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Genetic Diversity in Domestic and Introduced Wheats

Genetic Diversity in Domestic and Introduced Wheats DOI: 10.2478/agri-2013-0009 MARTINA HUDCOVICOVÁ 1*, KATARÍNA ONDREICKOVÁ 1, PAVOL HAUPTVOGEL 1, JÁN KRAIC 1,2 1 Plant Production Research Center Piesany University of SS. Cyril and Methodius in Trnava HUDCOVICOVÁ, M. ONDREICKOVÁ, K. HAUPTVOGEL, P. KRAIC, J.: Genetic diversity in domestic and introduced wheats. Agriculture (Ponohospodárstvo), vol. 59, 2013, no. 3, pp. 101­110. A set of 33 wheat EST­SSR markers was designed and 18 from them were polymorphic and used for assessment of genetic diversity within 36 introduced genotypes of hexaploid bread wheat. Altogether 105 alleles were detected, in average 3.18 alleles per locus. Maximum number of alleles 14 was detected at the locus TDI389708. Five the most polymorphic markers were used for the evaluation and comparison of genetic variation within 46 domestic (Slovak) wheat genotypes and 36 introduced (foreign) wheat genotypes. The number of alleles per used primer pair within domestic genotypes varied from 7 to 19, with an average of 13.2 alleles, an average gene diversity 0.846 and PIC 0.980 per locus. The number of alleles per primer within introduced genotypes varied from 7 to 14, with an average of 10.8 alleles, an average gene diversity 0.780 and PIC 0.958 per locus. The level of polymorphism in EST­ SSRs was sufficient for discrimination between genotypes and variation within domestic genotypes was slightly higher than in introduced genotypes. Variation revealed by 5 selected EST­SSR markers clustered genotypes according to origin. Domestic and introduced wheats were grouped distinctly into two separate groups. Key words: genetic diversity, EST-SSR, microsatellites, polymorphism, bread wheat The genetic diversity is one of the most important factors for survival and adaptability of all species. Commonly, it is evaluated by pedigree studies, phenotype traits, biochemical and genetic characteristics, and molecular markers. Especially DNA markers are widely used because they are not affected by environmental conditions and they are distributed over whole genome. Microsatellites termed also as simple sequence repeats (SSRs) have been proposed as one of the most valuable molecular markers for assessment of genetic variation. SSRs possess high information content, codominance, locus specificity, simple analysis, multiallelism, and distribution along all chromosomes (Gadaleta et al. 2009; Song et al. 2012). Large number of SSRs reside in tran- scribed regions of genomes including protein-coding genes and expressed sequence tags (ESTs), although in general, repeat numbers and total lengths of SSRs in these regions are relatively small (Kantety et al. 2002). Expressed Sequence Tags ­ Simple Sequence Repeats (EST­SSRs), in comparison with microsatellites located in non-coding regions (SSRs), reveal usually only half level of polymorphism but they have much higher information content, provide better description of genetic diversity, higher levels of transferability among related species (Gupta et al. 2003), and have high ability for genotypic identification (Song et al. 2012). EST­SSR markers have the potential to become markers revealing functional diversity and for this reason the number of subsequent Mgr. Martina Hudcovicová, PhD. (*Corresponding author), Mgr. Katarína Ondreicková, PhD., Ing. Pavol Hauptvogel, PhD., doc. RNDr. Ján Kraic, PhD., Plant Production Research Center Piesany, 921 68 Piesany, Bratislavská 122, Slovak Republic. E-mail: hudcovicova@vurv.sk doc. RNDr. Ján Kraic, PhD., University of SS. Cyril and Methodius in Trnava, 917 01 Trnava, Nám. J. Herdu 2, Slovak Republic analyses should be reduced. Microsatellites located within genes are critical elements for normal gene function, regulation and modulation of gene expression due to their extension or reduction in coding regions directly affecting phenotype manifestation (Li et al. 2004). EST­SSR markers have several advantages in comparison to SSRs located within the non-coding regions. They detect variation in coding sequences and represent ,,perfect markers" indicating status of genes, creation of EST-database is less expensive than genomic SSR-database and can be used for determination of more distant genetic relationships whereas the degree of variation in the coding regions is lower (Gupta et al. 2003; Yu et al. 2004). Hexaploid bread wheat (Triticum aestivum L.) as one of the world's most important crops shows very low level of intraspecific polymorphism and SSRs have been used as one of the most suitable markers also for the assessment of genetic diversity among bread wheat cultivars and lines (Akkaya & Buyukunal-Bal 2004; Gregáová et al. 2005; Gregáová et al. 2008; Huang et al. 2002; Prasad et al. 2000). Many ESTs for bread wheat are already available in the public domain (e.g. http://www. ncbEST_summary.html) usable for development of EST­SSR markers and evaluation of genetic diversity (Gupta et al. 2003) as well as for identification of bread wheat cultivars (Yang et al. 2005; Fujita et al. 2009). EST­SSRs were successfully used also for evaluation of genetic diversity in durum wheats (Eujayl et al. 2001; Wang et al. 2007), hard red spring wheats (Fu et al. 2006), tetraploid and diploid wheats (Gadaleta et al. 2011), and Persian wheats (Zhuang et al. 2011). Long-time process of breeding and selection decreased genetic variation in modern wheat cultivars due to loss of alleles and relevant traits including resistance against different biotic and abiotic factors (Fu et al. 2006; Zhuang et al. 2011). Breeding activities in specific climatic conditions practised with limited variation of parental genotypes could lead to reduction of genetic diversity in new-created and cultivated crops. This is very serious reason to evaluate genetic diversity within wheat collections, crucial for effective conservation of the gene pool, and following exploitation of genetic resources. Therefore the aim of this study was to: i) analyse genetic variation within coding regions in domestic (original Slovak) and introduced (foreign) bread wheat genotypes using the EST­SSR markers, ii) compare content of genetic variation between both subsets of wheats. MATERIAL AND METHODS Plant material and DNA isolation Forty-six domestic (Slovak) cultivars, breeding lines, landraces and 36 introduced (foreign) hexaploid wheat (Triticum aestivum L.) genotypes (Table 1) were used for study of genetic diversity. All were obtained from the Genebank of the Slovak Republic (Plant Production Research Center Piesany). The young fresh leaves were ground to a fine powder using liquid nitrogen, homogenized, and total plant DNA was extracted using the DNeasy Plant Maxi Kit (Qiagen, Germany). Sample of each genotype represented bulk DNA collected from 10­15 individual plants. Concentration and purity of isolated DNA were pre-measured by Nanodrop 1000 Spectrophotometer (Thermo Fischer Scientific Inc.) and samples were diluted to the same final concentration 25 ng/l. EST-SSR analysis Microsatellite sequences of wheat containing di-, tri-, and tetra-nucleotide motifs located in coding regions (Table 2) were obtained from the DNA sequence database GenBank (www.ncbi.nlm.nih. gov). The Primer3 software (http://frodo.wi.mit. edu, Rozen and Skaletsky 2000) was used to design 33 flanking primers according to the following criteria: primer length 18­27 bp with optimum 20 bp, annealing temperature 57­63°C with optimum 60°C, GC content 2080%, PCR product size 100­200 bp, dimers should be avoided as much as possible. PCR amplification was carried out in 20 l reaction mixture containing 1 × PCR buffer (InvitrogenTM), 1.5 mM MgCl2 (InvitrogenTM), 0.2 mM of each forward and reverse primer, 0.2 mM dNTP (InvitrogenTM), 0.8 U of Taq DNA polymerase (InvitrogenTM), and 1 l template DNA. Amplifications were run in the GeneAmp® PCR System 9700 (Applied Biosystems®) with the following conditions: T a b l e 1 List of analyzed wheat genotypes Label S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33 S34 S35 S36 S37 S38 S39 S40 S41 Genotype Diosecká 85-6 Diosecká NR Diosecká 1013 Balada Radosinská Lontovská Bucianska Slovenská skorá Samorínska Rada Blava Butin Danubia Ilona Kosútka Viginta Regia Solida Livia Torysa Sana Agra Roxana Iris Istra Solaris Barbara Kondor (SO-8527) Bucianska cervenoklasá Bucianska V.T.16 Bucianska 16/438 Bucianska 106 Bucianska 202 Bucianska 316 Bucianska 316/515 Calovská Kosútská Nový Zivot Radosinská Dorada Radosinská Karola Radosinska Norma Origin SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK Label S42 S43 S44 S45 S46 F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 Genotype Radosinská poloraná 562 Radosinská raná 594 Slovenská B Slovenská intenzívna Slovenská 2 Amazok AM 51/59 Arbola Boka Boundary Certo Clever Cortez Dekan Elpa Gene Charger Kraljevica Lu Mai Mironovskaja 30 Mobewa Molera MV Koma Ouragan Ovest Perlina Lesostepi Pizol Semper Soraja Sulamit Sultan 95 Svitava Titlis Toronit Tudest Zajecarská 75 Zlatica 4321.124.05 4632.44 4928.14 5021.16 Origin SVK SVK SVK SVK SVK FRA USA SWI CZE USA DEU GBR DEU AUT DEU USA GBR SRB CHI UKR POL SWI HUN FRA ITA UKR SWI NLD POL CZE USA CZE SWI SWI ITA SRB YUG NZL NZL NZL NZL T a b l e 2 ESTSSRs and their characteristics GenBank ID TDI389708 CV782464 CV782422 AY857761 CV782549 CV782428 CV782531 AY299458 AY170867 WHTGLNA TSP238590 CV782560 I. CV781665 TSP130948 I. CV782529 AF519168 AY162186 TUR512491 TSP130948 II. CV782580 CV782462 AY650054 AY575717 AY748826 AY702957 CV782526 AJ622894 WHTGLNA CV782560 II. TSP010830 TSP010829 TSP010829 AY625682 Gene product gliadin anonymous cDNA anonymous cDNA peroxidase 7 anonymous cDNA anonymous cDNA anonymous cDNA glutenin precursor protein Q / gliadin E2F protein anonymous cDNA anonymous cDNA gliadin anonymous cDNA Trn T, Trn L, Trn F proteins extracellular invertase sulphate transporter gliadin anonymous cDNA anonymous cDNA ferritin vacuolar invertase LMW glutenin protein Q anonymous cDNA dynamin related protein / gliadin anonymous cDNA GRAB 2 protein GRAB 1 protein GRAB 1 protein transcription factor Repetition (AAC)29 (AG)20 (GCCA)6 (CG)5 (CTT)6 (CCAT)5 (TGG)5 (ACA)6 (CCG)4 (CAA)7 (CCG)5 (CT)8 N3 (TG)5 (TG)10 (AAC)5 (CTC)6 (TAT)4 (GGAT)4 (CCA)6 (CAG)7 (CAA)13 (CGC)5 (GA)16 (CCG)5 (GGC)4 (ACA)4 (CCG)4 N14 (CCG)4 (TAGC)4 (AAG)6 (ACA)11 N1 (CAA)7 (GGC)7 (GCA)4 (GC)5 (AGG)4 (CTC)4 Primer sequence [5'-3'] CAGTGTGCAGCCATCCATAG ATAGTGGCAGCAGGATACGC GGCGTATTTAAGGTGCGTTC CATCTTGTCGGTCTGAGCTG ACGCGTCCGCTCTCTTTC CCAAGAACCGCAAAATCACT AGCAGAGCAGAATCCGGTAG GCGTAGTACCCGACCCTGAG TTAGGCCTATTTAGGTGATCCA CTGACAAGTCAGCGGAATCA GGCCTGAGGGCTATTTAGGT TCATCGCGAGGAACGAC AAGTTTGCTGCGGTACCATC CTTTGCCCGGACCTTATCTT CGCAGCAACCACTATTTTCA ACCTTGCATGGGTTTAGCTG TTACGCTGCAGCATCATCAG CAACAAGCGTTACCGACGAC TGTCAACAGCTGTGGCAGAT GTGGGTTTTGCTGAGATGGT AGCCCACCCACCTACCTC CCAGACATAAGCCCGATCTC TGCTTGTCCTCCCATCTCTT GTGAAATCATGGCCATCTCC GCAGTGCTGATCATATGTGGA AGATGCAGCAGCTGGCTAGT GGCCATCCACAAAGTTGTTC CCTGTGGGTTTTGCTGAGAT GTCCGCCGAGAAGAAGAAG CTAAATAGCGCAGGGAGGTG CCCTCTATCCCCAAATCCTC TCTTCGCATTCCTTTGTGAA GAGCAGGGCTCAAGCCTATT TGCTGTTCCGAGAAACAATG ACCGTCACACAGACAGCAAC GACCTCGGTTGGTCCTTGTA CACAACCGCAACCACAGTAT TTCCATGCGCTATGTTGTGT ATATCCGCACCAGGAATCAA TATTCGCAGAGGGTCTGGAG TCCAACCTCCACTGAGTGCT TGGAGGAGACAACACAGCAG GAGATGTTGCCTAGGGTTGC GAGCACCTCCTTCCCCTTC AAATCGTCGTCGATGGAGTC CACGACCAGCACCACCAC TCCTCGTCTTTGCCCTTCTA GGTGGTTGTTGAGGAAATGG TTACGCTGCAGCATCATCAG CAACAAGCGTTACCGACGAC CCGGCTTAACCACACTCATC CACAGCCTTGCTGTTGAGAC CCTGGGAAGACCATGAAAAA TTCTGGTTGATTTCCTGATCG CACAGTATCCGCAACCACAA ATCTTGCATGCGCTATGTTG GAGGGAGAAAGGGATGGAAG TTTGTGGAACGTCTGGATCA CTCATGGACTCTCCGTCTGG CCATAGCCTGGTAGGGTGAG TCGACGGAGAAGAAGAAGTGA CGAACCGGTAGAGGTCGAG ACCAGTGGGAGAAGATGCAG ACCTCCTCCTTGGGCAGTAT GCAGCATTTTTATGCAGTAGC AGGTGGGAACGGAATCAATA Ta [°C] 58 58 60 62 58 60 62 58 60 60 62 58 56 60 60 62 62 58 60 58 62 62 60 56 60 58 62 56 62 62 60 60 60 size [bp] 163 179 128 185 153 200 124 196 192 184 162 137 179 149 146 167 172 160 183 183 148 174 177 175 192 105 178 180 125 199 200 190 122 initial denaturation at 94°C for 4 min, 35 cycles at 94°C for 1 min, annealing temperature (Table 2) for 1 min, 72°C for 1 min, and final extension at 72°C for 10 min. Five microliters of the reaction mixture were loaded into 6% denatured polyacrylamide gels and microsatellites were stained by silver staining method (Bassam et al. 1991). Data analysis Polymorphic DNA fragments amplified with each ESTSSR primer pair were considered as different alleles and scored as present (1) or absent (0). Based on frequencies of alleles the index of diversity (DI) 1 Pij2 (Pij = frequency of the jth allele of the ith primer), the probability of identity (PI) p4i + (2pipj)2, and the polymorphic information context (PIC) 1 (p2i) (2p2ipj2) were calculated (Paetkau et al. 1995; Weber 1990; Weir 1990). The un-weighted pair group method of cluster analysis using arithmetic means (UPGMA) was used for grouping of genotypes. Dendrograms were constructed using the Jaccard's similarity coefficients by the statistic software package SPSS 8.0 (SPSS Inc., USA). Principal component analysis (PCA) was done using the statistical software Statgraphics Centurion XV.II. RESULTS AND DISCUSSION Analyses of 36 introduced wheat genotypes by 33 EST­SSRs Thirty-three EST­SSR primer pairs were tested within group of 36 introduced wheat genotypes and 18 of them revealed polymorphism. Altogeth- T a b l e 3 Polymorphism characteristics of EST-SSRs of analyses 36 introduced and 46 domestic wheat genotypes Introduced genotypes GenBank ID TDI389708 CV782464 CV782422 AY857761 CV782549 Average CV782428 CV782531 AY299458 AY170867 WHTGLNA TSP238590 CV782560 I. CV781665 TSP130948 CV782529 AF519168 AY162186 TUR512491 Average Number of alleles 14 12 12 7 9 10.8 6 4 3 3 3 3 2 2 2 2 2 2 2 3.18* DI 0.831 0.839 0.781 0.682 0.769 0.780 0.410 0.535 0.273 0.275 0.500 0.488 0.392 0.162 0.162 0.043 0.162 0.461 0.263 0.446 PI 0.013 0.012 0.038 0.124 0.023 0.042 0.371 0.333 0.576 0.534 0.382 0.400 0.414 0.715 0.715 0.917 0.715 0.365 0.577 0.401 PIC 0.987 0.988 0.962 0.876 0.977 0.958 0.388 0.446 0.239 0.262 0.390 0.389 0.349 0.149 0.149 0.042 0.149 0.393 0.229 0.465 Domestic (Slovak) genotypes Number of alleles 12 19 16 12 7 13.2 DI 0.875 0.911 0.900 0.855 0.687 0.846 PI 0.033 0.009 0.014 0.017 0.030 0.020 PIC 0.967 0.991 0.986 0.983 0.970 0.980 *average number of alleles per locus was calculated including 15 monomorphic loci Figure 1. The frequency distribution of analysed ESTSSR alleles er 105 alleles (including null alleles) were detected, with an average of 3.18 alleles per locus. Maximum number of alleles (14) was detected at the locus TDI389708. Diversity index varied from 0.043 for locus CV782529 (with PIC 0.042) to 0.839 for locus CV782464 (PIC = 0.988), with an average DI 0.446 and PIC = 0.465 per locus (Table 3). These results are comparable to others who revealed wheat genetic diversity by EST­SSRs (Eujayl et al. 2001; Fu et al. 2006; Fujita et al. 2009; Wang et al. 2007; Zhuang et al. 2011). Gregáová at el. (2005) evaluated genetic diversity of 44 bread wheat genotypes of the Slovak and Czech origin by 15 genomic SSRs. An average number of alleles was 6.33 per locus and average diversity index was 0.68 per locus. Lower EST­ SSR diversity within group of introduced wheat genotypes was found in our study. Lower numbers of alleles (1­5 per locus) and lower values of gene diversity (0.105­0.780 per locus) at the EST­SSR loci detected Gupta et al. (2003). Results of their analyses within 52 bread wheat genotypes showed lower polymorphism detected by EST­SSRs than by SSRs, which was found also by Eujayl et al. (2001), Fu et al. (2006), Gadaleta et al. (2009, 2011). Comparison of EST­SSR polymorphism in domestic (Slovak) and introduced (foreign) wheats Five the most polymorphic loci (TDI389708, CV782422, CV782464, CV782549, and AY857761) were used for the evaluation and comparison of genetic variation of 46 domestic wheats and 36 introduced genotypes. Numbers of alleles per each primer pair were relatively high (Table 3), overall 66 alleles for domestic and 54 for introduced genotypes (including the null alleles) were detected. Null alleles were detected in all loci besides the locus CV 782549 within domestic genotypes and besides loci AY857761 and TDI389708 within introduced genotypes. According to Cordeiro et al. (2001) high frequency of null alleles in the EST­SSRs may be due to deletion or substitution at the 5´-end of the primer binding site (Gadaleta et al. 2009). The number of alleles per locus within the domestic genotypes varied from 7 (locus CV782549 with gene diversity 0.687 and PIC = 0.970) to 19 (locus CV782464 with gene diversity 0.911 and PIC = 0.991) with average of 13.2 alleles, average gene diversity 0.846, and PIC = 0.980 per locus. The number of alleles per primer within introduced genotypes varied from 7 (locus AY857761 with gene diversity 0.682 and PIC = 0.876) to 14 (locus TDI389708 with gene diversity 0.831 and PIC = 0.987), with an average of 10.8 alleles, average gene diversity 0.780, Figure 2. The dendrogram of 46 domestic and 36 introduced wheat genotypes differen tiated by 5 EST-SSR markers (domestic genotypes highlighted by bold letters) and PIC = 0.958 per locus. In comparison with results of other authors these values are rather high as we used 5 selected the most polymorphic EST­SSR loci. Similar to this study Gupta et al. (2003) found that each primer pair gave multiple bands, and they suggested conservation of EST­SSRs in 2­3 related wheat genomes. This is in agreement with findings that one-quarter of all genes motifs within the wheat genome are represented by two or more duplicate loci (Akhunov et al. 2003). Eujayl et al. (2001) also showed that many durum wheat genotypes had 2 or 3 alleles due to their heterogeneity or heterozygosity as expected because genotypes were not pure inbred lines. Due to relatively high variation at five selected EST­SSR loci and high PIC values, the indices of probability had relatively low values (Table 3). DI and PIC values were slightly higher for domestic genotypes than for introduced ones, what shows rather high diversity within domestic group and can be connected to presence of not only cultivars, but also landraces and breeding lines within this group. The frequency distribution of all alleles within domestic and introduced genotypes shows Figure 1. The observed allelic frequencies ranged from 0.006 to 0.484 with an average 0.076 within domestic genotypes and from 0.028 to 0.500 with an average 0.093 within introduced genotypes. Fifty alleles (75.76%) within domestic genotypes and 42 alleles (77.78%) within introduced genotypes appeared with the frequencies of 0.10 or lower suggesting the evidence of mutation or introduction of new gene resource in a germplasm pool (Wang et al. 2007) Five of selected EST­SSRs were sufficient for definite distinguishing of all compared wheats. The cluster analysis based on the calculated Jaccard's coefficients (Figure 2) presents four main clusters (I.­IV.). Out of the 46 domestic wheats analyzed, forty-five were grouped into the clusters I., three of them into the cluster I.A and 42 genotypes formed separate the cluster I.B. Within Figure 3. PCA analysis was done using binary data of 46 domestic (Slovak = S) and 36 introduced (foreign = F) wheat genotypes using 5 the most polymorphic EST-SSRs (labelling of samples is according to Table 1) the cluster I.B several domestic genotypes with similar pedigree grouped to smaller subclusters (different lines of Bucianska and Slovenská). This classification partially shows grouping of genotypes according to their country of origin as well as to pedigree, similar as found by Eujayl et al. (2001) within durum wheats, or by Zhuang et al. (2011) within the Persian wheat accessions. The most similar wheat genotypes from all analyzed were Ovest (from Italy) and Pizol (Switzerland) in the cluster I.A. They differ by only one allele. Only a single domestic cultivar (Agra) was included into the cluster II., although placed close to other domestic wheats in dendrogram. This domestic cultivar is grouped together with wheat cultivars originated from the USA and China. The second largest is the cluster III. including 8 introduced wheats originating from different European countries and one cultivar from the USA. The cluster IV. consisted of only two wheats originating from the Czech Republic and Germany. PCA analysis better indicates differences between groups of domestic and introduced wheats (Figure 3). Introduced wheats showed slightly higher degree of diversity among themselves. In the group of introduced wheat genotypes separate smaller subgroups composed from one or two wheat genotypes were created. Simultaneously, cultivars Ovest and Pizol (F20 and F22), as in the dendrogram, showed great similarity by using the PCA analysis. Introduced cultivar Tudest from Italy (F30) is located in a group of domestic wheat cultivars, while the domestic cultivars form a distinct group separated from introduced. Group of domestic cultivars, contrary to introduced, has higher cohesion. of polymorphism in EST­SSRs was sufficient for discrimination between genotypes. Variation of domestic genotypes was slightly higher than those of introduced genotypes. Analysis based on used 5 EST­SSR markers showed clustering of genotypes according to origin, domestic and introduced wheats were grouped distinctly into two separate groups. Acknowledgements. This work originated thanks to the support within Operational Programme Research and Development for the project: "Transfer, use and dissemination of research results of plant genetic resources for food and agriculture" (ITMS: 26220220058), cofinanced from the resources of the European Union Fund for Regional Development. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agriculture de Gruyter

Genetic Diversity in Domestic and Introduced Wheats

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Abstract

DOI: 10.2478/agri-2013-0009 MARTINA HUDCOVICOVÁ 1*, KATARÍNA ONDREICKOVÁ 1, PAVOL HAUPTVOGEL 1, JÁN KRAIC 1,2 1 Plant Production Research Center Piesany University of SS. Cyril and Methodius in Trnava HUDCOVICOVÁ, M. ONDREICKOVÁ, K. HAUPTVOGEL, P. KRAIC, J.: Genetic diversity in domestic and introduced wheats. Agriculture (Ponohospodárstvo), vol. 59, 2013, no. 3, pp. 101­110. A set of 33 wheat EST­SSR markers was designed and 18 from them were polymorphic and used for assessment of genetic diversity within 36 introduced genotypes of hexaploid bread wheat. Altogether 105 alleles were detected, in average 3.18 alleles per locus. Maximum number of alleles 14 was detected at the locus TDI389708. Five the most polymorphic markers were used for the evaluation and comparison of genetic variation within 46 domestic (Slovak) wheat genotypes and 36 introduced (foreign) wheat genotypes. The number of alleles per used primer pair within domestic genotypes varied from 7 to 19, with an average of 13.2 alleles, an average gene diversity 0.846 and PIC 0.980 per locus. The number of alleles per primer within introduced genotypes varied from 7 to 14, with an average of 10.8 alleles, an average gene diversity 0.780 and PIC 0.958 per locus. The level of polymorphism in EST­ SSRs was sufficient for discrimination between genotypes and variation within domestic genotypes was slightly higher than in introduced genotypes. Variation revealed by 5 selected EST­SSR markers clustered genotypes according to origin. Domestic and introduced wheats were grouped distinctly into two separate groups. Key words: genetic diversity, EST-SSR, microsatellites, polymorphism, bread wheat The genetic diversity is one of the most important factors for survival and adaptability of all species. Commonly, it is evaluated by pedigree studies, phenotype traits, biochemical and genetic characteristics, and molecular markers. Especially DNA markers are widely used because they are not affected by environmental conditions and they are distributed over whole genome. Microsatellites termed also as simple sequence repeats (SSRs) have been proposed as one of the most valuable molecular markers for assessment of genetic variation. SSRs possess high information content, codominance, locus specificity, simple analysis, multiallelism, and distribution along all chromosomes (Gadaleta et al. 2009; Song et al. 2012). Large number of SSRs reside in tran- scribed regions of genomes including protein-coding genes and expressed sequence tags (ESTs), although in general, repeat numbers and total lengths of SSRs in these regions are relatively small (Kantety et al. 2002). Expressed Sequence Tags ­ Simple Sequence Repeats (EST­SSRs), in comparison with microsatellites located in non-coding regions (SSRs), reveal usually only half level of polymorphism but they have much higher information content, provide better description of genetic diversity, higher levels of transferability among related species (Gupta et al. 2003), and have high ability for genotypic identification (Song et al. 2012). EST­SSR markers have the potential to become markers revealing functional diversity and for this reason the number of subsequent Mgr. Martina Hudcovicová, PhD. (*Corresponding author), Mgr. Katarína Ondreicková, PhD., Ing. Pavol Hauptvogel, PhD., doc. RNDr. Ján Kraic, PhD., Plant Production Research Center Piesany, 921 68 Piesany, Bratislavská 122, Slovak Republic. E-mail: hudcovicova@vurv.sk doc. RNDr. Ján Kraic, PhD., University of SS. Cyril and Methodius in Trnava, 917 01 Trnava, Nám. J. Herdu 2, Slovak Republic analyses should be reduced. Microsatellites located within genes are critical elements for normal gene function, regulation and modulation of gene expression due to their extension or reduction in coding regions directly affecting phenotype manifestation (Li et al. 2004). EST­SSR markers have several advantages in comparison to SSRs located within the non-coding regions. They detect variation in coding sequences and represent ,,perfect markers" indicating status of genes, creation of EST-database is less expensive than genomic SSR-database and can be used for determination of more distant genetic relationships whereas the degree of variation in the coding regions is lower (Gupta et al. 2003; Yu et al. 2004). Hexaploid bread wheat (Triticum aestivum L.) as one of the world's most important crops shows very low level of intraspecific polymorphism and SSRs have been used as one of the most suitable markers also for the assessment of genetic diversity among bread wheat cultivars and lines (Akkaya & Buyukunal-Bal 2004; Gregáová et al. 2005; Gregáová et al. 2008; Huang et al. 2002; Prasad et al. 2000). Many ESTs for bread wheat are already available in the public domain (e.g. http://www. ncbEST_summary.html) usable for development of EST­SSR markers and evaluation of genetic diversity (Gupta et al. 2003) as well as for identification of bread wheat cultivars (Yang et al. 2005; Fujita et al. 2009). EST­SSRs were successfully used also for evaluation of genetic diversity in durum wheats (Eujayl et al. 2001; Wang et al. 2007), hard red spring wheats (Fu et al. 2006), tetraploid and diploid wheats (Gadaleta et al. 2011), and Persian wheats (Zhuang et al. 2011). Long-time process of breeding and selection decreased genetic variation in modern wheat cultivars due to loss of alleles and relevant traits including resistance against different biotic and abiotic factors (Fu et al. 2006; Zhuang et al. 2011). Breeding activities in specific climatic conditions practised with limited variation of parental genotypes could lead to reduction of genetic diversity in new-created and cultivated crops. This is very serious reason to evaluate genetic diversity within wheat collections, crucial for effective conservation of the gene pool, and following exploitation of genetic resources. Therefore the aim of this study was to: i) analyse genetic variation within coding regions in domestic (original Slovak) and introduced (foreign) bread wheat genotypes using the EST­SSR markers, ii) compare content of genetic variation between both subsets of wheats. MATERIAL AND METHODS Plant material and DNA isolation Forty-six domestic (Slovak) cultivars, breeding lines, landraces and 36 introduced (foreign) hexaploid wheat (Triticum aestivum L.) genotypes (Table 1) were used for study of genetic diversity. All were obtained from the Genebank of the Slovak Republic (Plant Production Research Center Piesany). The young fresh leaves were ground to a fine powder using liquid nitrogen, homogenized, and total plant DNA was extracted using the DNeasy Plant Maxi Kit (Qiagen, Germany). Sample of each genotype represented bulk DNA collected from 10­15 individual plants. Concentration and purity of isolated DNA were pre-measured by Nanodrop 1000 Spectrophotometer (Thermo Fischer Scientific Inc.) and samples were diluted to the same final concentration 25 ng/l. EST-SSR analysis Microsatellite sequences of wheat containing di-, tri-, and tetra-nucleotide motifs located in coding regions (Table 2) were obtained from the DNA sequence database GenBank (www.ncbi.nlm.nih. gov). The Primer3 software (http://frodo.wi.mit. edu, Rozen and Skaletsky 2000) was used to design 33 flanking primers according to the following criteria: primer length 18­27 bp with optimum 20 bp, annealing temperature 57­63°C with optimum 60°C, GC content 2080%, PCR product size 100­200 bp, dimers should be avoided as much as possible. PCR amplification was carried out in 20 l reaction mixture containing 1 × PCR buffer (InvitrogenTM), 1.5 mM MgCl2 (InvitrogenTM), 0.2 mM of each forward and reverse primer, 0.2 mM dNTP (InvitrogenTM), 0.8 U of Taq DNA polymerase (InvitrogenTM), and 1 l template DNA. Amplifications were run in the GeneAmp® PCR System 9700 (Applied Biosystems®) with the following conditions: T a b l e 1 List of analyzed wheat genotypes Label S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33 S34 S35 S36 S37 S38 S39 S40 S41 Genotype Diosecká 85-6 Diosecká NR Diosecká 1013 Balada Radosinská Lontovská Bucianska Slovenská skorá Samorínska Rada Blava Butin Danubia Ilona Kosútka Viginta Regia Solida Livia Torysa Sana Agra Roxana Iris Istra Solaris Barbara Kondor (SO-8527) Bucianska cervenoklasá Bucianska V.T.16 Bucianska 16/438 Bucianska 106 Bucianska 202 Bucianska 316 Bucianska 316/515 Calovská Kosútská Nový Zivot Radosinská Dorada Radosinská Karola Radosinska Norma Origin SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK SVK Label S42 S43 S44 S45 S46 F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24 F25 F26 F27 F28 F29 F30 F31 F32 F33 F34 F35 F36 Genotype Radosinská poloraná 562 Radosinská raná 594 Slovenská B Slovenská intenzívna Slovenská 2 Amazok AM 51/59 Arbola Boka Boundary Certo Clever Cortez Dekan Elpa Gene Charger Kraljevica Lu Mai Mironovskaja 30 Mobewa Molera MV Koma Ouragan Ovest Perlina Lesostepi Pizol Semper Soraja Sulamit Sultan 95 Svitava Titlis Toronit Tudest Zajecarská 75 Zlatica 4321.124.05 4632.44 4928.14 5021.16 Origin SVK SVK SVK SVK SVK FRA USA SWI CZE USA DEU GBR DEU AUT DEU USA GBR SRB CHI UKR POL SWI HUN FRA ITA UKR SWI NLD POL CZE USA CZE SWI SWI ITA SRB YUG NZL NZL NZL NZL T a b l e 2 ESTSSRs and their characteristics GenBank ID TDI389708 CV782464 CV782422 AY857761 CV782549 CV782428 CV782531 AY299458 AY170867 WHTGLNA TSP238590 CV782560 I. CV781665 TSP130948 I. CV782529 AF519168 AY162186 TUR512491 TSP130948 II. CV782580 CV782462 AY650054 AY575717 AY748826 AY702957 CV782526 AJ622894 WHTGLNA CV782560 II. TSP010830 TSP010829 TSP010829 AY625682 Gene product gliadin anonymous cDNA anonymous cDNA peroxidase 7 anonymous cDNA anonymous cDNA anonymous cDNA glutenin precursor protein Q / gliadin E2F protein anonymous cDNA anonymous cDNA gliadin anonymous cDNA Trn T, Trn L, Trn F proteins extracellular invertase sulphate transporter gliadin anonymous cDNA anonymous cDNA ferritin vacuolar invertase LMW glutenin protein Q anonymous cDNA dynamin related protein / gliadin anonymous cDNA GRAB 2 protein GRAB 1 protein GRAB 1 protein transcription factor Repetition (AAC)29 (AG)20 (GCCA)6 (CG)5 (CTT)6 (CCAT)5 (TGG)5 (ACA)6 (CCG)4 (CAA)7 (CCG)5 (CT)8 N3 (TG)5 (TG)10 (AAC)5 (CTC)6 (TAT)4 (GGAT)4 (CCA)6 (CAG)7 (CAA)13 (CGC)5 (GA)16 (CCG)5 (GGC)4 (ACA)4 (CCG)4 N14 (CCG)4 (TAGC)4 (AAG)6 (ACA)11 N1 (CAA)7 (GGC)7 (GCA)4 (GC)5 (AGG)4 (CTC)4 Primer sequence [5'-3'] CAGTGTGCAGCCATCCATAG ATAGTGGCAGCAGGATACGC GGCGTATTTAAGGTGCGTTC CATCTTGTCGGTCTGAGCTG ACGCGTCCGCTCTCTTTC CCAAGAACCGCAAAATCACT AGCAGAGCAGAATCCGGTAG GCGTAGTACCCGACCCTGAG TTAGGCCTATTTAGGTGATCCA CTGACAAGTCAGCGGAATCA GGCCTGAGGGCTATTTAGGT TCATCGCGAGGAACGAC AAGTTTGCTGCGGTACCATC CTTTGCCCGGACCTTATCTT CGCAGCAACCACTATTTTCA ACCTTGCATGGGTTTAGCTG TTACGCTGCAGCATCATCAG CAACAAGCGTTACCGACGAC TGTCAACAGCTGTGGCAGAT GTGGGTTTTGCTGAGATGGT AGCCCACCCACCTACCTC CCAGACATAAGCCCGATCTC TGCTTGTCCTCCCATCTCTT GTGAAATCATGGCCATCTCC GCAGTGCTGATCATATGTGGA AGATGCAGCAGCTGGCTAGT GGCCATCCACAAAGTTGTTC CCTGTGGGTTTTGCTGAGAT GTCCGCCGAGAAGAAGAAG CTAAATAGCGCAGGGAGGTG CCCTCTATCCCCAAATCCTC TCTTCGCATTCCTTTGTGAA GAGCAGGGCTCAAGCCTATT TGCTGTTCCGAGAAACAATG ACCGTCACACAGACAGCAAC GACCTCGGTTGGTCCTTGTA CACAACCGCAACCACAGTAT TTCCATGCGCTATGTTGTGT ATATCCGCACCAGGAATCAA TATTCGCAGAGGGTCTGGAG TCCAACCTCCACTGAGTGCT TGGAGGAGACAACACAGCAG GAGATGTTGCCTAGGGTTGC GAGCACCTCCTTCCCCTTC AAATCGTCGTCGATGGAGTC CACGACCAGCACCACCAC TCCTCGTCTTTGCCCTTCTA GGTGGTTGTTGAGGAAATGG TTACGCTGCAGCATCATCAG CAACAAGCGTTACCGACGAC CCGGCTTAACCACACTCATC CACAGCCTTGCTGTTGAGAC CCTGGGAAGACCATGAAAAA TTCTGGTTGATTTCCTGATCG CACAGTATCCGCAACCACAA ATCTTGCATGCGCTATGTTG GAGGGAGAAAGGGATGGAAG TTTGTGGAACGTCTGGATCA CTCATGGACTCTCCGTCTGG CCATAGCCTGGTAGGGTGAG TCGACGGAGAAGAAGAAGTGA CGAACCGGTAGAGGTCGAG ACCAGTGGGAGAAGATGCAG ACCTCCTCCTTGGGCAGTAT GCAGCATTTTTATGCAGTAGC AGGTGGGAACGGAATCAATA Ta [°C] 58 58 60 62 58 60 62 58 60 60 62 58 56 60 60 62 62 58 60 58 62 62 60 56 60 58 62 56 62 62 60 60 60 size [bp] 163 179 128 185 153 200 124 196 192 184 162 137 179 149 146 167 172 160 183 183 148 174 177 175 192 105 178 180 125 199 200 190 122 initial denaturation at 94°C for 4 min, 35 cycles at 94°C for 1 min, annealing temperature (Table 2) for 1 min, 72°C for 1 min, and final extension at 72°C for 10 min. Five microliters of the reaction mixture were loaded into 6% denatured polyacrylamide gels and microsatellites were stained by silver staining method (Bassam et al. 1991). Data analysis Polymorphic DNA fragments amplified with each ESTSSR primer pair were considered as different alleles and scored as present (1) or absent (0). Based on frequencies of alleles the index of diversity (DI) 1 Pij2 (Pij = frequency of the jth allele of the ith primer), the probability of identity (PI) p4i + (2pipj)2, and the polymorphic information context (PIC) 1 (p2i) (2p2ipj2) were calculated (Paetkau et al. 1995; Weber 1990; Weir 1990). The un-weighted pair group method of cluster analysis using arithmetic means (UPGMA) was used for grouping of genotypes. Dendrograms were constructed using the Jaccard's similarity coefficients by the statistic software package SPSS 8.0 (SPSS Inc., USA). Principal component analysis (PCA) was done using the statistical software Statgraphics Centurion XV.II. RESULTS AND DISCUSSION Analyses of 36 introduced wheat genotypes by 33 EST­SSRs Thirty-three EST­SSR primer pairs were tested within group of 36 introduced wheat genotypes and 18 of them revealed polymorphism. Altogeth- T a b l e 3 Polymorphism characteristics of EST-SSRs of analyses 36 introduced and 46 domestic wheat genotypes Introduced genotypes GenBank ID TDI389708 CV782464 CV782422 AY857761 CV782549 Average CV782428 CV782531 AY299458 AY170867 WHTGLNA TSP238590 CV782560 I. CV781665 TSP130948 CV782529 AF519168 AY162186 TUR512491 Average Number of alleles 14 12 12 7 9 10.8 6 4 3 3 3 3 2 2 2 2 2 2 2 3.18* DI 0.831 0.839 0.781 0.682 0.769 0.780 0.410 0.535 0.273 0.275 0.500 0.488 0.392 0.162 0.162 0.043 0.162 0.461 0.263 0.446 PI 0.013 0.012 0.038 0.124 0.023 0.042 0.371 0.333 0.576 0.534 0.382 0.400 0.414 0.715 0.715 0.917 0.715 0.365 0.577 0.401 PIC 0.987 0.988 0.962 0.876 0.977 0.958 0.388 0.446 0.239 0.262 0.390 0.389 0.349 0.149 0.149 0.042 0.149 0.393 0.229 0.465 Domestic (Slovak) genotypes Number of alleles 12 19 16 12 7 13.2 DI 0.875 0.911 0.900 0.855 0.687 0.846 PI 0.033 0.009 0.014 0.017 0.030 0.020 PIC 0.967 0.991 0.986 0.983 0.970 0.980 *average number of alleles per locus was calculated including 15 monomorphic loci Figure 1. The frequency distribution of analysed ESTSSR alleles er 105 alleles (including null alleles) were detected, with an average of 3.18 alleles per locus. Maximum number of alleles (14) was detected at the locus TDI389708. Diversity index varied from 0.043 for locus CV782529 (with PIC 0.042) to 0.839 for locus CV782464 (PIC = 0.988), with an average DI 0.446 and PIC = 0.465 per locus (Table 3). These results are comparable to others who revealed wheat genetic diversity by EST­SSRs (Eujayl et al. 2001; Fu et al. 2006; Fujita et al. 2009; Wang et al. 2007; Zhuang et al. 2011). Gregáová at el. (2005) evaluated genetic diversity of 44 bread wheat genotypes of the Slovak and Czech origin by 15 genomic SSRs. An average number of alleles was 6.33 per locus and average diversity index was 0.68 per locus. Lower EST­ SSR diversity within group of introduced wheat genotypes was found in our study. Lower numbers of alleles (1­5 per locus) and lower values of gene diversity (0.105­0.780 per locus) at the EST­SSR loci detected Gupta et al. (2003). Results of their analyses within 52 bread wheat genotypes showed lower polymorphism detected by EST­SSRs than by SSRs, which was found also by Eujayl et al. (2001), Fu et al. (2006), Gadaleta et al. (2009, 2011). Comparison of EST­SSR polymorphism in domestic (Slovak) and introduced (foreign) wheats Five the most polymorphic loci (TDI389708, CV782422, CV782464, CV782549, and AY857761) were used for the evaluation and comparison of genetic variation of 46 domestic wheats and 36 introduced genotypes. Numbers of alleles per each primer pair were relatively high (Table 3), overall 66 alleles for domestic and 54 for introduced genotypes (including the null alleles) were detected. Null alleles were detected in all loci besides the locus CV 782549 within domestic genotypes and besides loci AY857761 and TDI389708 within introduced genotypes. According to Cordeiro et al. (2001) high frequency of null alleles in the EST­SSRs may be due to deletion or substitution at the 5´-end of the primer binding site (Gadaleta et al. 2009). The number of alleles per locus within the domestic genotypes varied from 7 (locus CV782549 with gene diversity 0.687 and PIC = 0.970) to 19 (locus CV782464 with gene diversity 0.911 and PIC = 0.991) with average of 13.2 alleles, average gene diversity 0.846, and PIC = 0.980 per locus. The number of alleles per primer within introduced genotypes varied from 7 (locus AY857761 with gene diversity 0.682 and PIC = 0.876) to 14 (locus TDI389708 with gene diversity 0.831 and PIC = 0.987), with an average of 10.8 alleles, average gene diversity 0.780, Figure 2. The dendrogram of 46 domestic and 36 introduced wheat genotypes differen tiated by 5 EST-SSR markers (domestic genotypes highlighted by bold letters) and PIC = 0.958 per locus. In comparison with results of other authors these values are rather high as we used 5 selected the most polymorphic EST­SSR loci. Similar to this study Gupta et al. (2003) found that each primer pair gave multiple bands, and they suggested conservation of EST­SSRs in 2­3 related wheat genomes. This is in agreement with findings that one-quarter of all genes motifs within the wheat genome are represented by two or more duplicate loci (Akhunov et al. 2003). Eujayl et al. (2001) also showed that many durum wheat genotypes had 2 or 3 alleles due to their heterogeneity or heterozygosity as expected because genotypes were not pure inbred lines. Due to relatively high variation at five selected EST­SSR loci and high PIC values, the indices of probability had relatively low values (Table 3). DI and PIC values were slightly higher for domestic genotypes than for introduced ones, what shows rather high diversity within domestic group and can be connected to presence of not only cultivars, but also landraces and breeding lines within this group. The frequency distribution of all alleles within domestic and introduced genotypes shows Figure 1. The observed allelic frequencies ranged from 0.006 to 0.484 with an average 0.076 within domestic genotypes and from 0.028 to 0.500 with an average 0.093 within introduced genotypes. Fifty alleles (75.76%) within domestic genotypes and 42 alleles (77.78%) within introduced genotypes appeared with the frequencies of 0.10 or lower suggesting the evidence of mutation or introduction of new gene resource in a germplasm pool (Wang et al. 2007) Five of selected EST­SSRs were sufficient for definite distinguishing of all compared wheats. The cluster analysis based on the calculated Jaccard's coefficients (Figure 2) presents four main clusters (I.­IV.). Out of the 46 domestic wheats analyzed, forty-five were grouped into the clusters I., three of them into the cluster I.A and 42 genotypes formed separate the cluster I.B. Within Figure 3. PCA analysis was done using binary data of 46 domestic (Slovak = S) and 36 introduced (foreign = F) wheat genotypes using 5 the most polymorphic EST-SSRs (labelling of samples is according to Table 1) the cluster I.B several domestic genotypes with similar pedigree grouped to smaller subclusters (different lines of Bucianska and Slovenská). This classification partially shows grouping of genotypes according to their country of origin as well as to pedigree, similar as found by Eujayl et al. (2001) within durum wheats, or by Zhuang et al. (2011) within the Persian wheat accessions. The most similar wheat genotypes from all analyzed were Ovest (from Italy) and Pizol (Switzerland) in the cluster I.A. They differ by only one allele. Only a single domestic cultivar (Agra) was included into the cluster II., although placed close to other domestic wheats in dendrogram. This domestic cultivar is grouped together with wheat cultivars originated from the USA and China. The second largest is the cluster III. including 8 introduced wheats originating from different European countries and one cultivar from the USA. The cluster IV. consisted of only two wheats originating from the Czech Republic and Germany. PCA analysis better indicates differences between groups of domestic and introduced wheats (Figure 3). Introduced wheats showed slightly higher degree of diversity among themselves. In the group of introduced wheat genotypes separate smaller subgroups composed from one or two wheat genotypes were created. Simultaneously, cultivars Ovest and Pizol (F20 and F22), as in the dendrogram, showed great similarity by using the PCA analysis. Introduced cultivar Tudest from Italy (F30) is located in a group of domestic wheat cultivars, while the domestic cultivars form a distinct group separated from introduced. Group of domestic cultivars, contrary to introduced, has higher cohesion. of polymorphism in EST­SSRs was sufficient for discrimination between genotypes. Variation of domestic genotypes was slightly higher than those of introduced genotypes. Analysis based on used 5 EST­SSR markers showed clustering of genotypes according to origin, domestic and introduced wheats were grouped distinctly into two separate groups. Acknowledgements. This work originated thanks to the support within Operational Programme Research and Development for the project: "Transfer, use and dissemination of research results of plant genetic resources for food and agriculture" (ITMS: 26220220058), cofinanced from the resources of the European Union Fund for Regional Development.

Journal

Agriculturede Gruyter

Published: Sep 1, 2013

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