Crop Science Journal of Natural Resources and Life Sciences Education
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Published online 2 December 2005
Published in Crop Sci 46:162-167 (2006)
© 2005 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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PLANT GENETIC RESOURCES

Analysis of Genetic Diversity in Rough Bluegrass Determined by RAPD Markers

Shanmugam Rajasekar, Shui-hang Fei* and Nick E. Christians

Department of Horticulture, 257 Horticulture Hall, Iowa State University, Ames, IA 50011, USA

* Corresponding author (sfei{at}iastate.edu)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Information on genetic variation in rough bluegrass (Poa trivialis L.), a cool-season grass that is grown for sports fields and lawns, is needed. The objective of this study was to assess genetic variation in 27 accessions of rough bluegrass obtained from the National Plant Germplasm System (NPGS) by random amplified polymorphic DNA (RAPD) markers. Fifteen of the 80 primers screened generated 64 highly repeatable polymorphic bands. A dendrogram constructed on the basis of the Unweighted Pair Group Method with Arithmetic Average (UPGMA) clustering algorithm revealed that 26 of 27 accessions formed two distinct clusters. Genetic similarity coefficients calculated from the RAPD data ranged from 0.07 to 0.74 with the lowest value of 0.07 measured between PI 254908, PI 594396, PI 250982, and PI 229782 from Iraq, the USA, Yugoslavia, and Iran, respectively. The highest value of 0.74 was measured between PI 225826, PI 289643, and PI 592521 from Denmark, Spain, and the USA, respectively. The cophenetic correlation coefficient (r) was 0.90, indicative of a very good fit between the data matrix and the resulting cluster analysis. Principal coordinate analysis (PCO) clearly grouped 26 accessions on the two axes, with a single accession that did not cluster with the others. The PCO clustering pattern corresponded well with the dendrogram. PI 254908 from Iraq did not cluster with any other accessions, either in the dendrogram or on the basis of the PCO.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
THE GENUS POA includes three important turfgrass species, Kentucky bluegrass (Poa pratensis L.), rough bluegrass, and annual bluegrass (Poa annua L.). Rough bluegrass is a cool-season perennial grass, well adapted to moist and shaded areas. It is native to northern Europe, temperate Asia, and northern Africa and has been introduced to Australia and North and South America (Hubbard, 1954). Rough bluegrass has moderately fine textured, light green leaves and forms a medium-dense turf. It spreads by leafy stolons and can be found in soils with a pH range of 5 to 8 (Hurley, 2003). It is a diploid, cross-pollinated species with 14 chromosomes (Ahmed et al., 1972). It germinates rapidly with good seedling vigor and displays relatively good color retention among the cool-season turfgrasses (Grime, 1980; Hurley, 2003).

Rough bluegrass forms the highest-quality turf among all the cool-season turfgrasses when it was winter overseeded on dormant warm-season turfgrasses in the southern USA (Christians, 2004), with excellent low-temperature hardiness. Because it is stoloniferous, it can tolerate lower mowing heights than can Kentucky bluegrass (Christians, 2004). Rough bluegrass can provide an excellent putting surface on golf course greens during the winter season (Hurley, 2003). It is best used as a shade-lawn grass on moist soils. However, because of its poor heat, drought, and wear tolerance, rough bluegrass is not widely used in the turf industry.

Compared with other turfgrass species, breeding efforts in rough bluegrass is lacking and little is known about the genetic diversity of this grass. This information would be a valuable tool in support of the genetic improvement of this species. Genetic variation is the basis for breeding programs; therefore, it is important to identify genetically distinct plants for breeding purposes. Because morphological characteristics are often influenced by environmental factors, parental selection should be based on genetic information that is reliable and consistent. Molecular markers are now widely used to determine genetic diversity (Brummer et al., 1995), create genetic maps, conduct linkage analyses of quantitative and qualitative traits (Grattapagalia and Sederoff, 1994) and determine phylogenetic relationships (Perez de la Vega, 1993). The RAPD marker analysis (Williams et al., 1990), based on a polymerase chain reaction (PCR) with arbitrary primers, is not influenced by the environment and is used effectively for analyzing genetic diversity in various allogamous grasses, including buffalograss [Buchlöe dactyloides (Nutt.) Engelm.] (Huff et al., 1993), switchgrass (Panicum virgatum L.) (Gunter et al., 1996), and perennial ryegrass (Lolium perenne L.) (Sweeny and Danneberger, 1997).

Most cultivars of rough bluegrass were developed by using phenotypic recurrent-selection methods (Hurley, 2003). At present, there are no breeding efforts at the molecular level to improve this species. In this study, RAPD markers are used for the first time to study genetic variation in rough bluegrass to assess its genetic diversity. Our primary objective was to analyze the genetic relationships among 27 rough bluegrass accessions and cultivars by using RAPD markers and provide genetic information for breeding programs.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Accessions Examined and DNA Extraction
Seed samples were obtained from the NPGS collections conserved by the Western Regional Plant Introduction Station (WRPIS), USDA, Pullman, WA. Our analysis was performed on 14 wild accessions and four cultivars of P. trivialis, eight wild accessions of P. trivialis subsp. sylvicola (Guss.) H. Lindb., and one of P. trivialis var. glabra Doll. (Table 1). Bulked genomic DNA was extracted from young leaves of 16 individual plants for each accession by using the modified hexadecyltrimethyl ammonium bromide (CTAB) extraction procedure (Murray and Thompson, 1980). Fresh leaves were ground to fine powder in liquid nitrogen and transferred to a 2-mL tube containing 0.5 mL of pre-heated (65°C) 2x CTAB extraction buffer [100 mM Tris-HCl, pH 8.0, 1.4 M NaCl, 20 mM ethylenediaminetetraacetic acid (EDTA), 2% (w/v) CTAB]. A 0.5 mL of chloroform: isoamyl alcohol (24:1) was added in equal volume and inverted vigorously for 7 min followed by a 10 min centrifuge. Aqueous phase was transferred to a new tube containing 0.4 mL of ice cold isoproponal and inverted gently to form a clump. The clump was then transferred to a new tube containing 0.5 mL CTAB wash solution [76% (v/v) ethanol, 0.2 M sodium acetate, pH 5.2] and incubated on ice for 20 min. The supernatant was poured off and the pellet was washed again with the same CTAB wash solution followed by a centrifuge for 1 min. The supernatant was removed and the pellet was allowed to dry for 3–5 min before a 50 µL TE was added with 1 µL of 10 mg/mL RNase and was incubated at 37°C for 30 min. Fifty microliters of 7.5 M ammonium acetate and 0.25 mL 100% ethanol were added to the solution and inverted gently followed by a centrifuge at maximum (15 800 g) for 5 min. The supernatant was removed and the remaining pellet was washed with 0.25 mL 70% ethanol followed by a brief centrifuge for 1 min. The supernatant was removed and the pellet was dried for 10 min and dissolved in 50 µL TE. To characterize genetic variation within populations, DNA was extracted from 16 individual plants for each of five randomly selected accessions (PI 314174, PI 380993, PI 289643, PI 303062, and PI 422592). The quantity and quality of DNA were determined both by spectrophotometric analysis and gel electrophoresis.


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  		Table 1. List of Plant Introductions (PI) of rough bluegrass (P. trivialis) and their geographic origin.

 

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  		Table 2. Pair-wise genetic similarity matrix between 27 rough bluegrass accessions based on Jaccard's coefficients.

 
RAPD Analysis
The PCR was performed in a Flexigene thermal cycler (Techne Ltd., Cambridge, UK). Amplification reactions were performed on the basis of the protocol of Williams et al. (1990) with modifications. The PCR reaction mixtures contained 1 µL of 100 ng DNA template, 1 µL of 50 mM MgCl2, 2 µL of 2.5 mM dNTP, 1.0 unit Taq DNA polymerase (Invitrogen, Carlsbad, CA), 0.4 µL of a random primer (Operon Technologies, Alameda, CA), 2.5 µL of 10x PCR buffer (200 mM Tris-HCl, 500 mM KCl, pH 8.0), and 17.9 µL of distilled, deionized water, resulting in a 25-µL solution. Amplifications were performed as follows: one cycle of initial denaturation of 5 min at 94°C, followed by 45 cycles of 1 min at 94°C, 90 s at 37°C, and 1 min at 72°C, followed by a final extension of 7 min at 72°C, and stored at 4°C. The PCR fragments were separated on a 1.5% (w/v) agarose gel in Tris-Acetate-EDTA (TAE) buffer and stained with ethidium bromide. Agarose gels were photographed with UV light (UVItec Ltd., Cambridge, UK) and printed on thermal paper. A 100-bp DNA ladder was used as a molecular-weight size marker for each gel. All PCR reactions were repeated twice, and only bright, repeatable bands were scored. Eighty decamer oligonucleotide primers from Operon Technologies, Inc. (primer kits A, B, C, and D) were screened for polymorphisms against a subset of four randomly selected accessions. Fifteen primers were then selected for RAPD analysis on the basis of their high levels of polymorphism obtained from the subset samples and were used to analyze all 27 accessions of P. trivialis.

RAPD Data Analysis
Polymorphic bands were considered as binary characters and scored as ‘1’ for presence and ‘0’ for absence for each bulked sample. These scores were then entered as a binary matrix for analysis by the Numerical Taxonomy and Multivariate Analysis System, NTSYS v.2.11s (Exeter Software, Setauket, NY) program (Rohlf, 2000). The data were analyzed with the SIMQUAL option, on the basis of Jaccard's coefficients, to generate genetic similarity coefficients among all possible pairs and ordered in a similarity matrix (Jaccard, 1908). The similarity matrix was run on Sequential, Agglomerative, Hierarchical and Nested (SAHN) clustering, (Sneath and Sokal, 1973) by using the Unweighted Pair Group Method with Arithmetic average (UPGMA) clustering algorithm (Sokal and Michener, 1958) to generate a dendrogram. The MXCOMP subroutine was used to calculate a cophenetic correlation matrix between the similarity matrix and original matrix to measure goodness-of-fit.

Principal Coordinate Analysis (PCO) was conducted by using the DCENTER and EIGEN programs as described by Gower (1996) in the NTSYS. This multivariate approach was chosen to complement the cluster analysis information, because cluster analysis is more sensitive to closely related individuals, whereas PCO is more informative regarding distances among major groups (Hauser and Crovello, 1982).

AMOVA Analysis
Analysis of molecular variance (AMOVA) was calculated to clarify patterns of within-population variation for the 80 individual plants sampled from five accessions. Within-accession variation was analyzed by AMOVA with ARLEQUIN 2.000 software (Schneider et al., 2000). The total variance was partitioned into variance among accessions and variance among individuals within accessions.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
Genetic variation of some major turfgrass species, such as creeping bentgrass (Agrostis stolonifera L.) (Casler et al., 2003) and Kentucky bluegrass (Johnson et al., 2002), has been studied by using RAPD markers. In this study, we used RAPD markers to analyze the genetic variation among 27 accessions of rough bluegrass assembled from a wide range of geographical regions. Fifteen of the 80 primers screened were selected for DNA amplification reactions because they yielded many highly repeatable polymorphic bands in the subset samples. Out of 75 bands, 64 (85%) were polymorphic and were scored for analysis in a binary matrix. On average, we observed 4.3 polymorphic bands per primer, with the most (eight bands) obtained from primer A13 and the least (two bands) obtained from primers B4, C16, C8, and D11. None of the RAPD markers was specific to a particular geographical region.

Among-Accession Variation
The high level of polymorphism corresponded to a high degree of genetic variation among these rough bluegrass accessions. The Jaccard's similarity coefficients ranged from 0.07 to 0.74 (Table 2). Since we observed no similarity coefficients close to 1.0 between any two accessions, there were no likely redundant accessions among those sampled in our study. The highest similarity coefficient (0.74) was measured between accession PI 225826 from Denmark and accessions PI 289643 from Spain and PI 592521 from the USA. This relationship was supported by results from the cluster analysis, where these three accessions were members of subgroup 1 of cluster 2 (Fig. 1 ). RAPD analysis suggested that a high rate of gene flow, germplasm exchange, and natural selection pressures could have resulted in high genetic similarity values. Accession PI 592521 from the USA is a cultivar named ‘Proam’ developed from a base population imported from Europe (Hurley, 2003). From the analysis of Jaccard's similarity coefficients, accession PI 594396 from the USA and accession PI 254908 from Iraq have the lowest similarity coefficient (0.07). PI 594396 is an American cultivar, Sabre, which was developed from 10 clones selected from golf course putting greens and fairways, close-cut lawns, and tennis courts located in the northeastern USA by three cycles of phenotypic recurrent selection (Dickson et al., 1980). This selection regimen was designed to increase the frequencies of alleles controlling winter hardiness, rapid germination, and good seedling vigor under environmental conditions quite different than those present in Iraq. This same low value for the lowest genetic similarity coefficient was measured between PI 254908 and accessions PI 250982 from Yugoslavia and PI 229782 from Iran. The accession PI 229782 from Iran belongs to the subspecies sylvicola and this contributes to the low genetic similarity between this accession and the accession PI 254908 from Iraq. The lowest genetic similarity between PI 254908 and PI 250982 may be due to a lack of genetic exchange and/or the highly different environmental conditions existing among these countries.



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  		Fig. 1. Unweighted Pair Group Method with Arithmetic Average (UPGMA) dendrogram of 27 accessions of rough bluegrass based on the RAPD data. The dendrogram was constructed from the Jaccard's similarity coefficients matrix (Table 2).

 
Morphologically, accession PI 254908 from Iraq has light green, dull leaves that curled at their tips and whitish-green stems. Accessions PI 250982, PI 229782, and PI 594396 all have dark green color, shiny leaves with straight tips and purple stems. Therefore, the morphological characteristics of accession PI 254908 were also distinct from these three accessions.

A dendrogram (Fig. 2 ) was constructed by using UPGMA cluster analysis on the basis of Jaccard's coefficients with one possible tie found between the closest pair. The dendrogram divided 26 out of 27 accessions into two clusters, excepting one accession, which did not group with the others. The second cluster was divided into three subgroups and two accessions: PI 283962 and PI 380993. The first subgroup consists of eight accessions: PI 220615, PI 229719, PI 225826, PI 592521, PI 251167, PI 289643, PI 250982, and PI 380992. The second subgroup consists of 11 accessions: PI 221908, PI 251407, PI 221951, PI 229775, PI 221915, PI 227462, PI 314174, PI 229782, PI 227672, PI 204484, and PI 227858. The third subgroup consists of two accessions: PI 303062 and PI 594396.



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  		Fig. 2. Plot of first two principal coordinate axes for 27 rough bluegrass accessions revealed by using the Jaccard's similarity coefficients based on the RAPD data (See Table 1 for accessions and cultivars identification). Two main clusters and one outliner are shown.

 
A cophenetic-value (ultrametric) matrix was generated from the coefficients of SAHN's cluster analysis of the similarity matrix. The cophenetic correlation coefficient between the cophenetic matrix and the data matrix for RAPD data was 0.90. Such a high value is considered a very good fit (Romesburg, 1990) and shows that the original matrix was well represented by our cluster analysis.

To affirm the genetic relationships among 27 rough bluegrass accessions revealed by cluster analysis, PCO (Fig. 2) was generated from the DCENTER and EIGEN with the program NTSYS. PCO clearly separated the 26 accessions, but the remaining one accession, PI 254908 from Iraq, did not group with any other accession. These results corresponded well with the cluster analysis obtained through UPGMA and confirmed the distinctness of accession PI 254908.

Of the two clusters displayed in Fig. 1, subgroup 2 of cluster 2 includes accessions whose geographic origins were closely related to the clustering pattern. For example, accession PI 229775 from Iran clustered with PI 221915 from Afghanistan, with a high similarity coefficient (0.73). Similarly, accessions PI 227672 from Iran and PI 204484 from Turkey were collected from nearby regions.

From dendrogram subgroup 3 of cluster 2, with accession PI 303062 from Denmark, also included PI 594396 from the USA, is consistent with the results from PCO where these two accessions are close to each other. The accession PI 303062 is the cultivar Ino daelmfeldts that has been imported into the USA from Europe (Hurley, 2003). As noted earlier, the parents of accession PI 594396 (cv. Sabre) were selected from golf courses, lawns, and tennis fields that had been seeded with grasses from Europe. Our results suggest that the accession PI 594396 might have some common origin with the accession PI 303062 from Denmark.

The eight accessions of subspecies sylvicola received from the NPGS, which supposedly shared certain morphological traits, were collected from different parts of the world. Contrary to expectations, these eight accessions did not form a single cluster. Their pair-wise similarity coefficients ranged from 0.32 to 0.69, similar to the diverse range of values exhibited among all 27 accessions. Because these accessions did not form a single cluster and displayed a wide range of variation, either this subspecies exhibits a high degree of variability, or possibly some of these accessions have been incorrectly identified.

Within-Accession Variation
Results from AMOVA (Table 3) indicated that the within-accession variation accounted for 87.24% of the total genetic variation and between-accession variation accounted for the remaining 12.76%. These results were not surprising because P. trivialis is an allogamous species. Allogamous species generally have substantial within-accession variation [88% for crested wheatgrass complex (Agropyron spp. Gaertn) (Mellish et al., 2002)], while autogamous species have relatively lower percentages of within-accession variation (43% for Hordeum spontaneum K. Koch) (Dawson et al., 1993). The level of variation observed in our study is consistent with several other analyses of allogamous species, including buffalograss (Peakall et al., 1995; Huff et al., 1993), smooth (Bromus inermis L.) and meadow bromegrass (Bromus riparius R.) (Ferdinandez et al., 2001), and perennial ryegrass (Huff, 1997).


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  		Table 3. Analysis of Molecular Variance (AMOVA) calculated from five different accessions, each represented by 16 individuals, based on 56 RAPD markers.

 
To our knowledge, this is the first molecular analysis of patterns of genetic variation in rough bluegrass. This paper reveals important information about genetic diversity of rough bluegrass accessions and cultivars assembled from various parts of the world. Our data suggest that RAPD markers are suitable for assessing genetic diversity within and among accessions of rough bluegrass germplasm. Information on genetic relationships revealed through this study should be useful for selection of parents for breeding or genetic studies. Future studies that include more accessions and varieties with even broader geographical background and that compare genetic relationships with morphological characteristics can help develop a greater understanding of this underexploited species.


   ACKNOWLEDGMENTS
 
The authors wish to thank Dr. Mark Widrlechner for his useful suggestions to improve this manuscript and Dr. R.C. Johnson of the USDA-ARS WRPIS, Pullman, WA, for providing seeds for this research. We also wish to thank Yanwen Xiong and Dr. Jyothi Rajagopalan for their technical assistance.

Received for publication April 15, 2005.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 





This Article
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Right arrow Articles by Rajasekar, S.
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Right arrow Cell Biology & Molecular Genetics
Right arrow Plant Genetic Resources

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