Crop Science Journal of Natural Resources and Life Sciences Education
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Published online 26 August 2005
Published in Crop Sci 45:2081-2086 (2005)
© 2005 Crop Science Society of America
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GENOMICS, MOLECULAR GENETICS & BIOTECHNOLOGY

Genetic Diversity within and among Nordic Meadow Fescue (Festuca pratensis Huds.) Cultivars Determined on the Basis of AFLP Markers

Siri Fjellheima,b and Odd-Arne Rognlib,*

a Dep. of Chemistry, Biotechnology and Food Science, Norwegian Univ. of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway
b Dep. of Plant and Environmental Sciences, Norwegian Univ. of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway

* Corresponding author (odd-arne.rognli{at}umb.no)


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Twelve Nordic cultivars and one Icelandic natural population of meadow fescue (Festuca pratensis Huds.) were assessed by AFLP (amplified fragment length polymorphism) marker technology to determine levels of genetic diversity within and genetic relationships between populations. Three cultivars were analyzed from each of the Nordic countries (Norway, Finland, Sweden, and Denmark), including germplasm of long, medium, and short antiquity. A total of 253 plants were analyzed by 89 AFLP markers. A substantial degree of genetic heterogeneity was uncovered, and all individuals were genetically distinct from one another. AMOVA revealed that most of the variation is distributed within rather than between cultivars. The genetic diversity within newly released cultivars was as large as within old cultivars, indicating that breeding has not eroded genetic diversity over time. PCO- and UPGMA-analyses revealed no clear structure on the basis of country of origin of the cultivars. This can probably be explained by the fact that an extensive exchange of breeding material between the Nordic countries has occurred since the genetic improvement of meadow fescue started at the beginning of the 20th century. These exchanges of breeding materials have counteracted genetic erosion and genetic differentiation between countries. The applicability of AFLP markers in cultivar identification in meadow fescue is discussed.


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
IN THE NORDIC COUNTRIES, grassland husbandry has always played an important role in agriculture because of the harsh climatic conditions, especially in the higher latitudes in which grassland agriculture is predominant. One of the major grassland species is meadow fescue (Festuca pratensis Huds.). In contrast to the rest of Europe, this species provides one of the most important constituents of Norwegian and Nordic leys because of its superior combination of winter-hardiness and forage quality. The species is distributed both in new and old meadows and as feral populations in all parts of this region, although less frequently in northern parts of Norway, Sweden, and Finland. Only a single population is known to be present in Iceland. Meadow fescue is, however, not indigenous to the Nordic area but was probably introduced as a forage grass in sown meadows (Elven, 1994). By the middle of the 18th century, its value was appreciated, when Linnaeus suggested breeding for improvement (Julén and Halling, 1953). In spite of this, meadow fescue was not being systematically used in meadows until the second half of the 19th century. Until the beginning of the 20th century, seed was either imported (mainly from North America) or raised locally (Newman, 1912). Imported seed material during the 19th century was of unknown quality and often was associated with low germination capacity and species admixture (Hasund, 1926). This called for a systematic improvement of forage crops adapted to Nordic conditions, which led to the initiation of meadow fescue breeding at the beginning of the 20th century (Newman, 1912; Linhard, 1926; Kivi, 1965; Wexelsen, 1965).

Meadow fescue is a diploid (2n = 2x = 14) outbreeder with a gametophytic self-incompatibility system controlled by two genes designated S and Z (Lundqvist, 1962). As a consequence, large genetic heterogeneity is expected to persist within populations. Estimates of inter- and intracultivar genetic diversity provide knowledge for plant breeders that can be used for the future development of commercial varieties, as shown by Tsegaye et al. (1996). Kölliker et al. (1999) demonstrated in a study of F. pratensis, Lolium perenne L., and Dactylis glomerata L. that genetic variability may have consequences for adaptability and persistency of individual cultivars. Good genetic and phenotypic characterization of cultivars may give farmers the option to choose cultivars that are well adapted to specific environments or for special needs. Knowledge of the genetic variation present in cultivars from different time periods would also be of great interest, given the indications that progressive erosion of the genetic base of commercial varieties has occurred as a result of the common practice of selective breeding from previously successful varieties (see e.g., Vellvé, 1993; Jung et al., 1996). Monitoring spatial and temporal changes in genetic diversity is important to prevent loss of genetic diversity and to secure the genetic basis for future development of new cultivars.

AFLP is a molecular marker technique that generates a large number of markers that are reliable, reproducible, and requires only nanograms of DNA (Vos et al., 1995). Several studies have described AFLP as a promising technique for cultivar identification (Schut et al., 1997; Cervera et al., 1998; Lombard et al., 2000; Forster et al., 2001; Kölliker et al., 2001). Guthridge et al. (2001) analyzed genetic variation within and between perennial ryegrass (Lolium perenne L.) populations using AFLPs and interpreted the observed relationships in terms of breeding history of cultivars. They showed that such an approach could effectively discriminate close-bred, restricted-base cultivars and also partially discriminate more variable ryegrass populations. Knowledge of genetic variation and the ability to discriminate between populations and cultivars is important both to be able to select the appropriate parent clones for varietal development and for identification of varieties and seed certification.

The aim of this investigation was to estimate genetic diversity within and between a collection of Nordic cultivars of meadow fescue by AFLP molecular marker technology. This has been used to assess whether breeding has resulted in any genetic differentiation of the cultivars from the Nordic countries and whether genetic diversity within cultivars has changed over time.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Plant Materials
Twelve registered cultivars were analyzed, three from each of the countries Norway, Finland, Sweden, and Denmark (Table 1). The cultivars were selected to represent both long established and newly released cultivars from each country. The oldest cultivar included is the Swedish cultivar Svalöfs Sena from 1917, and the most recently released cultivar is the Norwegian cultivar Norild from 2001. From Iceland, only one population of meadow fescue is known. This population has not been deliberately bred but has been propagated from seed and may consequently be regarded as a natural or ecotypic population. All these populations will be referred to as cultivars. In total, we analyzed 253 individuals, with the number of individuals analyzed from each population varying from 17 to 20.


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  		Table 1. Data on the origins of the cultivars analyzed in this study. Accession number is from the Nordic Gene Bank (NGB).

 
AFLP Analyses
DNA extraction followed the protocol of Sharp et al. (1988). Whole seeds were ground in a 1.5-L microtube with liquid nitrogen and sand. Primer combinations for AFLP analysis were chosen on the basis of a combined RFLP and AFLP linkage map of meadow fescue developed by Alm et al. (2003). Three primer combinations (P77M72, P77M66, and P64M17), which produce markers distributed throughout the linkage groups of meadow fescue, were chosen. Primer sequences were as listed in Alm et al. (2003). AFLP analyses were conducted according to the method of Becker et al. (1995), except for selective amplification that used the primer combinations P77M66 and P64M17 according to Vos et al. (1995).

Samples were separated by electrophoresis on a 6% (w/v) polyacrylamide gel. For primer combination P77M72, bands were visualized by silver staining following the method of Bassam et al. (1991). For the primer combinations P77M66 and P64M17, bands were visualized by exposing X-ray (Eastman Kodak Company, Rochester, NY) film to dried polyacrylamide gel for 1 to 5 d.

The bands were scored conservatively by manual inspection as absent or present.

Statistical and Multivariate Analysis
Two genetic diversity indices were calculated by the program Arlequin 2.0 (Schneider et al., 2000; http://anthro.unige.ch/arlequin; verified 19 May 2005). The indices were average difference between all genotypes in the population (Tajima, 1983, 1993) and average gene diversity over loci (Tajima, 1983; Nei, 1987). The differences in diversity indices between old (Løken, Paavo, Tammisto, Svalöfs Sena), medium-aged (Boris, Bottnia II, Pajbjerg, Leto Dæhnfeldt III), and new cultivars (Fure, Kalevi, Norild, Balder) were tested by the Duncan Multiple Range Test of PROC GLM of SAS (SAS, 2001). Three separate AMOVAs (Analyses of Molecular Variance; Excoffier et al., 1992) were performed by the Arlequin 2.0 program. In the first AMOVA, variation within and among all cultivars was estimated. In the second, cultivars were grouped according to country of origin. In the third, three groups were established on the basis of year of release of the cultivars. In the two latter analyses, the Icelandic population Petursey was excluded. Unweighted Pair Group Method with Arithmetic mean (UPGMA)-clustering of all 253 individuals was performed using four different similarity or distance coefficients (Dice, Simple matching, Jaccard, and Euclidean distance). The coefficients provided similar results, and we only present the results of the analyses based on Dice similarity, given by 2a/(2a + b + c), where a is the number of shared bands and b and c are the number of bands present in one sample but absent in the other sample. A matrix of corrected average pairwise differences between all pairs of populations (calculated in Arlequin 2.0) was used for UPGMA-clustering and Principal Coordinates analysis (PCO). A Minimum Spanning Tree (MST) was superimposed on the PCO plots of the cultivars. These analyses were performed by NTSYS-pc Version 2.1 (Rohlf, 2000).


   RESULTS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The three primer combinations produced 107 scorable markers with less than 5% missing data. Of these, 18 (16.8%) were monomorphic and were excluded from the analyses.

Genetic Diversity Indices
No individuals were genetically identical on the basis of AFLP fingerprint. Estimates of the two diversity indices (average difference between all genotypes in a population and average gene diversity over loci) are presented in Table 2. The cultivar Bottnia II showed both the highest average pairwise differences and the highest gene diversity over loci (18.70 and 0.215, respectively), whereas Norild showed the lowest values (11.41 and 0.125, respectively). No significant differences were found between different age classes.


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  		Table 2. Genetic diversity indices in 13 Nordic cultivars of F. pratensis based on 89 polymorphic AFLP markers. The indices are mean number of pairwise differences between individuals in populations (average difference) and average gene diversity over loci (gene difference).

 
Diversity Analysis
AMOVA-analysis of the complete dataset revealed that 20.7% of the variation was attributable to between populations (79.3% to within); just 1.0% was attributable to between countries of origin (18.8% among cultivars within country, and 80.2% within cultivars). No variation was found between groups of cultivars of different age, whereas 19.6% of the variation was found among cultivars (80.4% within cultivars) (Table 3). A PCO analysis was performed using corrected average pairwise differences between populations as a distance matrix (Fig. 1). In this analysis, the three first axes explained 91.3% of the variation. The first two axes (49.6% and 27.3%) separated the Danish cultivars, and Leto Dæhnfeldt III was very distinct. The Swedish and Finnish cultivars seem to constitute a single mixed group. The Norwegian cultivar Fure clustered with the Swedish and Finnish cultivars on the first and second axis, but separated from these on the third axis. Norild, Løken, and Petursey were clearly separated from all other cultivars. A MST superimposed on the plot shows that the Danish cultivars constitute a separate group, whereas the Swedish and Finnish cultivars were intermixed. The Swedish cultivar Svalöfs Sena was an exception, as it is most closely allied to the Danish cultivar Balder. The Norwegian cultivars appear to be a heterogeneous group, with Norild most closely connected to the Swedish cultivar Bottnia II and Løken and Fure closest to the Swedish cultivar Boris.


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  		Table 3. Analyses of molecular variance (AMOVA) based on 89 polymorphic AFLP markers scored in 253 genotypes of Nordic F. pratensis cultivars.

 


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  		Fig. 1. Principal coordinates analysis (PCO) of 13 Nordic F. pratensis cultivars based on 89 polymorphic AFLP markers. Analysis is based on corrected average pairwise differences. A minimum spanning tree (MST) is superimposed on the plot.

 
In the UPGMA-analysis, Norild, Petursey, Leto Dæhnfeldt III, and Løken were separate entries, while the remaining cultivars could be separated into two clusters, one containing Fure, Kalevi, Bottnia II, Boris, and Tammisto, the other containing Pajbjerg, Balder, Paavo, and Svalöfs Sena (Fig. 2). The highest level of division (Norild from the rest of the cultivars) was 6.59, whereas the two closest cultivars (Bottnia II and Boris) clustered at 1.12. The analysis applied to the 253 individuals showed that no cultivar was defined as a single cluster (data not shown).



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  		Fig. 2. Unweighted pair group method with arithmetic mean (UPGMA)-clustering of 13 Nordic F. pratensis cultivars based on 89 polymorphic AFLP markers. Analysis is based on corrected average pairwise differences.

 

   DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
This study demonstrates that substantial genetic heterogeneity exists both within and between Nordic meadow fescue cultivars, reflecting the outbreeding habit of this species. As much as 79.3% of the variation is distributed within the populations, comparable with the values obtained from similar studies of other outbreeding grass species (Guthridge et al., 2001; Ubi et al., 2003). Older, long-established cultivars are commonly based on natural populations, whereas newer cultivars are bred from a restricted number of clones, or earlier released cultivars. On the basis of this, there seems to be a general assumption that modern breeding methods will reduce genetic diversity (Vellvé, 1993; Clunies-Ross, 1995). In addition, newer cultivars have been subjected to a more intensive selection pressure, which could have contributed to lower genetic variability. However, this interpretation has not always been substantiated in practice, as shown by studies of flax (Linum usitatissimum L., Fu et al., 2003), and both British and Argentinean wheat (Triticum aestivum L.) varieties (Donini et al., 2000; Manifesto et al., 2001). Except for the Norwegian cultivars of meadow fescue, the genetic diversity indices calculated in the present study did not indicate any loss of genetic diversity in more recently released cultivars compared with older ones (Table 2). This lack of age-linked diversity levels might be explained by at least two processes. First, it could reflect the breeding methods used in forage grass breeding. The first cultivars produced in the early 1900s were based on seed multiplication of local populations, whereas newer cultivars are synthetic populations based on the selection of a restricted number of superior genotypes (10–20) from a large (2000–5000) and diverse breeding population, following some form of progeny testing (polycrosses, topcrosses, or paircrosses, Forster et al., 2001). With careful selection of parent clones, this can produce cultivars with a relatively wide genetic base and lead to genetic heterogeneity both within and among cultivars. Second, it seems that much of the breeding in the Nordic countries has been based on introduced material. There has been a substantial flow of seed among the Nordic countries, especially from Sweden to Finland, and from Denmark to Norway, because until recent times, both Finland and Norway experienced problems with the production of commercial seeds of domestic cultivars (Wexelsen, 1948; Kivi, 1965; Hillestad, 1990). In Sweden, meadow fescue was first used in the south, under the strong influence of agricultural practices that originated in Denmark, where widespread adoption of meadow fescue cultivation occurred earlier (Linhard, 1926). At the start of meadow fescue breeding in Sweden, the bulk of material was obtained from Denmark, although seed was also imported from North America, Germany, France, and Chile (Newman, 1912; Sjödin, 1986). Seeds of introduced cultivars could have given rise to naturalized (feral) populations that may have in turn become the basis for development of new cultivars. In this way, new genetic material has been introduced over the years and could have increased or sustained the level of diversity in the newer cultivars.

An exception from the general picture is the Norwegian cultivar Norild. This is the most recently released cultivar but shows the lowest genetic diversity of all cultivars analyzed, indicating the effect of a different method of cultivar development or a different outcome from standard breeding methods compared with other newly released cultivars. Norild is a synthetic cultivar based on only 11 clones selected among surviving plants following 3 yr of field testing of half-sib families at a field testing station in Alta, Finnmark (70° N, 23° E, Larsen et al., 2001). The local population that Norild was selected from has been compared at the genotypic and phenotypic level with 14 other local Norwegian populations and does not seem to differ from that found in the other local populations (Fjellheim and Rognli, in press). The breeding of this cultivar has certainly involved strong selection for adaptation to forage production at higher latitudes, which may explain the restricted genetic base of this cultivar. Similar findings have been presented for a perennial ryegrass cultivar by Huff (1997).

The exchange of germplasm among the Nordic countries has been extensive. This would have prevented genetic differentiation between cultivars from different countries and should be evident as genetic relatedness among cultivars. This is indeed the case. In the PCO analysis, no clear groupings based on country of origin of the cultivars were revealed, except for the three Danish cultivars partially separated from the main group. The Icelandic population Petursey and Norild are also partially separated from the other cultivars. The Danish cultivar Pajbjerg appears close to the Swedish and Finnish populations in the PCO analysis, but MST shows that it has its closest affinities with the two other Danish populations. Denmark is climatically and topographically quite homogenous and different from the other Nordic countries. In addition, Denmark has not had any significant import of seeds from the other Nordic countries. This might explain the separation of the Danish cultivars in the PCO analysis. A more extensive exchange of seeds has been the practice between the other Nordic countries, explaining the lack of structure in the PCO analyses among the cultivars from these countries. An exception is the Swedish cultivar Svalöfs Sena, released in 1917, which relates strongly to the Danish cultivars as shown by the MST (Fig. 1). This relationship might be explained by the early import of seeds from Denmark to Sweden.

Cultivar Identification
Several authors have reported that AFLP is an appropriate technique for cultivar identification both for inbreeders and vegetatively propagated crops such as barley (Hordeum vulgare L., Schut et al., 1997), grapevine (Vitis vinifera L., Cervera et al., 1998) and rapeseed (Brassica napus L., Lombard et al., 2000), and for outbreeders like grasses and clovers (Forster et al., 2001; Guthridge et al., 2001; Kölliker et al., 2001). However, outbreeders exhibit far more within- than among-population variation when fingerprinted by AFLP. Guthridge et al. (2001) found that AFLPs were suitable to distinguish close-bred restricted base cultivars of perennial ryegrass and could also partially discriminate genetically variable populations. In contrast, Huff (1997) investigated heterogeneous perennial ryegrass cultivars by RAPDs and found that closely related cultivars did not possess any clear population boundaries. This is also the case in our study. The UPGMA analysis conducted on all the individuals (not shown) did not define a single cultivar, indicating that it would be difficult to use AFLPs to identify meadow fescue cultivars. Genetic variation displayed by AFLPs need not necessarily reflect the division into cultivars, which is based on selection of morphological and agronomical traits. For other traits, the cultivars can be similar, or the variation within each cultivar can be great. Roldán-Ruiz et al. (2000) have compared molecular and morphological methods of describing relationships between perennial ryegrass varieties and found large inconsistency between morphological traits and AFLP markers. This problem could be solved if the markers chosen were cultivar-specific and preferably linked to phenotypic traits used in the DUS (Distinctness, Uniformity, and Stability) testing. In this study, no marker could be identified that was exclusively found in all genotypes of one cultivar and absent in the others.


   ACKNOWLEDGMENTS
 
This investigation was supported by a grant from the Nordic Gene Bank (project no. AG4 19). The authors thank Zanina Grieg for excellent technical assistance, and Robert Koebner, Siri Grønnerød and Anne-Cathrine Scheen for helpful comments on the manuscript.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
This investigation was supported by a grant from the Nordic Gene Bank (project no. AG4 19).

Received for publication January 28, 2005.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 


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