Association analysis of agro-physiological traits with SCoT markers in durum wheat (Triticum durum Desf.)

Document Type : Original Article

Authors

1 Dryland Agricultural Research Institute, Sararood Branch, Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran

2 Department of Production Engineering and Plant Genetics, Faculty of Agriculture, Razi University, Kermanshah, Iran

3 Department of Plant Protection, Faculty of Agriculture, Razi University, Kermanshah, Iran

Abstract

Introduction: Knowledge of genetic diversity in crop species can play an important role in exploiting genetic diversity and lead to the development and expansion of crop cultivation in drought-prone environments. In this regard, identifying and utilizing informative markers related to agro-physiological traits will be necessary for application in breeding programs and marker-assisted selection.
Materials and methods: This study was performed to investigate the relationship between SCoT markers and agro-physiological traits in the durum wheat breeding germplasm. For this purpose, 220 durum wheat genotypes were evaluated for agronomic, phenological, and physiological traits. They were received from the International Center for Agricultural Research in the Dry Areas (ICARDA) and International Maize and Wheat Improvement Center (CIMMYT) during two consecutive cropping seasons (2017-18 and 2018-19). The germplasm was also genotyped using five SCoT markers. In order to identify the informative markers related to each trait, the regression analysis method was used.
Results: According to the results, considerable variation for agro-physiological traits was observed in the studied germplasm. The majority of ICARDA germplasms that most favored by grain yield, 1000-kernel weight (TKW), normal difference vegetative index (NDVI), plant height (PH), and peduncle length (PL) well separated from the majority of CIMMYT germplasm that most favored late in the heading (DH) and maturity (DM) and higher canopy temperature (CT). These findings indicate that the breeding lines originally developed from ICARDA might possess traits of tolerance to drought conditions absent in those developed in CIMMYT. 13 SCoT loci were associated with at least three traits based on trait-marker association analysis. These markers would enhance the efficiency of parental selection in the durum wheat breeding programs. Six informative SCoT loci (SCoT16-845, SCoT16-965, SCoT33-780, SCoT24-1400, SCoT16-845, and SCoT25-680) were identified as repeatable markers that can be considered as candidate markers for assessment of other wheat germplasm collections and scanning the genome for the related traits.
Conclusion: This study based on phenotypic data and SCoT markers revealed a high level of diversity in durum wheat breeding germplasm that may be useful in breeding programs. This information is valuable for germplasm grouping and determination of different phenotypic and genotypic groups, developing high-yielding genotypes, and using cross-breeding programs.

Keywords

References

Altıntas, S., Toklu, F., Kafkas, S., Kilian, B., Brandolini A., & Zkan, H. O. 2008. Estimating genetic diversity in durum and bread wheat cultivars from Turkey using AFLP and SAMPL markers. Plant Breeding, 127, 9-14. https://doi.org/10.1111/j.1439-0523.2007.01424.x
Cabo, S., Ferreira, L., Carvalho, A., Martins-Lopes, P., Martín, A., & Lima-Brito, J. E. 2014. Potential of start codon targeted (SCoT) markers for DNA fingerprinting of newly synthesized tritordeums and their respective parents. Journal of Applied Genetics, 55, 307–312. https://doi.org/10.1007/s13353-014-0211-3
Dellaporta, S. L., Wood, J., & Hicks, J. B. 1983. A plant DNA mini preparation: version II. Plant Molecular Biology Reporter, 1, 19–21.
Food and Agriculture Organization. 2018. Statistics: FAOSTAT agriculture. Area harvested, total production and productivity of crops. http://www.fao.org/faostat/en/#data/QC. (Accessed 10 October 2018). Accessed on date. Retrieved October 10, 2018. from http://www.fao.org/faostat/en/#data/QC
Feng, S., He, R., Yang, S., Chen, Z., Jiang, M., Lu, J., & Wang, H. 2015. Start codon targeted (SCoT) and target region amplification polymorphism (TRAP) for evaluating the genetic relationship of Dendrobium species. Gene, 567 (2), 182–188. https://doi.org/10.1016/j.gene.2015.04.076
Guo, J., Pradhan, S., Shahi, D., Khan, J. A., Mcbreen, J., Bai, G., Murphy, J. P., & Babar, M, A. 2020. Increased Prediction accuracy using combined genomic information and physiological traits in a soft wheat panel valuated in multi-environments. Scientific Reports, 10, 7023. https://doi.org/10.1038/s41598-020-63919-3
Hou, Y., Yan, Z., Wei, Y., & Zheng, Y. 2005. Genetic diversity in barely from west China based on RAPD and ISSR analysis. Barely Genetics Newsletter, 35, 9-22.
Kumar, M., Mishra, G. P., Singh, R., Kumar, J., Naik, P. K., & Singh, S. B. 2009. Correspondence of ISSR and RAPD markers for comparative analysis of genetic diversity among different apricot genotypes from cold arid deserts of trans-Himalayas. Physiology and Molecular Biology of Plants, 15 (3), 225-236. https://doi.org/10.1007/s12298-009-0026-6
Gizaw, S.A., Garland-Campbell, K. & Carter, A.H. 2016. Use of spectral reflectance for indirect selection of yield potential and stability in Pacific Northwest winter wheat. Field Crops Research 196, 199–206. https://doi.org/10.1016/j.fcr.2016.06.022
Hailu, F., Johansson, E., & Merker, A. 2010. Patterns of phenotypic diversity for phonologic and qualitative traits in Ethiopian tetraploid wheat germplasm. Genetic Resources and Crop Evolution, 57 (5), 781–790. https://doi.org/10.1007/s10722-009-9518-z
Hammer, Ø, Harper, D. A. T., & Ryan, P. D. 2001. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4 (1), art. 4: 9pp., 178kb. http://palaeo-electronica.org/2001_1/past/issue1_01.htm
Kouhestani, M., Sadeghzadeh, B., Ebrahimi, M.A., & Yousefi, V. 2016. Identification of SSR markers associated with agronomic traits in durum wheat. 2nd International and 14th Iranian Genetic Congress, 21-23 May 2016, Tehran, Iran. [In Persian].
Lopes, M. S., & Reynolds, M. P. 2010. Partitioning of assimilates to deeper roots is associated with cooler canopies and increased yield under drought in wheat. Functional Plant Biology, 37 (2), 147–156.  https://doi.org/10.1071/FP09121
Lopes, M. S., Royo, C., Alvaro, F., Sanchez-Garcia, M., Ozer, E., Ozdemir, F., Karaman, M., Roustaii, M., Jalal-Kamali, M. R. & Pequeno, D. 2018. Optimizing winter wheat resilience to climate change in rain fed crop systems of Turkey and Iran. Frontiers in Plant Science, 9, 563. https://doi.org/10.3389/fpls.2018.00563
Luo, C., He, X., Chen, H., Ou, S., & Gao, M. 2010. Analysis of diversity and relationships among mango cultivars using Start Codon Targeted (SCoT) markers. Biochemical Systematics and Ecology, 38 (6), 1176–1184. https://doi.org/10.1016/j.bse.2010.11.004
Merida-Garcia, R., Liu, G., He, S., Gonzalez-Dugo, V., Dorado, G., Galvez, S., Solis, I., Zarco-Tejada, P. J., Reif, J. C., & Hernandez, P. 2019. Genetic dissection of agronomic and quality traits based on association mapping and genomic selection approaches in durum wheat grown in Southern Spain. PloS one, 14 (2), e0211718. https://doi.org/10.1371/journal.pone.0211718
McIntyre, C. L., Mathews, K. L., Rattey, A., Chapman, S. C., Drenth, J., Ghaderi, M. et al. (2010). Molecular detection of genomic regions associated with grain yield and yield-related components in an elite bread wheat cross evaluated under irrigated and rainfed conditions. Theoretical and Applied Genetics, 120, 527–541. https://doi.org/10.1007/s00122-009-1173-4
Mohammadi, R., Abdolahi, A., Mohammadi, M. S., Elahi, K., & Yari, S. R. 2016. Evaluation of yield gap of durum wheat genotypes under research and farmers' fields conditions. Research Achievements for Field and Horticulture Crops, 9 (2), 133-141. [In Persian]. DOI: https://doi.org/10.22092/RAFHC.2016.109760
Mohammadi, R., Etminan, A., & Shooshtari, L. 2019. Agro-physiological characterization of durum wheat genotypes under drought conditions. Experimental Agriculture, 55 (3), 484–499. https://doi.org/10.1017/S0014479718000133
Mohammadi, S. A. 2008. New methods of genetic analysis of quantitative traits in plants. Proceedings of the Tenth Congress of Agronomy and Plant Breeding, Seed and Plant Improvement Institute, Karaj. 183-201. [In Persian].
Morgounov, A., Özdemir, F., Keser, M., Akin, B., Dababat, A.A., Dreisigacker, S., Golkari, S., Koc, E., Küçükçongar, M., Muminjanov, H., Nehe, A., Rasheed, A., Roostaei, M., Sehgal, D., & Sharma, R 2021. Diversity and adaptation of currently grown wheat landraces and modern germplasm in Afghanistan, Iran and Turkey. Crops, 1 (2), 54–67. https://doi.org/10.3390/crops1020007
Powell, W., Morgante, M., Andre, C., Hanafey, M., Vogel, J., Tingey, S. & Rafalski, A. 1996. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Molecular Breeding, 2, 225-238. https://doi.org/10.1007/BF00564200
Rashidi Monfared, S., Mardi, M., Hoseinzadeh, A. H., & Naghavi, M. R. 2008. Association analysis of important agronomic traits to retrotransposon markers SSAPs in durum wheat accessions. Journal of Modern Genetics, 3, 29-35. [In Persian]. DOI: https://doi.org/20.1001.1.20084439.1387.3.2.4.3
Rawashdeh, N. K., Haddad, N. I., Al-Ajlouni, M. M., & Turk, M. A. 2007. Phenotypic diversity of durum wheat (Triticum durum Desf.) from Jordan. Genetic Resources and Crop Evolution, 54, 129–138. https://doi.org/10.1007/s10722-005-2636-3
Shavrukov, Y., Kurishbayev, A., Jatayev, S., Shvidchenko, V., Zotova, L., Koekemoer, F., de Groot, S., Soole, K., & Langridge, P. 2017. Early flowering as a drought escape mechanism in plants: How can it aid wheat production? Frontiers in Plant Science, 8, 1950. https://doi.org/10.3389/fpls.2017.01950
Soriano, J. M., Malosetti, M., Roselló, M., Sorrells, M. E., & Royo, C. 2017. Dissecting the old Mediterranean durum wheat genetic architecture for phenology, biomass and yield formation by association mapping and QTL meta-analysis. PloS one, 12 (5), e0178290. https://doi.org/10.1371/journal.pone.0178290
Tabasi, M., Sheidai, M., Hassani, D., &Koohdar, F. 2020. DNA fingerprinting and genetic diversity analysis with SCoT markers of Persian walnut populations (Juglans regia L.) in Iran. Genetic Resources and Crop Evolution, 67, 1437–1447. https://doi.org/10.1007/s10722-020-00914-7
Williams, J. G. K., Kubelik, A. R., Livak, K. J., Rafalski, J. A., & Tingey, S. V. 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Research, 18 (22), 6531–5.
Yousef, G. G., & Juvik, J. A. 2001. Comparison of phenotypic and marker-assisted selection for quantitative traits in sweet corn. Crop Science, 41, 645–655. https://doi.org/10.2135/cropsci2001.413645x

Files

Share

How to cite

Statistics