Assessment of genetic variation in tomato

JOURNAL OF

GENETICS AND GENOMICS J. Genet. Genomics 35 (2008) 373−379

www.jgenetgenomics.org

Assessment of genetic variation in tomato (Solanum lycopersicum L.) inbred lines using SSR molecular markers Solomon Benor a, b, 1, Mengyu Zhang a, 1, Zhoufei Wang a, Hongsheng Zhang a, * a

b

State Key Lab of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China Department of Agrobiodiversity, Institute of Crop Science, University of Kassel, 34109 Kassel, Germany; and Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Gatersleben, Germany Received for publication 26 November 2007; revised 29 February 2008; accepted 29 February 2008

Abstract A study was conducted to determine the genetic diversity of 39 determinate and indeterminate tomato inbred lines collected from China, Japan, S. Korea, and USA. Using 35 SSR polymorphic markers, a total of 150 alleles were found with moderate levels of diversity, and a high number of unique alleles existing in these tomato lines. The mean number of alleles per locus was 4.3 and the average polymorphism information content (PIC) was 0.31. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) clustering at genetic similarity value of 0.85 grouped the inbred lines into four groups, where one USA cultivar formed a separate and more distant cluster. The most similar inbred lines are from USA, both with determinate type, whereas the most different lines are from USA (Us-16) and Japan (Ja-2) with determinate and indeterminate growth habit, respectively. Clustering was consistent with the known information regarding geographical location and growth habit. The genetic distance information reported in this study might be used by breeders when planning future crosses among these inbred lines. Keywords: Solanum lycopersicum L.; SSR markers; genetic diversity; growth characterization

Introduction Tomato (Solanum lycopersicum L., formerly Lycopersicon esculentum L.), originated from South America, in the Andes Mountains of Peru, Ecuador, and Chile, is nowadays one of the most economically important and widely grown plants in Solanaceae family. Botanically, it is a fruit and horticulturally it is a vegetable. The popularity of tomato as fresh and processed crop has made it an important source of vitamin A and C in diets. In addition to its worldwide agricultural and economic importance as a crop, tomato is a pre-eminent model system for genetic studies in plants. Deoxyribonucleic acid (DNA) polymorphisms provide a powerful tool for quantifying the existing levels of genetic variation in plant germplasm, either cereals or vege* Corresponding author. Tel: +86-25-8439 9269, Fax: +86-25-8439 6326. E-mail address: [email protected] 1 These authors contributed equally to this work.

tables. Molecular markers can provide an effective tool for efficient selection of desired agronomic traits because they are based on the plant genotypes and thus, are independent of environmental variation. Nowadays, several molecular markers are developed, of which simple sequence repeats (SSRs) or microsatellites are the most widely used types. It is suggested that the variation or polymorphism of SSRs are a result of polymerase slippage during DNA replication or unequal crossing over (Levinson and Gutman, 1987). SSRs are not only very common, also are hypervariable for numbers of repetitive DNA motifs in the genomes of eukaryotes (Hamada et al., 1984; Edwards et al., 1991; Vosman and Arens, 1997; Rallo et al., 2000; van der Schoot et al., 2000). The use of molecular markers can facilitate tomato breeding by means of marker assisted selection (MAS) to improve agronomically important traits such as yield, fruit quality, and disease resistance. In several studies the genetic diversity of tomato has been investigated using different molecular techniques. However, with the exception of SSRs, limited information was obtained because of the

Solomon Benor et al. / Journal of Genetics and Genomics 35 (2008) 373− 379

374

lack of variability that was ascribed to the self-pollinating nature of modern tomato cultivars combined with their narrow genetic base (Alvarez et al., 2001; Zhang et al., 2003). The work of Smulders et al. (1997), Bredemeijer et al. (2002), He et al. (2003), Frary et al. (2005), Garcia-Martinez et al. (2006) and Song et al. (2006) confirmed the utility of SSRs for studying genetic diversity and variability in the genus Solanum and for selecting tomato cultivar. Up to now, only few studies have approved the genetic diversity among the tomato inbred lines collected from diverse geographical provenance (He et al., 2003; Frary et al., 2005; Jin et al., 2006; Song et al., 2006), but little research has been done in analyzing the genetic similarity between determinate and indeterminate tomato in bred lines. In this study, we evaluated molecular diversity of determinate and indeterminate tomato inbred lines, col-

lected from four different countries representing two continents, using 60 SSR markers.

Materials and methods Plant materials Thirty-nine determinate and indeterminate tomato inbred lines were obtained from China National Seed Group Corporation (Beijing, China), where the tomato seeds were kept in the medium-term germplasm conservation centre after several generations of self crossing. These lines originated from four geographical origins (Table 1) and consisted of seven (six determinate and one indeterminate) Chinese inbred lines. The other set consisted of three (two

Table 1 Plant materials and their origin used in this study No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 a

Code in this study Ch-1 Ch-2 Ch-3 Ch-4 Ch-5 Ch-6 Ch-7 Ko-1 Ja-1 Ko-2 Ko-3 Ja-2 Ja-3 Ja-4 Ja-5 Ja-6 Us-1 Us-2 Us-3 Us-4 Us-5 Us-6 Us-7 Us-8 Us-9 Us-10 Us-11 Us-12 Us-13 Us-14 Us-15 Us-16 Us-17 Us-18 Us-19 Us-20 Us-21 Us-22 Us-23

Inbred line code V06A1445 V06A1446 V06A1447 V06A1448 V06A1449 V06A1450 V06A1778 V06A1451 V06A1452 V06A1453 V06A1454 V06A1443 V06A1444 V06A1455 V06A1458 V06A1459 Q01M Q01F T01M T01F GWL009 GWL010 GWL011 GWL012 GWL013 GWL015 GWL016 GWL017 GWL019 GWL020 GWL021 GWL022 GWL023 GWL024 GWL025 GWL026 GWL027 GWL028 GWL029

Growth habit: determinate (D) or indeterminate (I).

Fruit shape Oval Round Long round Long round Long round Round Oblate Long round Round Round Round Long round Long round Round Round Oblate Plum Plum Cylindrical Oval Oblate Oblate Oval Round Oblate Round Oval Oval Oval Oval Oblate Round Round Oval Round Oblate Round Globe Long round

Av. fruit size (g) 125 200 50 60 50 225 112 12 25 12 17 12 15 20 15 12 50 50 60 60 225 150 90 125 275 150 60 60 60 16 85 8 110 110 225 300 85 65 60

Growth habit a D D D I D D D I D D D I I I I I D D D D D D D D I D D D D D D D D D I I D D D

Origin China China China China China China China Korea Japan Korea Korea Japan Japan Japan Japan Japan USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA


determinate and one indeterminate) lines from S. Korea, six (one determinate and five indeterminate) lines from Japan, and 23 (twenty determinate and three indeterminate) lines from USA. All these inbred lines were currently grown in the commercial or used as parents for hybrid cultivars. Seeds from each of the lines were sown in a plastic pot under greenhouse condition. One month after sowing, the leaves were collected from five plants each inbred line and bulked a sample for DNA isolation. DNA isolation Total genomic DNA was isolated from the bulked fresh leaves by potassium acetate extraction method (Scott et al., 1993) with a few modifications intended to improve the quality of DNA: two consecutive extractions with Phenol:Choloroform (25:24) were carried out by an additional wash of 97% (left at –20oC for 30 min) and 70% pre-cooled ethanol, respectively. DNA yield and quality were assessed by gel electrophoresis using standard DNA marker DL 15,000 bp.

lated according to the formula PIC = 1 - ∑pi2, where pi is the frequency of the ith allele for each SSR marker locus in the set of 39 tomato inbred lines investigated (Weir, 1990). Genetic similarity estimation and cluster analysis All distinct DNA fragments were scored as present (1) or absent (0) for each of the markers. The genetic similarity (Gs) estimates between two cultivars i and j was estimated following Nei and Li (1979), which is defined as Sij = 2Nij/(Ni + Nj), where Nij is the number of bands present in the cultivars i and j, and Ni and Nj representing the number of bands present in cultivar i and j, respectively. For phylogenetic analysis, data only from the polymorphic SSR loci were subjected to MVSP (Kovach, 1999) statistical software. All the 39 inbred lines were clustered based on the estimated genetic distance, and the phylogenetic analysis was carried out with the clustering method of the Unweighted Pair Group Method Using Arithmetic Average (UPGMA).

SSR markers and protocol

Results

Sixty SSR markers, on the basis of their repeat patterns (di-, tri-, tetra-, penta-, and hexa-nucleotide) were selected among the more polymorphic published so far: 35 tomato primers from He et al. (2003), 24 tomato primers from Song et al. (2006), which were originally screened from Solanum genomics network (http://www.sgn.cornell.edu) and one primer from Roy et al. (2006). These three sets of paired primers were commercially provided by SBS Gene, Shanghai, China. Amplification reactions were carried out in a total volume of 25 μL, which contained 10 ng genomic DNA, 0.32 μmol/L of each primer, 100 μmol/L deoxyribonucleotides, 50 mmol/L KCl, 20 mmol/L Tris-HCl (pH 8.4), 1.5 mmol/L MgCl2, and 1 U Taq DNA polymerase (Tiangen, Shanghai, China). The reactions were carried out in 96-well plates in Peltier Thermal Cycler with the following cycling conditions: one cycle of 94oC for 5 min; 35 cycles of 55oC for 1 min, 72oC for 2 min, and 94oC for 1 min. After the final cycle, 1 cycle of 55oC for 1 min and 72oC for 7 min was added. The PCR amplification products were verified by 8% polyacrylamide gel electrophoresis (PAGE), and time of electrophoresis runs were adjusted for each SSR, depending on its size. Bands were seen by silver nitrate staining. Allele size was determined with the use of 50 bp ladder of Tiangen (China). To confirm reproducibility, each marker was amplified with tomato lines twice.

Characteristics of SSR markers

Data collection and analysis To measure the marker polymorphism, the polymorphism information content (PIC) for each SSR was calcu-

375

Sixty microsatellite markers were used to test the genetic diversity of 39 inbred lines. Nineteen (31.7%) primers failed to amplify the expected PCR fragments and six (10%) markers amplified monomorphic banding patterns. The remaining 35 (58.3%) markers, which generated polymorphic banding patterns, were used in the analysis of genetic diversity. A total of 150 alleles were detected by these polymorphic markers. The mean PIC for the 35 SSR markers was 0.31, with values ranging from 0.050 for the primers SSR74, SSR75, SSR80, and SSR136 to 0.602 for the primer AW037347. The number of alleles per locus varied from 1 for TMS33 and LEata004 to 8 for SSR47, SSR139, and LEttc002 with a mean of 4.3 alleles per locus (Tables 2 and 3). The majority of polymorphic SSR loci generated two (20%) and five (20%) alleles, followed by four alleles (17%). Most of the SSR loci, for these tomato samples, contained di- (54.3%) and tri-nucleotide (31.4%) repeats and only 14.29 % of them had tetra-, penta-, and hexa-nucleotide repeats (Tables 2 and 4). The TA and AT were the most common repeat types followed by GA and AAT, respectively (Table 5). Genetic diversity levels The average genetic similarity among the tomato inbred lines was 0.71 with the values ranging from 0.45 between Us-16 and Ja-2 to 0.98 between Us-4 and Us-2. The most similar inbreds reported above are from USA, both with determinate type, whereas the most different are from USA


376

Table 2 Polymorphic simple sequence repeat markers used in this study No. SSR name Core motif 1 AI773078 (aat)14 2

AI778183

(aat)12

3

AW037347

(aat)12

4

AI491065

(at)9

5

Y09371

(at)12

6

AW034362

(cag)7

7

AI780156

(ct)12

8

X90937

(ctat)8

9

TMS26

(ga)20

10

TMS33

(ga)26 imperfect

11

TMS37

(ga)21(ta)20

12

TMS9

(gata)26

13

AI895126

(ta)9

14

AW031453

(ta)20

15

AQ368062

(ta)19

16

U81996

(ta)14

17

X13437

(ta)5

18

X90770

(ta)20

19

Y08306

(ta)11

20

TMS48

(ga)24(ta)31 imp erfect

21

AI486387

(tat)12

22

SSR47

(at)14

23

SSR80

(tttcaa)2, (gtacaa)2, (caa )7

24

SSR139

(aga)2, (gaa)7

25

LEata004

(ata)8

26

LEttc002

(ac)3(ttc)6 imp

27

SSR50

(tc)6, (ccttc)2

28

SSR74

(tct)7

29

SSR136

(cag)7

30

SSR9

(ata)10

31

SSR75

(aat)9

32

SSR572

(tc)11

33

Tom236-237

(at)16

34

LEat014

(at)9

35

AY562123

(ta)10

F: forward primer; R: reverse primer.

Primer sequence (5′→3′) F: gat gga cac cct tca att tat ggt R: tcc aag tat cag gca cac cag c F: gcg aag aag atg agt cta gag cat ag R: ctc tct ccc atg agt tct cct ctt c F: gcc acg tag tca tga tat aca tag R: gcc tcg gac aat gaa ttg F: act gca ttt cag gta cat act ctc R: ata aac tcg tag acc ata ccc tc F: tga gaa caa cgt tta gag gag ctg R: cgg gca gaa tct cga act c F: ccg cct ctt tca ctt gaa c R: cca gcg ata cga tta gat acc F: tcc aat ttc agt aag gac ccc tc R: ccg aaa acc ttt gct aca gag tag a F: tgc cca tga cgt tcc atc R: gac aga cag aga gac aga ctt aga g F: ttc ggt tta ttc tgc caa cc R: gcc tgt agg att ttc gcc ta F: agc atg gga aga aga cac gt R: ttg agc aaa aca tcg caa tc F: cct tgc agt tga ggt gaa tt R: tca agc acc tac aat caa tca F: ttg gta att tat gtt cgg ga R: ttg agc caa ttg att aat aag tt F: gct ctg tcc tta caa atg ata cct cc R: caa tgc tgg gac aga aga ttt aat g F: gcc gtt ctt ggt gga tta g R: cct cct ttc gtg tct ttg tc F: tga tcc taa gct ttt tcc gtg agt R: caa gtt cac ctc att tca ccc ct F: agg ttg atg aaa gct aaa tct ggc R: caa cca cca atg ttc att aca aga c F: gag cac cca tta att tcg tta cg R: gtg gcg gat cta gaa att taa act g F: tgt aga taa ctt cct agc gac aat c R: acg gac gga tgg aca aat g F: aac ggt gga aac tat tga aag g R: cac cac caa acc cat cgt c F: att gct cat aca taa ccc cc R: ggg aca aaa tgg taa tcc at F: acg ctt ggc tgc ctc gga R: aac ttt att att gcc acg tag tca tga F: tcc tca aga aat gaa gct ctg a R: cct tgg aga taa caa cca caa F: ggc aaa tgt caa agg att gg R: agg gtc atg ttc ttg att gtc a F: tgg gta tgg gat tta cac caa R: aaa cga agg caa caa cga ag F: caa ctg gat agg tcg atg g R: gat gtg gat gaa acg gat g F: ttc tca cac ctg cac aca cc R: agc ggg atg att aca gaa atg F: ccg tga ccc tct tta caa gc R: ttg ctt tct tct tcg cca tt F: act cac cat ggc tgc ttc tt R: ttt ctt gaa ggg tct ttc cc F: gaa acc gcc tct ttc act tg R: cag caa tga ttc cag cga ta F: ccc ttt gca agt tct tct tca R: ttc atg agc caa cat agg agg F: cca tct att atc ttc tct cca aca c R: ggt ccc aac tcg gta cac ac F: aat tca cct ttc ttc cgt cg R: tgc aaa gaa caa aga ccg tg F: gtt ttt tca aca tca aag agc t R: gga tag gtt tcg tta gtg aac t F: tgt gtt gcg tca tta cca cta aac R: ccc aac cac caa tac ttt cc F: cct gtt gat gcc aat aat caa a R: att cca ctc aac cca aca aat g

Allele no. 4

Size (bp) 145−190

PIC 0.484

2

120−150

0.405

2

180−250

0.602

4

200−250

0.500

4

175−250

0.355

3

130−175

0.492

3

100−150

0.426

3

300−375

0.142

5

240−300

0.326

1

280−350

0.184

6

150−250

0.497

2

350−400

0.497

4

125−160

0.460

3

300−400

0.326

5

300−400

0.426

6

175−250

0.460

4

200−300

0.184

5

250−350

0.355

5

200−250

0.097

2

200−300

0.355

2

200−300

0.224

8

300−400

0.260

5

180−225

0.050

8

180−275

0.326

1

180−225

0.224

8

150−250

0.381

6

225−300

0.473

2

220−230

0.050

4

150−180

0.050

5

175−250

0.260

5

150−200

0.050

7

180−300

0.184

7

175−250

0.500

7

200−300

0.142

2

200−500

0.097


(Us-16) and Japan (Ja-2) with determinate and indeterminate growth habit, respectively (Table 1). Table 3 Allelic variation among polymorphic SSR loci Number of alleles

Number of SSR loci

1

2

Polymorphic loci (%) 5.71

2

7

20.00

3

4

11.43

4

6

17.14

5

7

20.00

6

3

8.57

7

3

8.57

8

3

8.57

Table 4 The number of nucleotides per repeat and number of polymorphic SSR loci Repeat

Number of SSR loci

Polymorphic SSR loci (%)

Di-nucleotide

19

54.3

Tri-nucleotide

11

31.4

≥ Tetra-nucleotide

5

14.3

Table 5 The major types of SSRs and the number of polymorphic loci SSR type

Total number

Polymorphic loci (% )

TA/AT

13

41.9

AAT/ATA

5

16.1

GA/CT

5

16.1

377

Genetic diversity pattern UPGMA cluster analysis of the 39 inbred lines using the 35 polymorphic loci resulted in the phenogram shown in Fig. 1, which has quite a good fit to the genetic similarity matrix. Four groups can be distinguished by truncating the dendrogram at genetic similarity value of 0.84. The major group (denoted group I) consisted of 28 genotypes. All the Chinese and most of the USA inbred lines were grouped this cluster. Another group (Group II) included two of the Japanese inbred lines (Ja-2 and Ja-5) and one USA (Us-14) line. Group III consisted of seven inbred lines: four from Japan (Ja-3, Ja-1, Ja-4, and Ja-6) and three from S. Korea (Ko-1, Ko-2, and Ko-3). One cultivar of USA (Us-16) is well separated from the other groups and formed Group IV. Genetic similarity between determinate and indeterminate types In the current study, tomato inbred lines with 29 determinate and 10 indeterminate growth habits were included. All genetic groups had members with both determinate and indeterminate growth habits except for the fourth cluster that had only (determinate) accession. As shown in Fig. 1, a striking subgroup similarity was obtained between inbred lines with the same growth habit. When we see, for example, the result of indeterminate types, two inbred lines, Us-19, and Us-20, formed a separate subgroup under group I. The same pattern of distinct subgroup was obtained under group II with the two indeterminate inbred lines of Ja-2 and Ja-5. Similarly in group III, two distinct

Fig. 1 Genetic distances obtained using 35 SSR markers constructed by UPGMA clustering of Nei and Li (1979).

378


subgroups were formed: the first between inbred lines of Ko-1 and Ja-6 and the other distinct subgroup between Ja-3 and Ja-4. Out of the 10 indeterminate cultivar types, 8 (80%) of them formed a subcluster with their own growth habit, whereas only 2 (20%) were subgrouped with determinate types: Us-9 (indeterminate) with the Us-23 (determinate), and Ch-4 (indeterminate) with Us-21 (determinate).

Discussion In this study, the average number of SSR alleles per locus for the 35 polymorphic loci was 4.3. The average PIC was 0.31, which confirms that SSR markers are highly informative. Smulders et al. (1997) reported, on average, 3 alleles per locus, after testing 30 SSR loci on seven inbred lines of tomatoes. He et al. (2003) also reported, on average, 2.7 alleles per locus and a PIC value of 0.37 after testing 17 varieties and 2 parental lines of tomato using 65 polymorphic SSR loci. The present average number of alleles per locus was higher than the result reported in the two studies cited above. In the phylogenetic analysis, most of the tomato inbred lines were clustered together in respect to their geographical location (Fig. 1), and thus, might have a similar genetic background. Those clustered within the same group or subgroups are mostly from the same origin and those, which are distantly grouped, were from different geographical locations. The mean genetic similarity matrix within Chinese lines, for example, (0.909), is much larger than that within Japanese (0.76) or S. Korean lines (0.80). Although Chinese lines are mostly related among themselves, UPGMA clustering analyses almost completely separated Chinese inbred lines from those of Japan and S. Korea. This finding was also supported by Song et al. (2006) and all the Chinese varieties formed a separate cluster. The Japanese inbred lines were clustered together except Ja-6 was distantly related to lines of the same origin and grouped it with S. Korean line Ko-1. Most of the US inbred lines were also subgrouped with their own lines. The clear relationship was also observed in similarity of the inbred lines in terms of their growth habit. In group I, the two indeterminate inbred lines Us-19 and Us-20 are both from USA. The two indeterminate inbred lines in group II (Ja-2 and Ja-5) are from Japan. In group III, the two indeterminate inbred lines Ja-3 and Ja-4 are both from Japan. However, in group III, the S. Korean indeterminate cultivar, Ko-1 was clustered with the Japanese indeterminate cultivar of Ja-6. Clustering with the same growth habit was also noticed in the case of determinate tomato inbred lines. The average genetic similarity matrix result was also consistent with clustering of the inbred lines with their growth habit.

Allelic variation might be correlated with the number of repeats within a particular microsatellite locus. A positive relationship was found between the number of repeats and the PIC of earlier reports in tomato (Smulder et al., 1997; Areshchenkova and Ganal, 1999; He et al., 2003). However, no such relationship was found in the present study. In this study, SSR47 with the lower PIC (0.26) has 14 repeats comparing to AW037347, which has PIC 0.60 with 12 repeats. Moreover, similar to the report of He et al. (2003), no relationship was found between PIC and the number of nucleotides per repeat. However, there are reports that the polymorphism level in tri-nucleotide repeats is lower than that in di-nucleotide repeats for rice (Blair et al., 1999) and ryegrass (Jones et al., 2001). Earlier studies on beans and other crops reported that the AT/TA repeat was the most-frequent type of SSR in plants, followed by the CT/GA repeat (Wang et al., 1994; Yu et al., 1999; Danin-Poleg et al., 2001). In this study, the most-frequent type of microsatellite repeat was the AT/TA repeat (41.9%), however, no difference was found between AAT/ATA, GA/CT, and CT/GA (each 16.1%). Our study has established that the SSR marker system is useful for studying genetic diversity among tomato inbred lines collected from diverse geographical locations. The combination of polymorphism and the large number of bands obtained per assay shows that SSR is the most informative marker system of tomato genotyping. In view of all the Chinese varieties forming a separate cluster, it is very helpful to use more exotic materials in tomato breeding.

Acknowledgements This work was supported by grants from Research and Advanced Training Fellowship Program of the Academy of Science for Third World Countries (TWAS), Italy and the Scholarship to Foreign Students of Nanjing Agricultural University, China. We would like to thank Professor Yuanming Zhang and Dr. Rients Niks for their suggestion on the first draft manuscript. References Alvarez, A.E, van de Wiel, C.C.M., Smulders, M.J.M., and Vosman, B. (2001). Use of microsatellites to evaluate genetic diversity and species relationships in the genus Lycopersicon. Theor. Appl. Genet. 103: 1283−1292. Blair, M.W., Panaud, O., and McCouch, S.R. (1999). Inter-simple sequence repeat (ISSR) amplification for analysis of microsatellite motif frequency and fingerprinting in rice (Oryza sativa L.). Theor. Appl. Genet. 98: 780−792. Bredemeijer, G.M.M., Arens, P., and Wouters, D. (1998). The use of semiautomated fluorescent microsatellite analysis for tomato cultivar identification. Theor. Appl. Genet. 97: 584−590. Danin-Poleg, Y., Reis, N., Tzuri, G., and Katzir, N. (2001). Develop-

Solomon Benor et al. / Journal of Genetics and Genomics 35(2008) 373− 379 ment and characterization of microsatellite markers in Cucumis. Theor. Appl. Genet.102: 61−72. Edwards, A., Civitello, A., Hammond, H.A., and Caskey, C.T. (1991). DNA typing and genetic mapping with trimeric and tetrameric tandem repeats. Am. J. Hum. Genet. 49: 746−756. Frary, A., Xu, Y., Liu, J., Mitschell, S., Tedeschi, E., and Tanksley, S. (2005). Development of a set of PCR-based anchor markers encompassing the tomato genome and evaluation of their usefulness for genetics and breeding experiments. Theor. Appl. Genet. 111: 291−312. Garcia-Martinez, S., Andreani, L., Gracia-Gusano, M., and Geuna, F. (2006). Evaluation of amplified fragment length polymorphism and simple sequence repast for tomato germplasm fingerprinting: Utility for grouping closely related traditional cultivars. Genome. 49: 648−656. Hamada, H., Petrino, M.G., Kakunaga, T., Seidman, M., and Stollar, B.D. (1984). Characterization of genomic poly(dT-dG) poly(dC-dA) sequences: Structure, organization and conformation. Mol. Cell. Biol. 4: 2610−2621. He, C., Poysa, V., and Yu, K. (2003). Development and characterization of simple sequence repeat (SSR) markers and their use in determining relationships among Lycopersicon esculentum cultivars. Theor. Appl. Genet. 106: 363−373. Jin, F.M., Xue, J., Jia, Y.H., and Liu, Z.Q. (2006). The cluster analysis on tomato germplasms. Acta Agri. Boreali-Sin. 21: 49−54 (in Chinese with an English abstract). Jones, E.S., Dupal, M.P., Kolliker, R., Drayton, M.C., and Forster, J.W. (2001). Development and characterisation of simple sequence repeat (SSR) markers for perennial ryegrass (Lolium perenne L.). Theor. Appl. Genet. 102: 405−415. Kovach, W. (1999). MVSP-A Multivariate Statistical Package for Windows, ver. 3.1. (Kovach Computing Services, Pentraeth, Wales, UK), pp. 133. Levinson, G., and Gutman, G.A. (1987). Slipped-strand mispairing: A major mechanism for DNA sequence evolution. Mol. Biol. Evol. 4: 203−221. Nei, M., and Li ,W.H. (1979). Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci.

379

USA 76: 5269−5273. Rallo, P., Dorado, G., and Martin, A. (2000). Development of simple sequence repeats (SSRs) in olive tree (Olea europaea L.). Theor. Appl. Genet. 101: 984−989. Roy, A., Bandyopadhyay, A., Mahapatra, A.K., Ghosh, S.H, Singh, N.K, Bansal, K.C, Koundal, K.R., and Mohapatra, T. (2006). Evaluation of genetic diversity in jute (Corchorus species) using STMS, ISSR and RAPD markers. Plant Breeding 125: 292−297. Scott, R.P., Zeigler, R.S., and Nelson, R.J. (1993). A procedure for miniscale preparation of Pyricularia grisea DNA. Intl. Rice Res. Notes 18: 47−48. Song, J., Chen, J., Chen, H.Y., Liu, Y., and Zhuang, T.M. (2006). Research of genetic diversity of tomato using SSR markers. Journal of Shanghai Jiaotong University 24: 524−528 (in Chinese with an English abstract). Smulders, M.J.M., Bredemeijer, G., Rus-Kortekaas, W., Arens, P., and Vosman, B. (1997). Use of short microsatellites from database sequences to generate polymorphisms among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species.Theor. Appl. Genet. 97: 264−272. van der Schoot, J., Pospiskova, M., and Vosman, B. (2000). Development and characterization of microsatellite markers in black poplar (Populus nigra L.). Theor. Appl. Genet. 101: 317−322. Vosman, B., and Arens, P. (1997). Molecular characterization of GATA/GACA microsatellite repeats in tomato. Genome 40: 25−33. Wang, Z., Weber, J.L., Zhong, G., and Tanksley, S.D. (1994). Survey of plant short tandem DNA repeats. Theor. Appl. Genet. 88: 1−6. Weir, B.S. (1990). Genetic data analysis-methods for discrete population genetics dData. (Sunderland: Sinauer Associates, Inc). Yu, K., Park, S.J., and Poysa, V. (1999). Abundance and variation of microsatellite DNA sequences in beans (Phaseolus and Vigna). Genome 42: 27−34. Zhang, H.Y., Yu, D.N., Wang, R.P., Li, M.F., and Li, Q.Z. (2003). An analysis of genetic diversity of the germplasm resources of L. esculentum and the application with RAPD. J. Plant Genet. Res. 4: 151−156 (in Chinese with an English abstract).