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Published online 20 June 2006
Published in Crop Sci 46:1692-1700 (2006)
© 2006 Crop Science Society of America
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PLANT GENETIC RESOURCES

Evaluating the Genetic Diversity of Triticale with Wheat and Rye SSR Markers

C. Kuleunga, P. S. Baenzigera,*, S. D. Kachmanb and I. Dweikata

a Dep. of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68583-0915 USA
b Dep. of Statistics, University of Nebraska, Lincoln, NE 68583-0915 USA

* Corresponding author (pbaenziger1{at}unl.edu)


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Triticale (xTriticosecale Wittmack) is becoming increasingly important in agriculture and understanding its genetic diversity is essential for its continued improvement. Simple sequence repeat (SSR) markers are highly polymorphic and widely used for genetic diversity studies. Previous genetic diversity studies using SSRs have focused on the European winter triticale gene pool. Our objective was to investigate the genetic diversity and relationships of 80 hexaploid triticale accessions representing a more global gene pool using 43 wheat (Triticum spp.) and 14 rye (Secale cereale L.) SSR markers. Two hundred forty-one alleles from 57 markers were detected with an average of 4.2 alleles per locus (ranged from 2 to 11 alleles per locus). The average gene diversity was 0.54 with a range of 0.07 to 0.86. Cluster analysis grouped the 80 accessions into five clusters that were generally consistent with the available pedigree information, country of origin, growth habit, and release year. Every larger cluster, however, included lines with unrelated pedigrees, different countries of origin, growth habit, and release year, which most likely is due to germplasm exchange among breeding programs. Genetic diversity estimates of the accessions evaluated with markers from different sources were similar (0.55 and 0.53 for wheat and rye, respectively), indicating that the wheat and rye markers detected similar genetic variability in the wheat and rye genomes of triticale.

Abbreviations: EST, expressed sequence tag • GS, genetic similarity • SSR, simple sequence repeat • UPGMA, unweighted pair group method with arithmetic average


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
TRITICALE is a self-pollinated crop derived from a synthetic hybrid made by crossing of tetraploid wheat (Triticum durum L.) with rye. Hexaploid wheat (T. aestivum L.) has been used sometimes as a parent when it contains genes not found or rarely found in T. durum. Triticale is becoming an increasingly important crop for grain and forage as can be seen by Food and Agriculture Organization of the United Nations (FAO) records that the production area of triticale has increased from 638042 ha in 1980 to 3356778 ha in 2004 (FAOSTAT, 2005). Triticale can grow in harsh environments and is tolerant to many diseases, thus it is grown in areas that are not suitable for wheat. Many triticale cultivars have been released since the wheat x rye hybrid was first reported in 1876 (Wilson, 1876). Though wheat and rye are still sometimes used as genetic resources for triticale, triticale cultivars and germplasm are an immediate and a major gene pool for triticale improvement. Therefore, understanding their genetic diversity would facilitate effective parent selection for breeding purposes (Smith et al., 1990).

Before the advent of molecular techniques, genetic diversity was estimated from pedigree or agronomic and morphological characteristics. However, the disadvantage of pedigree-based estimation is that many of the assumptions—such as equal genetic contribution of both parents, the unrelatedness of parents with no common ancestral line, and no selection, genetic drift, and mutation—are violated in the breeding process. Hence, estimates based on pedigree information are generally inflated and often unrealistic (Almanza-Pinzon et al., 2003; Cox et al., 1986; Souza and Sorrells, 1989). Additionally, most pedigrees of triticale are complicated or unreported, making it hard or impossible to acquire estimates of genetic diversity from them. Many previous studies of genetic diversity in triticale have used morphological characteristics to estimate diversity (Kamboj and Mani, 1983; Royo et al., 1995; Furman et al., 1997). The drawback of morphologically based genetic diversity estimates is that morphological characteristics are limited in number and are influenced by the environment (van Beuningen and Bush, 1997). Therefore, neither pedigree-based nor morphology-based estimates may reflect the actual genetic difference of studied populations.

Molecular markers have advantages over morphology and pedigree for studying genetic diversity. Molecular markers are not influenced by environment and reflect genetic similarity without previous knowledge of pedigree information (Bohn et al., 1999). Microsatellite or SSR markers are abundant, multiallelic, and highly polymorphic. They are widely used for genetic diversity studies in many species such as wheat (Fahima et al., 2002), peach [Prunus persica (L.) Batsch] and sweet cherry (P. avium L.) (Dirlewanger et al., 2002), and pearl millet [Pennisetum glaucum (L.) R.Br.] (Budak et al., 2003). In pioneering studies for triticale, Tams et al. (2004, 2005) used SSR markers from wheat and rye and AFLP markers to study genetic diversity of European winter triticale. Their results showed moderate and low diversity for SSRs and AFLPs, respectively, and no distinct clusters of the lines from the same breeding sources. However, there is no similar study for triticale using a more global set of lines. Triticale germplasm is widely shared among breeding centers from around the world and it is essential to know the genetic diversity of triticale from a more globally diverse gene pool. Therefore, our objective in this study was to evaluate genetic diversity of 80 accessions representing a broad range of historic and contemporary hexaploid triticale germplasm using the SSR markers.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Plant Materials
Eighty accessions of hexaploid triticale were selected to assess genetic diversity. Lines were chosen to represent a broad spectrum of historic (including 12 primary triticales) and modern triticale germplasm that is publicly available in the world collection. The origin country, growth habit, year that National Plant Germplasm System received the accession materials or year that the accession was released, and pedigree (if available) are presented in Table 1. Materials and information of accession number 1 to 73 were obtained from USDA, ARS, National Genetic Resources Program (Germplasm Resources Information Network [GRIN] Online Database, available at http://www.ars-grin.gov). Materials and information for accessions 74 to 80 were obtained from Dr. P. Stephen Baenziger, Department of Agronomy and Horticulture, University of Nebraska–Lincoln.


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  		Table 1. Characterization of 80 accessions of triticale used in the genetic diversity assessment.

 
DNA Extraction, PCR Procedure, and Gel Electrophoresis
Leaves from five plants of each accession were combined and their DNA was extracted. DNA extraction, PCR reaction mixture, and gel electrophoresis were performed as described by Kuleung et al. (2004). PCR program for wheat primers consisted of initial denaturation for 3 min at 94°C, followed by 32 cycles of 30 s at 94°C, 50 s at 53°C, 50 s at 72°C, and final extension for 5 min at 72°C. The PCR program of rye primers followed the protocols of Saal and Wricke (1999) and Hackauf and Wehling (2002) for the rye genome-based and rye EST-based SSR markers, respectively.

Marker Selection
From the previous study (Kuleung et al., 2004), 176 wheat and rye SSR markers (GrainGenes, 2006; Röder et al., 1998; Saal and Wricke, 1999) were screened for transferability, amplification, and readability in five lines of wheat (‘Newton’, ‘Sullivan’, ‘MV-Matador’, ‘Bobwhite’, ‘Arapahoe’), rye (‘Emory’, ‘Aitta’, ‘Kaltenberger’, ‘Blanco’, ‘Langauer taner’), and triticale (‘NE95T427’, ‘Presto’, ‘Newcale’, ‘Kolding’, ‘Wanad’). Thirty-seven additional markers (12 wheat and 25 rye EST-based [Hackauf and Wehling, 2002]) were screened in this study. The markers that gave amplification products in triticale were used to amplify across 80 triticale accessions.

Genetic Diversity Estimation
Genetic diversity was calculated by Weir's (1996) gene diversity, Dl = 1 – FormulaPlu2 where Plu is the frequency of the uth allele of lth marker locus. Generally, only one allele of polymorphic marker was present in each accession. Hence, frequency of the present allele u of lth locus of line i (Plui) is equal to 1. In case of a line presenting more than one allele at a polymorphic locus, Plui will be given with equal frequency to each allele, for example, 0.5 for two alleles. Plu was then calculated as the average of the Plui. Null alleles (those alleles where none of the alleles were present) were treated as missing data, which were omitted in calculation.

DNA segments at polymorphic loci were scored as presence (1) or absence (0) of an allele and used to construct a binary matrix, which was then transformed to genetic similarity matrix using Dice similarity coefficient (Dice, 1945; Nei and Li, 1979). Genetic similarities (GS) between pairs of accessions were measured as GS = 2a/(2a + b + c) where a is the number of positive matches (presence of an allele in both accessions) and b + c is the number of mismatches (presence of an allele either in one of the accessions but absent in the other accession). Null alleles were treated as missing data, which were omitted in the analysis. The genetic similarity matrix of all accessions was analyzed by using unweighted pair group method with arithmetic average (UPGMA) algorithm, and the result was used to construct a dendrogram. To observe the discrimination power of markers from different sources, data obtained from wheat and rye markers were separately used for generating the matrices of genetic similarity and cophenetic values (Thormann et al., 1994; Powell et al., 1996). Then correlations between matrices of genetic similarity or cophenetic values were calculated and statistically tested by Mantel's test with 1000 random permutations. All cluster analyses were performed using NTSYSpc version 2.02 (Exeter Software, Setanket, NY).


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
Of 213 markers, 123 markers (94, 11, and 18 from wheat, genomic rye, and EST rye, respectively) that gave amplification products in five screened lines of triticale were used to amplify across 80 triticale accessions. After excluding markers that were ambiguous, nonpolymorphic, or had more than 15% null alleles of total accessions (those lines where none of the polymorphic alleles were present), 57 SSR markers (43, 3, and 11 from wheat, genomic rye, and EST rye, respectively) that were distributed throughout A, B, and R genomes were selected for the diversity analysis. All selected markers produced a discrete band or band set, which usually consisted of a single strong polymorphic band with one or more cosegregating bands. Triticale is a self-pollinated crop that occasionally outcrosses (may be as high as 19%; Malik, 1984). However, two different bands in a line were most likely the result of line heterogeneity (in the generation of selection, the selected plant was heterozygous which became homozygous for the alleles on further selfing) rather than the tested line being heterozygous Fig. 1 .


Figure 1
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  		Fig. 1. SSR analysis of the triticale parental and their F2 progeny lines. Top panel represents the cross between Wanad (P1) and Newcale (P2) amplified with the rye marker SCM0112. Lower panel represents the progeny of Titan (P1) and NE95T427 (P2) amplified with the wheat SSR marker BARC012. The amplification products were fractionated on 12% native acrylamide gel electrophoresis.

 
The 57 markers produced 241 polymorphic alleles in the 80 triticale accessions, ranging from 2 to 11 alleles per locus with the average of 4.2 alleles per locus (Table 2). The 57 SSR markers originated from three different genomes of wheat and rye (18, 18, 14, and 4 markers from A, B, R, and D genomes, respectively) and presumably amplify corresponding loci in triticale (Table 2). The three remaining markers were not assigned to a specific genome (Table 2). The four markers from D genome were also included, because some hexaploid triticale lines that descended from crosses using bread wheat (AABBDD) or octaploid triticale (AABBDDRR) may have D-genome chromosomes substituted for homoeologous chromosomes of other genomes (e.g., incomplete triticales), there may be introgressed DNA segments of D genome into homeologous chromosomes of the other genomes (Gustafson and Bennet, 1976), or they may be amplifying loci in the A, B, or R genomes.


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  		Table 2. Characterization of wheat and rye simple sequence repeat (SSR) markers, number of alleles, and diversity amplified in triticale.

 
Genetic Diversity Estimation and Cluster Analysis
Using all 80 triticale lines, the genetic diversity using SSR markers ranged from 0.12 for BARC1021 to 0.86 for BARC004 (Table 2), with the average of 0.54 ± 0.02 for all loci (Table 3) revealing moderate variability among accessions. Similarly, GS between pairs of 80 accessions based on 57 SSR markers showed an average of 0.45, ranging from 0.16 to 0.98. The genetic similarity of the 12 primary triticale lines (0.41, ranging from 0.21 to 0.61) was similar to that estimated using remaining 68 lines (0.47 ranging from 0.19 to 0.98) and to the previous estimate using all 80 lines. The greatest diversity was observed between PI308881 (no. 52), a spring triticale line from Spain, and PI428842 (no. 68), a winter triticale line from Canada with similarity coefficient of 0.16.


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  		Table 3. Number of markers, number of alleles per locus, and average diversity of rye, wheat, and combined sets investigated across 80 triticale accessions.

 
The accessions could be divided into five clusters using the UPGMA dendrogram based on Dice genetic similarity when drawing a phenon line at the average similarity (0.45) with cluster II containing only one accession (PI386148) from Russia (Leningrad) (Fig. 2 ). Although the dendrogram clusters were not distinct (e.g., did not show a pattern based on the characteristics that we observed: country of origin, growth habit, pedigree, or year submitted to the collection or released), we found that most accessions sharing at least one of the above characteristics were usually clustered together.


Figure 2
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  		Fig. 2. Dendrogram of 80 triticale accessions estimated by Dice similarity coefficient based on 57 wheat and rye SSR markers. The designation is accession number, country of origin, and growth habit (refer to Table 1).

 
Cluster I consisted of mostly spring lines that were released after 1970. It was further divided into three subgroups, I-a, I-b, and I-c. Most of the accessions from CIMMYT that shared ‘Armadillo’ in their pedigree and the near-isogenic lines from Sweden which also had Armadillo as a parent were in the subgroup I-a. The accessions of subgroup I-b included accessions from African and European countries such as South Africa, Morocco, Hungary, and Poland. In this subgroup, Presto (no. 74), a Polish winter grain line that was well adapted to North America, and three North American winter grain lines (no. 75–77) were clustered with the accessions that were a mixture of spring and winter types. Subgroup I-c had a single member, PI422264, a CIMMYT spring line, suggesting genetic distinction from the other CIMMYT lines in the subgroup I-a. Cluster III consisted of spring accessions except one winter accession from Canada, PI428840 (no. 66) that was grouped with a Canadian spring line, PI428795 (no. 65) developed by the same breeders. One CIMMYT accession, PI661793 (no. 22), was grouped with other accessions from USA (California) that shared ‘Snoopy’ in their pedigrees. Cluster IV included most of the ancestral accessions released from 1931 to 1970. All accessions from Russia except PI386148 (no. 60) that was alone in cluster II were in this cluster. The Russian accessions bred from Moscow (no. 55–58) and Saratov (no. 61–63) separated in different subclusters, and they had different growth habits. Three spring lines from Spain (Zaragosa), which shared ‘Gator’ in their pedigree, were also in this cluster grouping with spring Russian lines. Cluster V consisted of only winter accessions from Canada, Hungary, and USA. The related forage lines from Nebraska, NE422T (no. 78) and NE96T441 (no. 79), were grouped with their parental forage line ‘Trical’ (no. 80).

Since many triticale lines have unknown or complex pedigrees, the accuracy of our cluster analysis could only be evaluated using those accessions with available pedigree information. Generally, accessions sharing a parent or pedigree were observed in the same cluster, for example, accessions sharing ‘Armadillo’ in cluster I-a, accessions sharing ‘Gator’ in cluster IV, accessions sharing ‘Trical’ in cluster V. These results served as an internal control for our analysis, providing confidence that the molecular marker analysis methods were reliable.

Breeders usually use a superior line as a parent in crosses to generate new lines. As a result, related lines were more likely to receive the same alleles controlling a preferred character from the parents (especially when coupled with selection), which contributed to their genetic similarity. Some accessions with the same pedigree, however, were not the most similar; for instance, PI422263 (no. 9) and PI422271 (no. 13), and PI422268 (no. 11) and PI611466 (no. 18), were not grouped together. The dissimilarity between the latter two triticales may be explained by their being an octoploid triticale crossed to a hexaploid triticale and stable derivatives could have considerable genetic differences. Nevertheless the accessions of both pairs were grouped very closely and the closer accession that they were grouped with also shared another common parent. This result is possibly the result of the clustering process that will group a line with only the most similar line when there may exist two related lines in different clusters. Many studies (Bohn et al., 1999; Tams et al., 2005) have been demonstrated that genetic relationships based on molecular markers do not totally agree with those estimated by pedigree information because of the unrealistic assumptions for estimating coancestry coefficient (f). Tams et al. (2005) reported low but significant correlation between f and genetic similarity based on molecular markers (0.32 and 0.33 for SSR and AFLP markers, respectively) of European winter triticale while Bohn et al. (1999) reported a moderate correlation (r = 0.45) between molecular (RFLP, SSR, and AFLP) based genetic similarity and f of winter wheat cultivars.

Though some accessions from the same country were clustered together, some accessions were clustered with accessions developed from different countries possibly because germplasm exchange among breeding centers would contribute to a clustering of accessions from different geographic origins that share common parents. Based on morphological characteristics, Kamboj and Mani (1983) investigated genetic diversity of Indian and CIMMYT triticale accessions. They suggested that the mingled clustering pattern of Indian and CIMMYT lines was primarily due to derivation of Indian lines from crossing CIMMYT triticale and Indian wheat. Similar results were also found in other studies (Furman et al., 1997; Royo et al., 1995; Tams et al., 2004, 2005). Moreover, triticale line clusters were also influenced by the selection criteria of different breeders and release year (Hoshino and Seko, 1996; Pecetti and Annicchiarico, 1998).

For the growth habit, cluster V had only winter accessions while the other clusters with multiple lines had both winter and spring accessions. In contrast, Royo et al. (1995) reported a clear separation, based on agronomical and morphological characteristics, of winter and spring triticales as would be expected by the greatly differing growth habits. The distinct clusters of spring and winter types were caused by their chosen criteria that were used to distinguish the genotypes. In our study, clustering of accessions with different growth habits may result from the lines coming from crosses between spring and winter parents followed by selection. In one instance, PI611786 (no. 23), a CIMMYT winter triticale, had both spring parents, 6TA-204 and Armadillo 133. PI611786 was clustered among the spring triticales in cluster I-a, indicating that it may possess many common SSR markers with other Armadillo derived spring growth habit lines. Otherwise PI611786 may actually be misclassified and is a spring triticale. Although the markers that we used could partially differentiate accessions with different growth habits, we do not know whether our markers were linked to the traits. Unlinked markers to growth habit traits would reduce the genetic diversity estimates between winter and spring types when compared to the estimates of markers linked to and classification systems based on different growth habit.

Genetic diversity estimation and cluster analysis revealed the moderate relationships among the 80 triticale accessions (0.54). Comparable to our study, Tams et al. (2004) reported moderate (0.54) polymorphic information content of European winter triticale germplasm pool based on wheat and rye SSR loci. Their results indicated that the European winter triticale germplasm is as diverse as the more global triticale germplasm. This result may be explained as Europe having the largest hectarage of triticale production, many of the most active breeding programs, and some of the best breeding programs. Tams et al. (2005), however, reported lower genetic diversity of the same genotypes using AFLP markers, which they assumed was due to SSR and AFLP markers detecting variation in different part of the genomes (Tams et al., 2005).

In considering the genetic diversity identified in this study and those by Tams et al. (2004, 2005), the low to moderate diversity of triticale may be the consequence of the relatively narrow genetic base during the initial establishment of triticale and the limited number of germplasm resources available to triticale breeders. Relatively few triticale breeders create new germplasm because new primary triticale lines are difficult to create. Most triticale breeders create new triticale lines from crosses between triticale parents or triticale and wheat genotypes. Compared to its progenitors, the diversity of triticale in our study was lower than genetic diversity based on SSR markers of rye (0.6) reported by Saal and Wricke (1999) and of wheat (0.72) presented by Manifesto et al. (2001). However, the diversity in our study was higher than wheat diversity (0.30) reported by Bohn et al. (1999). Saal and Wricke (1999) studied open-pollinated rye cultivars and Manifesto et al. (2001) used only highly polymorphic SSR markers which may explain the greater variation of rye and wheat in their studies. The lower diversity of the study by Bohn et al. (1999) may be a result of materials used originating from the same origin.

Correlation between Wheat and Rye Markers
A similar ability of the same number of wheat and rye markers to differentiate these triticale lines might be expected, though rye is normally cross pollinated and wheat is self pollinated and has large genetic resources and numerous breeding programs. Separate analyses of rye and wheat markers were performed to compare the discrimination power of markers from different sources to measure genetic diversity of the wheat and rye genomes of triticale. Comparison of genetic similarity matrices and cophenetic value matrices between each subset (data from wheat or rye markers) and the entire data (combined set) showed that the combined set, as expected, associated to wheat more than rye most likely due to the greater number of wheat markers. Correlation of matrices between wheat and rye markers showed significant correlations (0.45 and 0.58 for similarity and cophenetic matrices, respectively; Table 4). Likewise, their genetic diversity values were also similar (0.55 and 0.53; Table 3). These results indicated that these sets of wheat and rye markers illustrated similar genetic variability of the wheat and rye genomes of triticale. In contrast, Tams et al. (2004) reported greater variation in the wheat genomes (0.6) than rye genome (0.45) of European winter triticales based on SSR markers from wheat and rye. They discussed that lower value from rye markers was possibly related to low polymorphism of EST-derived rye markers. Alternatively, it may be due to lower genetic diversity in the ancestral rye lines used to create European winter triticale.


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  		Table 4. Correlation of similarity coefficient (below the diagonal) and cophenetic value (above the diagonal) derived from the rye, wheat and combined sets of markers.

 
The SSR markers did reveal the genetic similarity among the triticale accessions regardless of their pedigree, geographic origin, growth habit, and year submitted to the collection or released, which indicated that wheat and rye SSR markers are valuable and reliable for examining relationships of triticale genotypes. With this set of markers, we could differentiate genetically very closely related accessions, for example, the near-isogenic lines. The results provided an insight to the genetic diversity of triticale that should facilitate efficient utilization and management of triticale germplasm. It is our intention to devise a molecular marker–based strategy for selecting parents to create elite lines based their parental genetic diversity. Triticale genomic comparisons with other closely related species also should provide insight to the short-term molecular evolution of polyploidization.


   ACKNOWLEDGMENTS
 
The authors would like to thank Dr. Hikmet Budak (Biological Sciences and Bioengineering Program, Faculty of Engineering and Natural Sciences, Sabanci University, Turkey) for providing the NTSYS program, Drs. Perry Cregan and Qijian Song (Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD 20705) and Dr. P. Wehling (Federal Centre for Breeding Research on Cultivated Plants) for kindly providing the sequence information for the BARC markers and the rye EST-based SSR markers and thank the Ministry of University Affairs, Thailand for partial support of this research. Partial funding for P.S. Baenziger is from USDA- IFAFS competitive grant 2001-04462 and USDA, NRICGP 00-353000-9266 and 2004-35300-1470.


   NOTES
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 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
A contribution of the University of Nebraska Agricultural Research Division, Lincoln, NE 68583. Journal Series # 14831.

Received for publication October 3, 2005.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 





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The SCI Journals Agronomy Journal Vadose Zone Journal
Journal of Natural Resources
and Life Sciences Education		 Soil Science Society of America Journal
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Environmental Quality		 The Plant Genome