207

96

0.46

0.182±0.098

24

Amirim

217

58

0.27

0.112±0.062

28

Bet-Oren

215

2

0.01

0.002±0.002

30

Bat-Shelomo

175

82

0.47

0.186±0.100

33

Givat Koach

204

48

0.24

0.063±0.035

36

W. Diyarbakir, 22km

202

77

0.38

0.118±0.064

 

Mean

205.9

72.8

0.36

0.138±0.063

a Population numbers are according to Nevo & Beiles [4];
b The number of loci included in the analyses of each population depends on the amount of missing data (loci included have less than 5% missing data).

 

Genetic distance

Table 4 shows the genetic distances calculated as pair-wise comparisons for the averages of all populations. The greatest distance (0.9421) was found between Bet-Oren and Yehudiyya and the shortest (0.2185) between Mt. Gilboa and Mt. Gerizim. These results also show that Yehudiyya (distance ≥ 0.6391), Tabigha (distance ≥ 0.6068) and Bet-Oren (distance ≥ 0.5994) are all very separated from the others as well as each other. The geographical distribution of the samples does not explain the genetic distance. For example, the genetic distance between West Diyarbakir in Turkey and many Israeli populations is shorter than the distance between some Israeli populations (figure 4). This excludes the isolation by distance model.

 

Table 4. Genetic distances as pair-wise comparisons between the 15 wild emmer wheat populations. Population numbers are according to Nevo and Beiles (1989) 

 

 

1

7

8

9

11

16

17

18

19

23

24

28

30

33

36

1

Mt. Hermon

0.0000

 

 

 

 

 

 

 

 

 

 

 

 

 

 

7

Yehudiyya

0.6849

0.0000

 

 

 

 

 

 

 

 

 

 

 

 

 

8

Gamla

0.4590

0.7727

0.0000

 

 

 

 

 

 

 

 

 

 

 

 

9

Rosh Pinna

0.2902

0.6738

0.4605

0.0000

 

 

 

 

 

 

 

 

 

 

 

11

Tabigha

0.6284

0.6430

0.7464

0.6514

0.0000

 

 

 

 

 

 

 

 

 

 

16

Mt. Gilboa

0.2525

0.6391

0.4650

0.3549

0.6068

0.0000

 

 

 

 

 

 

 

 

 

17

Mt. Gerizim

0.2593

0.6786

0.4660

0.3430

0.6443

0.2185

0.0000

 

 

 

 

 

 

 

 

18

Gitit

0.3406

0.6641

0.5077

0.4063

0.6460

0.3132

0.3255

0.0000

 

 

 

 

 

 

 

19

Kokhav H.

0.3724

0.7430

0.5438

0.3786

0.7187

0.3692

0.3726

0.4259

0.0000

 

 

 

 

 

 

23

J'aba

0.3597

0.6724

0.4880

0.3772

0.6427

0.2721

0.2891

0.2749

0.3666

0.0000

 

 

 

 

 

24

Amirim

0.4738

0.8041

0.5914

0.4443

0.7674

0.4472

0.5383

0.5010

0.4311

0.4948

0.0000

 

 

 

 

28

Bet-Oren

0.6773

0.9421

0.8171

0.6909

0.8995

0.6215

0.6756

0.6961

0.7205

0.5994

0.8070

0.0000

 

 

 

30

Bat-Shelomo

0.2992

0.6730

0.4367

0.3466

0.6384

0.2305

0.3114

0.3506

0.3832

0.3180

0.4143

0.6596

0.0000

 

 

33

Givat Koach

0.5879

0.8388

0.7156

0.5573

0.8010

0.4794

0.5343

0.5499

0.5835

0.4604

0.6757

0.8894

0.5121

0.0000

 

36

W. Diyarbakir

0.4226

0.7530

0.5860

0.5090

0.7254

0.4626

0.4720

0.5076

0.5534

0.4941

0.6163

0.8092

0.4620

0.7030

0.0000

Fig. 4. A phenogram obtained for the populations of Triticum dicoccoides. Bootstrap percentages are shown above the branches
 
Fig. 4. A phenogram obtained for the populations of Triticum dicoccoides. Bootstrap percentages are shown above the branches

 

Principal component analysis

The principal component analysis managed to separate most of the populations. Figure 5 shows that Yehudiyya and Tabigha form one group, Bet-Oren is a monomorphic group, West Diyarbakir separates as a group of its own, J’aba is clustered as a group, Mt. Gilboa and Mt. Gerizim form one group, and Amirim with Kokhav Hashahar separates clearly. The other accessions fail to separate clearly from the others.

Fig. 5. Plot of principal components among the 15 wild emmer wheat populations. A Amirim, B Bat-Shelomo, C Bet-Oren, D Rosh-Pinna, E Tabigha, F Yehudiyya, G Gamla, H Mt. Hermon, J J’aba, K Kokhav Hashahar, M Mt. Gilboa, N Mt. Gerizim, O Gitit and P Givat Koach
 
Fig. 5. Plot of principal components among the 15 wild emmer wheat populations. A Amirim, B Bat-Shelomo, C Bet-Oren, D Rosh-Pinna, E Tabigha, F Yehudiyya, G Gamla, H Mt. Hermon, J J’aba, K Kokhav Hashahar, M Mt. Gilboa, N Mt. Gerizim, O Gitit and P Givat Koach

 

Multiple regression analysis

Based on the analysis, latitude had a significant negative effect: R2 = 0.844 (p < 0.0001) on the proportion of polymorphic loci. Furthermore, longitude had a significant positive effect: R2 = 0.918 (p<0.0001) on genetic diversity. No other ecogeographical variables (table 1) had a significant correlation with the genetic diversity data.

 

DISCUSSION

In this study, the retrotransposon marker techniques IRAP and REMAP were found useful when assessing genetic differentiation in T. dicoccoides. The possibility of getting from 8 to 24 scorable bands with each primer pair makes the techniques more effective than RAPDs. In addition, the specificity of the primers makes them more reliable. IRAP and REMAP do not suffer from poor reproducibility of bands (data not shown).

The families Triticum and Hordeum are so close to each other genetically that using barley primers on wheat caused no problems. For example the sequences of Wis2H of wheat and BARE-1 [18] of barley are very similar. On less related species, there would be very few polymorphisms or the same primers would not work. According to Vicient et al [29], the active retrotransposon families appear to be shared by grasses.

The same 15 populations that were used in this study had been used earlier in allozyme studies by Nevo and Beiles [4], in RAPD studies by Fahima et al [2] and in microsatellite studies by Fahima et al. [5]. The level of observed diversity was similar to that observed using RAPDs, although the correlation was lowest. Most DNA is non-coding (mostly retrotransposons), and RAPD primers mostly amplify non-coding regions like retrotransposons. The genetic diversity of the marginal population of Bet-Oren is almost zero, as observed earlier also, because of a small founding population.

An interesting result is that genetic diversity using retrotransposon markers correlates well with allozyme data, which represent the coding region. The possibility that the specific bands we scored would contain coding region is small, because retrotransposons are usually clustered [29]. Retrotransposons should also be independent of the phenotype of the plant, if they are considered neutral elements. However not all retrotransposon insertions are neutral, because they may occur in places that affect the function of genes or have some other unknown effect. Allozymes have provided useful information on the genetic structure of wild emmer wheat, but the number of scorable loci is limited, which partly explains the smaller observed diversity. The coding region also varies less than the non-coding region. The best correlation is expectedly with microsatellite data, which represents non-coding region.

In contrast to earlier results, the genetic diversity detected using retrotransposon markers could not be predicted significantly by any other variable than latitude and longitude. However, when using the allele frequencies of all alleles in a population separately, several alleles were found to correlate with environmental variables (data not shown). This is an expected result, because the loci may code for genes related to adaptation. The result suggests that retrotransposon insertions are not neutral at a local level.

The fact that there is no relationship to be found between the genetic distance (D) and the geographical distance may be a result of the wide polymorphism found within and between the populations. The same result was obtained using all other marker methods. Northern Israel is considered the center of divergence for wild emmer wheat [4], which makes one expect a wide range of different genotypes.

Wild emmer wheat is a self-pollinating species, so its forming of several separate genotypes on a small area is possible. Another thing to consider is that all the populations in Israel are reachable by animals that may carry seeds. There is a wide heterogeneity on micro- and macroscale, which may have caused spatio-temporal selection. The plants that have had the best fitness have survived and others have died. On some sites, many plant lines have had good fitness, but the non-coding regions of their genomes have been different from each other. On other sites, only few lines have survived which has decreased the diversity.

 

Acknowledgements

This work was supported by the project no. О.0659 «Development of new technology of genetic identification of wheat varieties with economically valuable traits» (2014-2016), Ministry of Education and Science of the Republic of Kazakhstan.

 

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ЖАБАЙЫ БОРАЙ БИДАЙДЫҢ (TRITICUM DICOCCOIDES) ГЕНЕТИКАЛЫҚ ТҮРЛІЛІГІН ТАЛДАУ ҮШІН РЕТРОТРАНСПОЗОНДЫ МАРКЕРЛЕРДІ ПАЙДАЛАНУ

Ұлттық биотехнология орталығы
Қорғалжын тас жолы, 13/5, Астана, 010000, Қазақстан
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ТҮЙІН

Егілетін барлық тетра және гексаплоидты бидайлардың жабайы ата-тегі жабайы борай бидайдың (Triticum dicoccoides) генетикалық түрлілігі үлкен. Бұл түрлілік эко-географиялық заңдылықтардың өзгеруі мен жергілікті орта жағдайларына бейімделу әсерінен болуы мүмкін. Бидайдың геномды ДНҚ құрамына кіретін өздігінен реплицирленетін ретротранспозондар, олардың транспозициялық қызметтерінде бейтарап вариация ретінде пайдаланылады деп жоспарлануда. Бұл мақалада біз IRAP және REMAP молекулярлы маркерлер негізінде жабайы борай бидайдың бір түрік және он төрт Израиль популяцияларының генетикалық түрлілігін қарастырдық. Анықталған генетикалық түрліліктің деңгейі, гендер мен басқа геномды компоненттерді бағалайтын маркерлі жүйелер жөнінде жүргізілген алдындағы зерттеулерге сәйкес келеді. Генетикалық алшақтық пен географиялық аралық арасында ара-қатынас болмады. Алайда, полиморфты локустардың пайызы популяцияның ендігі және генетикалық түрліліктің бойлылығымен корреляцияланады.

Негізгі сөздер: Triticum dicoccoides, жабайы борай бидай, IRAP, REMAP, генетикалық түрлілік.