Theoretical and Applied Genetics

, Volume 111, Issue 7, pp 1260–1270 | Cite as

Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust

  • M. I. Vales
  • C. C. Schön
  • F. Capettini
  • X. M. Chen
  • A. E. Corey
  • D. E. Mather
  • C. C. Mundt
  • K. L. Richardson
  • J. S. Sandoval-Islas
  • H. F. Utz
  • P. M. Hayes
Original Paper

Abstract

The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n=409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods—resampling, selective genotyping, and selective phenotyping—to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping.

Keywords

Hordeum vulgare Puccinia striiformis f. sp. hordei Quantitative trait loci Selective genotyping Selective phenotyping Random sampling 

Supplementary material

122_2005_43_MOESM1_ESM.pdf (41 kb)
Supplementary material

References

  1. Allison DB, Fernandez JR, Moonseong H, Shankuan Z, Etzel C (2002) Bias in estimates of quantitative-trait-locus effect in genome scans: demonstration of the phenomenon and a method-of-moments procedure for reducing bias. Am J Hum Genet 70:575–585CrossRefPubMedGoogle Scholar
  2. Ayoub M, Mather DE (2002) Effectiveness of selective genotyping for detection of quantitative trait loci: an analysis of grain and malt quality traits in three barley populations. Genome 45:1116–1124CrossRefPubMedGoogle Scholar
  3. Beavis WB (1998) QTL analyses: power, precision, and accuracy. In: Patterson AH (eds) Molecular dissection of complex traits. CRC Press, Boca RatonGoogle Scholar
  4. Bennewitz J, Reinsch N, Kalm E (2002) Improved confidence intervals in quantitative trait loci mapping by permutation bootstrapping. Genetics 160:1673–1686PubMedGoogle Scholar
  5. Blum E, Mazourek M, O’Connell M, Curry J, Thorup T, Liu K, Jahn M, Paran I (2003) Molecular mapping of capsaicinoid biosynthesis genes and quantitative trait loci analysis for capsaicinoid content in Capsicum. Theor Appl Genet 108:79–86CrossRefPubMedGoogle Scholar
  6. Castro AJ, Chen XM, Hayes PM, Knapp SJ, Line RF, Toojinda T, Vivar H (2002a) Coincident QTL which determine seedling and adult plant resistance to stripe rust in barley. Crop Sci 42:1701–1708CrossRefGoogle Scholar
  7. Castro AJ, Hayes PM, Fillichkin T, Rossi C (2002b) Update of barley stripe rust resistance QTL in the Calichima-sib×Bowman mapping population. Barley Genetics Newsl 32:1–12Google Scholar
  8. Castro AJ, Capettini F, Corey AE, Filichkin T, Hayes PM, Kleinhofs A, Kudrna D, Richardson K, Sandoval-Islas S, Rossi C, Vivar H (2003a) Mapping and pyramiding of qualitative and quantitative resistance to stripe rust in barley. Theor Appl Genet 107:922–930CrossRefPubMedGoogle Scholar
  9. Castro AJ, Chen XM, Hayes PM, Johnston M (2003b) Pyramiding quantitative trait locus (QTL) alleles determining resistance to barley stripe rust: effects on resistance at the seedling stage. Crop Sci 43:651–659CrossRefGoogle Scholar
  10. Chen F, Hayes PM (1989) A comparison of Hordeum bulbosum - mediated haploid production efficiency in barley using in vitro floret and tiller culture. Theor Appl Genet 77:701–704Google Scholar
  11. Chen XM, Line RF (2001) Races of barley stripe rust in the United States. Barley Newsl 44. http://grain.jouy.inra.fr/ggpages/BarleyNewsletter/44/WashReport2.html
  12. Chen F, Prehn D, Hayes PM, Mulrooney D, Corey A, Vivar H (1994). Mapping genes for resistance to barley stripe rust (Puccinia striiformis f. sp. hordei). Theor Appl Genet 88: 215–219Google Scholar
  13. Cooper LD, Marquez-Cedillo L, Singh J, Sturbaum AK, Zhang S, Edwards V, Johnson K, Kleinhofs A, Rangel S, Carollo V, Bregitzer P, Lemaux PG, Hayes PM (2004) Mapping Ds insertions in barley using a sequence-based approach. Mol Gen Genomics 272:181–193CrossRefGoogle Scholar
  14. Dubin HJ, Stubbs RW (1985) Epidemic spread of barley stripe rust in South America. Plant Dis 70:141–144CrossRefGoogle Scholar
  15. Foolad MR, Zhang LP, Lin G (2001) Identification and validation of QTLs for salt tolerance during vegetative growth in tomato by selective genotyping. Genome 44:444–454CrossRefPubMedGoogle Scholar
  16. Goring HHH, Terwilliger JD, Blangero J (2001) Large upward bias in estimation of locus-specific effects from genome-wide scans. Am J Hum Genet 69:1357–1369CrossRefPubMedGoogle Scholar
  17. Hayes PM, Prehn D, Vivar H, Blake T, Comeau A, Henry I, Johnston M, Jones B, Steffenson B (1996) Multiple disease resistance loci and their relationship to agronomic and quality loci in a spring barley population. J Quant. Trait Loci http://www.probe.nalusda.gov:8000/otherdocs/jqtl/index.htm
  18. Hayes PM, Cerono J, Witsenboer H, Kuiper M, Zabeau M, Sato K, Kleinhofs A, Kudrna D, Kilian A, Saghai-Maroof M, Hoffman D, NABGMP (1997) Characterizing and exploiting genetic diversity and quantitative traits in barley (Hordeum vulgare). J Quant Trait Loci http://www.probe.nalusda.gov:8000/otherdocs/jqtl/jqtl1997-02/.
  19. Hjorth JSU (1994) Computer intensive statistical methods. Validation model selection and bootstrap. Chapman & Hall, LondonGoogle Scholar
  20. Jannink J-L (2005) Selective phenotyping to accurately map quantitative trait loci. Crop Sci 45:901–908CrossRefGoogle Scholar
  21. Kover PX, Caicedo AL (2001) The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites. Mol Ecol 10:1–16CrossRefPubMedGoogle Scholar
  22. Lander ES, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199PubMedGoogle Scholar
  23. Liu Z-W, Biyashev RM, Maroof MAS (1996) Development of simple sequence repeat DNA markers and their integration into a barley linkage map. Theor Appl Genet 93:869–876Google Scholar
  24. Melchinger AE, Utz HF, Schön CC (1998) Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics 149:383–403PubMedGoogle Scholar
  25. Nandi S, Subudhi PK, Senadhira D, Manigbas NL, Sen-Mandi S, Huang N (1997) Mapping QTLs for submergence tolerance in rice by AFLP analysis and selective genotyping. Mol Gen Genet 255:1–8CrossRefPubMedGoogle Scholar
  26. Ramsay L, Macaulay M, Ivanissevich Sd, MacLean K, Cardle L, Fuller J, Edwards KJ, Tuvesson S, Morgante M, Massari A, Maestri E, Marmiroli N, Sjakste T, Ganal M, Powell W, Waugh R (2000) A simple sequence repeat-based linkage map of barley. Genetics 156:1997–2005PubMedGoogle Scholar
  27. SAS Institute (2001) The SAS system for Windows v. 8.02. SAS Institute Inc. Cary, NC, USAGoogle Scholar
  28. Schön CC, Utz HF, Groh S, Truberg B, Openshaw S, Melchinger AE (2004) Quantitative trait locus mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits. Genetics 167:485–498CrossRefPubMedGoogle Scholar
  29. Shen X, Zhou M, Lu W, Ohm H (2003) Detection of fusarium head blight resistance QTL in a wheat population using bulked segregant analysis. Theor Appl Genet 106:1041–1047PubMedGoogle Scholar
  30. Struss D, Plieske J (1998) The use of microsatellite markers for detection of genetic diversity in barley populations. Theor Appl Genet 97:308–315CrossRefGoogle Scholar
  31. Tanksley SD (1993) Mapping polygenes. Annu Rev Genet 27:205–233CrossRefPubMedGoogle Scholar
  32. Thiel T, Michalek W, Varshney RK, Graner A (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet 106:411–422PubMedGoogle Scholar
  33. Thomas WTB, Powell W, Waugh R, Chalmers KJ, Barua UM, Jack P, Lea V, Forster BP, Swanston JS, Ellis RP, Hanson PR, Lance RCM (1995) Detection of quantitative trait loci for agronomic, yield, grain and disease characters in spring barley (Hordeum vulgare L.). Theor Appl Genet 91:1037–1047CrossRefGoogle Scholar
  34. Tinker NA, Mather DE (1995) MQTL: software for simplified composite interval mapping of QTL in multiple environments. J Quant Trait Loci 1:2Google Scholar
  35. Toojinda T, Baird E, Booth A, Broers L, Hayes P, Powell W, Thomas W, Vivar H, Young G (1998) Introgression of quantitative trait loci (QTL) determining stripe rust resistance in barley: an example of marker-assisted line development. Theor Appl Genet 96:123–131CrossRefGoogle Scholar
  36. Toojinda T, Baird E, Broers L, Chen XM, Hayes PM, Kleinhofs A, Korte J, Kudrna D, Leung H, Line RF, Powell W, Vivar H (2000) Mapping quantitative and qualitative disease resistance genes in a doubled haploid population of barley. Theor Appl Genet 101:580–589CrossRefGoogle Scholar
  37. Utz HF (2001) PLABSTAT. A computer program for statistical analysis of plant breeding experiments (2F). Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, GermanyGoogle Scholar
  38. Utz HF, Melchinger AE (1996) PLABQTL: a program for composite interval mapping of QTL. J Quant Trait Loci 2:1–5Google Scholar
  39. 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 154:1839–1849PubMedGoogle Scholar
  40. Van Ooijen JW, Voorrips RE (2001) JoinMap 3.0. Software for the calculation of linkage maps. Plant Research International, Wageningen, the NetherlandsGoogle Scholar
  41. Vision TJ, Brown DG, Shmoys DB, Durrett RT, Tanksley SD (2000) Selective mapping: a strategy for optimizing the construction of high-density linkage maps. Genetics 155:407–420PubMedGoogle Scholar
  42. Wang S, Basten CJ, Zeng Z-B (2001–2003) Windows QTL cartographer 2.0. Department of Statistics, North Carolina State University, Raleigh, NC, USAGoogle Scholar
  43. von Wettstein-Knowles PV (1992) Cloned and mapped genes: current status. CAB International, WallinfgordGoogle Scholar
  44. Young ND (1996) QTL mapping and quantitative disease resistance in plants. Ann Rev Phytopathol 34:479–501CrossRefGoogle Scholar
  45. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468PubMedGoogle Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • M. I. Vales
    • 1
  • C. C. Schön
    • 2
  • F. Capettini
    • 3
  • X. M. Chen
    • 4
  • A. E. Corey
    • 1
  • D. E. Mather
    • 5
  • C. C. Mundt
    • 6
  • K. L. Richardson
    • 1
  • J. S. Sandoval-Islas
    • 7
  • H. F. Utz
    • 8
  • P. M. Hayes
    • 1
  1. 1.Department of Crop and Soil ScienceOregon State UniversityCorvallisUSA
  2. 2.State Plant Breeding InstituteUniversity of HohenheimStuttgartGermany
  3. 3.ICARDA/CIMMYT Barley ProgramMexicoMexico
  4. 4.U.S. Department of Agriculture, Agricultural Research ServiceWashington State UniversityPullmanUSA
  5. 5.School of Agriculture and WineUniversity of Adelaide / Molecular Plant Breeding Cooperative Research CentreGlen OsmondAustralia
  6. 6.Department of Botany and Plant PathologyOregon State UniversityCorvallisUSA
  7. 7.Instituto de FitosanidadColegio de PostgraduadosMexicoMexico
  8. 8.Institute of Plant Breeding, Seed Science and Population GeneticsUniversity of HohenheimStuttgartGermany

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