Skip to main content
Log in

Genome wide association mapping of agro-morphological and disease resistance traits in sugarcane

  • Published:
Euphytica Aims and scope Submit manuscript

Abstract

The objectives of the study were to assess genome wide association study (GWAS) for sugarcane on a panel of 183 accessions and to evaluate the impact of population structure and family relatedness on QTL detection. The panel was genotyped with 3327 AFLP, DArT and SSR markers and phenotyped for 13 traits related to agro-morphology, sugar yield, bagasse content and disease resistances. Marker-trait associations were detected using (i) general linear models that took population structure into account with either a Q matrix from STRUCTURE software or principal components from a principal component analysis added as covariates, and (ii) mixed linear models that took into account both population structure and family relatedness estimated using a similarity matrix K* computed using Jaccard’s coefficient. With general linear models analysis, test statistics were inflated in most cases, while mixed linear models analysis allowed the inflation of test statistics to be controlled in most cases. When only detections in which both population structure and family relatedness were correctly controlled were considered, only 11 markers were significantly associated with three out of the 13. Among these 11 markers, six were linked to the major resistance gene Bru1, which has already been identified. Our results confirm that the use of GWAS is feasible for sugarcane in spite of its complex polyploid genome but also underline the need to take into account family relatedness and not only population structure. The small number of significant associations detected suggests that a larger population and/or denser genotyping are required to increase the statistical power of association detection.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Aitken K, Hermann S, Karno K, Bonnett G, McIntyre L, Jackson P (2008) Genetic control of yield related stalk traits in sugarcane. Theor Appl Genet 117:1191–1203

    Article  CAS  PubMed  Google Scholar 

  • Aljanabi SM, Parmessur Y, Kross H, Dhayan S, Saumtally S, Ramdoyal K, Dookun-Saumtally A (2007) Identification of a major quantitative trait locus (QTL) for yellow spot (Mycovellosiella koepkei) disease resistance in sugarcane. Mol Breed 19:1–14

    Article  Google Scholar 

  • Alwala S, Kimbeng C, Veremis J, Gravois K (2009) Identification of molecular markers associated with sugar-related traits in a Saccharum interspecific cross. Euphytica 167:127–142

    Article  CAS  Google Scholar 

  • Andersen J, Schrag T, Melchinger A, Zein I, Lübberstedt T (2005) Validation of Dwarf8 polymorphisms associated with flowering time in elite european inbred lines of maize (Zea mays L.). Theor Appl Genet 111:206–217

    Article  CAS  PubMed  Google Scholar 

  • Arceneaux G (1967) Cultivated sugarcanes of the world and their botanical derivation. Proc Int Sug Cane Technol 12:844–854

    Google Scholar 

  • Asnaghi C, Paulet F, Kaye C, Grivet L, Deu M, Glaszmann J, D’Hont A (2000) Application of synteny across Poaceae to determine the map location of a sugarcane rust resistance gene. Theor Appl Genet 101:962–969

    Article  CAS  Google Scholar 

  • Bates D, Maechler M, Bolker B (2013) lme4: Linear mixed-effects models using S4 classes. R package version 0.999999-2. http://CRAN.R-project.org/package=lme4

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

    Google Scholar 

  • Besse P, Taylor G, Carroll B, Berding N, Burner D, McIntyre C (1998) Assessing genetic diversity in a sugarcane germplasm collection using an automated AFLP analysis. Genetica 104:143–153

    Article  CAS  PubMed  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 23:2633–2635

    Article  CAS  PubMed  Google Scholar 

  • Bradbury P, Parker T, Hamblin MT, Jannink JL (2011) Assessment of power and false discovery rate in genome-wide association studies using the BarleyCAP germplasm. Crop Sci 51:52–59

    Article  Google Scholar 

  • Butterfield M (2007). Marker assisted breeding in sugarcane: a complex polyploid, University of Stellenbosch. PhD Thesis: 164 pp

  • Cai S, Wu D, Jabeen Z, Huang Y, Huang Y, Zhang G (2013) Genome-wide association analysis of aluminum tolerance in cultivated and tibetan wild barley. PLoS ONE 8:e69776

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Caniato FF, Guimarães CT, Hamblin M, Billot C, Rami J-F, Hufnagel B, Kochian LV, Liu J, Garcia AAF, Hash CT, Ramu P, Mitchell S, Kresovich S, Oliveira AC, de Avellar G, Borém A, Glaszmann J-C, Schaffert RE, Magalhaes JV (2011) The relationship between population structure and aluminum tolerance in cultivated sorghum. PLoS ONE 6:e20830

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM, Smink LJ, Lam AC, Ovington NR, Stevens HE, Nutland S, Howson JMM, Faham M, Moorhead M, Jones HB, Falkowski M, Hardenbol P, Willis TD, Todd JA (2005) Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 37:1243–1246

    Article  CAS  PubMed  Google Scholar 

  • Cordeiro GM, Pan Y-B, Henry RJ (2003) Sugarcane microsatellites for the assessment of genetic diversity in sugarcane germplasm. Plant Sci 165:181–189

    Article  CAS  Google Scholar 

  • Costet L, Le Cunff L, Royaert S, Raboin L-M, Hervouet C, Toubi L, Telismart H, Garsmeur O, Rousselle Y, Pauquet J, Nibouche S, Glaszmann J-C, Hoarau J-Y, D’Hont A (2012a) Haplotype structure around Bru1 reveals a narrow genetic basis for brown rust resistance in modern sugarcane cultivars. Theor Appl Genet 125:825–836

    Article  CAS  PubMed  Google Scholar 

  • Costet L, Raboin L-M, Payet M, D’Hont A, Nibouche S (2012b) A major QTA for resistance to the Sugarcane yellow leaf virus (Luteoviridae). Plant Breed 131:637–640

    Article  CAS  Google Scholar 

  • D’Hoop BB, Paulo MJ, Kowitwanich K, Sengers MI, Visser RGF, Eck HJV, van Eeuwijk F (2010) Population structure and linkage disequilibrium unravelled in tetraploid potato. Theor Appl Genet 121:1151–1170

    Article  PubMed Central  PubMed  Google Scholar 

  • Da Silva JA, Bressiani JA (2005) Sucrose synthase molecular marker associated with sugar content in elite sugarcane progeny. Genet Mol Biol 28:294–298

    Article  Google Scholar 

  • Daugrois J, Grivet L, Roques D, Hoarau J, Lombard H, Glaszmann J-C, D’Hont A (1996) A putative major gene for rust resistance linked with a RFLP marker in sugarcane cultivar ‘R570′. Theor Appl Genet 92:1059–1064

    Article  CAS  PubMed  Google Scholar 

  • Devlin B, Roeder K (1999) Genomic control for association studies. Biometrics 55:997–1004

    Article  CAS  PubMed  Google Scholar 

  • Earl DA, vonHoldt BM (2012) Structure Harvester: a website and program for visualizing Structure output and implementing the Evanno method. Conser Genet Resour 4:359–361

    Article  Google Scholar 

  • Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6:e19379

    Article  PubMed Central  CAS  PubMed  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 

  • FAOSTAT (2012) http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor

  • Gallais A (1990) Théorie de la sélection en amélioration des plantes, Masson edn. France, Paris

    Google Scholar 

  • Gouy M, Nibouche S, Hoarau JY, Costet L (2013a) Improvement of yield per se in sugarcane. In: Varshney RK, Tuberosa R (eds) Translational genomics for crop breeding: abiotic stress, yield, and quality. John Wiley & Sons, Inc., Hoboken, pp 211–238

    Chapter  Google Scholar 

  • Gouy M, Rousselle Y, Bastianelli D, Lecomte P, Bonnal L, Roques D, Efile J-C, Roche S, Daugrois J, Toubi L, Nabenza S, Hervouet C, Telismart H, Denis M, Thong Chane A, Glaszmann JC, Hoarau J-Y, Nibouche S, Costet L (2013b) Experimental assessment of the accuracy of genomic selection in sugarcane. Theor Appl Genet 126:2575–2586

    Article  CAS  PubMed  Google Scholar 

  • Grivet L, Arruda P (2001) Sugarcane genomics: depicting the complex genome of an important tropical crop. Cur Opin Plant Biol 5:122–127

    Article  Google Scholar 

  • Hadfield JD (2010) MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J Stat Softw 33:1–22

    Google Scholar 

  • Hardy OJ, 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 

  • Heller-Uszynska K, Uszynski G, Huttner E, Evers M, Carlig J, Caig V, Aitken K, Jackson P, Piperidis G, Cox M, Gilmour R, D’Hont A, Butterfield M, Glaszmann J-C, Kilian A (2011) Diversity Arrays Technology effectively reveals DNA polymorphism in a large and complex genome of sugarcane. Mol Breed 28:37–55

    Article  CAS  Google Scholar 

  • Hoarau J-Y, Offmann B, D’Hont A, Risterucci A, Glaszmann JC, Roques D, Grivet L (2001) Genetic dissection of a modern sugarcane cultivar (Saccharum spp.). I. Genome mapping with AFLP markers. Theor Appl Genet 103:84–97

    Article  CAS  Google Scholar 

  • Hoarau J-Y, Grivet L, Offmann B, Raboin LM, Diorflar JP, Payet J, Hellmann M, D’Hont A, Glaszmann JC (2002) Genetic dissection of a modern sugarcane cultivar (Saccharum spp.). II. Detection of QTLs for yield components. Theor Appl Genet 105:1027–1037

    Article  PubMed  Google Scholar 

  • Husson F, Josse J, Le S, J M (2010) FactoMineR: multivariate exploratory data analysis and data mining with R. R package version 1.14. http://cran.r-project.org/web/packages/FactoMineR/

  • Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806

    Article  CAS  PubMed  Google Scholar 

  • Jannoo N, Grivet L, Seguin M, Paulet F, Domaingue R, Rao PS, Dookun A, D’Hont A, Glaszmann JC (1999) Molecular investigation of the genetic base of sugarcane cultivars. Theor Appl Genet 99:171–184

    Article  CAS  Google Scholar 

  • Jianbing Y, Warburton M, Crouch J (2011) Association mapping for enhancing maize (Zea mays L.) genetic improvement. Crop Sci 51:433–449

    Article  Google Scholar 

  • Kimbeng CA, Cox MC (2003) Early generation selection of sugarcane families and clones in Australia: a review. J Am Soc Sug Technol 23:21–39

    Google Scholar 

  • Klaus B and Strimmer K (2012) fdrtool: Estimation of (local) false discovery rates and higher criticism. R package version1.2.10. http://CRAN.R-project.org/package=fdrtool

  • Lander E, Kruglyak L (1995) Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet 11:241–247

    Article  CAS  PubMed  Google Scholar 

  • Lander ES, Schork NJ (1994) Genetic dissection of complex traits. Science 265:2037

    Article  CAS  PubMed  Google Scholar 

  • Lee S, Wright FA, Zou F (2011) Control of population stratification by correlation-selected principal components. Biometrics 67:967–974

    Article  PubMed Central  PubMed  Google Scholar 

  • Lima MLA, Garcia AAF, Oliveira KM, Matsuoka S, Arizono H, de Souza Jr CL, de Souza AP (2002) Analysis of genetic similarity detected by AFLP and coefficient of parentage among genotypes of sugar cane (Saccharum spp.). Theor Appl Genet 104:30–38

    Article  CAS  PubMed  Google Scholar 

  • Lu Y, D’Hont A, Paulet F, Grivet L, Arnaud M, Glaszmann JC (1994) Molecular diversity and genome structure in modern sugarcane varieties. Euphytica 78:217–226

    Article  Google Scholar 

  • MacLeod IM, Hayes BJ, Savin KW, Chamberlain AJ, McPartlan HC, Goddard ME (2010) Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms. J Anim Breed Genet 127:133–142

    Article  CAS  PubMed  Google Scholar 

  • Matsuoka S, Ferro J, Arruda P (2009) The Brazilian experience of sugarcane ethanol industry. In Vitro Cell Dev Biol: Plant 45:372–381

    Article  Google Scholar 

  • McIntyre C, Whan V, Croft B, Magarey R, Smith G (2005) Identification and validation of molecular markers associated with pachymetra root rot and brown rust resistance in sugarcane using map- and association-based approaches. Mol Breed 16:151–161

    Article  CAS  Google Scholar 

  • McVean G (2009) A genealogical interpretation of principal components analysis. PLoS Genet 5:e1000686

    Article  PubMed Central  PubMed  Google Scholar 

  • Ming R, Liu S-C, Moore PH, Irvine JE, Paterson AH (2001) QTL analysis in a complex autopolyploid: genetic control of sugar content in sugarcane. Genome Res 11:2075–2084

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Nibouche S, Raboin LM, Hoarau J-Y, D’Hont A, Costet L (2012) Quantitative trait loci for sugarcane resistance to the spotted stem borer Chilo sacchariphagus. Mol Breed 29:129–135

    Article  Google Scholar 

  • Nordborg M, Tavaré S (2002) Linkage disequilibrium: what history has to tell us. Trends Genet 18:83–90

    Article  CAS  PubMed  Google Scholar 

  • Pastina M, Malosetti M, Gazaffi R, Mollinari M, Margarido GRA, Oliveira K, Pinto L, Souza A, van Eeuwijk F, Garcia AAF (2012) A mixed model QTL analysis for sugarcane multiple-harvest-location trial data. Theor Appl Genet 124:835–849

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. PLoS Genet 2:2074–2092

    Article  CAS  Google Scholar 

  • Perrier X, Jacquemoud-Collet J (2006) DARwin software http://darwin.cirad.fr/

  • Plaschke J, Ganal MW, Roder MS (1995) Detection of genetic diversity in closely related bread wheat using microsatellite markers. Theor Appl Genet 91:1001–1007

    CAS  PubMed  Google Scholar 

  • Prasanna B, Cairns J, Xu Y (2013) Genomic tools and strategies for breeding climate resilient cereals. In: Kole C (ed) Genomics and breeding for climate-resilient crops, vol 2, p 487, Springer, pp 213–239

  • Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904–909

    Article  CAS  PubMed  Google Scholar 

  • Price AL, Zaitlen NA, Reich D, Patterson N (2010) New approaches to population stratification in genome-wide association studies. Nat Rev Genet 11:459–463

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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

    PubMed Central  CAS  PubMed  Google Scholar 

  • Raboin L-M (2005) Génétique de la résistance au charbon de la canne à sucre causé par Ustilago scitaminea: caractérisation de la diversité génétique du pathogène, cartographie de QTL dans un croisement bi-parental et étude d’associations dans une population de cultivars modernes. Thèse de doctorat, Montpellier, France, ENSAM 119p

  • Raboin L-M, Offmann B, Hoarau J-Y, Notaise J, Costet L, Telismart H, D’Hont A (2001) Undertaking genetic mapping of sugarcane smut resistance. In Proc. S Afr Sug Technol Ass 75:94–98

    Google Scholar 

  • Raboin L-M, Oliveira K, Lecunff L, Telismart H, Roques D, Butterfield M, Hoarau J, D‘Hont A (2006) Genetic mapping in sugarcane, a high polyploid, using bi-parental progeny: identification of a gene controlling stalk colour and a new rust resistance gene. Theor Appl Genet 112:1382–1391

    Article  CAS  PubMed  Google Scholar 

  • Raboin L-M, Pauquet J, Butterfield M, D’Hont A, Glaszmann J-C (2008) Analysis of genome-wide linkage disequilibrium in the highly polyploid sugarcane. Theor Appl Genet 116:701–714

    Article  CAS  PubMed  Google Scholar 

  • Roach B (1989) Origin and improvement of the genetic base of sugarcane Proc. Aust Soc Sug Technol 11:34–47

    Google Scholar 

  • Rott P, Fleites L, Marlow G, Royer M, Gabriel DW (2011) Identification of new candidate pathogenicity factors in the xylem-invading pathogen Xanthomonas albilineans by transposon mutagenesis. Mol Plant Microbe In 24:594–605

    Article  CAS  Google Scholar 

  • Selvi A, Nair NV, Noyer JL, Singh NK, Balasundaram N, Bansal KC, Koundal KR, Mohapatra T (2005) Genomic constitution and genetic relationship among the tropical and subtropical indian sugarcane cultivars revealed by AFLP. Crop Sci 45:1750–1757

    Article  CAS  Google Scholar 

  • Singh RK, Jena SN, Khan S, Yadav S, Banarjee N, Raghuvanshi S, Bhardwaj V, Dattamajumder SK, Kapur R, Solomon S, Swapna M, Srivastava S, Tyagi AK (2013) Development, cross-species/genera transferability of novel EST-SSR markers and their utility in revealing population structure and genetic diversity in sugarcane. Gene 524:309–329

    Article  CAS  PubMed  Google Scholar 

  • Skinner J (1971) Selection in sugarcane: a review. Proc Int Soc Sug Technol 14:149–162

    Google Scholar 

  • Skinner JC, Hogarth DM, Wu KK (1987) Selection methods, criteria and indices. In: Heinz D (ed) Sugar cane improvement through breeding. Elsevier, Amsterdam, pp 409–453

    Chapter  Google Scholar 

  • Strimmer K (2008) A unified approach to false discovery rate estimation. BMC Bioinformatics 9:303–316

  • Tai P, Miller J (2002) Germplasm diversity among four sugarcane species for sugar composition. Crop Sci 4:958–964

    Article  Google Scholar 

  • R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/

  • Tinker NA, Fortin MG, Mather DE (1993) Random amplified polymorphic DNA and pedigree relationships in spring barley. Theor Appl Genet 85:976–984

    Article  CAS  PubMed  Google Scholar 

  • Voight BF, Pritchard JK (2005) Confounding from cryptic relatedness in case-control association studies. PLoS Genet 1:e32

    Article  PubMed Central  PubMed  Google Scholar 

  • Waclawovsky AJ, Sato PM, Lembke CG, Moore PH, Souza GM (2010) Sugarcane for bioenergy production: an assessment of yield and regulation of sucrose content. Plant Biotech J 8:263–276

    Article  CAS  Google Scholar 

  • Wei X, Jackson P, McIntyre C, Aitken K, Croft B (2006) Associations between DNA markers and resistance to diseases in sugarcane and effects of population substructure. Theor Appl Genet 114:155–164

    Article  CAS  PubMed  Google Scholar 

  • Wei X, Jackson PA, Hermann S, Kilian A, Heller-Uszynska K, Deomano E (2010) Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker-trait associations in sugarcane. Genome 53:973–981

    Article  PubMed  Google Scholar 

  • Würschum T (2012) Mapping QTL for agronomic traits in breeding populations. Theor Appl Genet 25:201–210

    Article  Google Scholar 

  • Yu J, Buckler ES (2006) Genetic association mapping and genome organization of maize. Cur Opin Biotech 17:155–160

    Article  CAS  Google Scholar 

  • Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    Article  CAS  PubMed  Google Scholar 

  • Zhao K, Aranzana MJ, Kim S, Lister C, Shindo C, Tang C, Toomajian C, Zheng H, Dean C, Marjoram P, Nordborg M (2007) An Arabidopsis example of association mapping in structured samples. PLoS Genet 3:e4

    Article  PubMed Central  PubMed  Google Scholar 

  • Zhao K, Tung CW, Eizenga GC, Wright MH, Ali ML, Price AH, Norton GJ, Islam MR, Reynolds A, Mezey J (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature Communications 2:467

    Article  PubMed Central  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors wish to thank T. Dumont, H. Telismart, C. Lallemand, I. Promi, M. Hoarau and R. Tibère for their contributions to field work and phenotypic data acquisition. This study was funded by the eRcane company, by CIRAD (A French research centre working with developing countries to tackle international agricultural and development issues), by an ATP-SEPANG project grant, by the Conseil Régional de la Réunion, by the European Union (European regional development fund—ERDF), by ANR (Agence Nationale de la Recherche) through the Delicas project, grant ANR-08-GENM-001, and by the ANRT (Association Nationale de la Recherche et de la Technologie) through the CIFRE PhD. Grant No.°600/2012 of M. Gouy.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. Costet.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gouy, M., Rousselle, Y., Thong Chane, A. et al. Genome wide association mapping of agro-morphological and disease resistance traits in sugarcane. Euphytica 202, 269–284 (2015). https://doi.org/10.1007/s10681-014-1294-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10681-014-1294-y

Keywords

Navigation