Estimating Breeding Value of Agro-biological Traits in Maize Using IRAP and REMAP Markers

Document Type : Research Paper

Authors

1 M.Sc. Student in Agricultural Biotechnology, Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.

2 Professor, Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.

Abstract

Maize is the third most important cereal after wheat and rice in the world and is a major seed source for many people in Africa, Latin America and Asia. Knowledge on function and extent of genes effect is one of the necessities to achieve high yielding cultivars. In this regard, molecular marker technology has eliminated the need to know the pedigree of genotypes for estimating the kinship matrix to evaluate genotypes breeding values. In this research, 97 genotypes of maize were evaluated in a randomized complete block design (RCBD) with 6 replications for agronomical traits. In the molecular experiment, the molecular profiles of the genotypes were prepared with 28 pairs of Inter-retro transposon amplified polymorphism (IRAP) and Retro transposon-microsatellite amplified polymorphism )REMAP( primers. Estimation the breeding valueofstudied traits in maize genotypes was done through the best linear unbiased prediction (BLUP) in the mixed linear model framewo rk by integrating molecular data based calculated kinship matrix. Considering the sum of estimated breeding values ranks for the studied traits, genotypes P3L11, P10L9, P9L6, P19L5 Kahia and (Paternal) OH43 / 1042 had the highest ranks. Positive breeding value shows that these genotypes have the greatest potential in transmitting the value of traits to the next generation. Genotype P14L2 with positive and high breeding value for leaf length, leaf area, cob weight and leaf area index and P16L6 Kahia with positive and high breeding value for plant height to cob height, cob length and grain weight in the plant, can be introduced as desirable parents to improve these traits in maize breeding programs.

Keywords

Main Subjects

References

Ahmad, I., Ahmad, B., Boote, K., & Hoogenboom, G. (2020). Adaptation strategies for maize production under climate change for semi-arid environments. European Journal of Agronomy, 115, 126040. Agrama, H. A. S. (1996). Sequential path analysis of grain yield and its components in maize. Plant Breeding, 115(5), 343-346. Bauer, A. M., Reetz, T. C., & Léon, J. (2006). Estimation of breeding values of inbred lines using best linear unbiased prediction (BLUP) and genetic similarities. Crop Science, 46(6), 2685-2691. Bernardo, R. (1994). Prediction of maize single‐cross performance using RFLPs and information from related hybrids. Crop Science, 34(1), 20-25. Bernardo, R. (2002). Breeding for quantitative traits in plants (Vol. 1, p. 369). Woodbury: Stemma press. de Souza, V. A., Byrne, D. H., & Taylor, J. F. (2000). Predicted breeding values for nine plant and fruit characteristics of 28 peach genotypes. Journal of the American Society for Horticultural Science, 125(4), 460-465. Churchill, G. A., & Doerge, R. (1994). Empirical threshold values for quantitative trait mapping. Genetics, 138(3), 963-971. Ehteshami, S.M., Ebrahimi, P., Zand, B. (2014). Investigation of quantitative and qualitative characteristics of silage corn genotypes in Varamin region. Journal of Crop Production, 5(4), 19-38. Falconer, D. S. (1996). Introduction to quantitative genetics. Pearson Education India. Farshadfar, E. (1998). Application of quantitative genetics in plant breeding. Razi University Press, Kermanshah, Iran. (In Persian). Henderson, C. R. (1990). Statistical methods in animal improvement: historical overview. In Advances in statistical methods for genetic improvement of livestock (pp. 2-14). Springer, Berlin, Heidelberg. Hoxha, S., Shariflou, M. R., & Sharp, P. (2004). Evaluation of genetic diversity in Albanian maize using SSR markers [Zea mays L.; simple sequence repeat]. Maydica (Italy). Khalifani, S., Ghaffari Azar, A., Darvishzadeh, R., Kahrizi, D., & Alipour, H. Association analysis of agromorphological traits in maize lines using retrotransposon-based markers IRAP and REMAP. Journal of Crop Breeding, 0-0. Kuhn, B. C., López‐Ribera, I., da Silva Machado, M. D. F. P., & Vicient, C. M. (2014). Genetic diversity of maize germplasm assessed by retrotransposon‐based markers. Electrophoresis, 35(12-13), 1921-1927. Marzang, N., Abdollahi Mandoulakani, B., Shaaf, S., Ghadimzadeh, M., Bernousi, I., Abbasi Holasou, H., & Sadeghzadeh, B. (2020). IRAP and REMAP-based genetic diversity among Iranian, Turkish, and International Durum wheat (Triticum turgidum L.) cultivars. Journal of Agricultural Science and Technology, 22(1), 271-285. Meuwissen, T., & Goddard, M. (2010). Accurate prediction of genetic values for complex traits by whole-genome resequencing. Genetics, 185(2), 623-631. Meyer, K. (2007). WOMBAT-A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). Journal of Zhejiang University Science B, 8(11), 815-821. Morsali Aghajari, F., Darvishzadeh, R., & Gholami, G. (2020). The effect of salt stress on morphological traits and electrophoresis pattern of proteins in recombinant inbred lines population of oilseed sunflower derived from PAC2× RHA266 cross. Environmental Stresses in Crop Sciences, 13(2), 583-600. Murray, M. G., & Thompson, W. (1980). Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research, 8(19), 4321-4326. Mutschler, M. A., Doerge, R. W., Liu, S. C., Kuai, J. P., Liedl, B. E., & Shapiro, J.A. (1996). QTL analysis of pest resistance in the wild tomato Lycopersicon pennellii: QTLs controlling acylsugar level and composition. Theoretical and Applied Genetics, 92(6), 709-718. Nuss, E. T., & Tanumihardjo, S. A. (2010). Maize: a paramount staple crop in the context of global nutrition. Comprehensive Reviews in Food Science and Food Safety, 9(4), 417-436. Oliveira, G. H., Buzinaro, R., Revolti, L., Giorgenon, C. H., Charnai, K., Resende, D., & Moro, G. V. (2016). An accurate prediction of maize crosses using diallel analysis and best linear unbiased predictor (BLUP). Chilean journal of agricultural research, 76(3), 294-299. Patterson, H. D., & Thompson, R. (1971). Recovery of inter-block information when block sizes are unequal. Biometrika, 58(3), 545-554. Piepho, H. P., Möhring, J., Melchinger, A. E., & Büchse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 161(1), 209-228. Poormohammad Kiani, S., Maury, P., Nouri, L., Ykhlef, N., Grieu, P., & Sarrafi, A. (2009). QTL analysis of yield‐related traits in sunflower under different water treatments. Plant Breeding, 128(4), 363-373. Razi, M., Darvishzadeh, R., Doulati Baneh, H., Amiri, M. E., & Martinez-Gomez, P. (2020). Estimating breeding value of pomological traits in grape cultivars based on REMAP molecular markers. Journal of Plant Productions. Razi, M., Darvishzadeh, R., Doulati Baneh, H., Amiri, M. E., & Martinez-Gomez, P. (2020). Estimating the breeding value of some pomological traits in grape cultivars of West Azarbaijan using ISSR markers. Research in Pomology, 5(1), 126-138. Roudbari, Z., Mohammadi‐Nejad, G., & Shahsavand‐Hassani, H. (2017). Field screening of primary and secondary tritipyrum genotypes using selection indices based on blup under saline and normal conditions. Crop Science, 57(3), 1495-1503. Sadeghi, F., & Rahimi, M. (2017). The use of cluster analysis for best lines selection in Maize at S6 generation. Journal of Crop Breeding, 8(20), 98-91. Searle, S. R., Casella, G., & McCulloch, C. E. (2009). Variance components. John Wiley & Sons. Semagn, K., Bjørnstad, Å., & Xu, Y. (2010). The genetic dissection of quantitative traits in crops. Electronic Journal of Biotechnology, 13(5), 16-17. Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591-611. Tahmasbali, M., Darvishzadeh, R., & Fayaz Moghaddam, A. (2020). Estimating Breeding Value of Agronomic Traits in Oriental Tobacco Genotypes under Broomrape Stress and Normal Conditions. Plant Genetic Researches, 7(1), 103-126. Xu, W., Subudhi, P. K., Crasta, O. R., Rosenow, D. T., Mullet, J. E., & Nguyen, H. T. (2000). Molecular mapping of QTLs conferring stay-green in grain sorghum (Sorghum bicolor L. Moench). Genome, 43(3), 461-469. Zarei, L., Farshadfar, E., Haghparast, R., Rajabi, R., & Badieh, M. M. S. (2007). Evaluation of some indirect traits and indices to identify drought tolerance in bread wheat (Triticum aestivum L.). Asian Journal of Plant Sciences.

Files

Share

How to cite

Statistics