Volume 11, Issue 30 (9-2019)                   jcb 2019, 11(30): 58-67 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

feizi M, solouki M, sadeghzadeh B, fakheri B, mohammadi A. QTL Mapping for Higher Seed Zn Concentration and Content in Baley using SSR Markers. jcb. 2019; 11 (30) :58-67
URL: http://jcb.sanru.ac.ir/article-1-977-en.html
Department of Plant Breeding and Biotechnology, University of Zabol, Zabol, Iran
Abstract:   (195 Views)
There is a little information regarding the chromosomal regions conferring seed zinc accumulation in barley. With the aim of QTL mapping of Zn concentration and content, 121 barley genotypes (including local landraces, released cultivars, gene bank germplasm) were screened under field conditions. The trial was conducted in square latice in 2015-2017 cropping seasons at dryland agricultural research institute (DARI) in Maragheh. To construct genetic linkage map, 149 SSR markers were applied. Based on ANOVA, there was a great genotypic variation for seed Zn concentration and content among the genotypes, which approves the excessive diversity of genotypes. Five QTLs located on 2H, 3H, 4H and 5H were associated with seed Zn concentration, and could explain 81% of total phenotypic variation. Marker BMAG0720 had the highest (25%) phenotypic variation. This marker could also explain 23% of total variation for seed Zn content. Moreover, 5 genomic regions on 2H, 3H and and 4H were associated with seed Zn content. In conclusion, the identification of these major QTLs would provide an important starting point for marker assisted selection (MAS) that may contribute to the improvement of barley productivity and nutritional quality.
Full-Text [PDF 274 kb]   (70 Downloads)    
Type of Study: Research | Subject: General
Received: 2018/06/10 | Revised: 2019/08/31 | Accepted: 2018/11/10 | Published: 2019/09/11

References
1. Agricultural Statistics. 2017. Deputy Minister of Planning and Economics of Ministry of Agriculture, Volume 1, (Crop and Gardening).
2. Bradbury, P.J., Z. Zhang, D.E. Kroon, T.M. Casstevens, Y. Ramdoss and E.S. Buckler. 2007. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 23: 2633-2635. [DOI:10.1093/bioinformatics/btm308]
3. Cakmak, I. 2000. Possible roles of zinc in protecting plant cells from damage by reactive oxygen species. The New Phytologist 146: 185-205. [DOI:10.1046/j.1469-8137.2000.00630.x]
4. Cakmak, I. and H. Marschner. 1988. Enhanced superoxide radical production in roots of zinc-deficient plants. Journal of Experimental Botany 39: 1449-1460. [DOI:10.1093/jxb/39.10.1449]
5. Cakmak, I., R. Graham and R.M. Welch. 2002. Agricultural and molecular genetic approaches to improving nutrition and preventing micronutrient malnutrition globally, in: I. Cakmak and R. M. Welch, (eds.) Encyclopedia of Life Support Systems, 1075-1099. Eolss Publishers, Oxford, 1075-1099 pp.
6. Chen, W.R., Z.L. He, X.E. Yang and Y. Feng. 2009. Zinc Efficiency is correlated with Root Morphology, Ultrastructure, and Antioxidative Enzymes in Rice. Journal of Plant Nutrition, 32: 287-305. [DOI:10.1080/01904160802608627]
7. Erkan, H., S. Celik, B. Bilgi and H. Koksel. 2006. A new approach for the utilization of barley in food products: Barley tarhana. Food Chemistry, 97: 12-18. [DOI:10.1016/j.foodchem.2005.03.018]
8. Feiziasl, W. and Gh. Valizadeh. 2003. Effect of time and nitrogen consumption on wheat crop performance. Journal of Soil and Water, 17(1): 29-38.
9. Food and Agriculture Organization of the United States. FAOSTAT [Internet]. 2018 [cited 2018 October 3]. Available from: http://www.fao.org/faostat/en/#data/QC/visualize
10. Graham, R.D. and R.M. Welch. 1996. Breeding for staple-food crops with high micronutrient density Working Papers on Agricultural Strategies for Micronutrients, No. 3. International Food Policy Research Institute, Washington, D.C.
11. Guzman-Maldonado, S.H., O. Martinez, J.A. Scosta-Gallegos, F. Guevara-Lara and O. Paredes-Lopez. 2003. Putative quantitative trait loci for physical and chemical components of common bean. Crop Sciense, 43: 1029-1035. [DOI:10.2135/cropsci2003.1029]
12. Hatami-Maleki, H., N. Abdi, R. Darvishzadeh and M. Jafari. 2017. Mapping QTLs Controlling Drought Tolerance Indices in Sunflower (Helianthus annus L.). jcb, 8(20): 235-228.
13. Lakew, B., R.J. Henry, S. Ceccarelli, S. Grando, J. Eglinton and M. Baum. 2013. Genetic analysis and phenotypic associations for drought tolerance in Hordeum spontaneum introgression lines using SSR and SNP markers. Euphytica, 189: 9-29. [DOI:10.1007/s10681-012-0674-4]
14. Li, J.Z., T.G. Sjakste, M.S. Roder and M.W. Ganal. 2003. Development and genetic mapping of 127 new microsatellite markers in barley. Theoretical and Applied Genetics, 107: 1021-1027. [DOI:10.1007/s00122-003-1345-6]
15. Liu, J., J. Yang, R. Li, L. Shi, Ch. Zhang, Y. Long, F. Xu and J. Meng. 2009. Analysis of genetic factors that control shoot mineral concentration in rapeseed (Brassica napus) in different boron environments.Plant and Soil, 320: 255-266. [DOI:10.1007/s11104-009-9891-6]
16. Liu, Z.W., R.M. Biyashev and M.A. Saghai Maroof. 1996. Development of simple sequence repeat DNA markers and their integration into a barley linkage map. Theoretical and Applied Genetics, 93: 869-876. [DOI:10.1007/BF00224088]
17. Lorieux, M. 2012. MapDisto: fast and efficiency computation of genetic linkage map Mol. Breed, 30: 1231-1235. [DOI:10.1007/s11032-012-9706-y]
18. Majd, A.N., M. Fazel and S. Lak. 2015. The effect of foliar application of zinc (Zn) on yield and yield components of irrigated wheat cultivars in Ahvaz weather conditions. Int J Biosci, 6(3): 370-377. [DOI:10.12692/ijb/6.3.370-377]
19. Marschner, H. 1998. Role of root growth, arbuscular mycorrhiza, and root exudates for the efficiency in nutrient acquisition. Field Crops Research, 56: 203-207. [DOI:10.1016/S0378-4290(97)00131-7]
20. Martínez, M., M. Motilva, J. delas M. Hazas, C.L. Romero, M.P.K.Vaculova and I.A. Ludwig. 2018. Phytochemical composition and β-glucan content of barley genotypes from two different geographic origins for human health food production. Food chem, 245: 61-70. [DOI:10.1016/j.foodchem.2017.09.026]
21. Mikołajczak, K., P. Ogrodowicz, K. Gudyś, K. Krystkowiak, A. Sawikowska, W. Frohmberg, A. Górny, A. Kędziora, J. Jankowiak and D. Józefczyk. 2016: Quantitative trait loci for yield and yield-related traits in spring barley populations derived from crosses between European and Syrian cultivars. PLoS One 11, e0155938. doi:10.1371/journal.pone.0155938. [DOI:10.1371/journal.pone.0155938]
22. Peleg, Z., I. Cakmak and I. Ozturk. 2009. Quantitative trait loci conferring grain mineral nutrient concentration in durum wheat × wild emmer wheat RIL Population . Theoretical and Applied Genetics, 119: 353-369. [DOI:10.1007/s00122-009-1044-z]
23. Ramsay, L., M. Macaulay, D.S. Ivanissevich, K. MacLean, L. Cardle, J. Fuller, K.J. Edwards, S. Tuvesson, M. Morgante, A. Massari, E. Maestri, N. Marmiroli, T. Sjakste, M. Ganal, W. Powell and R. Waugh. 2000. A simple sequence repeat-based linkage map of barley. Genetics, 156: 1997-2005.
24. Ramsay, L., J. Russell, M. Macaulay, A. Booth, W.T.B. Thomas and R. Waugh. 2004. Variation shown by molecular markers in barley: Genomic and genetic constraints. Aspects of Applied Biology, 72: 147-154.
25. Rollins, J.A., B. Drosse, M.A. Mulki, S. Grando, M. Baum, M. Singh, S. Ceccarelli and M. von Korff, 2013. Variation at the vernalisation genes Vrn-H1 and Vrn-H2 determines growth and yield stability in barley (Hordeum vulgare) grown under dryland conditions in Syria. Theoretical and Applied Genetics, 126: 2803-2824. [DOI:10.1007/s00122-013-2173-y]
26. Rostoks, N., S. Mudie, L. Cardle, J. Russell, L. Ramsay, A. Booth, J.T. Svensson, S.I. Wanamaker, H. Walia, E.M. Rodriguez, P.E. Hedley, H. Liu, J. Morris, T.J. Close, D.F. Marshall and R. Waugh, 2005. Genome-wide SNP discovery and linkage analysis in barley based on genes responsive to abiotic stress. Molecular Genetics and Genomics, 274: 515-527. [DOI:10.1007/s00438-005-0046-z]
27. Sadeghzadeh, B. 2013. A review of zinc nutrition and plant breeding. Journal of Soil Science and Plant Nutrition, 13: 905-927. [DOI:10.4067/S0718-95162013005000072]
28. Sadeghzadeh, B. and G. Valizadeh. 2016. Soil-zinc application alleviates drought stress to improve bread and durum wheat production under cold rainfed conditions 15th International Cereal and Bread Congress, 18-21 Apr. 2016, Istanbul, Turkey, 241.
29. Sadeghzadeh, B., N. Sadeghzadeh and E. Sepehr. 2016. Barley genotypes differing in zinc efficiency when grown in various soil types. International Journal of Plant & Soil Science, 12: 1-13. [DOI:10.9734/IJPSS/2016/27713]
30. Sadeghzadeh, B., Z. Rengel and C. Li. 2008. Mapping of chromosome regions associated with seed Zn accumulation in barley, PhD Thesis, The University of Western Australia, Perth.
31. Sadeghzadeh, B., Z. Rengel and C. Li. 2009. Differential zinc efficiency of barley genotypes grown in soil and chelator-buffered nutrient solution. Journal of Plant Nutrition, 32: 1744 - 1767. [DOI:10.1080/01904160903150974]
32. Sadeghzadeh, B., Z. Rengel and C. Li. 2015. Quantitative Trait Loci (QTL) of Seed Zn Accumulation in Barley Population Clipper X Sahara. Journal of Plant Nutrition, 38: 1672-1684. [DOI:10.1080/01904167.2014.991036]
33. Sadeghzadeh, B., Z. Rengel, C. Li and H. Yang, 2010. Molecular marker linked to a chromosome region regulating seed Zn accumulation in barley. Molecular Breeding, 25: 167-177. [DOI:10.1007/s11032-009-9317-4]
34. Saghai, M., A. Maroof, K. Soliman, R.A. Tprgensen, R.W. Allard. 1984. Ribosomal DNA Spacer Lenth polymorphism in barley: Mendelian inheritance, chromosomal loCation and population dynamics. Proc .Natl. ACad. Sci. USA. 81: 8014-8018. [DOI:10.1073/pnas.81.24.8014]
35. Struss, P. and J. Plieske. 1998. The use of microsatellite markers for detection of genetic diversity in barley populations. Theoretical and Applied Genetics, 97: 308-315. [DOI:10.1007/s001220050900]
36. Sun, C., Y. Fu, L. Tan, A. Luisa and Garcia-Oliveira. 2009. Genetic identification of quantitative trait loci for contents of mineral nutrients in rice grain. Plant Biology, 51: 84-92. [DOI:10.1111/j.1744-7909.2008.00730.x]
37. Thiel, T., W. Michalek, R.K. Varshney and A. Graner. 2003. Exploiting EST databases for the development of cDNA derived microsatellite markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics, 106: 411-422. [DOI:10.1007/s00122-002-1031-0]
38. Trimigno, A., B. Khakimov, J.L.C. Mejia, M.S. Mikkelsen, M. Kristensen, B.M. Jespersen and S.B. Engelsen. 2017. Identification of weak and gender specific effects in a short 3 weeks intervention study using barley and oat mixed linkage β-glucan dietary supplements: a human fecal metabolome study by GC-MS. Metabolomics, 13(10): 108. [DOI:10.1007/s11306-017-1247-2]
39. Van Ooijen, J.W. 2006. JoinMap4, Software for the calculation of genetic linkage map in experimental populations. Kyazma B.V., Wageningen, Netherlands.
40. Varshney, R.K., I. Grosse, U. Hauhnel, R. Siefken, M. Prasad, N. Stein, P. Langridge, L. Altschmied, and A. Graner. 2006. Genetic mapping and BAC assignment of EST-derived SSR markers proves non-uniform distribution of genes in the barley genome. Theoretical and Applied Genetics, 113: 239-250. [DOI:10.1007/s00122-006-0289-z]
41. Wang, M., N. Jiang, T. Jia, L. Leach, J. Cockram, R. Waugh, L. Ramsay, B. Thomas and Z. Luo. 2012. Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars Theor. Appl. Genet, 124: 233-246. [DOI:10.1007/s00122-011-1697-2]
42. Wenzl, P., H. Li, J. Carling, M. Zhou, H. Raman, E. Paul, P. Hearnden, C. Maier, L. Xia and V. Caig. 2006. A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits. BMC Genom, 7 pp. [DOI:10.1186/1471-2164-7-206]
43. Yu, J.M., G. Pressoir, W.H. Briggs, I.V. Bi, M. Yamasaki, J.F. Doebley, M.D. McMullen, B.S. Gaut, D.M. Nielsen and J.B. Holland. 2006. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet, 38: 203-208. [DOI:10.1038/ng1702]
44. Zali, H., O. Sofalian, M. Zeinalabedini, T. hasanloo, A. asgharii and B. Alizadeh. 2018. Assessment of Variability and Genetic Structure of Canola cultivars and Lines using SSR Markers Related on Drought Tolerance QTLs, 10(26): 65-75.

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


© 2020 All Rights Reserved | Journal of Crop Breeding

Designed & Developed by : Yektaweb