Journal of Genetics

, 99:5 | Cite as

Variation of grain quality characters and marker-trait association in rice (Oryza sativa L.)

  • K. SUMAN
  • C. N. NEERAJAEmail author
Research Article


A set of 24 genotypes were studied for 17 grain quality characters and validated with the reported associated rice microsatellite markers with grain quality characters. Using 23 polymorphic markers distributed across 11 chromosomes marker-trait associations were studied. The percentage of polymorphism information content (PIC) of the markers ranged between 54.0 and 86.7. Eight markers with >80% and seven markers with >70% of PIC were found to be efficient in differentiating the studied grain quality characters. A total of 37 significant marker-trait associations (P ≤ 0.09) were found with R2 ranging from 4.70% to 43.80%. Eight markers a (RM246, RM11, RM241, RM16427, RM421, RM3, RM234 and RM257) showed association with more than one character suggesting their utility for the selection for grain quality characters which can be deployed in the rice crop improvement programmes.


grain quality microsatellite markers association validation. 



Authors are thankful to ICAR-CRP-Biofortification project, ICAR-Indian Institute of Rice Research, Hyderabad for financial support and providing facilities.


  1. Akinwale M. G., Gregorio G., Nwilene F., Akinyele B. O., Ogunbayo S. A. and Odiyi A. C. 2011 Heritability and correlation coefficient analysis for yield and its components in rice (Oryza sativa L). Afr. J. Plant Sci. 5, 207–212.Google Scholar
  2. Bai X. F., Luo L. J., Yan W. H., Kovi M. R., Zhan W. and Xing Y. Z. 2010 Genetic dissection of rice grain shape using a recombinant inbred line population derived from two contrasting parents and fine mapping a pleiotropic quantitative trait locus qGL7. BMC Genet. 11, 16.CrossRefGoogle Scholar
  3. Balaji Suresh P., Srikanth B., Hemanth Kishore V., SubhakaraRao I., Vemireddy L. N. and Dharika N. 2012 Fine mapping of Rf3 and Rf4 fertility restorer loci of WA-CMS of rice (Oryza sativa L.) and validation of the developed marker system for identification of restorer lines. Euphytica 187, 421–435.CrossRefGoogle Scholar
  4. Ban T. 1971 Rice cracking in high rate drying. Jpn. Agr. Res. Q. 6, 113–116.Google Scholar
  5. Bautista R. C., Siebenmorgen T. J. and Cnossen A. G. 2000 Fissure formation characterization in rice kernels using video microscopy. In Proceedings of the 2000 international drying symposium. Noordwijkerhout, The Netherlands.Google Scholar
  6. Blair M. W. and McCouch S. R. 1997 Microsatellite and sequenced tagged site markers diagnostic for the rice bacterial leaf blight resistance gene xa-5. Theor. Appl. Genet. 95, 174–184.CrossRefGoogle Scholar
  7. Boualaphanh C., Calingaciona M., Cuevasa R. P., Jothityangkoonb D., Sanitchonb J. and Fitzgeralda M. 2011 Yield and quality of traditional and improved Lao varieties of rice. Sci. Asia 37, 89–97.CrossRefGoogle Scholar
  8. Bouis H. E. and Welch R. M. 2010 Biofortification is a sustainable agricultural strategy for reducing micronutrient malnutrition in the global south. Crop Sci. 50, S20–S32.CrossRefGoogle Scholar
  9. Bradbury P. J., Zhang Z., Kroon D. E., Casstevens T. M., Ramdoss Y. and Buckler E. S. 2007 Tassel:software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635.Google Scholar
  10. Cagampang G. B., Perez C. M. and Juliano B. O. 1973 A gel consistency test for eating quality in rice. J. Sci. Food Agric. 24, 1589–1594.CrossRefGoogle Scholar
  11. Cnossen A. G. and Siebenmorgen T. J. 2000 The glass transition temperature concept in rice drying and tempering effect on milling quality. Trans. ASAE 23, 1661–1667.CrossRefGoogle Scholar
  12. Enoki H., Sato H. and Koinuma K. 2002 SSR analysis of genetic diversity among maize inbred lines adapted to cold regions of Japan. Theor. Appl. Genet. 104, 1270–1277.CrossRefGoogle Scholar
  13. Fan C. C., Yu X. Q., Xing Y. Z., Xu C. G., Luo L. G. and Zhang Q. F. 2005 The main effects, epistatic effects and environmental interactions of QTLs on the cooking and eating quality of rice in a doubled-haploid line population. Theor. Appl. Genet. 110, 1445–1452.CrossRefGoogle Scholar
  14. Gregorio G. B. 2002 Progress in breeding for trace minerals in staple crops. J. Nutr. 132, 500–502.CrossRefGoogle Scholar
  15. He P., Li S. G., Qian Q., Ma Y. Q., Li J. Z., Wang W. L. et al. 1999 Genetic analysis of rice grain quality. Theor. Appl. Genet. 98, 502–508.CrossRefGoogle Scholar
  16. IRRI 2015 Steps to successful rice production, pp. 1–27. International Rice Research Institute, Manila.Google Scholar
  17. Johanson H. W., Robinson H. F. and Comstock R. E. 1955 Estimates of genetic and environmental variability in soybean. Agron. J. 47, 314–318.CrossRefGoogle Scholar
  18. Joshi S. P., Gupta V. S., Aggarwal R. K., Ranjekar P. K. and Brar D. S. 2000 Genetic diversity and phylogenetic relationship as revealed by inter simple sequence repeat (ISSR) polymorphism in the genus Oryza. Theor. Appl. Genet. 100, 1311–1320.CrossRefGoogle Scholar
  19. Juliano B. O. 1971 Simplified assay for milled-rice amylose. Cereal Sci. Today 16, 334–338.Google Scholar
  20. Juliano B. O. 1985 Criteria and test for rice grain quality. In Rice chemistry and technology, 2nd edition, pp. 443–513. American Association of Cereal Chemists, Minnesota.Google Scholar
  21. Juliano B. O. and Bechtel D. B. 1985 The rice grain and its gross composition. In Rice chemistry and technology, 2nd edition, pp. 17–57. American Association of Cereal Chemists, Minnesota.Google Scholar
  22. Khush G. S., Paule C. M. and Dela Cruz N. M. 1979 Rice grain quality evaluation and improvement at IRRI. In Proceedings of the workshop on chemical aspects of rice grain, pp. 21–31. International Rice Research Institute, Manila, Philippines.Google Scholar
  23. Kiranmayi S. L., Manorama K., Venkata V. G. N. T., Radhika K., Cheralu C., Roja V. et al. 2014 Identification of markers associated with iron and zinc concentration in recombinant inbred lines of brown rice. Indian J. Genet. Plant Breed. 74, 423–429.CrossRefGoogle Scholar
  24. Kongseree N. and Juliano B. O. 1972 Physiochemical properties of rice grain and starch from lines differing in amylose content and gelatinization temperature. J. Sci. Food Agric. 20, 714–718.CrossRefGoogle Scholar
  25. Kunze O. R. 1979 Fissuring of the rice grain after heated air drying. Trans. ASAE 22, 1197–1202.CrossRefGoogle Scholar
  26. Lin H. X., Min-Shao K., Xiong Z. M., Qian H. R., Zhuang J. Y., Lu J. et al. 1995 RFLP mapping of QTLs for grain shape traits in indica rice (Oryza sativa L. subsp. indica). Sci. Agric. Sin. 28, 1–7.Google Scholar
  27. Little R. R., Hilder G. B. and Dawson E. H. 1958 Differential effect of dilute alkali on 25 varieties of milled white rice. Cereal Chem. 35, 111–126.Google Scholar
  28. Madhubabu P., Suman K., Ramya Rathod., Fiyaz R. A., Rao S. D., Sudhakar P. et al. 2017 Evaluation of grain yield, quality and nutrients content in four rice (Oryza sativa L.) genotypes. Curr. J. Appl. Sci. Technol. 22, 1–12.Google Scholar
  29. Ni J. J., Colowit P. M. and Mackill D. J. 2002 Evaluation of genetic diversity in rice sub-species using microsatellite markers. Crop Sci. 42, 601–607.CrossRefGoogle Scholar
  30. Pandey M. K., Rani N. S., Madhav M. S., Sundaram R. M., Varaprasad G. S., Sivaranjani A. K. P. et al. 2012 Different isoforms of starch-synthesizing enzymes controlling amylose and amylopectin content in rice (Oryza Sativa L.). Biotechnol. Adv. 30, 1697–1706.CrossRefGoogle Scholar
  31. Parikh M., Motiramani N. K., Rastogi N. K. and Sharma B. 2012 Agro-morphological characterization and assessment of variability in aromatic rice germplasm. Bangladesh J. Agric. Res. 37, 1–8.CrossRefGoogle Scholar
  32. Rabiei B., Valizadeh M., Ghareyazie B., Moghaddam M. and Ali A. J. 2004 Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers. Euphytica 137, 325–332.CrossRefGoogle Scholar
  33. Rao S. D., Madhu Babu P., Swarnalatha P., Suneetha K., Bhadana V. P., Varaprasad G. S. et al. 2014 Assessment of grain zinc and iron variability in rice germplasm using energy dispersive X-ray fluorescence spectrophotometer (ED-XRF). J. Rice Res. 7, 45–52.Google Scholar
  34. Rehal J., Kaur G. J. and Singh A. K. 2017 Influence of milling parameters on head rice recovery: a review. Int. J. Curr. Microbiol. App. Sci. 6, 1278–1295.CrossRefGoogle Scholar
  35. RKMP 2014 Rice knowledge management portal (
  36. Sangeetha A., Malhotra P. K., Bhatia V. K. and Rajendra P. 2008 Statistical package for agricultural research (SPAR 2.0). J. Indian Soc. Agric. Stat. 62, 65–74.Google Scholar
  37. Sarwar A. K. M. G., Ali M. A. and Karim M. A. 1998 Correlation of grain characters in rice (Oryza sativa. L). J. Natn. Sic. Foundation Sri Lanka 26, 209–215.CrossRefGoogle Scholar
  38. SES (Standard Evaluation System for Rice) 2013 5th edition. IRRI, Manila, Philippines (
  39. Talukdar P. R., Rathi S., Pathak K., Chetia S. K. and Sarma R. N. 2017 Population structure and marker-trait association in indigenous aromatic rice. Rice Sci. 24, 145–154.CrossRefGoogle Scholar
  40. Tan Y. F., Li J. X., Yu S. B., Xing Y. Z., Xu C. G. and Zhang Q. 1999 The three important traits for cooking and eating quality of rice grains are controlled by a single locus in an elite rice hybrid, Shanyou 63. Theor. Appl. Genet. 99, 642–648.CrossRefGoogle Scholar
  41. Temnykh S., DeClerck G., Lukashova A., Lipovich L., Cartinhour S. and McCouch S. 2001 Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, and genetic marker potential. Genome Res. 11, 1441–1452.CrossRefGoogle Scholar
  42. Yadav B. K., and Jindal V. K. 2007 Dimensional changes in milled rice (Oryza sativa L.) kernel during cooking in relation to its physicochemical properties by image analysis. J. Food Eng. 81, 710–720.CrossRefGoogle Scholar
  43. Yu J., Pressoir G., Briggs W. H., Bi I. V., Yamasaki M., Doebley J. F. et al. 2006 A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38, 203–208.CrossRefGoogle Scholar
  44. Zheng K., Huang N., Bennett J. and Khush G. S. 1995 PCR-based marker assisted selection in rice breeding. In IRRI Discussion Paper Series, No. 12. International Rice Research Institute, Manila.Google Scholar

Copyright information

© Indian Academy of Sciences 2020

Authors and Affiliations

  • K. SUMAN
    • 1
    • 2
    • 1
    • 1
    • 1
    • 2
    • 2
    • 1
    • 1
    • 1
    Email author
  1. 1.Indian Institute of Rice ResearchHyderabadIndia
  2. 2.Department of Genetics and BiotechnologyOsmania UniversityAmberpet, HyderabadIndia

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