گروه‌بندی هتروتیک و پیش بینی عملکرد هیبریدهای ذرت با استفاده از نشانگرهای SNP

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد، گروه تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه، ایران

2 دانشیار، گروه تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه، ایران

3 استادیار، گروه تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه ارومیه، ارومیه، ایران

چکیده

تولید ارقام هیبرید یکی از روش­ های مهم اصلاح ذرت است که می ­تواند بر اساس گروه­بندی هتروتیک ارقام تسهیل شود. در این پژوهش، ابتدا 93 لاین اینبرد ذرت از منابع مختلف براساس داده­های SNP در دو گروه هتروتیک متفاوت، گروه­بندی و سپس تعداد شش لاین از این دو گروه، انتخاب و به­همراه دو لاین B73 و MO17 به­عنوان شاهد در قالب یک طرح دای­آلل کامل تلاقی داده شدند. 64 هیبرید حاصل از تلاقی­ها در قالب طرح لاتیس ساده با سه تکرار در مرکز تحقیقات توتون ارومیه مورد ارزیابی قرار گرفتند. سپس بر اساس داده­های حاصل از عملکرد این هیبریدها و داده­های SNP، عملکرد دانه 1566 هیبرید که بالقوه می­توانند از تلاقی افراد دو گروه هتروتیک حاصل شوند، با مدل خطی مخلوط پیش­بینی شد. نتایج نشان داد که هیبرید H50 (1_4×18_2) دارای عملکرد دانه بیش­تری از هیبرید سینگل­کراس 704 بود. با توجه به اینکه این هیبرید (H50) زودرس­تر از هیبرید شاهد سینگل­کراس 704 (به­عنوان هیبرید غالب منطقه) بود، بنابراین در صورتی که این نتیجه در آزمایش­های تکمیلی نیز تایید شود، آن را می­توان به­عنوان یک هیبرید جدید معرفی کرد. در ادامه آزمایش به­منظور به­ دست آوردن نتایج تکمیلی، تعداد 13 هیبرید شامل H4، H9، H10، H11، H17، H18، H38، H41، H42، H45، H47، H49 و H50 به­عنوان هیبریدهای مطلوب این آزمایش به­همراه هیبریدهای Simon، SC703 و SC704 به­عنوان شاهد در شرایط محیطی کرج مورد ارزیابی مجدد قرار گرفتند. نتایج این ارزیابی نشان داد که هرچند هیبریدهای شاهد SC703، Simon و SC704 به­ترتیب با متوسط 63/12، 01/12 و 64/10 تن در هکتار عملکرد بالایی داشتند، اما هیبرید H50 با متوسط عملکرد دانه 50/10 تن در هکتار، نه­تنها عملکرد مطلوبی داشت، بلکه تعداد روز تا تاسل­دهی و کاکل­دهی کم­تری نیز در مقایسه با هیبریدهای شاهد نشان داد. بنابراین، هیبرید H50 با وجود ویژگی مطلوب زودرسی، عملکرد نسبتاً بالایی نیز داشت و برای ارزیابی در آزمایشات ناحیه‌ای عملکرد به­منظور معرفی آن به­عنوان یک هیبرید جدید پرمحصول و زودرس پیشنهاد می­ شود.

کلیدواژه‌ها


عنوان مقاله [English]

Heterotic grouping and prediction of hybrids performance in maize using SNP markers

نویسندگان [English]

  • Reza Darvishzadeh 1
  • Iraj Bernousi 2
  • Hadi Alipour 3
1 Prof., Dept. of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
2 Assoc. Prof., Dept. of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
3 Assist Prof., Dept. of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
چکیده [English]

The production of hybrid cultivars is one of the most major maize breeding methods, which can be facilitated based on the heterotic grouping of cultivars. In this study, 93 maize inbred lines from different sources were grouped into two different heterotic groups based on SNP markers data. Then, six selected inbred lines from these two heterotic groups along with B73 MO17 as check inbred lines were crossed in a complete diallel crosses, and the grain yield of 64 produced hybrids were evaluated in a simple lattice design with three replications at the Urmia Tobacco Research Center, Urmia, West Azarbaijan province, Iran. Based on the grain yield of these F1 hybrids and the SNP markers data, grain yield of 1566 hybrids, which can be potentially produced from the cross of individuals of two heterotic groups, was predicted using a mixed linear model. The results showed that the hybrid H50 (1_4×18_2) had higher grain yield than the check hybrid SC704. Since this hybrid (H50) was early maturity compared to SC704 hybrid (as the dominant hybrid in the region), so if this result is confirmed in the other complementary experiments, it can be introduced as a new hybrid. To obtain the complementary results, 13 superior hybrids of the current study including H4, H9, H10, H11, H17, H18, H38, H41, H42, H45, H47, H49 and H50 along with three check hybrids, Simon, SC703 and SC704, were re-evaluated under environmental conditions of Karaj region, Alborz province, Iran. The results showed that although the check hybrids SC703, Simon and SC704 had high yields with an average of 12.63, 12.01 and 10.64 ton/ha, respectively, however, H50 hybrid with an average of 10.50 ton/ha not only had a desirable grain yield, but also showed fewer days to tasseling and silking compared to the check hybrids. Therefore, H50 as the superior hybrid of this experiment is suggested for evaluation in the regional trials to introduce as a new early maturity and high-yielding hybrid.

کلیدواژه‌ها [English]

  • BLUP
  • Early maturity
  • Hybrid cultivars
  • Next generation sequencing
Acosta-Motos, J. R., Ortuño, M. F., Bernal-Vicente, A., Diaz-Vivancos, P., Sanchez-Blanco, M. J., Hernandez, J. A. 2017. Plant responses to salt stress: Adaptive mechanisms. Agronomy 7 (1): 18. https://doi.org/10.3390/agronomy7010018.##Akhunov, E., Nicolet, C. and Dvorak, J. 2009. Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay. Theoretical and Applied Genetics 119 (3): 507-517.##Aranzana, M. J., Kim, S., Zhao, K., Bakker, E., Horton, M., Jakob, K., Lister, C., Molitor, J., Shindo, C., Tang, C. and Toomajian, C. 2005. Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes. PLoS Genet 1 (5): e60.##Balestre, M. V., Pinho, R. G. and Souza, J. C. 2010. Prediction of maize single cross performance by mixed linear models with microsatellite marker information. Genetics and Molecular Research 9: 1054-1068.##Balestre, M. V., Pinho, R. G. and Souza, J. C. 2011. Prediction of maize double-cross hybrids using the best linear unbiased prediction with microsatellite marker information. Genetics and Molecular Research 10 (1): 25-35.##Bernardo, R. 1994. Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Science 34 (1): 20-25.##Bernardo, R. 1995a. Genetic models for predicting maize single-cross performance in unbalanced yield trial data. Crop Science 35: 141-147.##Bernardo, R. 1995b. Relationship between single-cross performance and molecular marker heterozygosity. Theoretical and Applied Genetics 83: 628-634.##Bernardo, R. 1996a. Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance. Theoretical and Applied Genetics 93: 1098-1102.##Bernardo, R. 1996b. Best linear unbiased prediction of maize single-cross performance. Crop Science 36: 50-56.##Bernardo, R. 1996c. Best linear unbiased prediction of maize single-cross performance given erroneous inbred relationships. Crop Science 36: 862-866.##Bernardo, R. 1996d. Best linear unbiased prediction of the performance of crosses between untested maize inbreds. Crop Science 36: 872-876.##Bernardo, R. 1996e. Testcross selection prior to further inbreeding in maize: Mean performance and realized genetic variance. Crop Science 36: 867-871.##Bernardo, R. 1999. Marker-assisted best linear unbiased prediction of single-cross performance. Crop Science 39: 1277-1282.##Bernardo, R. 2010. Breeding for quantitative traits in plants. 2nd Edition. Stemma Press, Woodbury, MN. ISBN 978-0-9720724-1-0.##Bernardo, R. 2014. Genome-wide selection when major genes are known. Crop Science 54: 68-75.##Chen, E. B., Lee, M. and Lamke, L. M. 2012. Relationship of restriction fragment length polymorphisms to single-cross hybrid performance of maize. Theoretical and Applied Genetics 80: 273-280.##Choukan, R. 2006. Heterotic grouping of maize inbred lines based on specific combining ability with tester lines. Seed and Plant Journal 22 (3): 399-409. (In Persian with English Abstract).##Combs, E. and Bernardo, R. 2013. Genome-wide selection to introgress semidwarf maize germplasm into U.S. Corn Belt inbreds. Crop Science 53: 1427-1436.##Coulondre, C., Miller, J. F., Farabaugh, P. J. and Gilbert, W. 1978. Molecular basis of substitution hotspots in Escherichia coli. Nature 274: 775-780.##Dehghanpour, Z. 2001. Final report: Semi-final yield trail of early, very early and extremely early
maturity of maize hybrids. Seed and Plant Improvement Institute, Karaj, Iran. (In Persian).##Dehghan Naieri, F., Abd-Mishani, S., Shakib, A. M., Seyede Tabatabaii, S. B. E. and Bankesaz, A. 2005. Utilization of microsatellite markers for determining genetic relationships in maize inbred lines. Iranian Journal of Agricultural Sciences 36 (1): 43-49. (In Persian with English Abstract).##Ganal, M. W., Durstewitz, G., Polley, A., Bérard, A., Buckler, E. S., Charcosset, A., Clarke, J. D., Graner, E. M., Hansen, M., Joets, J. and Le Paslier, M. C. 2011. A large maize (Zea mays L.) SNP genotyping array: Development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PloS One 6 (12): e28334.##Graner, A., Ludwig, W. F. and Melchinger, A. E. 1994. Relationships among European barley germplasm: II. Comparison of RFLP and pedigree data. Crop Science 34: 1199-1205.##Hallauer, A. R. 1990. Methods used in developing maize inbreeds. Maydica 35: 1-16.##Hallauer, A. R. and Miranda, J. B. 1998. Quantitative genetic in maize breeding. Iowa State University Press, Ames.##Han, G. G, Vasal, S. K., Beck, D. L. and Elis, E. 1991. Combining ability of inbred lines derives from CIMMYT maize (Zea mays L.) germplasm. Maydica 36: 57-64.##Henderson, C. 1990. Statistical methods in animal improvement: Historical overview. Advances in statistical methods for genetic improvement of livestock. Springer. pp: 2-14.##Karimizadeh, R., Dehghani, H. and Dehghanpour, Z. 2006. Using cluster analysis for stability of maize hybrids. Journal of Crop Production and Processing 10 (3): 337-348. (In Persian with English Abstract).##Murray, M. G. and Thompson, W. F. 1980. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research 8 (19): 4321-4326.##Pootakham, W., Jomchai, N., Ruang-Areerate, P., Shearman, J. R., Sonthirod, C., Sangsrakru, D., Tragoonrung, S. and Tangphatsornruang, S. 2015. Genome-wide SNP discovery and identification of QTL associated with agronomic traits in oil palm using genotyping-by-sequencing (GBS). Genomics 105 (5-6): 288-95. https://doi.org/10.1016/j.ygeno.2015.02.002.##Poorsarebani, N., Pirseyedi, S. M., Mardi, M., Chogan, R., Babaeian, N. A., Mohammadi, S. A. and Ghareyazie, B. 2005. Heterotic groups determination in maize inbred lines using morphological and molecular markers. 4th Iranian National Biotechnology Congress, Kerman, Iran. (In Persian).##Semagn, K., Vanbessler, M., Vivek, B. S., Makumbi, D., Beyenr, Y., Stephen, M., Prasanna, B. M. and Warburton, M. L. 2012. Molecular characterization of diverse CIMMYT maize inbred lines from eastern and southern Africa using single nucleotide polymorphic markers. BMC Genomics 13: 113. https://doi.org/10.1186/1471-2164-13-113.##Smith, J. S. C. and Smith, S. O. 1992. Fingerprinting crop varieties. Advances in Agronomy 47:  85-129.##Tajbakhsh, M., 1996. Corn. Ahrar Publishers, Tabriz, Iran. (In Persian).##Terron, A., Preciade, E., Cordova, H., Mickelson, H. and Lopez, R. 1997. Determinacion del patron heterico de 30 lineas de miaze derivadas del la poblacion 43 SR del CIMMYT. Agronomía Mesoamericanna 8: 26-34. (In Spanish with English Abstract).##Toms, R. M. Carlini-Garcia, L. A. and Garcia, A. A. F. 2005. Comparison between molecular markers and diallel crosses in the assignment of maize lines to heterotic groups. Maydica 48: 63-73.##Unterseer, S., Bauer, E., Haberer, G., Seidel, M., Knaak, C., Ouzunova, M., Meitinger, T., Strom, T. M., Fries, R., Pausch, H. and Bertani, C. 2014. A powerful tool for genome analysis in maize: Development and evaluation of the high density 600k SNP genotyping array. BMC Genomics 15 (1): 823. https://doi.org/10.1186/1471-2164-15-823.##Warburton, M. L., Ribaut, J. M., Franco, J. and Crossa, J. 2005. Genetic characterization of 218 elite CIMMYT maize inbred lines using RFLP markers. Euphytica 142: 97-106.##Yu, Y., Wang, R., Shi, Y., Song, Y., Wang, T. and Li, Y. 2007. Genetic diversity and structure of the core collection for maize inbred lines in China. Maydica 52: 181-194.##Zhao, K., Aranzana, M. J., Kim, S., Lister, C., Shindo, C., Tang, C., Toomajian, C., Zheng, H., Dean, C., Marjoram, P. and Nordborg, M. 2007. An arabidopsis example of association mapping in structured samples. PLoS Genetics 3: e4. https://doi.org/10.1371/journal.pgen.0030004.##Ziaie Bidhendi, M., Choukan, R., Darvish, F., Mostafavi, K. and Majidi Hervan, E. 2012. Classifying of maize inbred lines into heterotic groups using diallel analysis. World Academy of Science, Engineering and Technology 6: 1159-1162.##