Bazı Ekmeklik Buğday (Triticum aestivum L.) Genotiplerinin Kuraklığa Tepkisinin SSR Markörleri ile Belirlenmesi

Öz

Bu çalışmada, 32 ekmeklik buğday genotipi, kuraklığa tepkileri açısından SSR markörleri kullanılarak değerlendirilmiştir. Tüm genotiplere on adet SSR primeri uygulanmış ve bunların yedisinin polimorfik olduğu belirlenmiştir. Toplam 25 polimorfik allel elde edilmiş, lokus başına allel sayısı 2 ile 6 arasında değişmiş ve SSR lokusu başına ortalama allel sayısı 3.6 olarak hesaplanmıştır. PIC değerleri 0.31 ile 0.97 arasında değişmiş ve ortalama 0.70 olarak bulunmuştur. En düşük ve en yüksek değerler sırasıyla Xbarc17 ve Xbarc12 primerlerinden elde edilmiştir. Genotipler arasındaki ikili genetik farklılık indeksleri minimum 0.083 ve maksimum 0.800 olarak belirlenmiştir. Bayraktar 2000 ve LR5 genotipleri, kuraklığa tolerant Gerek 79 çeşidine en yakın genotipler olurken; Sertak52 (C5) ile BL7 ve BL4 genotipleri ise kuraklığa tolerant Bayraktar 2000 çeşidine en yakın genotipler olarak belirlenmiştir. Sonuç olarak, bu çalışmada kullanılan genotiplerin ve SSR markörlerinin, gelecekte kuraklıkla ilgili ıslah çalışmaları ve genetik çalışmalar için ön verilerin oluşturulmasına yardımcı olacağı düşünülmektedir

Anahtar Kelimeler

• ekmeklik buğday
• ıslah
• kuraklık SSR markörleri

Destekleyen Kurum

Selçuk Üniversitesi Bilimsel Araştırmalar Koordinatörlüğü

Proje Numarası

13201040

Etik Beyan

Gerek yok

Genetic Diversity of Some Bread Wheat (Triticum aestivum L.) Genotypes Using SSR Markers Associated with Drought

Öz

This study aimed to assess the genetic diversity of 32 bread wheat genotypes using SSR markers associated with drought. In the study, 10 SSR primers were applied to all genotypes; BARC 024, WMC 9, and WMC 603 showed monomorphic patterns, while seven primers were polymorphic. In total, 25 polymorphic alleles were detected, with the number of alleles per locus ranging from 2 to 6 and a mean of 3.6 alleles per SSR locus. PIC (Polymorphic Information Content) values ranged from 0.31 to 0.97, with a mean value of 0.70. The lowest and highest values were obtained from Xbarc17 and Xbarc12, respectively. The dendrogram was constructed using UPGMA analysis, and the bread wheat genotypes were divided into three groups. Cluster I is further divided into two sub-clusters, Ia and Ib. Cluster II is further divided into two other sub-clusters, IIa and IIb. The pair-wise genetic dissimilarity indices revealed a minimum difference index of 0.083 and a maximum of 0.800 between genotypes. Bayraktar 2000 and LR5 and LR6 showed genetic similarity to the drought-tolerant cultivar Gerek 79, whereas BL8 and the drought-sensitive cultivar Bezostaja 1 (C10) showed the greatest genetic distance. Sertak52 (C5) and BL7 and BL4 showed genetic similarity to the drought-tolerant cultivar Bayraktar 2000, while BL6 and Bezostaja 1 (C10) showed the greatest genetic distance. BL1, BL3, and BL5 showed genetic similarity to the drought-sensitive cultivar Bezostaja 1, whereas LR1, LR2, LR5, and LR6 showed the greatest genetic distance. Overall, the genotypes and SSR markers used in this study provide preliminary data for future breeding and genetic studies related to drought-associated traits.

Anahtar Kelimeler

• bread wheat
• breedin
• drought
• SSR markers

Destekleyen Kurum

Selçuk University Scientific Research Projects Coordinatorship

Proje Numarası

13201040

Etik Beyan

Not applicable

Kaynakça

1. Adhikari, U., Nejadhashemi, A. P., & Woznicki, S. A. (2015). Climate change and eastern Africa: a review of impact on major crops. Food and energy security, 4(2), 110-132.
2. Ali, A., Ali, N., Ullah, N., Ullah, F., Adnan, M., & Ahmed, Z. (2013). Research article effect of drought stress on the physiology and yield of the pakistani wheat germplasms. Agriculture, 2(7), 419.
3. Ayana, A., & Bekele, E. (1998). Geographical patterns of morphological variation in sorghum (Sorghum bicolor (L.) Moench) germplasm from Ethiopia and Eritrea: qualitative characters. Hereditas, 129(3), 195-205.
4. Brbaklić, L., Trkulja, D., Kondić-Špika, A., Treskić, S., & Kobiljski, B. (2013). Detection of QTLs for important agronomical traits in hexaploid wheat using association analysis. Czech Journal of Genetics & Plant Breeding, 49(1), 1-8.
5. Carter, A. H., Chen, X., Garland-Campbell, K., & Kidwell, K. (2009). Identifying QTL for high-temperature adult-plant resistance to stripe rust (Puccinia striiformis f. sp. tritici) in the spring wheat (Triticum aestivum L.) cultivar ‘Louise’. Theoretical and Applied Genetics, 119(6), 1119-1128.
6. Ciucă, M., & Petcu, E. (2009). SSR markers associated with membrane stability in wheat (Triticum aestivum L.). Romanian Agricultural Research, 26, 21-24.
7. Dai, A. (2013). Increasing drought under global warming in observations and models. Nature Climate Change, 3(1), 52-58.
8. Dodig, D., Zorić, M., Kobiljski, B., Šurlan-Momirović, G., & Quarrie, S. A. (2010). Assessing drought tolerance and regional patterns of genetic diversity among spring and winter bread wheat using simple sequence repeats and phenotypic data. Crop and Pasture Science, 61(10), 812-824.

9. Dreisigacker, S., Zhang, P., Warburton, M., Skovmand, B., Hoisington, D., & Melchinger, A. (2005). Genetic diversity among and within CIMMYT wheat landrace accessions investigated with SSRs and implications for plant genetic resources management. Crop Science, 45(2), 653-661.
10. Dreisigacker, S., Zhang, P., Warburton, M., Van, Ginkel, M., Hoisington, D., Bohn, M., & Melchinger, A. (2004). SSR and pedigree analyses of genetic diversity among CIMMYT wheat lines targeted to different megaenvironments. Crop Science, 44(2), 381-388.
11. El-Maghraby, M., Moussa, M., Hana, N., & Agrama, H. (2005). Combining ability under drought stress relative to SSR diversity in common wheat. Euphytica, 141, 301-308.
12. Faheem, M., Mahmood, T., Shabbir, G., Akhtar, N., Kazi, A. G., & Mujeeb-Kazi, A. (2015). Assessment of D-genome based genetic diversity in drought tolerant wheat germplasm. International Journal of Agriculture and Biology, 17(4).
13. FAO. (2024). Food Agriculture Organization, Crops and livestock products staticial data
14. Farshadfar, E., Rafiee, F., & Hasheminasab, H. (2013). Evaluation of genetic parameters of agronomic and morpho-physiological indicators of drought tolerance in bread wheat (Triticum aestivum L.) using diallel mating design. Australian Journal of Crop Science, 7(2), 268-275.
15. Fleury, D., Jefferies, S., Kuchel, H., & Langridge, P. (2010). Genetic and genomic tools to improve drought tolerance in wheat. Journal of Experimental Botany, 61(12), 3211-3222.
16. Gupta, P., Balyan, H., Edwards, K., Isaac, P., Korzun, V., Röder, M. S., ... & Leroy, P. (2002). Genetic mapping of 66 new microsatellite (SSR) loci in bread wheat. Theoretical and applied genetics, 105(2), 413-422.
17. Hirt, H., & Shinozaki, K. (2004). Plant responses to abiotic stress Springer. In.
18. Huang, X., Börner, A., Röder, M., & Ganal, M. (2002). Assessing genetic diversity of wheat (Triticum aestivum L.) germplasm using microsatellite markers. Theoretical and Applied Genetics, 105(5), 699-707.
19. Jaccard, P. (1908). Nouvelles research sur la distribution florare. Bull De Lasociete Vaudoise Des Sciences Naturelles, 44, 223-270.
20. Janmohammadi, M., Dezfuli, P. M., & Sharifzadeh, F. (2008). Seed invigoration techniques to improve germination and early growth of inbred line of maize under salinity and drought stress. Gen Appl Plant Physiol, 34(3-4), 215-226.
21. Mehta, G., Muthusamy, S. K., Singh, G., & Sharma, P. (2021). Identification and development of novel salt-responsive candidate gene based SSRs (cg-SSRs) and MIR gene based SSRs (mir-SSRs) in bread wheat (Triticum aestivum). Scientific Reports, 11(1), 1-15.
22. Nei, M., & Li, W. H. (1979). Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences, 76(10), 5269-5273.
23. Perrier, X., Jacquemoud-Collet, J. (2006). DARwin software: http://darwin. cirad. fr/darwin. 5 edn. Cirad, Montpellier. In: France.
24. Plaschke, J., Ganal, M., & Röder, M. (1995). Detection of genetic diversity in closely related bread wheat using microsatellite markers. Theoretical and Applied Genetics, 91(6), 1001-1007.
25. Rampino, P., Pataleo, S., Gerardi, C., Mita, G., & Perrotta, C. (2006). Drought stress response in wheat: physiological and molecular analysis of resistant and sensitive genotypes. Plant, cell & environment, 29(12), 2143-2152.
26. Röder, M. S., Korzun, V., Wendehake, K., Plaschke, J., Tixier, M. H., Leroy, P., & Ganal, M. W. (1998). A microsatellite map of wheat. Genetics, 149(4), 2007-2023.
27. Röder, M. S., Plaschke, J., König, S. U., Börner, A., Sorrells, M. E., Tanksley, S. D., & Ganal, M. W. (1995). Abundance, variability and chromosomal location of microsatellites in wheat. Molecular and General Genetics MGG, 246, 327-333.
28. Russell, J., Fuller, J., Young, G., Thomas, B., Macaulay, M., Waugh, R., ... & Taramino, G. (1997). Discriminating between barley genotypes using microsatellite markers. Genome, 40(4), 442-450.
29. Santra, D., Chen, X., Santra, M., Campbell, K., & Kidwell, K. (2008). Identification and mapping QTL for high-temperature adult-plant resistance to stripe rust in winter wheat (Triticum aestivum L.) cultivar ‘Stephens’. Theoretical and Applied Genetics, 117(5), 793-802.
30. Sharma, P., Mehta, G., Shefali, Muthusamy, S. K., Singh, S. K., & Singh, G. P. (2021). Development and validation of heat-responsive candidate gene and miRNA gene based SSR markers to analysis genetic diversity in wheat for heat tolerance breeding. Molecular Biology Reports, 48(1), 381-393.
31. Sharma, R., Singh, S., Singh, S. K., Sharma, P., & Singh, G. P. (2021). Genetic diversity among bread wheat (Triticum aestivum L.) genotypes as assessed by SSRs. Journal of Cereal Research 13 (2): 205-210. http://doi.org/10.25174/2582-2675/2021112954
32. Singroha, G., Kumar, S., Singh, S. K., Singh, G., Singh, G. P., & Sharma, P. (2021). Validation of molecular markers linked with QTLs for heat and drought stress tolerance in wheat. Journal of Cereal Research, 12(3).
33. Smith, J., Chin, E., Shu, H., Smith, O., Wall, S., Senior, M., Mitchell, S., Kresovich, S., & Ziegle, J. (1997). An evaluation of the utility of SSR loci as molecular markers in maize (Zea mays L.): comparisons with data from RFLPs and pedigree. Theoretical and Applied Genetics, 95, 163-173.
34. Somers, D. J., Isaac, P., & Edwards, K. (2004). A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theoretical and Applied Genetics, 109(6), 1105-1114.
35. Song, Q. J., Shi, J. R., Singh, S., Fickus, E. W., Costa, J. M., Lewis, J., ... & Cregan, P. (2005). Development and mapping of microsatellite (SSR) markers in wheat. Theoretical and applied genetics, 110(3), 550-560.
36. Tomar, R. S. S., Tiwari, S., Vinod, Naik, B. K., Chand, S., Deshmukh, R., ... & Tomar, S. M. S. (2016). Molecular and morpho-agronomical characterization of root architecture at seedling and reproductive stages for drought tolerance in wheat. PloS one, 11(6), e0156528.
37. Triboi, E., & Triboi-Blondel, A. M. (2002). Productivity and grain or seed composition: a new approach to an old problem. European Journal of Agronomy, 16(3), 163-186.
38. Valdes, A. M., Slatkin, M., & Freimer, N. B. (1993). Allele frequencies at microsatellite loci: the stepwise mutation model revisited. Genetics, 133(3), 737-749.