**6.4 RAPD (Random Amplified Polymorphic DNA)**

RAPD analysis uses conserved or general primers that amplify from many anonymous sites throughout the genome. It is indeed rapid, and need only short primers of random sequence, but suffers from low polymorphism information content (PIC), poor correlation with other marker data, and problems in reproducibility due to the low annealing temperatures in the reactions.

The genetic diversity in the wild soybean populations from the Far East region of Russia was analyzed using RAPD markers (Seitova *et al*., 2004). The results obtained suggest that (1) genetically different groups of wild soybean have active development, (2) level of polymorphism was significantly higher than in the cultivated soybean and (3) geographically isolated subpopulations showed maximum distance from the main population of wild soybean. The high level of polymorphism between the wild and cultivated soybean accessions was also reported by Kanazawa *et al*. (1998) in their study on

reliable, compared to pedigree analysis and traditionally used morphological markers. The genetic markers include RFLP, RAPD, SSR and AFLP markers were used to probe the genetic differences between wild and cultivated soybeans or for the origin and dissemination of soybeans (Brown-Guedira *et al*., 2000; Tian *et al*., 2000; Li & Nelson, 2001; Xu & Zhao, 2002; Abe *et al*., 2003). These studies have revealed higher levels of genetic

This analysis exploits variation in the occurrence of restriction sites in genomic sequences hybridizing to a cloned probe. Originally, RFLP analysis required Southern blotting and hybridization, making the method fairly slow and laborious. This technique is still used to generate ''anchor'' markers, used by many scholars to make consensus recombinational maps, though it is often implemented with the polymerase chain reaction (PCR) to generate

Chung *et al*. (2006) evaluated levels of genetic diversity in USDA soybean germplasm (107 accessions), originated from six provinces in central China, using RFLP analysis. They detected significant genetic differentiation among the six provinces (mean *G*ST = 0.133). These results suggest that Chinese germplasm accessions from various regions or provinces in the USDA germplasm collection could be used to enhance the genetic diversity of US

AFLP is an anonymous marker method, detects restriction sites by amplifying a subset of all the sites for a given enzyme pair in the genome by PCR between ligated adapters. To some extent, it like RFLP detects single nucleotide polymorphisms (SNPs) at restriction sites. Ude *et al*. (2003) analyzed the genetic diversity within and between Asian and North American soybean cultivars by AFLP. They found that the average genetic distance between the North American soybean cultivars and the Chinese cultivars was 8.5% and between the North American soybean cultivars and the Japanese cultivars was 8.9%, but the Chinese soybean was not completely separated from the Japanese soybean. They also revealed that Japanese cultivars may constitute a genetically distinct source of useful genes for yield

RAPD analysis uses conserved or general primers that amplify from many anonymous sites throughout the genome. It is indeed rapid, and need only short primers of random sequence, but suffers from low polymorphism information content (PIC), poor correlation with other marker data, and problems in reproducibility due to the low annealing

The genetic diversity in the wild soybean populations from the Far East region of Russia was analyzed using RAPD markers (Seitova *et al*., 2004). The results obtained suggest that (1) genetically different groups of wild soybean have active development, (2) level of polymorphism was significantly higher than in the cultivated soybean and (3) geographically isolated subpopulations showed maximum distance from the main population of wild soybean. The high level of polymorphism between the wild and cultivated soybean accessions was also reported by Kanazawa *et al*. (1998) in their study on

diversity in wild soybean.

Cultivars.

improvement.

temperatures in the reactions.

**6.2 RFLP (Restriction Fragment Length Polymorphism)** 

**6.3 AFLP (Amplified Fragment Length Polymorphism)** 

**6.4 RAPD (Random Amplified Polymorphic DNA)** 

the polymorphic fragments (Schulman, 2007).

soybean accessions from the Far East using RAPD profiles of mitochondrial and chloroplast DNA. Xu & Gai (2003), Pham Thi Be Tu *et al*. (2003), An *et al*. (2009) confirmed the results of Kanazawa *et al*. (1998) and Seitova *et al*. (2004) in terms of the high genetic variation between the wild and cultivated soybean accessions. They also found that the diversity of *G. soja* was higher than that of *G. max*; and environmental factors may play important roles in soybean evolution. Furthermore, they revealed that accessions within each species tend to form subclusters that are in agreement with their geographical origins, demonstrating that an extensive geographical genetic differentiation exists in both species. Consequently, it was indicated that geographical differentiation plays a key role in the genetic differentiation of both wild and cultivated soybeans. The relationship between geographical differentiation and genetic diversity appeared in the work of Chen & Nelson (2005) who identified significant genetic differences between soybean accessions collected from different provinces in China. Their data provided pronounced evidence that primitive cultivars of China were generally genetically isolated in relatively small geographical areas. Similar results were obtained by Li & Nelson (2001, 2002) in their study on soybean accessions from 8 provinces in China using a core set of RAPD primers with high polymorphism in soybean (Thompson *et al.*, 1998). On the contrary, Brown-Guedira *et al*. (2000) did not find an association between origin and RAPD markers among soybean lines of more modern origin. It is likely that these genotypes have been dispersed by human intervention from the areas of actual origin.

The relationship between genetic differentiation and origin of 120 soybean accessions from Japan, South Korea and China was evaluated with RAPDs (Li & Nelson, 2001). They found that the Japanese and South Korean populations were more similar to each other, whereas both were genetically distinct from the Chinese population, suggesting that the S. Korean and Japanese gene pools might be probably derived from a relatively few introductions from China. Li *et al*. (2001) compared the genetic diversity of ancestral cultivars of the N. American (18) as well as the Chinese soybean germplasm pools (32) using RAPD markers, the N. American ancestors have a slightly lower level of genetic diversity. Cluster analyses generally separated the two gene pools. In particular, a great genetic variability was detected between the ancestors of northern U.S. and Canadian soybeans and the Chinese ancestors.

Chowdhury *et al*. (2002) examined the level of genetic similarity among forty-eight soybean cultivars imported out of their country Thailand using DNA (RAPD) markers. They found high level of genetic similarities between these cultivars. Cluster analysis of the obtained data classified the 48 cultivars into four groups at 0.57 similarity scale, even though the cultivars are morphologically or geographically very close. Comparing agronomic performance and RAPD analysis via dendrogram, a total of 11 cultivars can be useful to soybean breeders in Thailand who want to utilize genetically diverse introductions in soybean improvement. Baránek et *al*. (2002) evaluated the genetic diversity within 19 soybean genotypes included in the Czech National Collection of Soybean Genotypes by RAPD method. The polymorphism among the studied genotypes was 46%. Presented results enable the selection of genetically distinct individuals. Such information may be useful to breeders willing to use genetically diverse introductions in soybean improvement process.

### **6.5 SSRs (Simple sequence repeats)**

SSRs molecular markers have been widely applied in the genetic diversity studies of the soybean germplasm (Abe *et al.*, 2003; Wang *et al*., 2006; Fu *et al*., 2007; Li *et al*., 2008; Wang &

Genetic Diversity and Allele Mining in Soybean Germplasm 11

and the absence of region-specific clusters in the southeast and south/central Asian populations suggested that soybean in these areas has been introduced repeatedly and independently from the diverse Chinese germplasm pool. Therefore the two germplasm pools can be used as exotic genetic resources to enlarge the genetic bases of the respective

Chotiyarnwong *et al.* (2007) evaluated the genetic diversity of 160 Thai indigenous and recommended soybean varieties by examining the length polymorphism of alleles found in 18 SSR loci from different linkage groups. UPGMA-Cluster analysis and principal component analysis (PCA) separated Thai indigenous varieties from recommended soybean varieties. However, the genetic differentiation between the indigenous and recommended

Shi *et al*. (2010) performed genetic diversity and association analysis among 105 food-grade soybean genotypes using 65 simple sequence repeat (SSR) markers distributed on 20 soybean chromosomes. Based on the SSR marker data, the 105 soybean genotypes were divided into four clusters with six sub-groups. Thirteen SSR markers distributed on 11 chromosomes were identified to be significantly associated with oil content and 19 SSR markers distributed on 14 chromosomes with protein content. Twelve of the SSR markers were associated with both protein and oil QTL. A negative correlation was obtained

Mimura *et al*. (2007) investigated SSR diversity in 130 vegetable soybean accessions including 107 from Japan, 10 from China and 12 from the United States. Eighteen of the 130 accessions were outliers, and the rest of the accessions were grouped into nine clusters. The majority of food-grade soybean cultivars were released from Japan and South Korea because of the market availability and demands. However, the genetic diversity of South Korea

Nguyen *et al.* (2007) used 20 genomic SSR and 10 EST-SSR SSR to explore the genetic diversity in accessions of soybean from different regions of the world. The selection of the thirty SSR primer-pairs was based on their distribution on the 20 genetic linkage groups of soybean, on their trinucleotide repetition unit and on their polymorphism information content. All analyzed loci were polymorphic. A low correlation between SSR and EST-SSR data was observed, thus genomic SSR and EST-SSR markers are required for an appropriate analysis of genetic diversity in soybean. They observed high genetic diversity which allowed the formation of five groups and several subgroups. They also observed a moderate

Xie *et al*. (2005) analyzed genetic diversity of 158 Chinese summer soybean germplasm, from the primary core collection of *G. max* using 67 SSR loci. The Huanghuai and Southern summer germplasm were different in the specific alleles, allelic-frequencies and pairwise genetic similarities. UPGMA cluster analysis based on the similarity data clearly separated the Huanghuai from Southern summer soybean accessions, suggesting that they were different gene pools. The data indicated that Chinese Huanghuai and Southern summer soybean germplasm can be used to enlarge genetic basis for developing elite summer

Most diversity studies on cultivated soybean published by now have focused on North American (Brown-Guedira *et al*., 2000; Narvel *et al*., 2000; Fu *et al.,* 2007) Asian (Abe *et al*., 2003; Xie *et al*., 2005; Wang *et al*., 2006; Li *et al.,* 2008; Wang *et al*., 2008; Yoon *et al*., 2009) as well as South American (Bonato *et al*., 2006) soybean germplasm. In several studies only a few genotypes of European origin have been represented among germplasm studied

relationship between genetic divergence and geographic origin of accessions.

Asian soybean populations.

soybean varieties was small.

between protein and oil content.

food-grade soybean remains unreported (Mimura *et al*., 2007).

soybean cultivars by exchanging their germplasm.

Takahata, 2007; Wang *et al*., 2008; Yoon *et al.*, 2009). The advantages of SSR over other types of molecular markers are that they are abundant, have a high level of polymorphism, are codominant, can be easily detected with PCR and typically have a known position in the genome. High levels of polymorphism at SSR loci have been reported for both the number of alleles per locus and the gene diversity (Diwan & Cregan, 1997; Abe *et al*., 2003; Wang *et al*., 2006; Fu *et al*., 2007 ; Wang *et al.,* 2010).

Wang *et al*. (2010) used 40 SSR primer pairs to study genetic variability in 40 soybean accessions of cultivars, landraces and wild soybeans collected from China. These results indicated that wild soybeans and landraces possessed greater allelic diversity than cultivars and might contain alleles not present in the cultivars which can strengthen further conservation and utilization. The UPGMA (Unweighted Pair Group Method with Arithmetic) results also exhibited that wild soybean was of more abundant genetic diversity than cultivars.

A total of 2,758 accessions of Korean soybean landraces were profiled and evaluated for genetic structure using six SSR loci (Yoon *et al*., 2009). The accessions within collections were classified based on their traditional uses such as sauce soybean (SA), sprouted soybean (SP), soybean for cooking with rice (SCR), and others-three different Korean *Glycine max* collections and for groups distinguished by their usage, such as SA, SP, and SCR. Nei's average genetic diversity ranged from 0.68 to 0.70 across three collections, and 0.64 to 0.69 across the usage groups. The average between-group differentiation (Gst) was 0.9 among collections, and 4.1 among the usage groups. The similar average diversity among three collections implies that the genetic background of the three collections was quite similar or that there were a large number of duplicate accessions in three collections (Yoon *et al*., 2009). The selection from the four groups classified based upon usage may be a useful way to select accessions for developing a Korean soybean landrace core collection at the RDA gene bank.

Hudcovicová *et al*. (2003) analyzed allelic profiles at 18 SSR loci of 67 soybean genotypes of various origins. Six only of SSR markers differentiated all 67 genotypes each from others successfully. Guan *et al*. (2010) investigated the genetic relationship between 205 Chinese soybean accessions that represent the seven different soybean ecotypes and 39 Japanese soybean accessions from various regions using 46 SSR loci. Cluster analysis with UPGMA separated the Chinese accessions from Japanese accessions, suggesting that soybean in these two countries form different gene pools. It also showed that (1) accessions from China have more genetic diversity than those from Japan, (2) studied germplasm was divided into three distinct groups, "corresponding to Japanese soybean, Northern China soybean, Southern China soybean and a mixed group in which most accessions were from central China", and (3) Japanese accessions had more close relationship with Chinese northeast spring and southern spring ecotypes. This study provides interesting insights into further utilization of Japanese soybean in Chinese soybean breeding.

Abe *et al*. (2003) analyzed allelic profiles at 20 SSR loci of 131 accessions introduced from 14 Asian countries. UPGMA-cluster analysis clearly separated the Japanese from the Chinese accessions, suggesting that the Japanese and Chinese populations formed different germplasm pools; showed that Korean accessions were distributed in both germplasm pools, whereas most of the accessions from south/central and southeast Asia were derived from the Chinese pool; indicated that genetic diversity in the southeast and south/central Asian populations was relatively high; and exhibited the absence of region-specific clusters in the southeast and south/central Asian populations. The relatively high genetic diversity

Takahata, 2007; Wang *et al*., 2008; Yoon *et al.*, 2009). The advantages of SSR over other types of molecular markers are that they are abundant, have a high level of polymorphism, are codominant, can be easily detected with PCR and typically have a known position in the genome. High levels of polymorphism at SSR loci have been reported for both the number of alleles per locus and the gene diversity (Diwan & Cregan, 1997; Abe *et al*., 2003; Wang *et* 

Wang *et al*. (2010) used 40 SSR primer pairs to study genetic variability in 40 soybean accessions of cultivars, landraces and wild soybeans collected from China. These results indicated that wild soybeans and landraces possessed greater allelic diversity than cultivars and might contain alleles not present in the cultivars which can strengthen further conservation and utilization. The UPGMA (Unweighted Pair Group Method with Arithmetic) results also exhibited that wild soybean was of more abundant genetic diversity

A total of 2,758 accessions of Korean soybean landraces were profiled and evaluated for genetic structure using six SSR loci (Yoon *et al*., 2009). The accessions within collections were classified based on their traditional uses such as sauce soybean (SA), sprouted soybean (SP), soybean for cooking with rice (SCR), and others-three different Korean *Glycine max* collections and for groups distinguished by their usage, such as SA, SP, and SCR. Nei's average genetic diversity ranged from 0.68 to 0.70 across three collections, and 0.64 to 0.69 across the usage groups. The average between-group differentiation (Gst) was 0.9 among collections, and 4.1 among the usage groups. The similar average diversity among three collections implies that the genetic background of the three collections was quite similar or that there were a large number of duplicate accessions in three collections (Yoon *et al*., 2009). The selection from the four groups classified based upon usage may be a useful way to select accessions for developing a Korean soybean landrace core collection at the RDA gene

Hudcovicová *et al*. (2003) analyzed allelic profiles at 18 SSR loci of 67 soybean genotypes of various origins. Six only of SSR markers differentiated all 67 genotypes each from others successfully. Guan *et al*. (2010) investigated the genetic relationship between 205 Chinese soybean accessions that represent the seven different soybean ecotypes and 39 Japanese soybean accessions from various regions using 46 SSR loci. Cluster analysis with UPGMA separated the Chinese accessions from Japanese accessions, suggesting that soybean in these two countries form different gene pools. It also showed that (1) accessions from China have more genetic diversity than those from Japan, (2) studied germplasm was divided into three distinct groups, "corresponding to Japanese soybean, Northern China soybean, Southern China soybean and a mixed group in which most accessions were from central China", and (3) Japanese accessions had more close relationship with Chinese northeast spring and southern spring ecotypes. This study provides interesting insights into further utilization of

Abe *et al*. (2003) analyzed allelic profiles at 20 SSR loci of 131 accessions introduced from 14 Asian countries. UPGMA-cluster analysis clearly separated the Japanese from the Chinese accessions, suggesting that the Japanese and Chinese populations formed different germplasm pools; showed that Korean accessions were distributed in both germplasm pools, whereas most of the accessions from south/central and southeast Asia were derived from the Chinese pool; indicated that genetic diversity in the southeast and south/central Asian populations was relatively high; and exhibited the absence of region-specific clusters in the southeast and south/central Asian populations. The relatively high genetic diversity

*al*., 2006; Fu *et al*., 2007 ; Wang *et al.,* 2010).

Japanese soybean in Chinese soybean breeding.

than cultivars.

bank.

and the absence of region-specific clusters in the southeast and south/central Asian populations suggested that soybean in these areas has been introduced repeatedly and independently from the diverse Chinese germplasm pool. Therefore the two germplasm pools can be used as exotic genetic resources to enlarge the genetic bases of the respective Asian soybean populations.

Chotiyarnwong *et al.* (2007) evaluated the genetic diversity of 160 Thai indigenous and recommended soybean varieties by examining the length polymorphism of alleles found in 18 SSR loci from different linkage groups. UPGMA-Cluster analysis and principal component analysis (PCA) separated Thai indigenous varieties from recommended soybean varieties. However, the genetic differentiation between the indigenous and recommended soybean varieties was small.

Shi *et al*. (2010) performed genetic diversity and association analysis among 105 food-grade soybean genotypes using 65 simple sequence repeat (SSR) markers distributed on 20 soybean chromosomes. Based on the SSR marker data, the 105 soybean genotypes were divided into four clusters with six sub-groups. Thirteen SSR markers distributed on 11 chromosomes were identified to be significantly associated with oil content and 19 SSR markers distributed on 14 chromosomes with protein content. Twelve of the SSR markers were associated with both protein and oil QTL. A negative correlation was obtained between protein and oil content.

Mimura *et al*. (2007) investigated SSR diversity in 130 vegetable soybean accessions including 107 from Japan, 10 from China and 12 from the United States. Eighteen of the 130 accessions were outliers, and the rest of the accessions were grouped into nine clusters. The majority of food-grade soybean cultivars were released from Japan and South Korea because of the market availability and demands. However, the genetic diversity of South Korea food-grade soybean remains unreported (Mimura *et al*., 2007).

Nguyen *et al.* (2007) used 20 genomic SSR and 10 EST-SSR SSR to explore the genetic diversity in accessions of soybean from different regions of the world. The selection of the thirty SSR primer-pairs was based on their distribution on the 20 genetic linkage groups of soybean, on their trinucleotide repetition unit and on their polymorphism information content. All analyzed loci were polymorphic. A low correlation between SSR and EST-SSR data was observed, thus genomic SSR and EST-SSR markers are required for an appropriate analysis of genetic diversity in soybean. They observed high genetic diversity which allowed the formation of five groups and several subgroups. They also observed a moderate relationship between genetic divergence and geographic origin of accessions.

Xie *et al*. (2005) analyzed genetic diversity of 158 Chinese summer soybean germplasm, from the primary core collection of *G. max* using 67 SSR loci. The Huanghuai and Southern summer germplasm were different in the specific alleles, allelic-frequencies and pairwise genetic similarities. UPGMA cluster analysis based on the similarity data clearly separated the Huanghuai from Southern summer soybean accessions, suggesting that they were different gene pools. The data indicated that Chinese Huanghuai and Southern summer soybean germplasm can be used to enlarge genetic basis for developing elite summer soybean cultivars by exchanging their germplasm.

Most diversity studies on cultivated soybean published by now have focused on North American (Brown-Guedira *et al*., 2000; Narvel *et al*., 2000; Fu *et al.,* 2007) Asian (Abe *et al*., 2003; Xie *et al*., 2005; Wang *et al*., 2006; Li *et al.,* 2008; Wang *et al*., 2008; Yoon *et al*., 2009) as well as South American (Bonato *et al*., 2006) soybean germplasm. In several studies only a few genotypes of European origin have been represented among germplasm studied

Genetic Diversity and Allele Mining in Soybean Germplasm 13

improving a target trait (Kaur *et al*., 2008). The availability of sequence and sequence variation that affects the plant phenotype is of utmost importance for the utilization of

The existing allelic diversity in any crop species is caused by mutations, the evolutionary driving force (Kumar *et al*., 2010). Mutations create new alleles or cause variations in the existing allele and allelic combinations. They take place in coding and non-coding regions of the genome either as single nucleotide polymorphism (SNP) or as insertion and deletion (InDel). As far it is known, there is no cited literatures on the effect of mutations on transcript synthesis and accumulation which in turn alter the trait expression in 5′ UTR including promoter, introns and 3′ UTR in the genome of soybean. In coding region, it may have tremendous effect on the phenotype by altering the encoded protein structure and/or function. For example, the AtAHASL protein encoded by *csr1-2* differs from the native AtAHASL protein by one amino acid substitution of a serine with an asparagine at residue 653 (S653N) which results in tolerance to imidazolinone containing herbicides. Besides the altered herbicide binding, the protein retains its biological function in the plant. Soybean line CV127 is tolerant to herbicides that contain imidazolinone. The another example is the mutations in soybean microsomal omega-3 fatty acid desaturase genes which resulted in reduce of linolenic acid concentration in soybean seeds (Bilyeu *et al*., 2005). Alternatively, several studies suggested that many diseases resistant alleles like soybean aphid [*Aphis glycines* Matsumura (Hemiptera: Aphididae)] resistance like *Rag1* from Germplasm collection (Kim *et al.*, 2010), brown Stem Rot resistance like *Rbs1* and *Rbs3* from soybean lines L78-4049 and PI 437.833, and PI 84946-2 (Eathington *et al*., 1995; Klos *et al.,* 2000), soybean cyst nematode (SCN) resistance genes like *rhg*1 and *Rhg*4 *from soybean* lines PI 88788, PI 437.654, Peking, PI90763 and PI209332, sudden death syndrome (SDS) resistance

like Rfs1, rfs2, and rft from soybean lines PI 437654 ( Meksem *et al*., 2001).

Two major approaches are available for the identification of sequence polymorphisms for a given gene in the naturally occurring populations: (1) modified Targeting Induced Local

In the TILLING approach, the polymorphisms (more specifically point mutations) resulting from induced mutations in a target gene can be identified by heteroduplex analysis (Till *et al*. 2003). This technique represents a means to determine the extent of variation in mutations artificially induced. EcoTilling represents a means to determine the extent of natural variation in selected genes in the primary and secondary crop gene pools (Comai and Henikoff, 2006 and Kumar *et al.* 2010). Like TILLING, it also relies on the enzymatic cleavage of heteroduplexed DNA, formed due to single nucleotide mismatch in sequence between reference and test genotype, with a single strand specific nuclease under specific conditions followed by detection through Li-Cor genotypers. At point mutations, there will be a cleavage by the nuclease to produce two cleaved products whose sizes will be equal to the size of full length product. The presence, type and location of point mutation or SNP will be confirmed by sequencing the amplicon from the test genotype that carry the mutation.

This technique involves amplification of alleles in diverse genotypes through PCR followed by identification of nucleotide variation by DNA sequencing. Sequencing-based allele

Lesions in Genomes (TILLING) procedure and (2) sequencing based allele mining.

**7.2 Approaches** 

**7.2.1 TILLING approach** 

**7.2.2 Sequencing-based allele mining** 

genetic resources in crop improvement (Graner, 2006).

(Brown-Guedira *et al*., 2000; Narvel *et al*., 2000; Fu *et al.,* 2007; Hwang *et al*., 2008). Baranek *et al*. (2002) evaluated genetic diversity of 19 G*lycine max* accessions from the Czech National Collection using RAPD markers. Recently, Tavaud-Pirra *et al.* (2009) evaluated SSR diversity of 350 cultivated soybean genotypes including 185 accessions from INRA soybean collection originating from various European countries and 32 cultivars and recent breeding lines representing the genetic improvement of soybean in Western Europe from 1950 to 2000. They found the genetic diversity of European accessions to be comparable with those of the Asian accessions from the INRA collection, whereas the genetic diversity observed in European breeding lines was significantly lower. Breeding material and registered soybean cultivars in southeast European countries are strongly linked to Western breeding programs, primarily in the USA and Canada. There is little reliable information regarding the source of germplasm introduction, its pedigree and breeding schemes applied. Consequently, use of these genotypes in making crosses to develop further breeding cycles can result in an insufficient level of genetic variability. Assessing the genetic diversity of this germplasm at genomic DNA level would complement the knowledge on the European soybean gene pool (germplasm) and facilitate the utilization of the resources from southeastern Europe by soybean breeders. Ristova *et al*. (2010) therefore assess genetic diversity and relationships of 23 soybean genotypes representing several independent breeding sources from southeastern Europe and five plant introductions from Western Europe and Canada using 20 SSR markers. Cluster analysis clearly separated all genotypes from each other assigning them into three major clusters, which largely corresponded to their origin. Results of clustering were mainly in accordance with the known pedigrees.
