Skip to main content
SpringerLink
Log in

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

  • Research Article
  • Published:
Journal of Genetics Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • 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.

  • 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.

    Article  CAS  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • Bollich C. N., Webb B. D., Marchetti M. A. and Scott J. E. 1985 Registration of ‘Lemont’ rice. Crop Sci. 25, 883–885.

    Article  Google Scholar 

  • 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.

    PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Chang T. T. 1976 The origin, evolution, cultivation, dissemination, and diversification of Asian and African rices. Euphytica 25, 435–441.

    Article  Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Felsenstein J. 1985 Confidence limits in phylogenies: an approach using bootstrap. Evolution 39, 783–791.

    Article  Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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 

  • Ge Y., Dudoit S. and Speed T. P. 2003 Resampling-based multiple testing for microarray data analysis. Test 12, 1–44.

    Article  Google Scholar 

  • 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 

  • Goldstein H. 1991 Multilevel modelling of survey data. The Statistician 40, 235–244.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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 

  • Hedrick P. W. 1987 Gametic disequilibrium measures: proceed with caution. Genetics 117, 331–341.

    PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • IRRI 1985 Parentage of IRRI crosses IR1-IR50000. Genetic evaluation and utilisation program. International Rice Research Institute, Manila, Philippines.

    Google Scholar 

  • 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 

  • Ishimaru K. 2003 Identification of a locus increasing rice yield and physiological analysis of its function. Plant Physiol. 133, 1083–1090.

    Article  PubMed  CAS  Google Scholar 

  • Jackson M. T. and Juggan R. 1993 Sharing the diversity of rice to feed the world. Diversity 9, 22–25.

    Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • 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.

    CAS  Google Scholar 

  • Khush G. S. and Virk P. S. 2005 IR varieties and their impact. International Rice Research Institute, Los Baños, Philippines.

    Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • Liu H. L. 1993 Study and progress of crop breeding. Agriculture Press, Beijing, China.

    Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • 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 

  • 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.

    Article  PubMed  Google Scholar 

  • 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 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • McCough S. R. and Doerge R. W. 2005 QTL mapping in rice. Trends Genet. 11, 482–487.

    Article  Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  CAS  Google Scholar 

  • Oka H. I. 1988 Origin of cultivated rice. Tokyo/Elsevier Science/Japan Scientific Societies Press, Amsterdam, The Netherlands.

    Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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 

  • 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 

  • 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.

    PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Pritchard J. K., Stephens M. and Donnelly P. 2000 Inference of population structure using multilocus genotype data. Genetics 155, 945–959.

    PubMed  CAS  Google Scholar 

  • Pritchard J. K., Wen X. and Falush D. 2010 Documentation for structure software: version 2.3. University of Chicago (http://pitch.bsd.uchicago.edu/sructure.html.).

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  PubMed  Google Scholar 

  • Rezai A. and Frey K. J. 1990 Multivariate analysis of variation among wild oat accessions-seed traits. Euphytica 49, 111–119.

    Article  Google Scholar 

  • Rohlf F. J. and Sokal R. R. 1981 Comparing numerical taxonomic studies. Syst. Zool. 30, 459–490.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • Searle S. R. 1987 Linear models for unbalanced data. John Wiley, New York, USA.

    Google Scholar 

  • 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 

  • Sokal R. R. and Michener C. D. 1958 A statistical method for evaluating systematic relationships. Univ. Kansas Sci. Bull. 38, 1409–1438.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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.

    Article  PubMed  CAS  Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  CAS  Google Scholar 

Download references

Author information

Author notes

  1. C. VANNIARAJAN

    Present address: Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, 625 104, India

Authors and Affiliations

  1. Plant Research International, Wageningen University and Research Centre, 6700 AA, Wageningen, The Netherlands

    C. VANNIARAJAN & ANDY PEREIRA

  2. Indian Agricultural Research Institute, Rice Breeding and Genetics Research Centre, Aduthurai, 612 101, India

    K. K. VINOD

  3. Departments of Crop, Soil and Environmental Sciences and Plant Pathology, University of Arkansas, Fayetteville, AR 72701, USA

    ANDY PEREIRA

Authors
  1. C. VANNIARAJAN
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. K. VINOD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. ANDY PEREIRA
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. K. VINOD.

Additional information

Vanniarajan C., Vinod K. K. and Pereira A. 2012 Molecular evaluation of genetic diversity and association studies in rice (Oryza sativa L.). J. Genet. 91, xx–xx

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

(PDF 506 KB)

Rights and permissions

Reprints and permissions

About this article

Cite this article

VANNIARAJAN, C., VINOD, K.K. & PEREIRA, A. Molecular evaluation of genetic diversity and association studies in rice (Oryza sativa L.). J Genet 91, 9–19 (2012). https://doi.org/10.1007/s12041-012-0146-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12041-012-0146-6

Keywords

Search

Navigation