Volume 10, Issue 26 (9-2018)                   jcb 2018, 10(26): 65-75 | Back to browse issues page


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Zali H, Sofalian O, Zeinalabedini M, hasanloo T, asgharii A, Alizadeh B. (2018). Assessment of Variability and Genetic Structure of Canola cultivars and Lines using SSR Markers Related on Drought Tolerance QTLs. jcb. 10(26), 65-75. doi:10.29252/jcb.10.26.65
URL: http://jcb.sanru.ac.ir/article-1-749-en.html
Agricultural Research, Education and Extension Organization
Abstract:   (3294 Views)

In the present study, genetic diversity among 41 lines and genotypes of canola including 19 open-pollinated and hybrid cultivars, 17 promising lines and 5 double-haploid lines were determined using simple sequence repeat (SSR) markers related on drought tolerance QTLs. Thirty-six selected primers produced 166 discernible bands, with 157 (94.58%) being polymorphic, indicating considerable genetic diversity among lines and genotypes. The polymorphic information content values of loci were varied from 0.046 (FITO133) to 0.327 (BRMS-024), respectively. The average of PIC index was estimated 0.212. Cultivars were classified into two sub-populations according to analysis of population structure including (Talaye, Hyola420 and Hyola401 genotypes and DH1, DH5, DH8, Dh9 and DH11 double haploids) as first group and winter cultivars as second group (other cultivars and lines). Based on the analysis of molecular variance, intra-population variance was higher than inter-population variance. The results showed that average of marker index including Nei’s gene diversity, Shannon’s information index, the effective number of alleles were 1.508, 0.449 and 0.298 respectively in line and genotypes of canola. In total, the marker wasn't found to be using it as a marker for selecting genotypes of drought tolerant used in the first step of breeding programs.
 

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Type of Study: Applicable | Subject: اصلاح نباتات مولكولي
Received: 2017/04/4 | Revised: 2018/09/29 | Accepted: 2017/08/13 | Published: 2018/09/26

References
1. Bus, A., N. Korber, R.J. Snowdon and B. Stich. 2011. Patterns of molecular variation in a species-wide germplasm set of Brassica napus. Theoretical and Applied Genetics, 123: 1413-1423. [DOI:10.1007/s00122-011-1676-7]
2. Chen, W., Y. Zhang, L. Xueping, B. Chen, J. Tu and F. Tingdong. 2007. Detection of QTL for six yield-related traits in oilseed rape (Brassica napus L.) using DH and immortalized F2 populations. Theoretical and Applied Genetics, 115: 849-858. [DOI:10.1007/s00122-007-0613-2]
3. Chen, S., M.N. Nelson, K. Ghamkhar, T. Fu and W.A. Cowling. 2008. Divergent patterns of allelic diversity from similar origins: the case of oilseed rape (Brassica napus L.) in China and Australia. Genome, 51: 1-10. [DOI:10.1139/G07-095]
4. Darvishnia, F.D., B.A. Fakheri, F. Nazarian firouzabadi and N. Panjehkeh. 2015. Genetic diversity of rapeseed (Brassica napus L.) using SSR and ISJ molecular markers. Iranian Journal of Agricultural Science, 46(1): 1-14 (In Persian).
5. Dellaporta, S.L., J. Wood and J.B. Tickes. 1993. A plant molecular DNA mini preparation. Version П. Plant Molecular Biology Reporter, 1: 19-21. [DOI:10.1007/BF02712670]
6. Diers, B.W. and T.C. Osborn. 1994. Genetic diversity of oilseed Brassica napus germplasm based on restriction fragment length polymorphisms. Theoretical and Applied Genetics, 88: 662-668. [DOI:10.1007/BF01253968]
7. Evanno, G., S. Regnaut and J. Goudet. 2005. Detecting the number of clusters of individuals using the software structure: a simulation study. Molecular ecology, 14: 2611-2620. [DOI:10.1111/j.1365-294X.2005.02553.x]
8. Fares, K., F. Guasmi, L. Touil, T. Triki and A. Ferchichi. 2009. Genetic diversity of Pistachio tree using Inter-Simple Sequence markers (ISSR) supported by morphological and chemical markers. Biotechnology, 8(1): 24-34. [DOI:10.3923/biotech.2009.24.34]
9. Flakelar, C.L., D.J. Luckett, J.A. Howitt, G. Dorana and P.D. Prenzler. 2015. Canola (Brassica napus) oil from Australian cultivars shows promising levels of tocopherols and carotenoids, along with good oxidative stability. Journal of Food Composition and Analysis, 42: 179-186. [DOI:10.1016/j.jfca.2015.03.010]
10. Hasan, M., W. Friedt, J. Pons-Ku¨hnemann, N.M. Freitag, K. Link and R.J. Snowdon. 2008. Association of gene-linked SSR markers to seed glucosinolate content in oilseed rape (Brassica napus ssp. napus). Theoretical and Applied Genetics, 116:1035-1049. [DOI:10.1007/s00122-008-0733-3]
11. Howell, P.M., A.G. Sharpe and D.J. Lydiate. 2003. Homoeologous loci control the accumulation of seed glucosinolates in oilseed rape (Brassica napus). Genome, 46: 454-460. [DOI:10.1139/g03-028]
12. Johnson, U., J. West, C. Lister, S. Michwels, R. Amasino and C. Dean. 2000. Molecular analysis of FRIGIDA, a major determinant of natural variation in Arabidopsis flowering time. Science, 290: 344-347. [DOI:10.1126/science.290.5490.344]
13. Jun, Z., J. Congcong, C. Zhengying, L. Ruiyuan, L. Yan, C. Sheng and M. Jinling. 2010. Association mapping of seed oil content in Brassica napus and comparison with quantitative trait loci identified from linkage mapping. Genome, 53: 908-916. [DOI:10.1139/G10-075]
14. Li, Z., Sh. Mei, Zh. Mei, X. Liu, T. Fu, G. Zhou andJ. Tu. 2014. Mapping of QTL associated with waterlogging tolerance and drought resistance during the seedling stage in oilseed rape (Brassica napus). Euphytica, 197: 341-353. [DOI:10.1007/s10681-014-1070-z]
15. Long, Y., J. Shi, D. Qiu, R. Li, C. Zhang, J. Wang, J. Hou, J. Zhao, L. Shi, B.S. Park, S.R. Choi, Y.P. Lim and J. Meng. 2007. Flowering time quantitative trait loci analysis of oilseed Brassica in multiple environments and genome wide alignment with Arabidopsis. Genetics, 177: 2433-2444. [DOI:10.1534/genetics.107.080705]
16. Lowe, A.J., C. Moule, M. Trick and K.J. Edwards. 2003. Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theoretical and Applied Genetics. [DOI:10.1007/s00122-003-1522-7]
17. Lowe, A.J., C. Moule, M. Trick and K.J. Edwards. 2004. Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theoretical and Applied Genetics, 108:1103-1112. [DOI:10.1007/s00122-003-1522-7]
18. Mahjoob, B., H. Najafi-Zarini and SH.R. Hashemi. 2014. Assessment of genetic relationships among 36 Brassica genotypes using ISSR molecular markers. Journal of Crop Breeding, 6(14): 96-106 (In Persian).
19. Moghaddam, M., S.A. Mohammadi, N. Mohebalipour, M. Toorchi, S. Aharizad and F. Javidfar. 2009. Assessment of genetic diversity in rapeseed cultivars as revealed by RAPD and microsatellite markers. African Journal of Biotechnology, 8(14): 3160-3167.
20. Moghaieb, R.E.A., F.H.K. Mohammed and S.S. Youssief. 2014. Genetic diversity among some canola cultivars as revealed by RAPD, SSR and AFLP analyses. Biotechnology, 4: 403-410. [DOI:10.1007/s13205-013-0165-x]
21. Mohammadi, S.A. and B.M. Prasanna. 2003. Analysis of Genetic diversity in crop plants: Salient statistical tools and consideration. Crop Science, 43: 1235-1248. [DOI:10.2135/cropsci2003.1235]
22. Naghavi, M.R., M. Mardi, S.M. Pirseyedi, M. Kazemi, P. Potki and M.R. Ghaffari. 2007. Comparison of genetic variation among accessions of Aegilops tauschii using AFLP and SSR markers. Genetic Resources and Crop Evolution, 54: 237-240. [DOI:10.1007/s10722-006-9143-z]
23. Nakao Kubo, M.H. 2008. Development and characterization of simple sequence repeat (SSR) markers in the. Aquatic Botany, 2164-2168.
24. Nei, M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89: 583-590.
25. Piquemal, J., E. Cinquin, F. Couton, C. Rondeau, E. Seignoret, I. Doucet, D. Perret, M.J. Villeger, P. Vincourt and P. Blanchard. 2005. Construction of an oilseed rape (Brassica napus L.) genetic map with SSR markers. Theoretical and Applied Genetics, 111: 1514-1523. [DOI:10.1007/s00122-005-0080-6]
26. Powell, W., M. Morgante, C. Ander, M. Hanafey, J. Vogel, S. Tingy and A. Rafalaski. 1996. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) marker for germplasm analysis. Journal of Molecular Breeding, 2: 225-238. [DOI:10.1007/BF00564200]
27. Pritchard, J.K., M. Stephens and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945-959.
28. Qu, C., M. Hasan, K. Lu, L. Liu, X. Liu, J. Xie, M. Wang, J. Lu, N. Odat, R. Wang, L. Chen, Z. Tang and J. Li. 2012. Genetic diversity and relationship analysis of the Brassica napus germplasm using simple sequence repeat (SSR) markers. African Journal of Biotechnology, 11(27): 6923-6933. [DOI:10.5897/AJB11.3475]
29. Reddy, M.P., N. Sarla and E.A. Siddiq. 2002. Inter simple sequence repeat (ISSR) polymorphism and its application in plant breeding. Euphytica, 128: 9-17. [DOI:10.1023/A:1020691618797]
30. Rezaei Zad, A., V.A. Mohammadi, A.A. Zali, H. Zeinali and M. Mardi. 2012. Mapping QTLs controlling yield and yield components of oilseed rape under normal irrigation and drought stress conditions. Journal of Breeding Seed and Plant, 27: 199-218 (In Persian).
31. Roder, M.S., V. Korzun, K. Wendehake, J. Plaschke, M.H. Tixier, P. Leroy and M.W. Ganal. 1998. A microsatellite map of wheat. Genetics, 149: 2007-2023.
32. Shannon C.E. and W. Weaver. 1949. The mathematical theory of communication. University of Illinois Press, Urbana.
33. Siahsar, B.A., M. Allahdoo and H. Shahsavand Hasani. 2010. Evaluation of genetic diversity of tritipyrum, triticale and wheat lines through RAPD and ISJ markers. Iran Journal of field Crop Science, 41(3): 555-568 (In Persian).
34. Somers, D.J., K.R.D. Friesen and G. Rakow, G. 1998. Identification of molecular markers associated with linoleic acid desaturation in Brassica napus. Theoretical and Applied genetics, 96: 897-903. [DOI:10.1007/s001220050817]
35. Suwabe, K., H. Iketani, T. Nunome, T. Kage and M. Hirai. 2002. Isolation and characterization of microsatellites in Brassica rapa L. Theoretical and Applied Genetics, 104: 1092-1098. [DOI:10.1007/s00122-002-0875-7]
36. Suwabe, K., H. Tsukazaki, H. Iketani, K. Hatakeyama, M. Fujimura, T. Nunome, H. Fukuoka, S. Matsumoto and M. Hirai. 2003. Identification of two loci for resistance to clubroot (Plasmodiophora brassicae Woronin) in Brassica rapa L. Theoretical and Applied Genetics, 107: 997-1002. [DOI:10.1007/s00122-003-1309-x]
37. Tondelli, A., X. Xu, M. Moragues, R. Sharma, F. Schnaithmann, Ch. Ingvardsen, O. Manninen, J. Comadran, J. Russell and R. Waugh. 2013. Structural and temporal variation in genetic diversity of European spring two-row barley cultivars and association mapping of quantitative traits. The Plant Genome. 6(2). [DOI:10.3835/plantgenome2013.03.0007]
38. Turi, N., A. Farhatullah, M.A. Rabbani and Z.K. Shinwari. 2012. Genetic diversity in the locally collected Brassica species of Pakistan based on microsatellite markers. Pakestanian Journal Botany, 44: 1029-1035.
39. Zali, H., O. Sofalian, T. Hasanloo, A. Asgharii and M. Zeinalabedini. 2016. Drought stress effect on physiological parameter and amino acids accumulations in canola. Journal of Crop Breeding, 8: 191-203 (In Persian). [DOI:10.29252/jcb.8.18.191]
40. Zali, H., O. Sofalian, T. Hasanloo, A. Asghari and M. Zeinalabedini. 2016. Appropriate strategies for selection of drought tolerant genotypes in canola. Journal of Crop Breeding, 78(20): 77-90 (In Persian).
41. Zhao, J. and J. Meng. 2003. Genetic analysis of loci associated with partial resistance to Sclerotinia sclerotiorum in rapeseed (Brassica napus L.). Theoretical and Applied Genetics, 106: 759-764. [DOI:10.1007/s00122-002-1171-2]

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