Skip to main content
SpringerLink
Log in

Multiple-line cross quantitative trait locus mapping in sugar beet (Beta vulgaris L.)

  • Published:
Molecular Breeding Aims and scope Submit manuscript

Abstract

Linkage mapping based on multiple-line crosses is a promising strategy for mapping quantitative trait loci (QTL) underlying important agronomic traits. The main goal of this survey was to study the advantages of QTL mapping across versus within biparental populations using experimental data from three connected sugar beet (Beta vulgaris L.) populations evaluated for beet yield and potassium and sodium content. For the combined analysis across populations, we used two approaches for cofactor selection. In Model A, we assumed identical cofactors for every segregating population. In contrast, in Model B we selected cofactors specific for every segregating population. Model A performed better than Model B with respect to the number of QTL detected and the total proportion of phenotypic variance explained. The QTL analyses across populations revealed a substantially higher number of QTL compared to the analyses of single biparental populations. This clearly emphasizes the potential to increase QTL detection power with a joint analysis across biparental populations.

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

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Beavis WD, Grant D, Albertsen M, Fincher R (1991) Quantitative trait loci for plant height in four maize populations and their associations with qualitative genetic loci. Theor Appl Genet 83:141–145

    Article  Google Scholar 

  • Blanc G, Charcosset A, Mangin B, Gallais A, Moreau L (2006) Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize. Theor Appl Genet 113:206–224

    Article  PubMed  CAS  Google Scholar 

  • Buckler ES, Holland JB, Bradbury PJ, Acharya CB, Brown PJ et al (2009) The genetic architecture of maize flowering time. Science 325:714–718

    Article  PubMed  CAS  Google Scholar 

  • Cochran WG, Cox GM (1957) Experimental designs, 2nd edn. Wiley, New York

    Google Scholar 

  • Coles ND, McMullen MD, Balint-Kurti PJ, Pratt RC, Holland JB (2010) Genetic control of photoperiod sensitivity in maize revealed by joint multiple population analysis. Genetics 184:799–812

    Article  PubMed  CAS  Google Scholar 

  • Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285–294

    PubMed  CAS  Google Scholar 

  • Haley CS, Knott SA (1992) A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Theor Appl Genet 103:601–606

    Google Scholar 

  • Hallden C, Hjerdin A, Rading IM, Sall T, Fridlundh B, Johannisdottir G, Tuvesson S, Akesson C, Nilsson N (1996) A high density RFLP linkage map of sugar beet. Genome 39:634–645

    Article  PubMed  CAS  Google Scholar 

  • Holland JB, Portyanko VA, Hoffman DL, Lee M (2002) Genomic regions controlling vernalization and photoperiod responses in oat. Theor Appl Genet 105:113–126

    Article  PubMed  CAS  Google Scholar 

  • Jannink J, Jansen R (2001) Mapping epistatic quantitative trait loci with one-dimensional genome searches. Genetics 157:445–454

    PubMed  CAS  Google Scholar 

  • Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 148:1203–1213

    Google Scholar 

  • Kosambi D (1944) The estimation of map distances from recombination values. Ann Eugen 12:172–175

    Google Scholar 

  • Lander ES, Botstein S (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199

    PubMed  CAS  Google Scholar 

  • Liu W, Reif JC, Cossic F, Würschum T (2012) Comparison of biometrical approaches for QTL detection in multiple segregating populations. Theor Appl Genet 125:987–998

    Article  PubMed  Google Scholar 

  • Medini M, Hamza S, Rebaï A, Baum M (2005) Analysis of genetic diversity in Tunisian durum wheat cultivars and related wild species by SSR and AFLP markers. Genet Resour Crop Evol 52:21–31

    Article  CAS  Google Scholar 

  • Mihaljevic R, Utz HF, Melchinger AE (2004) Congruency of quantitative trait loci detected for agronomic traits in testcrosses of five populations of European maize. Crop Sci 44:114–124

    Article  CAS  Google Scholar 

  • Muranty H (1996) Power of tests for quantitative trait loci detection using full-sib familiars in different schemes. Heredity 76:56–165

    Article  Google Scholar 

  • Negeri AT, Coles ND, Holland JB, Balint-Kurti PJ (2011) Mapping QTL controlling southern leaf blight resistance by joint analysis of three related recombinant inbred line populations. Crop Sci 51:1571–1579

    Article  Google Scholar 

  • Piepho HP (2000) Optimal marker density for interval mapping in a backcross population. Heredity 84:437–440

    Article  PubMed  Google Scholar 

  • R Development Core Team (2010) R: a language and environment for statistical computing. Available at http://www.R-project

  • Rebaï A, Goffinet B (1993) Power of tests for QTL detection using replicated progenies derived from a diallel cross. Theor Appl Genet 86:1014–1022

    Article  Google Scholar 

  • Rebaï A, Goffinet B (2000) More about quantitative trait locus mapping with diallel designs. Genet Res 75:243–247

    Article  PubMed  Google Scholar 

  • Reif JC, Liu W, Gowda M, Maurer HP, Möhring J, Fischer S, Schechert A, Würschum T (2010) Genetic basis of agronomically important traits in sugar beet (Beta vulgaris L.) investigated with joint linkage association mapping. Theor Appl Genet 121:1489–1499

    Article  PubMed  Google Scholar 

  • SAS Institute (2008) SAS/STAT 9.2 user’s guide. SAS Institute, Cary

    Google Scholar 

  • Schneider K, Kulosa D, Soerensen TR, Möhring S, Heine M, Durstewitz G, Polley A, Weber E, Jamsari, Lein J, Hohmann U, Tahiro E, Weisshaar B, Schulz B, Koch G, Jung C, Ganal M (2007) Analysis of DNA polymorphisms in sugar beet (Beta vulgaris L.) and development of an SNP-based map of expressed genes. Theor Appl Genet 115:601–615

    Article  PubMed  CAS  Google Scholar 

  • Schumacher K, Schondelmaier J, Barzen E, Steinrücken G, Borchardt D, Weber WE, Jung C, Salamini F (1997) Combining different linkage maps in sugar beet (Beta vulgaris L.) to make one map. Plant Breed 116:23–38

    Article  Google Scholar 

  • Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464

    Article  Google Scholar 

  • Steinhoff J, Liu W, Maurer HP, Würschum T, Longin CFH (2011) Multiple-line cross QTL-mapping in European elite maize. Crop Sci 51:2505–2516

    Article  Google Scholar 

  • Steinhoff J, Liu W, Maurer HP, Würschum T, Longin CFH, Ranc N, Reif JC (2012a) Exploitation of elite maize (Zea mays L.) germplasm across maturity zones. Crop Sci 52:1534–1542. doi:10.2135/cropsci2011.10.0533

    Article  Google Scholar 

  • Steinhoff J, Liu W, Reif JC, Porta GD, Ranc N, Würschum T (2012b) Detection of QTL for flowering time in multiple families of elite maize. Theor Appl Genet. doi:10.1007/s00122-012-1933-4

    PubMed  Google Scholar 

  • Utz HF, Melchinger AE, Schön CC (2000) Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics 154:1839–1849

    PubMed  Google Scholar 

  • van Ooijen JW, Voorrips RE (2001) JoinMap 3.0: Software for the calculation of genetic linkage maps. Plant Research International BV, Wageningen

    Google Scholar 

  • Verhoeven KJF, Jannink J, McIntyre LM (2006) Using mating designs to uncover QTL and the genetic architecture of complex traits. Heredity 96:139–149

    Article  PubMed  CAS  Google Scholar 

  • Visscher PM, Thompson R, Haley CS (1996) Confidence intervals in QTL mapping by bootstrapping. Genetics 143:1013–1020

    PubMed  CAS  Google Scholar 

  • Weber WE, Borchardt DC, Koch G (1999) Combined linkage maps and QTLs in sugar beet (Beta vulgaris L.) from different populations. Plant Breed 118:193–204

    Article  CAS  Google Scholar 

  • Weber WE, Borchardt DC, Koch G (2000) Marker analysis for quantitative traits in sugar beet. Plant Breed 119:97–106

    Article  CAS  Google Scholar 

  • Weißhaar B, Dohm JC, Minoche A, Schulz B, Kraft T, Wolf M, Holtgraewe D, Himmelbauer H (2011) The draft genome sequence of sugar beet (Beta vulgaris). Plant & Animal Genomes XIX Conference W563: Sugar Beet

  • Würschum T (2012) Mapping QTL for agronomic traits in breeding populations. Theor Appl Genet 125:201–210

    Article  PubMed  Google Scholar 

  • Würschum T, Maurer HP, Schulz B, Möhring J, Reif JC (2011a) Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet. Theor Appl Genet 123:109–118

    Article  PubMed  Google Scholar 

  • Würschum T, Maurer HP, Kraft T, Janssen G, Nilsson C, Reif JC (2011b) Genome-wide association mapping of agronomic traits in sugar beet. Theor Appl Genet 123:1121–1131

    Article  PubMed  Google Scholar 

  • Würschum T, Liu W, Gowda M, Maurer HP, Fischer S, Schechert A, Reif JC (2012) Comparison of biometrical models for joint linkage association mapping. Heredity 108:332–340

    Article  PubMed  Google Scholar 

  • Xu S (1998) Mapping quantitative trait loci using multiple families of line crosses. Genetics 148:517–524

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This research was conducted within the “Biometric and Bioinformatic Tools for Genomic based Plant Breeding” project of the GABI-FUTURE initiative. D.D. Schwegler was supported by DFG within the project “Genetische Architektur der Eigen- versus Testkreuzungsleistung für wichtige agronomische Merkmale beim Roggen” (Grant ID:MI/519/1-1). M. Gowda was supported by BMBF within the HYWHEAT project (Grant ID: FKZ0315945D).

Author information

Authors and Affiliations

  1. State Plant Breeding Institute, University of Hohenheim, 70599, Stuttgart, Germany

    Diana D. Schwegler, Manje Gowda, Tobias Würschum & Jochen C. Reif

  2. Crop Genetics and Breeding Department, China Agricultural University, 100193, Beijing, China

    Wenxin Liu

  3. KWS SAAT AG, 37574, Einbeck, Germany

    Britta Schulz

Authors
  1. Diana D. Schwegler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenxin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manje Gowda
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tobias Würschum
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Britta Schulz
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jochen C. Reif
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jochen C. Reif.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schwegler, D.D., Liu, W., Gowda, M. et al. Multiple-line cross quantitative trait locus mapping in sugar beet (Beta vulgaris L.). Mol Breeding 31, 279–287 (2013). https://doi.org/10.1007/s11032-012-9788-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11032-012-9788-6

Keywords

Search

Navigation