Skip to main content
Log in

Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.)

  • Original Article
  • Published:
Planta Aims and scope Submit manuscript

Abstract

Key message

Twenty-seven QTLs were identified for rice seed vigor, in which 16 were novel QTLs. Fifteen elite parental combinations were designed for improving seed vigor in rice.

Abstract

Seed vigor is closely related to direct seeding in rice (Oryza sativa L.). Previous quantitative trait locus (QTL) studies for seed vigor were mainly derived from bi-parental segregating populations and no report from natural populations. In this study, association mapping for seed vigor was performed on a selected sample of 540 rice cultivars (419 from China and 121 from Vietnam). Population structure was estimated on the basis of 262 simple sequence repeat (SSR) markers. Seed vigor was evaluated by root length (RL), shoot length (SL) and shoot dry weight in 2011 and 2012. Abundant phenotypic and genetic diversities were found in the studied population. The population was divided into seven subpopulations, and the levels of linkage disequilibrium (LD) ranged from 10 to 80 cM. We identified 27 marker–trait associations involving 18 SSR markers for three traits. According to phenotypic effects for alleles of the detected QTLs, elite alleles were mined. These elite alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the elite alleles per QTL (apart from possible epistatic effects). Our results demonstrate that association mapping can complement and enhance previous QTL information for marker-assisted selection and breeding by design.

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
Fig. 4

Similar content being viewed by others

Abbreviations

ANOVA:

Analysis of variance

FDR:

False discovery rate

GLM:

General linear model

H 2B :

Heritability in the broad sense

F IS :

F-statistics; individuals within subpopulations

F ST :

F-statistics; subpopulations within the total population

LD:

Linkage disequilibrium

MCMC:

Markov Chain Monte Carlo

PIC:

Polymorphic information content

PVE:

Proportion of phenotypic variance explained

QTL:

Quantitative trait locus

RL:

Root length

SDW:

Shoot dry weight

SL:

Shoot length

SSR:

Simple sequence repeat

References

  • 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, Eizenga GC, Yan W (2007) Association mapping of yield and its components in rice cultivars. Mol Breed 19:341–356

    Article  Google Scholar 

  • Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 57:289–300

    Google Scholar 

  • Borba TCO, Brondanil RPV, Breseghello F, Coelho ASG, Mendonça JA, Range PHN, Brondani C (2010) Association mapping for yield and grain quality traits in rice (Oryza sativa L.). Gen Mol Biol 33:515–524

    Article  Google Scholar 

  • Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 2:2633–2635

    Article  Google Scholar 

  • Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177

    Article  PubMed Central  PubMed  Google Scholar 

  • Cardon L, Bell J (2001) Association study designs for complex diseases. Nat Rev Genet 2:91–99

    Article  CAS  PubMed  Google Scholar 

  • Cui KH, Peng SB, Xing YZ, Xu CG, Yu SB, Zhang Q (2002) Molecular dissection of seedling-vigor and associated physiological traits in rice. Theor Appl Genet 105:745–753

    Article  CAS  PubMed  Google Scholar 

  • Cui D, Xu CY, Tang CF, Yang CG, Yu TQ, A XX, Cao GL, Xu FR, Zhang JG, Han LZ (2013) Genetic structure and association mapping of cold tolerance in improved japonica rice germplasm at the booting stage. Euphytica 193:369–382

    Article  CAS  Google Scholar 

  • Dingkuhn M, Johnson DE, Sow A, Audebert AY (1999) Relationship between upland rice canopy characteristics and weed competitiveness. Field Crop Res 61:71–95

    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 

  • Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50

    CAS  PubMed Central  Google Scholar 

  • Farnir F, Coppieters W, Arranz JJ, Berzi P, Cambisano N, Grisart B, Karim L, Marcq F, Moreau L, Mni M, Nezer C, Simon P, Vanmanshoven P, Wagenaar D, Georges M (2000) Extensive genome-wide linkage disequilibrium in cattle. Genome Res 10:220–227

    Article  CAS  PubMed  Google Scholar 

  • Flint-Garcia S, Thornsberry J, Buckler ES (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374

    Article  CAS  PubMed  Google Scholar 

  • Gupta P, Rustgi S, Kulwal P (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485

    Article  CAS  PubMed  Google Scholar 

  • Hardy O, Vekemans X (2002) SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620

    Article  Google Scholar 

  • Huang Z, Yu T, Su L, Yu SB, Zhang ZH, Zhu YG (2004) Identification of chromosome regions associated with seedling vigor in rice. Acta Genetica Sinica 31:596–603

    CAS  PubMed  Google Scholar 

  • Huang XH, Wei XH, Sang T (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42:961–969

    Article  CAS  PubMed  Google Scholar 

  • Ishimaru K, Yano M, Aoki N, Ono K, Hirose T, Lin SY, Monna L, Sasaki T, Ohsugi R (2001) Toward the mapping of physiological and agronomic characters on a rice function map: QTL analysis and comparison between QTLs and expressed sequence tags. Theor Appl Genet 102:793–800

    Article  CAS  Google Scholar 

  • Jia LM, Yan WG, Zhu CS, Agrama HA, Jackson A, Yeater K, Li XB, Huang BH, Hu BL, McClung A, Wu DX (2012) Allelic analysis of sheath blight resistance with association mapping in rice. PLoS One 7:e32703

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Jin L, Lu Y, Xiao P, Sun M, Corke H, Bao JS (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 

  • Kassem MA, Shultz J, Meksem K, Cho Y, Wood AJ, Iqbal MJ, Lightfoot DA (2006) An updated ‘Essex’ by ‘Forrest’ linkage map and Wrst composite interval map of QTL underlying six soybean traits. Theor Appl Genet 113:1015–1026

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  • Lü HY, Liu XF, Wei SP, Zhang YM (2011) Epistatic association mapping in homozygous crop cultivars. PLoS One 6:e17773

    Article  PubMed Central  PubMed  Google Scholar 

  • Marri PR, Sarla N, Reddy LV, Siddiq EA (2005) Identification and mapping of yield and yield related QTLs from an Indian accession of Oryza rufipogon. BMC Genet 6:1–14

    Article  Google Scholar 

  • Mather K, Caicedo A, Polato N, Olsen K, McCouch S, Purugganan MD (2007) The extent of linkage disequilibrium in rice (Oryza sativa L.). Genetics 177:2223–2232

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • McCouch SR, Teytelman L, Xu YB, Lobos KB, Clare K, Walton M, Fu BY, Maghirang R, Li ZK, Xing YZ, Zhang QF, Kono I, Yano M, Jellstorm RF, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L (2002) Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res 9:199–207

    Article  CAS  PubMed  Google Scholar 

  • Mei HW, Li ZK, Shu QY, Guo LB, Wang YP, Yu XQ, Ying CS, Luo LJ (2005) Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two backcross populations. Theor Appl Genet 110:649–659

    Article  CAS  PubMed  Google Scholar 

  • Moncada P, Martinez CP, Borrero J, Chatel M, Gauch H, Guimaraes E, Tohme J, McCouch SR (2001) Quantitative trait loci for yield and yield components in an Oryza sativa × Oryza rufipogon BC2F2 population evaluated in an upland environment. Theor Appl Genet 102:41–42

    Article  CAS  Google Scholar 

  • Murray MG, Thompson WF (1980) Rapid isolation of high-molecular-weight-plant DNA. Nucleic Acids Res 8:4321–4325

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Olsen KM, Caicedo AL, Polato N, McClung A, McCouch S, Purugganan MD (2006) Selection under domestication: evidence for a sweep in the rice waxy genomic region. Genetics 173:975–983

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Ordonez SA Jr, Silva J, Oard JH (2010) Association mapping of grain quality and flowering time in elite japonica rice germplasm. J Cereal Sci 51:337–343

    Article  Google Scholar 

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

    CAS  PubMed Central  PubMed  Google Scholar 

  • Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000b) Association mapping in structured populations. Am J Hum Genet 67:170–181

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Rakshit S, Rakshit A, Matsumura H, Takahashi Y, Hasegawa Y, Ito A, Ishii T, Miyashita NT, Terauchi R (2007) Large-scale DNA polymorphism study of Oryza sativa and O. rufipogon reveals the origin and divergence of Asian rice. Theor Appl Genet 114:731–743

    Article  CAS  PubMed  Google Scholar 

  • Rao AN, Johnson DE, Sivaprasad B, Ladha JK, Mortimer AM (2007) Weed management in direct-seeded rice. Adv Agron 93:153–255

    Article  CAS  Google Scholar 

  • Redoňa ED, Mackill DJ (1996a) Genetic variation for seedling vigor traits in rice. Crop Sci 36:285–290

    Article  Google Scholar 

  • Redoňa ED, Mackill DJ (1996b) Mapping quantitative trait loci for seedling-vigor in rice using RFLPs. Theor Appl Genet 92:395–402

    Article  PubMed  Google Scholar 

  • Regan KL, Siddique KHM, Turner NC, Whan BR (1992) Potential for increasing early vigor and total biomass in spring wheat. II. Characteristics associated with early vigor. Aust J Agric Res 43:541–553

    Article  Google Scholar 

  • Sasaki T, Burr B (2000) International rice genome sequencing project: the effort to completely sequence the rice genome. Curr Opin Plant Biol 3:138–141

    Article  CAS  PubMed  Google Scholar 

  • Segura V, Vilhjálmsson BJ, Platt A, Korte A, Seren Ü, Long Q, Nordborg M (2012) An efficient multi-locus mixed model approach for genome-wide association studies in structured populations. Nat Genet 44:825–830

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Temnykh S, Park WD, Ayres N, Cartinhour S, Hauck N, Lipovich L, Cho YG, Ishii T, McCouch SR (2000) Mapping and genome organization of microsatellite sequence in rice (Oryza sativa L.). Theor Appl Genet 100:697–712

    Article  CAS  Google Scholar 

  • Vanniarajan C, Vinod KK, Pereira A (2012) Molecular evaluation of genetic diversity and association studies in rice (Oryza sativa L.). J Genet 91:1–11

    Article  Google Scholar 

  • Wang J, McClean P, Lee R, Goos R, Helms T (2008) Association mapping of iron deficiency chlorosis loci soybean (Glycine max L. Merr.) advanced breeding lines. Theor Appl Genet 116:777–787

    Article  CAS  PubMed  Google Scholar 

  • Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370

    Article  Google Scholar 

  • Weir BS, Hill WG (2002) Estimating F-statistics. Annu Rev Genet 36:721–750

    Article  CAS  PubMed  Google Scholar 

  • Wen WW, Mei HW, Feng FJ, Yu SB, Huang ZC, Wu JH, Chen L, Xu XY, Luo LJ (2009) Population structure and association mapping on chromosome 7 using a diverse panel of Chinese germplasm of rice (Oryza sativa L.). Theor Appl Genet 119:459–470

    Article  PubMed  Google Scholar 

  • Xiao JH, Li JM, Yuan LP, Tanksley SR (1996) Identification of QTLs affecting traits of agronomic importance in a recombinant inbred population derived from a subspecific rice cross. Theor Appl Genet 92:230–244

    Article  CAS  PubMed  Google Scholar 

  • Xu Y, Crouch J (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407

    Article  Google Scholar 

  • Yamauchi M, Winn T (1996) Rice seed vigor and seedling establishment in anaerobic soil. Crop Sci 36:680–686

    Article  Google Scholar 

  • Yan JQ, Zhu J, He CX, Benmoussa M, Wu P (1998) Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.). Genetics 150:1257–1265

    CAS  PubMed Central  PubMed  Google Scholar 

  • Yan WG, Li Y, Agrama HA, Luo DG, Gao FY, Lu XJ, Ren GJ (2009) Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.). Mol Breed 24:277–292

    Article  PubMed Central  PubMed  Google Scholar 

  • Yu JM, Buckler ES (2006) Genetic association mapping and genome organization of maize. Biotechnology 17:155–160

    CAS  Google Scholar 

  • Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2005) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    Article  PubMed  Google Scholar 

  • Zhang ZH, Qu XS, Wan S, Chen LH, Zhu YG (2005a) Comparison of QTL controlling seedling vigour under different temperature conditions using recombinant inbred lines in rice (Oryza sativa). Ann Bot 95:423–429

    Article  CAS  PubMed  Google Scholar 

  • Zhang ZH, Yu SB, Yu T, Huang Z, Zhu YG (2005b) Mapping quantitative trait loci (QTLs) for seedling-vigor using recombinant inbred lines of rice (Oryza sativa L.). Field Crop Res 91:161–170

    Article  Google Scholar 

  • Zhang YM, Mao YC, Xie CQ, Smith H, Luo L, Xu SZ (2005c) Mapping QTL using naturally occurring genetic variance among commercial inbred lines of maize (Zea mays L.). Genetics 169:2267–2275

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Zhang N, Xu Y, Akash M, McCouch S, Oard JH (2005d) Identification of candidate markers associated with agronomic traits in rice using discriminant analysis. Theor Appl Genet 110:721–729

    Article  CAS  PubMed  Google Scholar 

  • Zhang ZW, Ersoz E, Lai CQ, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu JM, Arnett DK, Ordovas JM, Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Zhou X, Stephens M (2012) Genome-wide efficient mixed model analysis for association studies. Nat Genet 44:821–824

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Zhou L, Wang JK, Yi Q, Wang YZ, Zhu YG, Zhang ZH (2007) Quantitative trait loci for seedling vigor in rice under field conditions. Field Crop Res 100:294–301

    Article  Google Scholar 

  • Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors are grateful to Dr. Linglong Liu (National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University) for critical review of the manuscript. Funding support was provided by a grant from the China national “863” program (2010AA101301), a grant from key program of Scientific Base Platform of Chinese Government (505005) and a grant from doctoral found of Educational Ministry (B0201100690).

Conflict of interest

No conflict of interest among authors and in the research work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Delin Hong.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dang, X., Thi, T.G.T., Dong, G. et al. Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.). Planta 239, 1309–1319 (2014). https://doi.org/10.1007/s00425-014-2060-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00425-014-2060-z

Keywords

Navigation