Using SSR markers for assessment genetic diversity and detection drought escape candidate genes in barley lines (Hordeum vulgare L.)
Vahideh Gougerdchi
Department of Agricultural Biotechnology, Faculty of Agriculture, Payame Noor University, Karaj, Alborz, Iran (Iran, Islamic Republic of)
Sara Dezhsetan
sdezhsetan@uma.ac.irGenomics Department; Agricultural Biotechnology Institute Northwest and West (Tabriz), Agricultural Biotechnology Research Institute of Iran (ABRII), Assistant Professor, Dept .of Agronomy & Plant Breeding, Faculty of Agricultural Sciences, University of Mohaghegh Ardabili, Ardabil, Iran (Iran, Islamic Republic of)
Mohammad Ali Ebrahimi
Department of Agricultural Biotechnology, Payame Noor University, Tehran, Iran. (Iran, Islamic Republic of)
Behzad Sadeghzadeh
Dryland Agricultural Research Insti. (DARI), Maragheh, Iran. (Iran, Islamic Republic of)
Sona Savari
Department of Agronomy & Plant Breeding, Faculty of Agriculture, University of Tabriz, Iran. (Iran, Islamic Republic of)
Abstract
Assessment of genetic diversity using molecular markers is one of the primary and important steps in breeding programs. In this study, genetic diversity of 52 barley lines evaluated using 68 SSR primer pairs and 47 primer pairs produced clear and polymorphic banding pattern. In general, 153 polymorphic alleles de-tected. The number of observed polymorphic alleles varied from 2 to 9, with an average of 3.26 alleles per locus. Polymorphic Information Content (PIC) ranged from 0.07 to 0.81, with an average of 0.45. In this research, SSR markers differentiated the studied lines efficiently. Using cluster analysis, studied barley lines divided into two groups. Genetic diversity was relatively corresponding with geographical origins, because the lines related to a country somewhat diverged from each other. Two-rowed Iranian and Chinese barleys classified in one subgroup. Also, most six-rowed barleys classified in one subgroup. Association mapping analysis was used to identify candidate genes for drought escape in barley lines and 16 informative markers were identified after which confirmation in other tests could be suitable for marker assisted breeding drought escape.
Keywords:
Association analysis, barley, genetic diversity, Microsatellite markers (SSR), drought escapeReferences
Agrama, H.A.; Eizenga, G.C.; Yan, W. Association mapping of yield and its components in rice cultivars. Molecular Breeding, v.19, p.341–356, 2007.
Google Scholar
Bassam, B.J.; Caetano-Anolles, G.; Gresshoff, P. M. Fast and sensitive silver staining of DNA in polyacryla-mide gels. Analytical Biochemistry, v.19, p.680–683, 1991.
Google Scholar
Doulis, A.; Harfouche, A.; Aravanopoulos, F. Rapid, high quality DNA isolation from cypress (Cupressus sempervirens L.) needles and optimization of the RAPD marker technique. Plant Molecular Biology Reporter, v.17, p. 411-412, 1999.
Google Scholar
El-Awady, A.M.M; El-Tarras, A.E.A. Genetic diversity of some Saudi barley (Hordeum vulgare L.) landraces based on microsatellite markers. African journal of biotechnology, v.11 (21), p. 4826 4832, 2012.
Google Scholar
Excoffier, L.; Laval, G.; Schneider, S. Arlequin Version 3.0. An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online, v.1, p. 47–50, 2005.
Google Scholar
FAO. FAO statistical database. http://faostat.fao.org/faostat/collections?subset=agriculture. 2010.
Google Scholar
Feng, Z.Y.; Zhang, Y.Z.; Zhang, L.L.; Ling, H. Q. Genetic diversity and geographical differentiation of Hor-deum vulgar ssp. spontaneum in Tibet using microsatellite markers. High Technology Letters, v.13, p.46-53, 2003.
Google Scholar
Hamza, S.; Ben Hamida, W.; Rebaï, A.; Harrabi, M. SSR-based genetic diversity assessment among Tunisian winter barley and relationship with morphological traits. Biological Science. Euphytica, v.135, p. 107-118, 2004.
Google Scholar
Kannan, B.; Senapathy, S.; Raj, A.G.B.; Chandra, S.; Muthiah, A.; Dhanapal, A.P.; Hash, C.T. Association Analysis of SSR Markers with Phenology ,Grain, and Stover-Yield Related Traits in Pearl Millet (Pennisetum glaucum (L.) R. Br.). The scientific world journal, p.1-15, 2014.
Google Scholar
Kraakman, A.T.; Niks, R.E.; van den Berg, P.M.; Stam, P.; van Eeuwijk, F.A. Linkage disequilibrium map-ping of yield and yield stability in modern spring barley cultivars. Genetics, v.168, p.435 446, 2004.
Google Scholar
Liu, J. PowerMarker V3.25 Manual. http://www.powermarker.net. 2004.
Google Scholar
Liu, Z.W.; Biyashev, R.M.; Saghaie Maroof, M.A. Development of simple sequence repeat DNA markers and their integration into a barley linkage map. Theoretical and Applied Genetics, v.93(5), p.869-876, 1996.
Google Scholar
Matsuoka, Y.; Mitchell, S.E.; Kresovich, S.; Goodman, M.; Doebley, J. Microsatellite in Zea variability, patterns of mutations and use for evolutionary studies. Theoretical and Applied Genetics, v.104, p.436-450, 2002.
Google Scholar
Meszaros, K.; Karsai, I.; Kuti, C.; Banyai, J.; Lang, L.; Bedo, Z. Efficiency of different marker systems for genotype fingerprinting and for genetic diversity studies in barley (Hordeum vulgare L.). South African Journal of Botany, p.43-48, 2007.
Google Scholar
Nandha, P.S.; Singh, J. Comparative assessment of genetic diversity between wild and cultivated barley using SSR and EST-SSR markers. Plant Breeding, v.133 (1), p. 28–35, 2014.
Google Scholar
Oweis, T.; Hachum, A. Supplemental Irrigation for Improved Rainfed Agriculture in WANA Region. In: S.P. Wani et al. (Ed.). Rainfed Agriculture: unlocking the potential. CAB International, London, UK, 2009. p.182-196.
Google Scholar
Peakall, R.; Smouse, P.E. GENALEX 6: Genetic analysis in excel. Population genetic software for teaching and research. Molecular Ecology Notes, v.6, p.288-295, 2006.
Google Scholar
Pirseyedi, S.M.; Mardi, M.; Naghavi, M.R.; Poor Iran Doost, H.; Sadeghzadeh, D.; Mohammadi, S.A.; Ghare-yazie, B. Evalution of genetic diversity and identification of informative markers for morphological characters in Sardari derivated wheat lines. Pakistan Journal of Biological Sciences, v.9(13), p.2411-2418, 2006.
Google Scholar
Russell, J.; Fuller, J.D.; Macaulay, M.; Hatz, B.G.; Jahoor, A.; Powell, W.; Waugh, R. Direct comparison of levels of genetic variation among barley accessions detected by RFLPs, AFLPs, SSRs and RAPDs. Theoretical and Applied Genetics, v.95(4), p. 714-722, 1997.
Google Scholar
Saghai Maroof, M.A.; Biyashev, R.; Yang, G.P.; Zhang, Q.; Allard, R.W. Extraordinarily polymorphic mi-crosatellite DNA in barley: species diversity, chromosomal locations and population dynamics. Proceed-ings of the National Academy of Sciences, v.91(12), p.5466-5470, 1994.
Google Scholar
Samarah, N.H. Effects of drought stress on growth and yield of barley. Agronomy for Sustainable Develop-ment, p.145–149, 2005.
Google Scholar
Senior, M.L.; Murphy, J.P.; Goodman, M.M.; Stuber, C.W. Utility of SSRs for determining genetic similari-ties and relationships in maize using an agarose gel system. Crop Science, v.38, p.1088–1098, 1998.
Google Scholar
Struss, D.; Plieske, J. Use of microsatellite markers for detection of genetic diversity in barley populations. Theoretical and Applied Genetics, v.97, p.308- 315. 1998.
Google Scholar
Tamura, k.; Peterson, D.; Peterson, N.; Stecher, G.; Nei, M.; Kumar, S. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution, v.28(10), p.2731–2739, 2011.
Google Scholar
Varshney, R.K.; Marcel, T.C.; Ramsay, L.; Russell, J.; Röder, M.S.; Stein, N.; Waugh, R.; Langridge, P.; Niks, R.E.; Graner, A. A high density barley microsatellite consensus map with 775 SSR loci. Theoreti-cal and Applied Genetics, v.114(6), p. 1091-1103, 2007.
Google Scholar
Wei, Y.M.; Hou, Y.C.; Yan, Z.H.; Wu, W.; Zhang, Z.Q.; Liu, D.C.; Zheng, Y.L. Microsatellite DNA poly-morphism divergence in Chinese wheat (Triticum aestivum L.) landraces highly resistant to Fusarium head blight. Journal of Applied Genetics, v.46, p. 3-9, 2005.
Google Scholar
Wilson, L.M.; Whitt, S.R.; Ibanez, A.M.; Rocheford, T.R.; Goodman, M.M.; Buckler, I.V. Dissection of maize kernel composition and starch production by candidate gene association. Plant Cell, v.16, p. 2719–2733, 2004.
Google Scholar
Zhang, D.; Bowden, R.L; Yu, J.; Carver, B.F.; Bai, G. Association Analysis of Stem Rust Resistance in U.S. Winter Wheat. The Scientific World Journal. PLoS One, v.9 (7): e103747, 2014.
Google Scholar
Zhang, X.Y.; Li, C.W.; Wang, L.F.; Wang, H.M.; You, G.X.; Dong, Y.S. An estimation of the minimum number of SSR alleles needed to reveal genetic relationships in wheat varieties. Information from large-scale planted varieties and cornerstone breeding parents in Chinese wheat improvement and production. Theoretical and Applied Genetics, v.106(1), p.112-117, 2002.
Google Scholar
Authors
Vahideh GougerdchiDepartment of Agricultural Biotechnology, Faculty of Agriculture, Payame Noor University, Karaj, Alborz, Iran Iran, Islamic Republic of
Authors
Sara Dezhsetansdezhsetan@uma.ac.ir
Genomics Department; Agricultural Biotechnology Institute Northwest and West (Tabriz), Agricultural Biotechnology Research Institute of Iran (ABRII), Assistant Professor, Dept .of Agronomy & Plant Breeding, Faculty of Agricultural Sciences, University of Mohaghegh Ardabili, Ardabil, Iran Iran, Islamic Republic of
Authors
Mohammad Ali EbrahimiDepartment of Agricultural Biotechnology, Payame Noor University, Tehran, Iran. Iran, Islamic Republic of
Authors
Behzad SadeghzadehDryland Agricultural Research Insti. (DARI), Maragheh, Iran. Iran, Islamic Republic of
Authors
Sona SavariDepartment of Agronomy & Plant Breeding, Faculty of Agriculture, University of Tabriz, Iran. Iran, Islamic Republic of
Statistics
Abstract views: 175PDF downloads: 150
License
All articles published in electronic form under CC BY-SA 4.0, in open access, the full content of the licence is available at: https://creativecommons.org/licenses/by-sa/4.0/legalcode.pl .
