Journal of Genetics

, Volume 91, Issue 1, pp 9–19 | Cite as

Molecular evaluation of genetic diversity and association studies in rice (Oryza sativa L.)

  • K. K. VINODEmail author
Research Article


In the present study, we tested rice genotypes that included un(der)exploited landraces of Tamil Nadu along with indica and japonica test cultivars to ascertain their genetic diversity structure. Highly polymorphic microsatellite markers were used for generating marker segregation data. A novel measure, allele discrimination index, was used to determine subpopulation differentiation power of each marker. Phenotypic data were collected for yield and component traits. Pattern of molecular differentiation separated indica and japonica genotypes; indica genotypes had two subpopulations within. Landraces were found to have indica genome, but formed a separate subgroup with low linkage disequilibrium. The landraces further separated into distinct group in both hierarchical clustering analysis using neighbour-joining method as well as in the model based population structure analysis. Japonica and the remaining indica cultivars formed two other distinct groups. Linkage disequilibrium observed in the whole population was considerably reduced in subpopulations. Low linkage disequilibrium of landforms suggests their narrow adaptation in local geographical niche. Many population specific alleles could be identified particularly for japonica cultivars and landraces. Association analysis revealed nine marker–trait associations with three agronomic traits, of which 67% were previously reported. Although the testing landraces together with known cultivars had permitted genome-wide association mapping, the experiment offers scope to study more landraces collected from the entire geographical region for drawing more reliable information.


microsatellite markers molecular diversity population structure association mapping landrace rice 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

12041_2012_146_MOESM1_ESM.pdf (506 kb)
(PDF 506 KB)


  1. Abdurakhmonov I. Y. and Abdukarimov A. 2008 Application of association mapping to understanding the genetic diversity of plant germplasm resources. Int. J. Plant Genomics 2008, no. 574927.Google Scholar
  2. Agrama H. A. and Eizenga G. C. 2008 Molecular diversity and genome wide linkage disequilibrium patterns in a worldwide collection of Oryza sativa and its wild relatives. Euphytica 160, 339–355.CrossRefGoogle Scholar
  3. Agrama H. A., Eizenga G. C. and Yan W. 2007 Association mapping of yield and its components in rice cultivars. Mol. Breed. 19, 341–356.CrossRefGoogle Scholar
  4. Anbumalarmathi J., Nadarajan N. and Ganesh S. K. 2008 Studies on root characters for drought resistant in rice (Oryza sativa L.). Indian J. Agri. Res. 42, 71–74.Google Scholar
  5. Bollich C. N., Webb B. D., Marchetti M. A. and Scott J. E. 1985 Registration of ‘Lemont’ rice. Crop Sci. 25, 883–885.CrossRefGoogle Scholar
  6. Botstein D., White R. L., Skolnik M. and Davis R. W. 1980 Construction of genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet. 32, 314–331.PubMedGoogle Scholar
  7. Bradbury P. J., Zhang Z., Kroon D. E., Casstevens R. M., Ramdoss Y. and Buckler E. S. 2007 TASSEL: Software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635.PubMedCrossRefGoogle Scholar
  8. Chang T. T. 1976 The origin, evolution, cultivation, dissemination, and diversification of Asian and African rices. Euphytica 25, 435–441.CrossRefGoogle Scholar
  9. Coburn J. R., Temnykh S. V., Paul E. M. and McCouch S. R. 2002 Design and application of microsatellite marker panels for semiautomated genotyping of rice (Oryza sativa L.). Crop Sci. 42, 2092–2099.CrossRefGoogle Scholar
  10. Dale M. F. B., Ford-Loyd B. V. and Arnold M. H. 1985 Variation in some agronomically important characters in a germplasm collection of beet. Euphytica 34, 449–455.CrossRefGoogle Scholar
  11. Evanno G., Regnaut S. and Goudet J. 2005 Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611–2620.PubMedCrossRefGoogle Scholar
  12. Felsenstein J. 1985 Confidence limits in phylogenies: an approach using bootstrap. Evolution 39, 783–791.CrossRefGoogle Scholar
  13. Fulton T. M., Chunwongse J. and Tanksley S. D. 1995 Microprep protocol for extraction of DNA from tomato and other herbaceous plants. Plant Mol. Biol. Rep. 13, 207–209.CrossRefGoogle Scholar
  14. Gao L. Z., Zhang C. H., Chang L. P., Jia J. Z., Qiu Z. E. and Dong Y. S. 2005 Microsatellite diversity within Oryza sativa with emphasis on indica–japonica divergence. Genet. Res. (Camb.) 85, 1–14.CrossRefGoogle Scholar
  15. Garris A. J., Tai T. H., Coburn J. R., Kresovich S. and McCouch S. 2005 Genetic structure and diversity in Oryza sativa L. Genetics 169, 1631–1638.PubMedCrossRefGoogle Scholar
  16. Gascuel O. 1997 Concerning the NJ algorithm and its unweighted version, UNJ. In Mathematical hierarchies and biology (ed. B. G. Mirkin), pp. 149–170. American Mathematical Society, Providence, USA.Google Scholar
  17. Ge Y., Dudoit S. and Speed T. P. 2003 Resampling-based multiple testing for microarray data analysis. Test 12, 1–44.CrossRefGoogle Scholar
  18. Geetha S., Shanthi P., Jebaraj S. and Mohammed S. E. N. 2006 Gene action of sodicity tolerance in rice. Indian J. Crop Sci. 1, 201–202.Google Scholar
  19. Goldstein H. 1991 Multilevel modelling of survey data. The Statistician 40, 235–244.CrossRefGoogle Scholar
  20. Gomez S. M. and Kalamani A. 2002 Variability analysis of traits related to callus growth and plant regeneration indrought resistant local land races of rice (Oryza sativa L). Asian J. Plant Sci. 1, 583–584.CrossRefGoogle Scholar
  21. Gomez S. M., Rangasamy P. and Nadarajan N. 2003 Assessing the best combiners in rice (Oryza sativa L.) suitable for drought prone areas of Tamil Nadu. Res. Crops 4, 79–84.Google Scholar
  22. Gupta P. K., Rustgi S. and Kulwal P. L. 2005 Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol. Biol. 57, 461–485.PubMedCrossRefGoogle Scholar
  23. Hanamaratti N. G., Prashanthi S. K., Salimath P. M., Hanchinal R. R., Mohankumar H. D., Parameshwarappa K. G. and Raikar S. D. 2008 Traditional land races of rice in Karnataka: Reservoirs of valuable traits. Curr. Sci. 94, 242–247.Google Scholar
  24. Hedrick P. W. 1987 Gametic disequilibrium measures: proceed with caution. Genetics 117, 331–341.PubMedGoogle Scholar
  25. Huang X., Wei X., Sang T., Zhao Q., Feng Q., Zhao Y. et al. 2010 Genome-wide association studies of 14 agronomic traits in rice landraces. Nat. Genet. 42, 961–967.PubMedCrossRefGoogle Scholar
  26. IRRI 1985 Parentage of IRRI crosses IR1-IR50000. Genetic evaluation and utilisation program. International Rice Research Institute, Manila, Philippines.Google Scholar
  27. Ishikawa H., Satoh T., Uwano T., Nitta M., Kiuchi Y. and Sasaki T. 1988 The new rice variety ‘Iwate-21’. Bull. Iwate-ken Agric. Exp. Stn. 27, 25–39.Google Scholar
  28. Ishimaru K. 2003 Identification of a locus increasing rice yield and physiological analysis of its function. Plant Physiol. 133, 1083–1090.PubMedCrossRefGoogle Scholar
  29. Jackson M. T. and Juggan R. 1993 Sharing the diversity of rice to feed the world. Diversity 9, 22–25.Google Scholar
  30. Jain S., Jain R. K. and McCouch S. R. 2004 Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently-labelled microsatellite Markers. Theor. Appl. Genet. 109, 965–977.PubMedCrossRefGoogle Scholar
  31. Jin L., Lu Y., Xiao P., Sun M., Corke H. and Bao J. 2010 Genetic diversity and population structure of a diverse set of rice germplasm for association mapping. Theor. Appl. Genet. 121, 475–487.PubMedCrossRefGoogle Scholar
  32. Kanagaraj P., Prince K. S. J., Sheeba J. A., Biji K. R., Paul S. B., Senthil A. and Babu R. C. 2010 Microsatellite markers linked to drought resistance in rice (Oryza sativa L.). Curr. Sci. 98, 836–839.Google Scholar
  33. Khush G. S. and Virk P. S. 2005 IR varieties and their impact. International Rice Research Institute, Los Baños, Philippines.Google Scholar
  34. Lisa L. A., Elias S. M., Rahman M. S., Shahid S., Iwasaki T., Hasan A. K. M. M. et al. 2011 Physiology and gene expression of the rice landraceunder salt stress. Funct. Plant Biol. 38, 282–292.CrossRefGoogle Scholar
  35. Liu H. L. 1993 Study and progress of crop breeding. Agriculture Press, Beijing, China.Google Scholar
  36. Lu H., Redus M. A., Coburn J. R., Rutger J. N., McCouch S. R. and Tai T. H. 2005 Population structure and breeding patterns of 145 U.S. rice cultivars based on SSR marker analysis. Crop Sci. 45, 66–76.CrossRefGoogle Scholar
  37. Mahalingam L., Mahendran S., Sivakumar T., Hemalatha M., Chitra N., Babu R. C. et al. 2004 Evaluation of rice lines for drought tolerance in target production environment. In Resilient crops for water limited environments: proceedings of a workshop (ed. D. Poland), pp. 108–109. International Maize and Wheat Improvement Center (CiMMYT), Mexico.Google Scholar
  38. Malysheva-Otto L. V., Ganal M. W. and Röder M. S. 2006 Analysis of molecular diversity, population structure and linkage disequilibrium in a worldwide survey of cultivated barley germplasm (Hordeum vulgare L.). BMC Genet. 7, 6.PubMedCrossRefGoogle Scholar
  39. Manoharan M. K., Velayudham K. and Shunmugavalli N. 1993 PRA: An approach to find felt needs of crop varieties. RRA Notes 18, 66–68.Google Scholar
  40. Mather K. A., Caicedo A. L., Polato N. R., Olsen K. M., McCouch S. and Purugganan M. D. 2007 The extent of linkage disequilibrium in rice (Oryza sativa L.). Genetics 177, 2223–2232.PubMedCrossRefGoogle Scholar
  41. McCough S. R. and Doerge R. W. 2005 QTL mapping in rice. Trends Genet. 11, 482–487.CrossRefGoogle Scholar
  42. Morishima H., Sano Y. and Oka H. I. 1992 Evolutionary studies in cultivated rice and its wild relatives. Oxf. Surv. Evol. Biol. 8, 135–184.Google Scholar
  43. Muthuramu S., Jebaraj S. and Gnanasekaran M. 2011 AMMI biplot analysis for drought tolerance in rice (Oryza sativa L.). Res. J. Agric. Sci. 2, 98–100.Google Scholar
  44. Ni J., Colowit P. M. and Mackill D. J. 2002 Evaluation of genetic diversity in rice subspecies using microsatellite markers. Crop Sci. 42, 601–607.CrossRefGoogle Scholar
  45. Oka H. I. 1988 Origin of cultivated rice. Tokyo/Elsevier Science/Japan Scientific Societies Press, Amsterdam, The Netherlands.Google Scholar
  46. Olsen K. M., Caicedo A. L., Polato N., McClung A., McCouch S. and Purugganan D. 2006 Selection under domestication: evidence for a sweep in the rice Waxy genomic region. Genetics 173, 975–983.PubMedCrossRefGoogle Scholar
  47. Perrier X., Flori A. and Bonnot F. 2003 Data analysis methods. In Genetic diversity of cultivated tropical plants (ed. P. Hamon), pp. 43–76. Science Publishers, Montpellier, France.Google Scholar
  48. Pervaiz Z. H., Tehrim S., Rabbani M. A., Masood M. S. and Malik S. A. 2011 Diversity in major seed storage proteins of rice landraces of Pakistan. Pak. J. Bot. 43, 1607–1612.Google Scholar
  49. Podolsky R. H. and Holtsford T. P. 1995 Population structure of morphological traits in Clarkia dudleyana. I. Comparison of F ST between allozymes and morphological traits. Genetics 140, 733–744.PubMedGoogle Scholar
  50. Price A. H., Cairns J. E., Horton P., Jones H. G. and Griffiths H. 2002 Linking drought-resistance mechanisms to drought avoidance in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses. J. Exp. Bot. 53, 989–1004.PubMedCrossRefGoogle Scholar
  51. Pritchard J. K. and Rosenberg N. A. 1999 Use of unlinked genetic markers to detect population stratification in association studies. Am. J. Hum. Genet. 65, 220–228.PubMedCrossRefGoogle Scholar
  52. Pritchard J. K., Stephens M. and Donnelly P. 2000 Inference of population structure using multilocus genotype data. Genetics 155, 945–959.PubMedGoogle Scholar
  53. Pritchard J. K., Wen X. and Falush D. 2010 Documentation for structure software: version 2.3. University of Chicago (
  54. Qian Q., Zeng D., He P., Zheng X., Chen Y. and Zhu L. 2000 QTL analysis of the rice seedling cold tolerance in a double haploid population derived from anther culture of a hybrid between indica and japonica rice. Chin. Sci. Bull. 45, 448–453.CrossRefGoogle Scholar
  55. Rajagoplan R., Robin S., Sivasubramanian P., Mohammad S. E. N., Ali A. J., Kandasamy M. and Sivanandam M. 2004 TRY(R)2: a short duration salt tolerant rice variety. Int. Rice Res. Notes 29, 28.Google Scholar
  56. Ram S. G., Thiruvengadam V. and Vinod K. K. 2007 Genetic diversity among cultivars, landraces and wild relatives of rice as revealed by microsatellite markers. J. Appl. Genet. 48, 337–345. PubMedCrossRefGoogle Scholar
  57. Rezai A. and Frey K. J. 1990 Multivariate analysis of variation among wild oat accessions-seed traits. Euphytica 49, 111–119.CrossRefGoogle Scholar
  58. Rohlf F. J. and Sokal R. R. 1981 Comparing numerical taxonomic studies. Syst. Zool. 30, 459–490.CrossRefGoogle Scholar
  59. Rostocks N., Ramsay L., MacKenzie K., Cardle L., Bhat P. R., Roose M. L. et al. 2006 Recent history of artificialoutcrossing facilitates whole genome association mapping in elite crop varieties. Proc. Natl. Acad. Sci. USA 103, 18656–18661.CrossRefGoogle Scholar
  60. Sasaki T. and Burr B. 2000 International rice genome sequencing project: the effort to completely sequence the rice genome. Curr. Opin. Plant Biol. 3, 138–141.PubMedCrossRefGoogle Scholar
  61. Searle S. R. 1987 Linear models for unbalanced data. John Wiley, New York, USA.Google Scholar
  62. Shanmugasundaram P., Mohanasundram K., Rangaswamy M., Ganesan K., Wilfred Manuel W., Sundaram T. et al. 1997 ASD20(AS89044): A short duration high yielding rice variety for Tamil Nadu. Madras Agric. J. 84, 274–276.Google Scholar
  63. Sokal R. R. and Michener C. D. 1958 A statistical method for evaluating systematic relationships. Univ. Kansas Sci. Bull. 38, 1409–1438.Google Scholar
  64. Subashri M., Robin S., Vinod K. K., Rajeswari S., Mohanasundaram K. and Raveendran T. S. 2009 Trait identification and QTL validation for reproductive stage drought resistance in rice using selective genotyping of near flowering RILs. Euphytica 166, 291–305.CrossRefGoogle Scholar
  65. Swamy B. P. M., Kaladhar K., Ramesha M. S., Viraktamath B. C. and Sarla N. 2011 Molecular mapping of QTLs for yield and related traits in Oryza sativa cv Swarna x O. nivara (IRGC81848) backcross population. Rice Sci. 18, 178–186.CrossRefGoogle Scholar
  66. Temnykh S., Park W. D., Ayres N., Cartinhour S., Hauck N., Lipovich L. et al. 2000 Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor. Appl. Genet. 100, 697–712.CrossRefGoogle Scholar
  67. Tenaillon M. I., Sawkins M. C., Long A. D., Gaut R. L., Doebley J. F. and Gaut B. S. 2001 Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Proc. Natl. Acad. Sci. USA 98, 9161–9166.PubMedCrossRefGoogle Scholar
  68. Thiyagarajan T. M. and Selvaraju R. 2001 Water-saving rice cultivation in India. In Water-saving rice production systems (ed. H. Hengsdijk and P. Bindraban.), pp. 15–46. Plant Research International B.V., Wageningen, The Netherlands.Google Scholar
  69. Thomson M. J., Tai T. H., McClung A. M., Lai X.-H., Hinga M. E., Lobos K. B. et al. 2003 Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theor. Appl. Genet. 107, 479–493.PubMedCrossRefGoogle Scholar
  70. Thomson M. J., Septiningsih E. M., Suwardjo F., Santoso T. J., Silitonga T. S. and McCouch S. R. 2007 Genetic diversity analysis of traditional and improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers. Theor. Appl. Genet. 114, 559–568.PubMedCrossRefGoogle Scholar
  71. Tsai K. H. and Oka H. I. 1965 Genetic studies of yielding capacity and adaptability in crop plants. 1. Characters of isogenic lines in rice. Bot. Bull. Acad. Sinica 6, 19–31.Google Scholar
  72. Vikas V. K., Satheesh V., Subramanian M., Kalarani M. and Singh V. P. 2009 Evaluation of rice hybrids and their parents for drought tolerance. Ind. J. Plant Physiol. 14, 156–161.Google Scholar
  73. Zhao X., Qin Y. and Sohn J.-K. 2010 Identification of main effects, epistatic effects and their environmental interactions of QTLs for yield traits in rice. Genes & Genomics 32, 37–45.CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2012

Authors and Affiliations

  1. 1.Plant Research InternationalWageningen University and Research CentreWageningenThe Netherlands
  2. 2.Indian Agricultural Research Institute, Rice Breeding and Genetics Research CentreAduthuraiIndia
  3. 3.Departments of Crop, Soil and Environmental Sciences and Plant PathologyUniversity of ArkansasFayettevilleUSA

Personalised recommendations