ГЕНЕТИКА, 2010, том 46, № 11, с. 1500-1506
ГЕНЕТИКА РАСТЕНИЙ
УДК 575.17:633.11
ASSESSMENT OF GENETIC DIVERSITY AMONG SYRIAN DURUM (Triticum turgidum ssp. durum) AND BREAD WHEAT (Triticum aestivum L.)
USING SSR MARKERS
© 2010 S. Achtar1, M. Y. Moualla1, A. Kalhout2, M. S. Roder3, N. MirAli4
department of Field Crops, Faculty of Agriculture, Tishreen University, Latakia, Syria 2Agricultural Research Center of Aleppo, GCSAR, Aleppo, Syria 3Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany 4Department of Molecular Biology and Biotechnology, AECS, Damascus P.O. Box 6091, Syria;
e-mail: scientific@aec.org.sy Received October 28, 2009
Genetic diversity among 49 wheat varieties (37 durum and 12 bread wheat) was assayed using 32 microsatellites representing 34 loci covering almost the whole wheat genome. The polymorphic information content (PIC) across the tested loci ranged from 0 to 0.88 with average values of 0.57 and 0.65 for durum and bread wheat respectively. B genome had the highest mean number of alleles (10.91) followed by A genome (8.3) whereas D genome had the lowest number (4.73). The correlation between PIC and allele number was significant in all genome groups accounting for 0.87, 074 and 0.84 for A, B and D genomes respectively, and over all genomes, the correlation was higher in tetraploid (0.8) than in hexaploid wheat varieties (0.5). The cluster analysis discriminated all varieties and clearly divided the two ploidy levels into two separate clusters that reflect the differences in genetic diversity within each cluster. This study demonstrates that microsatellites markers have unique advantages compared to other molecular and biochemical fingerprinting techniques in revealing the genetic diversity in Syrian wheat varieties that is crucial for wheat improvement.
Wheat is one of the most important food crops in the world. Its cultivation history is more than 13000 years ago. The oldest evidence for both einkorn and emmer wheat found to date was at Abu Hureyra (Syria), in occupation layers [1].
The development of high-yielding and stable varieties requires a continuous supply of new germplasm as a source of desirable genes and or gene complexes [2]. The availability of such germplasm needs the identification of diversity area ofvarious agronomicaly important characters. In addition, information on the extent and patterns of distribution of genetic variation of a crop species is essential for effective utilization of germplasm in plant breeding programs [3]. Landraces and improved varieties are both very important components in all national breeding programs around the world. Landraces become a source of genes for several biotic, abiotic stresses and quality traits since they are considered as an early cultivated form of a crop species, evolved from a wild population.
Wheat genotyping or DNA-fingerprinting is a technology used to characterize and compare DNA sequences of different wheat genotypes. Many wheat scientists have studied genetic diversity in wheat using different molecular markers such as randomly amplified polymorphic DNA (RAPDs) [4], restriction fragment length polymorphism (RFLPs) [5], amplified fragment length polymorphism (AFLPs) [6], and inter-specific simple sequence repeats (ISSRs) [7].
However most of these marker systems show a low level of polymorphism in wheat. Among all other PCR based molecular markers, short sequence repeats (SSRs) referred to as microsatellites offer a number of advantages, such as the high level of polymorphism, locus specificity, co-dominance, reproducibility, ease to use through PCR and random distribution throughout the genome [8]. SSR markers have been confirmed as an efficient tool for estimating genetic variation in wheat [9-11].
The objectives of this study were to assess the genetic diversity among a set of tetraploid and hexaploid wheat varieties that contains recently released wheat varieties as well as old local and land races using microsatellites (SSR) as molecular markers.
MATERIALS AND METHODS
Plant material. A collection of 37 tetraploid and 12 hexaploid varieties containing recently released varieties as well as old local and wheat land races, was provided by the GCSAR genebank and used in this study (Table 1).
DNA extraction and PCR amplification. Total ge-nomic DNA was extracted from pooled leaves of 2-week-old seedlings grown in a growth room. The extraction was performed according to Dellaporta et al. [12]. PCR amplifications were performed as described by Roder et al. [8]. The PCR reaction contained 50-
100 ng template DNA, 2.5 |l of10 x PCR buffer (1 M Tris-HCl PH 8, 1 M KCl, 1 M MgCl2, dH2O ),1 U Taq DNA polymerase in a total volume of 25 |l. Fragments were detected by an Automated Laser Florescence (ALF express) sequencer (Amersham Biosciences). Fragement sizes were calculated using the computer program fragement analyzer 1.02 (Amer-sham Biosciences) by comparison with internal size standards [8].
Microsatellite markers (SSR). Thirty-two Gatersle-ben wheat microsatellite (gwm) markers for 32 loci representing at least one microsatellite marker from each chromosome ofA, B and D genomes were selected for the genotyping in this study (Table 2). Roder et al. [8] described all these microsatellites except for primer taglgap which was described by Devos et al.
[13]. To ensure the size accuracy and the uniformity between tetra and hexaploid in different gels, the tet-raploid variety 'Horani Adi' was chosen as a control in each hexaploid run and the hexaploid variety 'Kanda-hari Ahmar' was the control in each tetraploid run.
Data analysis. Polymorphic bands were scored as present (1) or absent (0). Genetic similarity was measured with SIMQUAL (Similarity for Qualitative Data) program to generate Dice similarity coefficients
[14]. These, were used to construct dendrograms using the Unweighted Pair Group Method with arithmetic averages (UPMGA), and the genetic similarity trees were obtained by clustering the similarity data with the SHAN-clustering program. Analyses were performed with NTSYS program [15]. Gene diversity was calculated according to the formula of Nei [16]: Gene diversity = [1 — ^Lpij ], where p^ is the frequency of the j th allele for the i th locus summed across all alleles for the locus. Gene diversity was occasionally reffered to as the polymorphic information content (PIC) [17].
To study the effect of breeding progress on genetic diversity at all studied loci we looked for the lost alleles from landraces and gained alleles in improved cultivars through breeding system.
RESULTS
Polymorphism of 32 SSR loci
Thirty-two microsatellite markers were used to characterize and estimate the genetic diversity of forty nine wheat genotypes. The total number of detected alleles was 255 with an average alleles number of 7.97 alleles per locus. The number of alleles per locus ranged form two for Xgwm 232 locus on D genome to 17 for Xgwm 46 locus on B genome. Noteworthy, locus Xgwm4 on A genome produced only one monomor-phic allele with size of 246 bp. In general, alleles size ranged from 74 bp at locus Xgwm3 on chromosome 3D to 265 bp at locus taglgap on chromosome 1B. The average PIC value reflecting the gene diversity of 34 microsatellite loci was 0.65. It ranged from 0 at locus xgwm4 to 0.876 at locus Xgwm 459 (Table 2). The
Table 1. Triticum durum and Triticum aestivum varieties used in this study with their codes
Species Variety name Code
T. turgidum ssp. du- Aeinzein Aei
rum (Desf.) Husn. Azghar1 Azg
(cultivars) Bouhouth.5 Bou.5
Bouhouth.7 Bou.7
Bouhouth.9 Bou.9
Bouhouth.11 Bou.11
Douma.1 Dou.1
Douma.20602 Dou. 0602
Douma.26823 Dou.26823
H-5948 H-5948
Jidara.21 Jid.21
Otorob Oto
Cham.1 Cha.1
Cham.3 Cha.3
Cham.5 Cha.5
Cham.7 Cha.7
Umbeit.1 Umb.1
I. T. turgidum ssp. du- Bayadi Bay
rum (Desf.) Husn. Baladye Hamra Bal.H
(landraces) Farouni A. Far.A
Hamari.Adi Ham.ad
Hamari.Ahmar Ham.ah
Hourani.A Hor.A
Hourani.Adi Hor.adi
Hourani.Ayubie Hor.Ayu
Hourani.B Hor.B
Hourani.C Hor.C
Hourani.Nawawi Hor.n
Hourani.Short Hor.s
Hourani.27 Hor.27
Koko Kok
Masrye.A Mas.A
Nabljamal Nab
Rzy Rzy
Sawadi Saw
Shihani Shi
Siklawi Sik
II. T. aestivum L. Bouhouth.4 Bou.4
(cultivars) Bouhouth.6 Bou.6
Douma.2 Dou.2
Sham.4 Sha.4
Sham.8 Sha.8
III. T. aestivum L. Baladye Hamra Bal.H
(landraces) Breiji Bre
Florence Auror Flo.Au
Kandahari Abyad Kan.Ab
Kandahari Ahmar Kan.Ah
Salamoni Sal
Sueid Sue
Table 2. Description of 32 wheat microsatellite, their chromosomal location, motif, fragment size in Chinese spring as well as size range of produced alleles
Microsatellite Chromosomal location Motif Size range of alleles, bp PIC No. of alleles
A genome
Xgwm 4 4A (CA)13(TA>26 246 0 1
Xgwm 95 2A (AC>!6 101-127 0.769 8
Xgwm 160 4A (GA)21 162-184 0.681 15
Xgwm 192 4A (CT>46 129-141 0.418 5
Xgwm 357 1A (GA>!8 109-127 0.681 10
Xgwm 459 6A (GA) > 28 115-167 0.876 13
Xgwm 614 2A (GA)23imp 131-159 0.612 7
Xgwm 631 7A (GT>23 190-200 0.261 4
Xgwm 698 7A (GA)44 153-207 0.738 10
Xgwm 720 3A (GA)33 126-202 0.803 10
Averages B genome 0.5839 8.3
Xgwm 18 1B (CA)nGA(TA)4 105-189 0.359 13
Xgwm 46 7B (GA)2GC(GA)33 129-179 0.692 17
Xgwm 67 5B (CA)i0 82-88 0.704 4
Xgwm 120 2B (CT)11(CA)18 120-166 0.669 12
Xgwm 408 5B (CA)22(TA)(CA)7(TA)9 145-193 0.799 11
Xgwm 513 4B (CA)!2 140-150 0.733 5
Xgwm 566 3B (CA)2!(GA)2(TA)8 120-136 0.748 7
Xgwm 577 7B (CA)!4(TA)6 Null, 121-207 0.849 17
Xgwm 619 2B (CT)19 135-179 0.833 14
Xgwm 680 6B (GT)7(GA)24imp 118-144 0.784 7
Xtaglgap 1B (CAA)3! Null, 213-265 0.751 12
Averages D genome 0.72 10.8
Xgwm 3 3D (CA)!8 74-82 0.625 3
Xgwm 111 7D (CT)32(GT)17 133-149 0.576 4
Xgwm 174 5D (CT)22 145-225 0.861 8
Xgwm 190 5D (CT)22 197-213 0.715 5
Xgwm 232 1D (GA)19 119-121 0.153 2
Xgwm 261 2D (CT)21 163-213 0.545 4
Xgwm 325 6D (CT)!6 135-149 0.744 5
Xgwm 337 1D (CT)5(CACT)6(CA)43 170-188
Для дальнейшего прочтения статьи необходимо приобрести полный текст. Статьи высылаются в формате PDF на указанную при оплате почту. Время доставки составляет менее 10 минут. Стоимость одной статьи — 150 рублей.