**6. Genetic diversity**

Genetic diversity analysis is necessary in plant breeding, plant systematics and evolution, plant pathology. SRAP is an adequate molecular marker system for genetic diversity analy‐ sis in plants and fungi. Since SRAP has many features such as simplicity, reliability, flexibili‐ ty, detection of multiple loci and cost-effectiveness, which allows beginners and experienced people to perform SRAP routinely with limited facilities or in well-established genomics labs. Since genome sequence information is not necessary for SRAP detection, SRAP can be used to perform genetic diversity analysis in a wide range of living organisms. We first used SRAP to analyze the genetic diversity of parental lines that were used to produce hybrid cultivars in *B. napus* (Riaz et al., 2001). As expected, we found that there was a positive cor‐ relation of genetic distance and hybrid performance. In celery, we used SRAP to tag a major resistance locus to celery mosaic virus (Ruiz et al., 2001).

In melons, Ferriol et al., (200) used SRAP and AFLP to analyze 69 accessions selected from morphotypes and unclassified types that belong to two subspecies, *Cucurbita pepo* ssp. *pepo* and ssp. *ovifera*. Among these accessions, some commercial cultivars and Span‐ ish landraces represent diversified types in Europe. Their results showed that SRAP markers characterized well the morphological variability and the evolutionary history of these tested accessions better than AFLP markers. Molecular markers were used to iden‐ tify new types for the development of new cultivars. The genetic diversity in the landra‐ ces of *C. pepo* spp. *ovifera* was detected with molecular markers, which is useful for preserving the diversity in this species.

In grasses, Budak et al., (2004a; 2004b; 2005) used SRAP to analyze genetic diversity and ploidy complexity in buffalograss. They found that SRAP markers were abundant and that they could distinguish genetic diversity among closely related cultivars. Their data showed that among several molecular markers (SSRs, ISSRs, SRAPs, and RAPDs), SRAP estimated the highest mean genetic dissimilarities in buffalograss. Additionally, they used SRAP and other markers to analyze ploidy complex and geographic origin of the *Buchloe dactyloides* genome and identified a significant correlation between the ploidy levels such as diploid, tetraploid, pentaploid, and hexaploid and the numbers of alleles detected using nuclear DNA markers. SRAP again was the best one among three molecular markers (ISSR, SSR, and SRAP, r = 0.39, 0.39, and 0.41).

Similarly, Gulsen et al., (2009) used SRAP, peroxidase gene polymorphism (POGP), ISSR and RAPD to study the relationship of ploidy levels, geographic locations and genetic di‐ versity in bermudagrass. They found that there was a significant correlation between ploidy levels in diploids, triploids, tetraploids, pentaploids, and hexaploids and band fre‐ quencies of molecular markers (r = 0.62, P < 0.001), suggesting that ploidy levels resulted in genome variation and genetic diversity. Geographic locations of Cynodon accessions also contributed to genetic diversity based on molecular marker analysis. They suggested that combining several molecular markers would be more efficient to evaluate genetic di‐ versity and genetic structure in bermudagrass and eventually broaden genetic basis for developing new cultivars.

huanpaa et al 2007). The concentration of toxic cadmium in oat grains is often over the ac‐ cepted limit and must be reduced. SRAP, RAPD and retrotransposon-microsatellite amplified polymorphism (REMAP) markers were used to perform BSA analysis in an F*2* population and four molecular markers were identified to be associated with cadmium con‐ centration in oat grains. All these four markers were located on the same linkage group, sug‐ gesting that this mapped QTL had major effect on grain cadmium concentration in oat.

Genetic diversity analysis is necessary in plant breeding, plant systematics and evolution, plant pathology. SRAP is an adequate molecular marker system for genetic diversity analy‐ sis in plants and fungi. Since SRAP has many features such as simplicity, reliability, flexibili‐ ty, detection of multiple loci and cost-effectiveness, which allows beginners and experienced people to perform SRAP routinely with limited facilities or in well-established genomics labs. Since genome sequence information is not necessary for SRAP detection, SRAP can be used to perform genetic diversity analysis in a wide range of living organisms. We first used SRAP to analyze the genetic diversity of parental lines that were used to produce hybrid cultivars in *B. napus* (Riaz et al., 2001). As expected, we found that there was a positive cor‐ relation of genetic distance and hybrid performance. In celery, we used SRAP to tag a major

In melons, Ferriol et al., (200) used SRAP and AFLP to analyze 69 accessions selected from morphotypes and unclassified types that belong to two subspecies, *Cucurbita pepo* ssp. *pepo* and ssp. *ovifera*. Among these accessions, some commercial cultivars and Span‐ ish landraces represent diversified types in Europe. Their results showed that SRAP markers characterized well the morphological variability and the evolutionary history of these tested accessions better than AFLP markers. Molecular markers were used to iden‐ tify new types for the development of new cultivars. The genetic diversity in the landra‐ ces of *C. pepo* spp. *ovifera* was detected with molecular markers, which is useful for

In grasses, Budak et al., (2004a; 2004b; 2005) used SRAP to analyze genetic diversity and ploidy complexity in buffalograss. They found that SRAP markers were abundant and that they could distinguish genetic diversity among closely related cultivars. Their data showed that among several molecular markers (SSRs, ISSRs, SRAPs, and RAPDs), SRAP estimated the highest mean genetic dissimilarities in buffalograss. Additionally, they used SRAP and other markers to analyze ploidy complex and geographic origin of the *Buchloe dactyloides* genome and identified a significant correlation between the ploidy levels such as diploid, tetraploid, pentaploid, and hexaploid and the numbers of alleles detected using nuclear DNA markers. SRAP again was the best one among three molecular markers (ISSR, SSR,

Similarly, Gulsen et al., (2009) used SRAP, peroxidase gene polymorphism (POGP), ISSR and RAPD to study the relationship of ploidy levels, geographic locations and genetic di‐

**6. Genetic diversity**

32 Plant Breeding from Laboratories to Fields

resistance locus to celery mosaic virus (Ruiz et al., 2001).

preserving the diversity in this species.

and SRAP, r = 0.39, 0.39, and 0.41).

In elephant grass, Xie et al., (2009) used SRAP markers to study the genetic diversity and relationships of commonly used cultivars in China. They generated 1,395 genetic loci with 62 SRAP primer combinations with an average of 22.5 genetic loci per primer combination. They found that SRAP loci were very polymorphic (72.8%) and used these SRAPs to esti‐ mate the genetic diversity within and between elephant grass cultivars. The results showed the genetic diversity within cultivars was less than that among tested cultivars and the rela‐ tionship of those tested cultivars was also estimated.

In cereal crops, Zaefizadeh and Goleiv (2009) analyzed genetic diversity and relationships among durum wheat landraces by SRAP marker and phenotypic differences. They used 65 SRAP markers and 27 traits to perform cluster analysis of 40 subconvars of *Triticum durum* landraces from the region of North West Iran and Azerbaijan. Traits failed to detect any geo‐ graphic association in durum landraces while 12 combinations of SRAP markers were dis‐ tinguishable among these landraces, suggesting that SRAP technology is useful for genetic diversity and evolutionary relationship analysis, marker assisted selection and genetic map construction in durum wheat. Yang et al., (2010) used SRAP markers to analyze the genetic diversity of hulless barley cultivars from Sichuan, Gansu, Tibet, Qinghai and Yunnan prov‐ inces of the Qinghai-Tibet Plateau in China. With 20 SRAP primer combinations, they de‐ tected 153 polymorphic loci and used these SRAP markers to classify 68 hulless barley accessions into four major groups using a unweighted pair-grouping method with arithmet‐ ic averages (UPGMA) analysis. They concluded that SRAP was an effective method to per‐ form genetic diversity in hulless barley and develop new cultivars.

In rice, Dai et al., (2012) developed indica- and japonica-specific markers using SRAP, TRAP, and SSR markers and performed genetic diversity analysis of Asian *Oryza sativa* varieties. In general, rice varieties are classified into *O. sativa* ssp. *japonica* kata and ssp. *indica* kata. In this report, they used 45 rice varieties in a cultivated and wild rice collection to study the genetic diversity in rice. By developing 90 indica- and japonica-specific genetic loci, they could easily distinguish typical indica and japonica subspecies and determined whether a domesticated rice variety came from the indica or japonica type.

In alfalfa, Vandemark et al.,(2006) used SRAP markers to analyze genetic relationships among historical sources of alfalfa germplasm in North American. Their results showed that SRAP detected highly polymorphic loci (>90%) in alfalfa, which distinguished nine original sources of Medicago germplasm based on genetic similarity calculated with SRAP markers. They suggested that SRAP technology is an adequate marker system for detecting polymorphisms in alfalfa.

In sesame, Zhang et al., (2010b) performed genetic diversity analysis using SRAP and SSR markers. They analyzed 404 landraces from a sesame collection in China. Using11 SRAP and 3 SSR markers, they produced 175 fragments, of which 126 were polymorphic with an aver‐ age polymorphism rate of 72%. They calculated several parameters such as Jaccard's genetic similarity coefficients, Nei's gene diversity and Shannon's information index and construct‐ ed a dendrogram with all the 404 landraces. According to the dendrogram, landraces from different agro-ecological zones did not cluster together, suggesting that geographical loca‐ tions did not represent the greater genetic variation among the sesame landraces. They con‐ cluded that SRAP and SSR markers would be useful to study sesame genetic diversity and understand the relationship of those indigenous landraces, which would guide the collec‐ tion, protection and utilization of sesame landraces in breeding purposes.

In banana and plantain, Youssef et al., (2011) used SRAP and AFLP markers to analyze 40 Musa accessions including commercial cultivars and wild species. They developed 353 SRAP and 787 AFLP markers to perform cluster analysis using an unweighted pair-group‐ ing method with arithmetic averages (UPGMA) and principal coordinate (PCO) analysis. They eventually assigned all the 40 accessions into corresponding *Eumusa*, *Australimusa*, *Cal‐ limusa* and *Rhodochlamys* sections and species. They found that SRAP and AFLP polymor‐ phism amongst sections and species and the relationships within *Eumusa* species and subspecies were not consistent and suggested that SRAP produced threefold more specific and unique loci than AFLP. Therefore, the data showed that SRAP markers were effective to distinguish *M. acuminata*, *M. balbisiana* and *M. schizocarpa* in the *Eumusa* section, and also triploid plantains and cooking bananas.

In grape, Guo et al., (2012) used SRAP markers to study genetic variability and relationships of cultivated wine-type *Vitis vinifera* and wild *Vitis* species. They selected 76 grape geno‐ types representing indigenous and new varieties and wild *Vitis* species from China and oth‐ er countries. After testing 100 SRAP primer combinations, they selected 19 primer combinations based on primer performance to produce 228 genetic loci, of which 78.63% were polymorphic with an average polymorphism information content value of 0.76. The SRAP markers were used to perform cluster analysis to evaluate Nei and Li's similarity coef‐ ficients by unweighted pair-group method of arithmetic averages (UPGMA) analysis. Addi‐ tionally, they performed principal coordinate analysis (PCoA) to plot all 76 grape genotypes which showed a similar cluster pattern to that in the dendrogram, representing their geo‐ graphical origins and taxonomic classification of these grape varieties. All the results indi‐ cated that three main groups including table grape of *V. vinifera*, table grape of Euro-America hybrids and wine grape of *V. vinifera*, wild *Vitis* species were identified and also the table *V. vinifera* group was genetically different from the wine-type *V. vinifera* and wild *Vitis* species originated from America and China. So they suggested that SRAP markers are infor‐ mative and grape germplasm in China contains abundant genetic diversity.

In medicinal plants, Ortega et al., (2007) analyzed genetic diversity of cultivated and non-cultivated mashua, *Tropaeolum tuberosum* that were grown in six communities in the Cusco region of Perú and selected from the germplasm collection at the International Po‐ tato Center (CIP) using SRAP markers. Mashua is used as a medicinal plant, possibly due to a high concentration of glucosinolates in mashua roots. DNA fingerprinting gen‐ erated by SRAP markers showed that mashua is a genetically variable crop. The genetic analysis also showed that most non-cultivated accessions were likely feral races resulting from escape from cultivation rather than wild relatives. In another medicinal plant, Wang et al., (2012) analyzed the genetic diversity of 35 wild goat's rue accessions (*Galega officinalis* L.) collected from Russia and Europe countries using ISSR and SRAP markers. Although there was some discrepancy between ISSR and SRAP markers, the clustering patterns of genotypes were relatively consistent between these two kinds of molecular markers in this study. They indicated that both markers were useful for goat's rue germ‐ plasm characterization, improvement, and conservation.

In sesame, Zhang et al., (2010b) performed genetic diversity analysis using SRAP and SSR markers. They analyzed 404 landraces from a sesame collection in China. Using11 SRAP and 3 SSR markers, they produced 175 fragments, of which 126 were polymorphic with an aver‐ age polymorphism rate of 72%. They calculated several parameters such as Jaccard's genetic similarity coefficients, Nei's gene diversity and Shannon's information index and construct‐ ed a dendrogram with all the 404 landraces. According to the dendrogram, landraces from different agro-ecological zones did not cluster together, suggesting that geographical loca‐ tions did not represent the greater genetic variation among the sesame landraces. They con‐ cluded that SRAP and SSR markers would be useful to study sesame genetic diversity and understand the relationship of those indigenous landraces, which would guide the collec‐

In banana and plantain, Youssef et al., (2011) used SRAP and AFLP markers to analyze 40 Musa accessions including commercial cultivars and wild species. They developed 353 SRAP and 787 AFLP markers to perform cluster analysis using an unweighted pair-group‐ ing method with arithmetic averages (UPGMA) and principal coordinate (PCO) analysis. They eventually assigned all the 40 accessions into corresponding *Eumusa*, *Australimusa*, *Cal‐ limusa* and *Rhodochlamys* sections and species. They found that SRAP and AFLP polymor‐ phism amongst sections and species and the relationships within *Eumusa* species and subspecies were not consistent and suggested that SRAP produced threefold more specific and unique loci than AFLP. Therefore, the data showed that SRAP markers were effective to distinguish *M. acuminata*, *M. balbisiana* and *M. schizocarpa* in the *Eumusa* section, and also

In grape, Guo et al., (2012) used SRAP markers to study genetic variability and relationships of cultivated wine-type *Vitis vinifera* and wild *Vitis* species. They selected 76 grape geno‐ types representing indigenous and new varieties and wild *Vitis* species from China and oth‐ er countries. After testing 100 SRAP primer combinations, they selected 19 primer combinations based on primer performance to produce 228 genetic loci, of which 78.63% were polymorphic with an average polymorphism information content value of 0.76. The SRAP markers were used to perform cluster analysis to evaluate Nei and Li's similarity coef‐ ficients by unweighted pair-group method of arithmetic averages (UPGMA) analysis. Addi‐ tionally, they performed principal coordinate analysis (PCoA) to plot all 76 grape genotypes which showed a similar cluster pattern to that in the dendrogram, representing their geo‐ graphical origins and taxonomic classification of these grape varieties. All the results indi‐ cated that three main groups including table grape of *V. vinifera*, table grape of Euro-America hybrids and wine grape of *V. vinifera*, wild *Vitis* species were identified and also the table *V. vinifera* group was genetically different from the wine-type *V. vinifera* and wild *Vitis* species originated from America and China. So they suggested that SRAP markers are infor‐

mative and grape germplasm in China contains abundant genetic diversity.

In medicinal plants, Ortega et al., (2007) analyzed genetic diversity of cultivated and non-cultivated mashua, *Tropaeolum tuberosum* that were grown in six communities in the Cusco region of Perú and selected from the germplasm collection at the International Po‐ tato Center (CIP) using SRAP markers. Mashua is used as a medicinal plant, possibly

tion, protection and utilization of sesame landraces in breeding purposes.

triploid plantains and cooking bananas.

34 Plant Breeding from Laboratories to Fields

In ornamental plants, Hao et al., (2008) used SRAP technology to perform genetic diversity analysis of 29 ornamental and medicinal Paeonia. Dendrogram and principle component analysis indicated that SRAP markers well characterized the genetic relationships of these 29 peony cultivars, which is useful to guide parent selection and molecular marker assisted se‐ lection in Paeonia breeding. In another ornamental plant, Feng et al., (2009b) performed ge‐ netic analysis of diversity and population structure of *Celosia argentea* and related species using SRAP markers. They included 16 populations of *C. argentea*. and 6 populations of *C. cristata*. from China. Using 10 SRAP primer combinations, they produced 507 scored bands, of which 274 were polymorphic. With UPGMA cluster analysis, they constructed a phyloge‐ netic tree and calculated genetic distances of all 22 populations. The results showed that the genetic distances of all populations were coincident with their geographic origins. Addition‐ ally, they identified one SRAP marker separating accessions in *C. argentea* from those in *C. cristata* and suggested that the extensive genetic diversity in *C. argentea* populations would be very useful for breeding and conservation of *C. argentea* varieties in the future.

In chrysanthemum, Zhang et al., (2011a) did a genetic diversity study on two flowering traits of chrysanthemum, initial blooming time and the duration of flowering. They identi‐ fied two pairs of major genes with high levels of inheritance. Using SRAP technology, they performed association mapping of these two traits and identified SRAP markers that were significantly associated with phenotypes, suggesting that SRAP markers might be useful in chrysanthemum breeding. In another report on ornamental plants, Soleimani et al., (2012) used wild, cultivated, and ornamental pomegranates (*Punica granatum* L.) in Iran to perform analysis of genetic diversity and population structure with SRAP molecular markers. They produced 133 SRAP markers with 13 SRAP primer combinations to evaluate the genetic di‐ versity of 63 pomegranate genotypes from five different geographical regions of Iran. Their data showed that the average polymorphism information content value was 0.28 and the ge‐ netic distance was 0.10 to 0.37 with an average of 0.24 in all 63 genotypes. Cluster analysis allowed them to identify the relationship between ornamental and wild genotypes. They found that the genetic variation of genotypes from various regions was bigger than that of intra regions. They concluded that SRAP markers could be an effective marker system in the analysis of genetic diversity and population structure in pomegranate.

In woody plants, Li et al., (2010) did genetic diversity analysis of sea buckthorn which is grown as a nutritious berry crop. They produced 191 polymorphic loci using SRAP technol‐ ogy to perform cluster analysis of 77 accessions, of which 73 *Hippophae rhamnoides* were clas‐ sified into 2 groups and 4 *H. salicifolia*, into 1 group. They associated SRAP markers with dried-shrink disease (DSD) resistance and suggested SRAP markers are useful for breeding new sea buckthorn lines with resistance to DSD. Feng et al., (2009a) reported on the genetic diversity analysis of *Pinus koraiensis* using SRAP markers. They obtained 24 to 33 loci per primer combination and used 143 SRAP markers to analyze 480 samples collected from 24 provinces in China. They found that there was no significant difference in genetic diversity among provinces. However, genetic variation of intra population accounted for 93.355% of the total variation.

In fungi, Sun et al., (2006) used SRAP markers to classify *Ganoderma lucidum* strains. They performed genetic diversity analysis with 31 accessions collected from several countries. Us‐ ing 75 polymorphic loci, they classified all 31 accessions into five groups. The results showed that *G. lucidum* strains were significantly different from *G. sinense* and *G. lucidum* in China, also different from *G. lucidum* in Yugoslavia. They suggested that SRAP markers are useful in taxonomy and systematics of Ganoderma strains within basidiomycetes. In anoth‐ er fungus, Tang et al., (2010) analyzed Chinese *Auricularia auricula* strains using SRAP and ISSR markers. They found both SRAP and ISSR markers were abundant in *A. auricula* and could be used to effectively distinguish all tested strains. After phylogenetic analysis, they classified 34 *A. auricula* strains into four or five major groups using the UPGMA method. They suggested that genetic diversity information would be used in *A. auricula* breeding programs to develop new medicinal mushroom. Fu et al., (2010) performed genetic diversity analysis in 23 elite *Lentinula edodes* strains from China using RAPD, ISSR and SRAP markers. In total, they used 16 RAPD primers, 5 ISSR primers and 23 SRAP primer combinations to produce 138, 77 and 144 bands, respectively. After UPGMA clustering analysis, they classi‐ fied all 23 *L. edodes* strains into three or four groups. However, all groups showed high lev‐ els of similarity, showing a low level of genetic diversity in all tested strains.
