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Research Article
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Genetic Diversity of Persian Wheat (Triticum turgidum ssp. carthlicum) Accessions by EST-SSR Markers
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Ping-ping Zhuang,
Qin-ce Ren,
Wei Li
and
Guo-Yue Chen
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ABSTRACT
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To estimate the allelic variation at the expressed sequence tag simple sequence repeats (EST-SSR) among Persian wheat (Triticum turgidum ssp. carthlicum L.) accessions collected from fifteen countries and provide information for wheat breeding and improvement in southwest China, 87 Persian wheat accessions from fifteen countries were investigated by using EST-SSR markers. EST-SSRs were molecular markers belonging to the transcribed region of the genome. Therefore, any polymorphism detected by EST-SSRs might reflect better relationship among species or varieties. Fourteen primer pairs could successfully amplify the fragments in the 87 accessions, of which tri-nucleotide repeats were the dominant type. A total of 33 eSSR alleles were detected, and the number of alleles detected by single pair primers ranged from 3 to 7 per locus, with an average of 3.71. Clustering analysis suggested that most of the accessions with adjacent geographic origins had the tendency to cluster together. Therefore, when used in Persian wheat genetic analysis, EST-SSR markers not only act as genetic markers but also reveal differences in related gene expression. |
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| Received:
October 11, 2010; Accepted: December 17, 2010;
Published: February 07, 2011 |
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INTRODUCTION
Since great number of alleles was lost through breeding and selection, more
difficulties in wheat improvement have emerged for the modern agriculture system
(Allard, 1996; Hoisington et al.,
1999). The narrow genetic basis weakens the resistance of current wheat
cultivars facing adverse factors and threatened further improvement for wheat
(Wang et al., 2007). It is essential and urgent
to exploit genetic resources from relatives of wheat with the richness of desirable
genes.
Triticum turgidum ssp. carthlicum L. (AABB, 2n = 4x = 28), with
the common name of Persian wheat, was early-maturing wheat with spring habit.
And it is an important crop for human consumption. It is mainly grown in the
Former Soviet Union Transcaucasia, Russian Federation Dagest, Georgia and northeast
Turkey (Dong and Dian-Sheng, 1998). It has many beneficial
traits, such as good resistance to powdery mildew dustbrand and stem rust, higher
number of tillers and fertility, good fecundity, tolerance to low temperature
and preharvest sprouting (Belay et al., 1994;
Raut et al., 1984; Gol-denberg,
1984). With many beneficial traits and easiness of gene transferring to
common wheat, T. carthlicum has been suggested as one of the most
desirable donors for bread wheat improvement (Anamthawat
Jonsson, 1996; Merker and Lantai, 1997; Pandey
and Rao,1987; De Moraes et al., 2000; Balatero
and Darvey, 1993; De Pienaar and Sears, 1973). The
genetic relationship between Persian wheat genotypes has been extensively studied
based on morphology, agronomic traits, as well as enzymatic and molecular markers
(Zhuang et al., 2005).
Microsatellites, also described as simple sequence repeats (SSRs), are tandem
repeated sequences comprised of mono-, di-, tri-, tetra-, penta-, or hexa-nucleotide
units (Chambers and Macavoy, 2000; Ellegren,
2004) and ubiquitous in prokaryotes and eukaryotes (Powell
et al., 1996). EST-SSRs (expressed sequence tag simple sequence repeats)
belong to the transcribed region of the genome and might be relatively well
conserved. Therefore, any polymorphism detected by EST-SSRs might reflect better
relationship between species or varieties. Evaluation of the germplasm with
SSRs derived from ESTs might enhance the role of genetic markers by assaying
variations in transcribed and known-function genes (Eujayl
et al., 2002). The controversy about the current status of the germplasm
pool and the influence of breeding programs has not been solved for many years
(Maccaferri et al., 2003). Collection of germplasm
is a continuous process requiring accurate monitoring of the status of the elite
gene pool. For effective conservation and use of genetic resource, the evaluation
of genetic variation within collections is crucial and could be dramatically
enhanced by using molecular genotyping tools (Eujayl et
al., 2002).
The aim of this study was to estimate the allelic variations at the expressed sequences among Persian wheat accessions collected from fifteen countries based on EST-SSR markers and provide information for wheat breeding and improvement in Southwest China. MATERIALS AND METHODS Materials: The materials were kindly provided by Dr. Bockelaman (American National Plant Germplasm System) and the germplasm lab of the Triticeae Research Institute, Sichuan Agricultural University. A total of 87 Persian wheat accessions were collected from 15 countries (Table 1). The materials spanned most of the ecological range of Persian wheat in the world were selected to evaluate genetic diversity based on the adaptability for the environment in southwest China.
Methods
Genomic DNA extraction: Genomic DNA was extracted from bulk sampling
of a minimum of ten individual plants for all accessions, following the procedure
described by Sharp et al. (1988). Primers (Table
2) derived from bread and durum wheat EST sequences, were retrieved from
the Triticeae EST-SSR coordination project published by Peng
and Lapitan (2005), Eujayl et al. (2002),
Nicot et al. (2004), Chen
et al. (2005) and Yang et al. (2005).
PCR reaction: PCR (Polymerase Chain Reaction) reactions contained 10 mM Tris-HCl (pH 8.3), 50 mM KCl, 1.5 mM MgCl2, 0.2 mM dNTPs, 0.25 μM primer and 25 ng template DNA in a reaction volume of 25 μL. The amplification program consisted of the following cycles: 94°C for 4 min.
| Table 1: |
Materials detected in this research |
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40 cycles of 94°C for 1 min, 55 to 63°C (depending on the primer sets)
for 1 min and 72°C for 1 min and a final extension at 72°C for 10 min.
Amplification products were separated by electrophoresis in 6% polyacrylamide
gel and silver stained (Tixier et al., 1997).
Genetic diversity and clustering analysis: Bands were scored as 1 for
present and 0 for absent. Population genetic analysis was carried out using
POPGENE version 1.31 (Yeh and Boyle, 1997), based on
the model for codominant markers with diploid individuals. The raw data matrix
was subjected to the calculation of the genetic similarity coefficient (GS)
between accessions: GS = 2Nij/(Ni+Nj), where Nij is the number of alleles in
common between accessions i and j and Ni and Nj are the total numbers of alleles
observed for accessions i and j, respectively. The dendrogram was constructed
based on the genetic similarity coefficient using the UPGMA (unweighted pair
group with arithmetic average) method with the computer software NTSYS-pc (Rohlf,
1990).
RESULTS EST-SSR polymorphisms: Genetic variations in the 87 Persian wheat accessions were detected by 14 EST-SSR primers on all seven wheat homologous chromosome groups (Table 2). The 14 EST-SSR loci consisted of 4 SSR types, 1 di-, 8 tri-, 1 tetra-, and 2 penta-nucleotide repeats (the remaining 2 types were not reported). A total of 33 EST-SSR alleles were detected and the number of alleles detected on a single locus ranged from 3 (BE473227, SWES178, SWES19, SWES209, BE424205, SWES3 and GPW7055) to 7 (CAU12), with an average of 3.71. The average PIC value of each locus was 0.483, with the highest of 0.714 for SWES86 and the lowest of 0.150 for BE424205 and SWES19. Genetic distance: The genetic distances (GD=1-GS) were calculated for paired comparisons of all 87 accessions. Higher genetic variations in the 87 Persian wheat accessions were observed.
| Table 2: |
Chromosome locations, number of alleles, repeat motif and
PIC values of EST-SSR markers |
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The value of GD varied from 0.059 to 0.800, with the mean of 0.398. The genetic distance between accessions PI532484 (from Turkey) and PI286070 (from Poland) was the highest (GD = 0.800), whereas accessions PI94750 and PI352278 (both from Georgia) was the lowest (GD = 0.059). From all the GD data, it was found that there was usually lower genetic distance among the accessions located close regions, vice versa. Clustering analysis: To visualize genetic relationships between the 87 Persian wheat accessions, a dendrogram was constructed (Fig. 1). Each genotype had a unique banding profile and all genotypes were clustered to four major groups at the average GS value of 0.602. Group I included 4 genotypes from Turkey, 3 genotypes from Former Soviet and 1 genotype from Iraq; Group II included 3 genotypes all from Turkey. Group III consisted of 38 genotypes from 8 countries, they are all genotypes from United States, most of the genotypes from Turkey and others were from Russian, Armenia, Former Soviet, Canada, China and Albania. Group IV possessed the remaining 38 genotypes, including all the genotypes from Iran, Georgia, Poland, England and Hungry, besides, the other genotypes were from Albania, Canada, Russian and Turkey. According to the dendrogram, it was noteworthy that the accessions from Iran, Georgia, Poland, England, United States and most accessions from Turkey were clustered together, respectively. It was suggested that most of the accessions with adjacent geographic origins had the tendency to cluster together. DISCUSSION
Microsatellite markers are becoming the markers of choice due to the level
of polymorphism as well as higher reliability (Plaschke et
al., 1995; Fu et al., 2005). In this
study, we detected relatively higher plymorphism in Persian wheat accessions
compared with that in durum wheat (Wang et al., 2007).
The PIC value of markers indicates the usefulness of DNA markers for gene mapping,
molecular breeding and germplasm evaluation(Peng and Lapitan,
2005). The average PIC value of each locus was 0.483 in Persian wheat and
0.459 in durum wheat, with the highest of 0.714 and the lowest of 0.150 in the
former while with the highest of 0.838 and the lowest of 0 in the latter, respectively.
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| Fig. 1: |
Geographic distributions of the tested accessions of Persian
wheat |
It might be the reason that Persian wheat collected in this study was from
more extensive range of Geographic origin than that in Wang
et al. (2007). Another reason could be that different markers were
used in the two experiments.
In the previous research, high variations of storage protein and agronomic
traits were observed in the Persian wheat accessions (Zhuang
et al., 2007). In this study, high EST-SSR polymorphism were detected
among 87 Persian wheat. While the EST-SSR, derived from the coding region could
more directly and effectively reflect the genetic information and evaluate the
genetic diversity. Different genetic markers only can interprete different genetic
information of the Persian wheat. Therefore, we should combine all the research
to make better use of Persian wheat.
It was found that the estimate of genetic distance was geographically independent
when studying the relationship of the allozyme genetic distance and geographic
distance in wild emmer wheat populations (Fahima et al.,
1999, 2002). It was also proved that the genetic
differentiation between populations was independent of geographical distances
between the sites of collection by Mantel test (r = 0.104, p = 0.809) (Mantel,
1967). While, some studies showed that genetic distance had no significant
correlation with geographic distance in different dicoccoides wheat populations
(Nevo et al., 1982) and the Ethiopian tetraploid
wheat (Yifru et al., 2006). Even though, in this
study, we also found that some accessions located far from each other, had higher
genetic distance, and vise versa. For example, the accession PI532484 (from
Turkey, 39°55'45", N, 32°51'12", E) and PI286070 (from Poland, 52°14'42",
N, 21°00'43", E) was the farest from each other with the GD of 0.800, but
the accessions PI94750 and PI352278 (both of them from Georgia) with the GD
of 0.059.
CONCLUSION This research could provide some good information for persia wheat conservation and utilization. Meanwhile, EST-SSR, derived from the coding region, could more directly reflect influences imposed by breeding efforts on the elite germplasm. Therefore, more attention should be focused on the establishment of a genotype database using convenient and effective indicators such as EST-SSR, and hence monitoring the dynamic change in the gene pools and as a reference forgermplasm management and breeding strategies. ACKNOWLEDGMENTS This study was supported by the National High Technology Research and Development Program of China (863 program 2006AA10Z179 and 2006AA10Z1F8), the Key Technologies R and D Program of China (2006BAD01A02-23 and 2006BAD13B02).
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