MODERN TECHNOLOGIES TO IMPROVE CROP PLANTS
Keywords:
Marker Assisted Selection, QTLS, recurrent selection, heterozygous, mass selectionAbstract
In plant science selection plays a key breeding approach for improving economic features in many plants’ kind. Selection techniques vary based on the mechanism of reproduction. Self-pollinated crops employ pure line and mass selection methods, whereas cross-pollinated crops use recurrent selection. Vegetatively propagated plants use clonal selection. Regardless of Phenotypic recurrent selection is a successful approach for enhancing polygenic features. While increasing the frequency of desirable genes for economic characters can help maintain high genetic variability in heterozygous populations, the efficiency and effectiveness of this approach may not be satisfactory in most cases. This is due to phenotypic selection being influenced by environmental factors and genotypic selection taking at least 2-3 crop seasons per cycle. Molecular marker technology allows for faster and more efficient selection, as it is unaffected by environmental factors. Marker Assisted Recurrent Selection is a key strategy in molecular breeding because it allows for multiple QTLs to control complex traits, unlike Marker Assisted Selection and Marker Assisted Backcrossing
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Abbas, A., Arshad, A., Rehman, A. U., Bukhari, M. S., and Zaman, S. (2024). Revolutionizing plant breeding programs with advancements in molecular marker-assisted selection. Bulletin of Biological and Allied Sciences Research 2024, 57.
Arshad, A., Iqbal, M. A., Farooq, S., and Abbas, A. (2024). Genetic evaluation for seed yield and its component traits in sunflower (Helianthus annuus l.) using line × tester approach. Bulletin of Biological and Allied Sciences Research 2024, 63.
Bernardo, R. (2008). Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop science 48, 1649-1664.
Bernardo, R. (2010). Genomewide selection with minimal crossing in self‐pollinated crops. Crop Science 50, 624-627.
Bernardo, R., and Charcosset, A. (2006). Usefulness of gene information in marker‐assisted recurrent selection: A simulation appraisal. Crop Science 46, 614-621.
Bernardo, R., and Yu, J. (2007). Marker-assisted selection without QTL mapping: prospects for genome-wide selection for quantitative traits in maize.
Charmet, G., Robert, N., Perretant, M.-R., Gay, G., Sourdille, P., Groos, C., Bernard, S., and Bernard, M. (1999). Marker-assisted recurrent selection for cumulating additive and interactive QTLs in recombinant inbred lines. Theoretical and Applied Genetics 99, 1143-1148.
Crosbie, T. M., Eathington, S. R., Johnson Sr, G. R., Edwards, M., Reiter, R., Stark, S., Mohanty, R. G., Oyervides, M., Buehler, R. E., and Walker, A. K. (2006). Plant breeding: past, present, and future. In "Plant breeding: the Arnel R. Hallauer international symposium", pp. 3-50. Wiley Online Library.
Eathington, S. (2005). Practical applications of molecular technology in the development of commercial maize hybrids. In "Proceedings of the 60th annual corn and sorghum seed research conferences". American Seed Trade Association Washington, DC.
Eathington, S. R., Crosbie, T. M., Edwards, M. D., Reiter, R. S., and Bull, J. K. (2007). Molecular markers in a commercial breeding program. Crop Science 47, S-154-S-163.
Fatima, S., CHEEMA, K., Shafiq, M., Manzoor, M., Ali, Q., Haider, M., and Shahid, M. (2023). The genome-wide bioinformatics analysis of 1-aminocyclopropane-1-carboxylate synthase (acs), 1-aminocyclopropane-1-carboxylate oxidase (aco) and ethylene overproducer 1 (eto1) gene family of fragaria vesca (woodland strawberry). Bulletin of Biological and Allied Sciences Research 2023, 38-38.
Gazal, A., Dar, Z., Lone, A., Abidi, I., and Ali, G. (2015). Molecular breeding for resilience in maize-a review. Journal of Applied and Natural Science 7, 1057-1063.
Guo, Z., Tucker, D. M., Lu, J., Kishore, V., and Gay, G. (2012). Evaluation of genome-wide selection efficiency in maize nested association mapping populations. Theoretical and Applied Genetics 124, 261-275.
Haider, M., Sami, A., Mazhar, H., Akram, J., NISA, B., Umar, M., and Meeran, M. (2023). Exploring morphological traits variation in Gomphrena globosa: A multivariate analysis. Biological and Agricultural Sciences Research Journal 2023, 21-21.
Jiang, G.-L., Shi, J., and Ward, R. W. (2007). QTL analysis of resistance to Fusarium head blight in the novel wheat germplasm CJ 9306. I. Resistance to fungal spread. Theoretical and Applied Genetics 116, 3-13.
Johnson, R. (2004). Marker-assisted selection. Plant breeding reviews 24, 293-310.
Junaid, M. D., and Gokce, A. F. (2024). Global agricultural losses and their causes. Bulletin of Biological and Allied Sciences Research 2024, 66.
Lorenz, A. J. (2013). Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment. G3: Genes, Genomes, Genetics 3, 481-491.
Massman, J. M., Jung, H. J. G., and Bernardo, R. (2013). Genomewide selection versus marker‐assisted recurrent selection to improve grain yield and stover‐quality traits for cellulosic ethanol in maize. Crop Science 53, 58-66.
Meuwissen, T. H., Hayes, B. J., and Goddard, M. (2001). Prediction of total genetic value using genome-wide dense marker maps. genetics 157, 1819-1829.
Moreau, L., Charcosset, A., and Gallais, A. (2004). Experimental evaluation of several cycles of marker-assisted selection in maize. Euphytica 137, 111-118.
Nakaya, A., and Isobe, S. N. (2012). Will genomic selection be a practical method for plant breeding? Annals of botany 110, 1303-1316.
Ooijen, J. v., and Jansen, J. (1994). "Biometrics in plant breeding: applications of molecular markers. Proceedings of the ninth meeting of the EUCARPIA Section Biometrics in Plant Breeding, Wageningen, the Netherlands, 6-8 July 1994."
Openshaw, S., and Frascaroli, E. (1997). QTL detection and marker-assisted selection for complex traits in maize. In "52nd annual corn and sorghum industry research conference. ASTA, Washington, DC", pp. 44-53.
Peleman, J. D., and Van der Voort, J. R. (2003). Breeding by design. Trends in plant science 8, 330-334.
Ragot, M., Gay, G., Muller, J.-P., and Durovray, J. (2000). Efficient selection for the adaptation to the environment through QTL mapping and manipulation in maize. Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments, 128-130.
Rani, P. J., Satyanarayana, P., Chamundeswari, N., and Rani, M. G. (2014). A Review on Marker Assisted Selection in Crop Improvement.
Rasheed, M. U., Malik, A., and Ali, M. S. (2024). Genetic variation and heritability estimates in chickpea seedling traits: implications for breeding programs. Bulletin of Biological and Allied Sciences Research 2024, 59.
Ribaut, J.-M., and Ragot, M. (2007). Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations, and alternatives. Journal of experimental botany 58, 351-360.
Ribaut, J., De Vicente, M., and Delannay, X. (2010). Molecular breeding in developing countries: challenges and perspectives. Current opinion in plant biology 13, 213-218.
van Berloo, R., and Stam, P. (1998). Marker-assisted selection in autogamous RIL populations: a simulation study. Theoretical and Applied Genetics 96, 147-154.
Yi ChengXin, Y. C., Guo WangZhen, G. W., Zhu XieFei, Z. X., Min LiuFang, M. L., and Zhang TianZhen, Z. T. (2004). Pyramiding breeding by marker-assisted recurrent selection in upland cotton: II. Selection effects on resistance to Helicoverpa armigera.
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Copyright (c) 2024 M UZAIR, A ABBAS, AU REHMAM, MZ HAIDER (Author)
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