Microsatellites based parental polymorphism survey for moisture stress in Rice (Oryza sativa L.) between the parental genotypes HUR-1309 and CR Dhan 801
DOI:
https://doi.org/10.31783/elsr.2022.82248258Keywords:
drought tolerance, marker-assisted backcross breeding, microsatellites, parental polymorphism, riceAbstract
The present investigation was conducted during Rabi 2018-19. The parental polymorphism research was done at the Molecular Drought Breeding Laboratory (Department of Genetics and Plant Breeding), Institute of Agricultural Sciences, BHU, and the Crop Improvement Division, ICAR-NRRI, Cuttack. The purpose of this research was to identify the parental polymorphism markers, analyze their chromosomal distribution, and determine the repetitive motifs. The polymorphic markers will be helpful to introgress the drought tolerant yield QTLs (qDTY) from the donor CR Dhan 801 into the background of HUR-1309, a popular aromatic short duration variety through marker-assisted backcross breeding program. Polymerase chain reaction (PCR), agarose gel electrophoresis, and genomic DNA separation were carried out according to standard procedures. A total of 510 microsatellites were used for evaluation of the parental polymorphism and 90 markers showed polymorphism among the parents and the rest 420 markers are monomorphic for the studied QTLs (qDTY1.1, qDTY2.1, and qDTY3.1). The parental polymorphism in the present study ranged between 11.43% to 30.61%. Considering the 12 chromosomes of rice, the average polymorphism was observed 17.65%. Out of 90 polymorphic markers, 59 were dinucleotide repeats, 24 were trinucleotide repeats and 4 were tetra nucleotide repeats. The dinucleotides were highly present on chromosomes 1 (12), 2 (9), and 3 (9) and repeated 12, 9, and 9 times respectively. The markers which are found to be polymorphic can be used in the marker-assisted backcross breeding (MABB) program for grain yield under moisture stress.
References
[1] D. S. Rao, C. N. Neeraja, P. M. Babu, B. Nirmala, K. Suman, L. V. S. Rao and K. Surekha et al., (2020). Zinc biofortified rice varieties: challenges, possibilities, and progress in India. Front. Nutr., 7: 26. doi: 10.3389/fnut.2020.00026.
[2] B. Yue, W. Xue, L. Xiong, X. Yu, L. Luo, K. Cui and D. Jin et al., (2006). Genetic basis of drought resistance at reproductive stage in rice: separation of drought tolerance from drought avoidance. Genetics, 172: 1213-1228.
[3] G. S. Khush (2001). Green revolution: the way forward. Nature Rev. Genet., 2: 815-822.
[4] P. Vikram, B. P. M. Swamy, S. Dixit, H. U. Ahmed, M. T. S. Cruz, A. K. Singh and A. Kumar (2011). qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genet., 12: 89, doi: 10.1186/1471-2156-12-89.
[5] K. Sruthi, K. B. Eswari, K. B. Kemparaju, K. Jayaramulu and M. S. Madhav (2016). SSR marker aided parental polymorphism survey for stigma exsertion in maintainer lines of hybrid rice. Green Farming, 7: 783-786.
[6] S. Habde, S. K. Singh, M. Korada, A. Khaire, D. K. Singh, P. K. Majhi (2020). Study of allelic variation at genome wide SSR loci in parents of mapping population for high grain zinc in rice (Oryza sativa L.). J. Exp. Biol. Agric. Sci., 8: 558-575.
[7] S. R. McCouch, L. Teytelman, Y. Xu, K.B. Lobos, K. Clare, M. Walton and B. Fu et al., (2002). Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res., 9: 199-207.
[8] M. G. Murray and W. F. Thompson (1980). Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res., 8: 4321-4325.
[9] R. V. Berloo (2007). GGT: user manual Version 2.0. Wageningen (The Netherlands): Wegeningen University. Available on http:// www.plantbreeding.wur.nl/ Software/ggt/ ggt2_manual. (Accessed on 23 July, 2019).
[10] R. Van Berloo (2008). GGT 2.0: Versatile software for visualization and analysis of genetic data. J. Hered., 99: 232-236.
[11] W. M. Howell, P. C. Calder and R. F. Grimble (2002). Gene polymorphisms, inflammatory diseases and cancer. Proc. Nutr. Soc., 61: 447-456.
[12] G. S. Kumar, K. A. Kumari, C.V.D. Rani, R.M. Sundaram, S., Vanisree, M. Jamaloddin and G. Swathi (2013). Study of simple sequence repeat (SSR) polymorphism for biotic stress resistance in elite rice variety JGL 1798. Afr. J. Biotechnol., 12: 5833-5838.
[13] S. K. Biradar, R. M. Sundaram, T. Thirumurugan, J. S. Bentur, S. Amrudhan, V. V. Shenoy and B. Mishra et al., (2004). Identification of flanking SSR markers for a major rice gall midge resistance gene Gm1 and their validation. Theor. Appl. Genet., 109: 1468-1473.
[14] W. Xu, S. S. Virmani, J. E. Hernanadez, L. S. Sebastian, E. D. Redona and Z. Li (2002). Genetic diversity in the parental lines and heterosis of the tropical rice hybrids. Euphytica, 127: 139-148.
[15] S. Rathi, S. Upadhyay, P. K. Singh, R. Kumar, Pallavi, P. Bisen and B. Loitongbam et al., (2021). Study of parental polymorphism and allelic variation for grain quality and yield traits in rice (Oryza sativa L.) using SSR markers. Int. J. Plant Soil Sci., 33: 136-149,
[16] S. R. Yerva, S. K. Singh, D. K. Singh, S. Habde and P. P. Behera (2018). Parental polymorphic survey for high Zn and Fe content in grains of rice (Oryza sativa L.) using SSR markers. J. Pharmacogn. Phytochem., 7: 1362-1367.
[17] R. K. Gautam, M. Srikumar, P. K. Singh, A. K. Singh, K. Sakthivel, I. Ahmad and K. Devakumar (2015). Polymorphism between popular rice varieties of Andaman and bacterial blight resistant donor IRBB60 revealed through highly variable SSR markers. Vegetos, 29: 1-5.
[18] S. G. Waghmare, P. Sindhumole, M. R. Shylaja, D. Mathew, R. M. Francies, P. S. Abida and S. Sajini (2018). Analysis of simple sequence repeat (SSR) polymorphism between N22 and Uma rice varieties for marker assisted selection. Electron. J. Plant Breed., 9: 511-517.
[19] B. Marathi, S. Guleria, N. K. Singh, T. Mohapatra, K. V. Prabhu and A. K. Singh (2011). Molecular diversity and segregation distortion measured by SSR markers in a new plant type based recombinant inbred line population of rice. Indian J. Genet., 71: 297-303.
[20] S. Yadav, R. R. Kumar, G. Anuradha, V. L. N. Reddy and R. Sudhaka (2015). Screening of rice germplasms for sheath blight resistance and assessment of parental polymorphism using SSR markers. Eco. Env. Cons., 21: 295-301.
[21] V. Channamallikarjuna, H. Sonah, M. Prasad, G. J. N. Rao, S. Chand, H. C. Upreti, N. K. Singh and T. R. Sharma (2010). Identification of major quantitative trait loci qSBR11-1 for sheath blight resistance in rice. Mol. Breed., 25: 155-166.
[22] A. Grover, V. Aishwarya and P. C. Sharma (2007). Biased distribution of microsatellite motifs in the rice genome. Mol. Genet. Genomics, 277: 469-480.
[23] G. Narshimulu, M. Jamaloddin, L. R. Vemireddy, G. Anuradha and E. Siddiq (2011). Potentiality of evenly distributed hypervariable microsatellite markers in marker‐assisted breeding of rice. Plant Breed., 130: 314-320.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Author (s)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright © The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author(s) and source are properly credited, and the work is not modified or adapted.
