Skip to main content
Log in

Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection

  • Published:
Genetica Aims and scope Submit manuscript

Abstract

A rice mini-core collection consisting of 217 accessions has been developed to represent the USDA core and whole collections that include 1,794 and 18,709 accessions, respectively. To improve the efficiency of mining valuable genes and broadening the genetic diversity in breeding, genetic structure and diversity were analyzed using both genotypic (128 molecular markers) and phenotypic (14 numerical traits) data. This mini-core had 13.5 alleles per locus, which is the most among the reported germplasm collections of rice. Similarly, polymorphic information content (PIC) value was 0.71 in the mini-core which is the highest with one exception. The high genetic diversity in the mini-core suggests there is a good possibility of mining genes of interest and selecting parents which will improve food production and quality. A model-based clustering analysis resulted in lowland rice including three groups, aus (39 accessions), indica (71) and their admixtures (5), upland rice including temperate japonica (32), tropical japonica (40), aromatic (6) and their admixtures (12) and wild rice (12) including glaberrima and four other species of Oryza. Group differentiation was analyzed using both genotypic distance Fst from 128 molecular markers and phenotypic (Mahalanobis) distance D2 from 14 traits. Both dendrograms built by Fst and D2 reached similar-differentiative relationship among these genetic groups, and the correlation coefficient showed high value 0.85 between Fst matrix and D2 matrix. The information of genetic and phenotypic differentiation could be helpful for the association mapping of genes of interest. Analysis of genotypic and phenotypic diversity based on genetic structure would facilitate parent selection for broadening genetic base of modern rice cultivars via breeding effort.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abadie T, Cordeiro CMT, Fonseca JR, Alves RBN, Burle ML, Brondani C, Rangel PHN, Castro EM, Silva HT, Freire MS, Zimmermann FJP, Magalhaes JRSO (2005) Constructing a rice core collection for Brazil. Pesquisa Agropecu Bras 40:129–136

    Google Scholar 

  • Agrama HA, Eizenga GC (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 HA, Yan WG (2009) Genetic diversity and relatedness of rice cultivars resistant to straighthead disorder. Plant Breed. doi:10.1111/j.1439-0523.2009.01688.x

    Google Scholar 

  • Agrama HA, Yan WG, Lee F, Fjellstrom R, Chen MH, Jia M, McClung A (2009) Genetic assessment of a mini–core subset developed from the USDA rice Genebank. Crop Sci 49:1336–1346

    Article  Google Scholar 

  • Borba TCO, Brondani RPV, Rangel PHN, Brondani C (2005) Evaluation of the number and information content of fluorescent–labeled SSR for rice germplasm characterization. Crop Breed Appl Biotechnol 2:157–165

    Google Scholar 

  • Borba TCO, Brondani RPV, Rangel PHN, Brondani C (2009) Microsatellite marker–mediated analysis of the EMBRAPA rice core collection genetic diversity. Genetica 137:293–304

    Article  CAS  Google Scholar 

  • Brondani C, Borba TCO, Rangel PHN, Brondani RPV (2006) Determination of traditional varieties of Brazilian rice using microsatellite markers. Genet Mol Biol 29:676–684

    Article  CAS  Google Scholar 

  • Brown AHD (1989) Core collections: a practical approach to genetic resources management. Genome 31:818–824

    Google Scholar 

  • Cheng CY, Motohashi R, Tsuchimoto S, Fukuta Y, Ohstubo H, Ohtsubo E (2003) Polyphyletic origin of cultivated rice: based on the interspersion pattern of SINEs. Mol Biol Evol 20:67–75

    Article  CAS  PubMed  Google Scholar 

  • Cho YG, Ishii T, Temnykh S, Chen X, Lipovich L, McCouch SR, Park WD, Ayres N, Cartinhour S (2000) Diversity of microsatellites derived from genomic libraries and genbank sequences in rice (Oryza sativa L.). Theor Appl Genet 100:713–722

    Article  CAS  Google Scholar 

  • Chu Y, Ramos L, Holbrook CC, Ozias-Akins P (2007) Frequency of a loss-of-function mutation in oleoyl-PC desaturase (ahFAD2A) in the mini-core of the US peanut germplasm collection. Crop Sci 47:2372–2378

    Article  CAS  Google Scholar 

  • Elias M, Penet L, Vindry P, McKey D, Panaud O, Robert T (2001a) Unmanaged sexual reporoduction and the dynamics of genetic diversity of a vegetatively propagated crop plant, cassava (Manihot esculenta Crantz), in a traditional farming system. Mol Eco 10:1895–1907

    Article  CAS  Google Scholar 

  • Elias M, McKey D, Panaud O, Anstett MC, Robert T (2001b) Traditional management of cassava morphological and genetic diversity by the Makushi Amerindians (Guyana, South America): perspectives for on-farm conservation of crop genetic resources. Euphytica 120:143–157

    Article  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620

    Article  CAS  PubMed  Google Scholar 

  • Garris AJ, Tai TH, Coburn J, Kresovich S, McCouch SR (2005) Genetic structure and diversity in Oryza sativa L. Genetics 169:1631–1638

    Article  CAS  PubMed  Google Scholar 

  • Gaudeul M, Taberlet P, Till-Bottraud I (2000) Genetic diversity in an endangered alpine plant, Eryngium alpinum L. (Apiaceae), inferred from amplified fragment length polymorphism markers. Molecular Ecol 9:1625–1637

    Article  CAS  Google Scholar 

  • Gizaw S, Van Arendonk JAM, Komen H, Windig JJ, Hanotte O (2007) Population structure, genetic variation and morphological diversity in indigenous sheep of Ethiopia. Anim Genet 38:621–628

    Article  CAS  PubMed  Google Scholar 

  • Glaszmann JC (1987) Isozymes and classification of Asian rice varieties. Theor Appl Genet 74:21–30

    Article  CAS  Google Scholar 

  • Hamilton RS, Raymond R (2005) Toward a global strategy for the conservation of rice genetic resources. In: Toriyama K, Heong KL, Hardy B (eds) Rice is life: scientific perspectives for the 21st century. Proceedings of the world rice research conference held in Tsukuba, Japan, CD–ROM, pp 47–49

  • Holbrook CC, Dong W (2005) Development and evaluation of a mini core collection for the US peanut germplasm collection. Crop Sci 45:1540–1544

    Article  Google Scholar 

  • Hossain M (2007) Rice facts: a balancing act. Rice Today 6:37

    Google Scholar 

  • Jain S, Jain RK, McCouch SR (2004) Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently–labeled microsatellite markers. Theor Appl Genet 109:965–977

    Article  CAS  PubMed  Google Scholar 

  • Kouame CN, Quesenberry KH (1993) Cluster analysis of a world collection of red clover germplasm. Genet Res Crop Evo 40:39–47

    Article  Google Scholar 

  • Lewis PO, Zaykin D (2001) Genetic data analysis: computer program for the analysis of allelic data version 1.0. http://lewis.eeb.uconn.edu/lewishome/software.html. Cited 21 Nov 2001

  • Liang F, Deng Q, Wang Y, Xiong Y, Jin D, Li J, Wang B (2004) Molecular marker–assisted selection for yield–enhancing genes in the progeny of “9311 × O. rufipogon” using SSR. Euphytica 139:159–165

    Article  CAS  Google Scholar 

  • Liu K, Muse SV (2005) Powermarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129

    Article  CAS  PubMed  Google Scholar 

  • Mackill DJ (1995) Plant genetic resources: classifying japonica rice cultivars with RAPD markers. Crop Sci 35:889–894

    Article  CAS  Google Scholar 

  • Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27:209–220

    CAS  PubMed  Google Scholar 

  • Merilaè J, Crnokrak P (2001) Comparison of genetic differentiation at marker loci and quantitative traits. J Evol Biol 14:892–903

    Article  Google Scholar 

  • Nei M, Takezaki N (1983) Estimation of genetic distances and phylogenetic trees from DNA anlysis. Proc. 5th World Cong. Genet Appl Livstock Prod 21:405–412

    Google Scholar 

  • Pande S, Kishore GK, Upadhyaya HD, Rao JN (2006) Identification of sources of multiple disease resistance in mini-core collection of chickpea. Plant Dis 90:1214–1218

    Article  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    CAS  PubMed  Google Scholar 

  • Rohlf F (2000) NTSYSPC numerical taxonomy and multivariate analysis system ver 2.11L. Applied Biostatistics, NY

    Google Scholar 

  • Schneider S, Excoffier L (1999) Estimation of demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA. Genetics 152:1079–1089

    CAS  PubMed  Google Scholar 

  • Sharma R, Rao VP, Upadhyaya HD, Reddy VG, Thakur RP (2010) Resistance to grain mold and downy mildew in a mini-core collection of sorghum germplasm. Plant Dis 94:439–444

    Article  Google Scholar 

  • Sweeney MT, Thomson MJ, Pfeil BE, McCouch S (2006) Caught red-handed: Rc encodes a basic helix–loop–helix protein conditioning red pericarp in rice. Plant Cell 18:283–294

    Article  CAS  PubMed  Google Scholar 

  • Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24:1596–1599

    Article  CAS  PubMed  Google Scholar 

  • Tanksley S, McCouch SR (1997) Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277:1063–1066

    Article  CAS  PubMed  Google Scholar 

  • Thomson MJ, Septiningsih EM, Suwardjo F, Santoso TJ, Silitonga TS, McCouch SR (2007) Genetic diversity analysis of traditional and improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers. Theor Appl Genet 114:559–568

    Article  CAS  PubMed  Google Scholar 

  • Thomson MJ, Polato NR, Prasetiyono J, Trijatmiko KR, Silitonga TS, McCouch SR (2009) Genetic diversity of isolated populations of Indonesian landraces of rice (Oryza sativa L.) collected in east Kalimantan on the island of Borneo. Rice 2:80–92

    Article  Google Scholar 

  • Upadhyaya HD (2005) Variability for drought resistance related traits in the mini core collection of peanut. Crop Sci 45:1432–1440

    Article  Google Scholar 

  • Upadhyaya HD, Oritz R (2001) A mini-core collection for capturing diversity and promoting utilization of chickpea genetic resources in crop improvement. Theor Appl Genet 102:1292–1298

    Article  Google Scholar 

  • Upadhyaya HD, Reddy LJ, Gowda CLL, Reddy KN, Singh S (2006) Development of a mini core for enhanced and diversified utilization of pigeonpea germplasm resources. Crop Sci 46:2127–2132

    Article  Google Scholar 

  • Upadhyaya HD, Pundir RPS, Dwivedi SL, Gowda CLL, Reddy VG, Singh S (2009) Developing a mini core collection of sorghum for diversified utilization of germplasm. Crop Sci 49:1769–1780

    Article  Google Scholar 

  • Weir BS (1996) Genetic data analysis II: methods for discrete population genetic data. Sinauer assoc., Inc. Sunderland, MA

    Google Scholar 

  • Xin Z, Velten JP, Oliver MJ, Burke JJ (2003) Highthroughput DNA extraction method suitable for PCR. Biotechniques 34:820–826

    CAS  PubMed  Google Scholar 

  • Xu YB, Beachell H, McCouch SR (2004) A marker–based approach to broadening the genetic base of rice in the USA. Crop Sci 44:1947–1959

    Article  Google Scholar 

  • Yan W, Rutger JN, Bockelman HE, Tai TH. (2005a) Agronomic evaluation and seed stock establishment of the USDA rice core collection. In: RJ Norman et al. (ed.) BR wells rice research studies 2004. University of Arkansas, Agri Exp Sta Res Ser 529:63–68

  • Yan W, Rutger JN, Bockelman HE, Tai TH. (2005b). Evaluation of kernel characteristics of the USDA rice core collection. In: RJ Norman et al. (ed.) BR wells rice research studies 2004. University of Arkansas, Agri Exp Sta, Res Ser 529:69–74

  • Yan WG, Rutger JN, Bryant RJ, Bockelman HE, Fjellstrom RG, Chen MH, Tai TH, McClung AM (2007) Development and evaluation of a core subset of the USDA rice (Oryza sativa L.) germplasm collection. Crop Sci 47:869–878

    Article  Google Scholar 

  • Yan WG, Li Y, Agrama HA, Luo D, Gao F, Lu X, Ren G (2009) Association mapping of stigma and spikelet characteristics. Mol Breeding 24:277–292

    Article  Google Scholar 

  • Zeng Y, Shen S, Li Z, Yang Z, Wang X, Zhang H, Wen G (2003) Ecogeographic and genetic diversity based on morphological characters on indigenous rice (Oryza sativa L.) in Yunnan, China. Genet Res Crop Evo 50:567–577

    Article  Google Scholar 

  • Zhu C, Yu J (2009) Nonmetric multidimensional scaling corrects for population structure in whole genome association studies. Genetics 182:875–888

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors thank Ellen McWhirter for critical review, Tiffany Sookaserm, Tony Beaty, Yao Zhou, LaDuska Simpson, Curtis Kerns and Sarah Hendrix for technical assistance.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Wengui Yan or Dianxing Wu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, X., Yan, W., Agrama, H. et al. Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection. Genetica 138, 1221–1230 (2010). https://doi.org/10.1007/s10709-010-9521-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10709-010-9521-5

Keywords

Navigation