Skip to main navigation menu Skip to main content Skip to site footer

Research Articles

Early Access

Molecular characterization of Indian paddy varieties using SSR markers and unveiling G × E interactions of paddy varieties under the Cauvery Delta region

DOI
https://doi.org/10.14719/pst.7850
Submitted
21 February 2025
Published
01-07-2025
Versions

Abstract

Twenty-eight popular paddy varieties released and notified throughout India between 1976 and 2015 were molecularly characterized using SSR markers. The lab analysis was conducted at the Biotechnology Laboratory, Faculty of Agriculture, Annamalai University and stability study over three locations under the Cauvery Delta region during December 2022 to May 2023. The results showed that nine SSR primers were polymorphic and PIC values varied from 0.363 to 0.551, while the marker RM 118 had the highest PIC value (0.551). The range of the detected heterozygosity was 0.304 to 0.622. Neis’ genetic distance created the dendrogram, which divided the varieties into seven clusters. According to Neis’ genetic measure, variety G8 (ADT 39) from cluster I and G15 (TKM 9) from cluster VII confirmed the degree of genetic diversity among the varieties studied. From molecular genetic diversity, nine high-yielding varieties were chosen based on grain yield per plant and subjected to stability analysis in three different environments. Significant genotype × environment interaction was observed for all the characters; hence, these varieties' stability was assessed. Variety, G9 (ADT 48) showed non-significant S2di and regression coefficient value around unity with high mean for days to first flowering, grain length and grain yield per plant and plotted under group I in genotype grouping technique. Varieties viz., G8 (ADT 37), G9 (ADT 48), G15 (TKM 9) and G16 (MDU 6) are the most stable and acceptable for both favourable and unfavourable environments. It showed stability factor around unity for grain yield per plant and they will be selected as parents to develop stress-tolerant varieties.

References

  1. 1. Ashok S, Jyothula DPB, Ratnababu D. Genetic divergence studies for yield components and grain quality parameters in Rice (Oryza sativa L.). Elect J Plant Breed. 2017;8(4):1240–26. https://doi.org/10.5958/0975-928X.
  2. 2. Paddy Outlook, [internet]; 2024 [cited 2025 Feb 20]. Available from: www.usda.gov.
  3. 3. Gaballah MM, Attia, KA, Ghoneim AM, Khan N, El-Ezz AF, Yang B. Assessment of genetic parameters and gene action associated with heterosis for enhancing yield characters in novel hybrid rice parental lines. Plants 2022;11:266. https://doi.org/10.3390/plants11030266
  4. 4. Balasubramanian M, Vennila S. Genetic diversity, correlation and path co-efficient for yield and yield associated traits in rice (Oryza sativa L.). Crop Res. 2022;57(5&6):420–26. https://doi.org10.31830/2454-1761.2022.890
  5. 5. Balasubramanian M, Vennila S. Comprehensive Evaluation of rice genotypes for salt tolerance: in vitro screening, association studies and principal component analysis. Environ Ecol. 2024;42 (4A): 1677–87. https://doi.org/10.60151/envec/ZANZ3740
  6. 6. Aruna N, Elangaimannan R, Sriramachandrasekharan MV, Vennila S. Unravelling the genetic distance among traditional and commercial rice (Oryza sativa L.) genotypes using Mahalanobis D² statistics. Biochem Cellular Archives. 2024;24(1): 1357–64. https://doi.org/10.51470/bca.2024.24.1.1357
  7. 7. Vennila.S, Desika J, Suganthi S, Bhuveneshwari R. Genetic diversity in released and traditional rice (Oryza sativa L.) varieties of Tamilnadu using D2 statistics. Indian J Nat Sci.2022; 13(74): 47835–40.
  8. 8. Singh N, Choudhury DR, Tiwari G, Singh AK, Kumar S, Srinivasan K, et al. Genetic diversity trend in Indian rice varieties: an analysis using SSR markers. BMC Genet. 2016 Dec;17:1–3. https://doi.org/10.1186/s12863-016-0437-7
  9. 9. Balakrishnan D, Subrahmanyam D, Badri J, Raju AK, Rao YV, Beerelli K, et al. Genotype x environment interactions of yield traits in backcross introgression lines derived from Oryza sativa cv. Swarna/Oryza nivara. Fron Plant Sci. 2016;7:1530. https://doi.org/10.3389/fpls.2016.01530
  10. 10. Jiban S, Ujjawal KSK, Bidhya M, Sushil RS, Manoj K, Amrit PP, et al. Genotype × environment interaction and grain yield stability in Chinese hybrid rice. Ruhuna J Sci. 2020;11(1): 47–58. https://doi.org/10.4038/rjs.v11i1.86
  11. 11. Manivannan, N. 2014. TNAUSTAT-Statistical Package [internet]; 2014 [cited 2025 Feb 20]. Available from: https://sites.google.com/site/tnaustat
  12. 12. Nei M. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics. 1978;89(3):589–90. https://doi.org/10.1093/genetics/89.3.583
  13. 13. Shete S, Tiwari H, Elston RC. On estimating the heterozygosity and polymorphism information content value. Theor Popul Biol. 2000;57(3):265–71. https://doi.org/10.1006/tpbi.2000.1452
  14. 14. Eberhart SA, Russell WA. Stability parameters for comprising varieties. Crop Sci. 1966;6:36–40. https://doi.org/10.
  15. 2135/cropsci1966.0011183X000600010011x
  16. 15. Francis TR and Kannenberg LW. Yield stability studies in short-season maize. 1. a descriptive method for grouping genotypes. Can J Pl Sci. 1978;58:1029–34. https://doi.org/10.4141/cjps78-157
  17. 16. Lakshmi, M. Shanmuganathan, Jeyaprakash P, Ramesh T. Genetic variability and diversity analysis in selected rice (Oryza sativa L) varieties. Elect J Pl Breed. 2022;13(3):959–66. https://doi.org/10.37992/2022.1303.124.
  18. 17. Humaria Ashraf, Amjad MH, M Ashraf Bhat, GA Parray, Salim Khan, Nazir A Ganai. SSR based genetic diversity of pigmented and aromatic rice (Oryza sativa L.) genotypes of the western Himalayas region of India. Physiol Mole Biol Pl. 2016;22(4):547–55. https://doi.org/10.1007/s12298-016-0377-8. 16.
  19. 18. Dhama N, Saini RK, Kumar R, Chaudhary DP, Maurya BK, Sharma M, et al. Analysis of Genetic Diversity in Rice (Oryza sativa L.) cultivars using SSR Markers. Bull Environ Pharmac Life Sci. 2018;7:1–7. https://researchgate.net/publication/323915286
  20. 19. Shamim MZ. H.Manzar, Sharma, VK, Kumar P. Microsatellite marker based characterization and divergence analysis among rice varieties. Indian J Biotech.2016;(15):182–89.
  21. 20. Vigneshwari R., A. Vijaykumar, M. Raveendran. Characterization of South Indian paddy varieties under commercial cultivation through morphological and molecular markers. Intl J Agric Sci Res. 2017;7(4):465–72. https://doi.org/10.24247/ijasraug201759
  22. 21. Babu N, Hittalmani S, Shivakumar N, Nandini C. Effect of drought on yield potential and drought susceptibility index of promising aerobic rice (Oryza sativa L.) genotypes. Elect J Pl Breed. 2011;2:295–302.
  23. 22. Acuña TL, Lafitte HR, Wade LJ. Genotype x Environment interactions for grain yield of upland rice backcross lines in diverse hydrological environments. Field Crops Res. 2008;108:117–125. https://doi.org/10.1016/j.fcr.2008.04.003
  24. 23. Zelalem Zewdu, Tefera Abebe, Tesfaye Mitiku, Fisseha Worede, Abebaw Dessie, Assaye Berie, et al. Performance evaluation and yield stability of upland rice (Oryza sativa L.) varieties in Ethiopia. Cogent Food Agric. 2020:6(1):1842679. https://doi.org/10.1080/23311932.2020.1842679
  25. 24. Shrestha J, Kushwaha US, Maharjan B, Kandel M, Gurung SB, Poudel A P, et al. Grain Yield Stability of Rice Genotypes. Indonesian J Agric Res. 2020;3(2): 116–26. https://doi.org/10.32734/injar.v3i2.3868
  26. 25. Sriram Ajmera, S. Sudheer Kumar, V. Ravindrababu. Studies on stability analysis for grain yield and its attributes in rice (Oryza sativa L.) genotypes. International of Pure and Applied Bioscience. 2017; 5 (4): 892–908. https://doi.org/
  27. 10.18782/2320-7051.4079
  28. 26. Bose LK, Nagaraju M, Singh ON. Genotype × Environment interaction and stability analysis of lowland rice genotypes. Journal of Agricultural Sciences Belgrade, 2012;57:1–8. https://doi.org/10.2298/JAS1201001B
  29. 27. Jain BT, Sarial AK, Kaushik P. Stability analysis utilizing AMMI model and regression analysis for grain yield of basmati rice (Oryza sativa L.) genotypes. J Exp Biol Agric Sci. 2018;6(3):522–530. https://doi.org/10.18006/2018.6(3).
  30. 522.530
  31. 28. Hasan MJ, Kulsum MU, Hossain MM, Akond Z, Rahman MM. Identification of stable and adaptable hybrid rice genotypes. SAARC J Agri. 2014;12(2):1–15. https://doi.org/10.3329/SJA.V12I2.21912
  32. 29. Sadimantara GR, Kadidaa B, Suaib Sufan LO, Muhdin. Growth performance and yield stability of selected local upland rice genotypes in Buton Utara of Southeast Sulawesi. Earth Environ Sci. 2018;122:1–6. https://doi.org/10.108
  33. 8/1755-1315/122/1/012094
  34. 30. Sandhu N, Yadaw RB, Chaudhary B, Prasai H, Iftekharuddaula K, Venkateshwarlu C, et al. Evaluating the performance of rice genotypes for improving yield and adaptability under direct seeded aerobic cultivation conditions. Front Plant Sci. 2019;10. https://doi.org/10.3389/fpls.2019.00159.
  35. 31. Seyou M, Alamerew S, Bantte K. Stability analysis of grain yield in rice genotypes across environments of Jimma Zone Western Ethiopia. J Cereals Oilseeds, 2016;7(3):27–33. https://doi.org/10.5897/JCO2016.0159
  36. 32. Radhamani T, Sasikumar D, Packiaraj D, Veni K. Stability Analysis for grain quantity parameters among the mutant rice (Oryza sativa L.). Intl J Biol Res Stress Manage. 2017;8(1):20–25. https://doi.org/10.23910/IJBSM/2017.8.
  37. 1.1768

Downloads

Download data is not yet available.