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Theoretical and Applied Genetics

, Volume 132, Issue 8, pp 2425–2437 | Cite as

An experimental approach for estimating the genomic selection advantage for Fusarium head blight and Septoria tritici blotch in winter wheat

  • Cathérine Pauline Herter
  • Erhard Ebmeyer
  • Sonja Kollers
  • Viktor Korzun
  • Thomas MiedanerEmail author
Original Article

Abstract

Key message

The genomic selection advantage for Fusarium head blight is promising but failed for Septoria tritici blotch. Selection of new breeding parents based on predictions must be treated with caution.

Abstract

Genomic selection (GS) is an approach that uses whole-genome marker data to estimate breeding values of untested genotypes and holds the potential to improve the genetic gain in breeding programs by shortening the breeding cycle and increasing the selection intensity. However, reported realized gain from genomic selection is limited to few experiments. In this study, a training population of 1120 winter wheat lines derived from 14 bi-parental families was genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight (FHB) and Septoria tritici blotch (STB) severity, plant height and heading date. We used weighted ridge regression best linear unbiased prediction to calculate genomic estimated breeding values (GEBVs) of 2500 genotypes. Based on GEBVs, we selected the most resistant individuals as well as a random sample and tested them in a multi-location field trial. We computed moderate coefficients of correlation between observed and predicted trait values for FHB severity, plant height and heading date and achieved a genomic selection advantage of 10.62 percentage points for FHB resistance compared to the randomly chosen subpopulation. Genomic selection failed for the improvement of STB resistance with a genomic selection advantage of only 2.14 percentage points. Our results also indicate that the selection of new breeding parents based on GEBVs must be treated with caution. Taken together, the implementation of GS for FHB resistance, plant height and heading date seems to be promising. For traits with very strong genotype × environment variance, like STB resistance, GS appears to be still challenging.

Notes

Acknowledgements

We highly appreciate the excellent technical support of the teams at KWS LOCHOW and University of Hohenheim. This research was funded by the German Federal Ministry of Education and Research (BMBF, Grant No. 031B0011A + E) in the framework of Bioeconomy International (FusResist). The responsibility of the content of this publication rests with the authors.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Ethical standards

The experiments comply with the current laws of Germany in which they were performed.

Supplementary material

122_2019_3364_MOESM1_ESM.pdf (89 kb)
Supplementary material 1 (PDF 88 kb)

References

  1. Arruda M, Brown P, Lipka A, Krill A, Thurber C, Kolb F (2015) Genomic selection for predicting Fusarium head blight resistance in a wheat breeding program. Plant Genome 8:1–12CrossRefGoogle Scholar
  2. Arruda M, Lipka A, Brown P, Krill A, Thurber C, Brown-Guedira G et al (2016) Comparing genomic selection and marker-assisted selection for Fusarium head blight resistance in wheat (Triticum aestivum). Mol Breed 36:1–11CrossRefGoogle Scholar
  3. Bassi FM, Bentley AR, Charmet G, Ortiz R, Crossa J (2016) Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.). Plant Sci 242:23–36CrossRefPubMedGoogle Scholar
  4. Bernardo R (1994) Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci 34:20–25CrossRefGoogle Scholar
  5. Bernardo R (2003) Parental selection, number of breeding populations, and size of each population in inbred development. Theor Appl Genet 107:1252–1256CrossRefPubMedGoogle Scholar
  6. Beyene Y, Semagn K, Mugo S et al (2015) Genetic gains in grain yield through genomic selection in eight bi-parental maize populations under drought stress. Crop Sci 55:154–163CrossRefGoogle Scholar
  7. BSL (2008) Beschreibende Sortenliste für Getreide, Mais, Öl- und Faserpflanzen, Leguminosen, Rüben, Zwischenfrüchte [Descriptive variety list for cereals, maize, oil and fibre plants, pulse crops, beets, catch crops, in German]. Bundessortenamt, HannoverGoogle Scholar
  8. Burgueño J, de los Campos G, Weigel K, Crossa J (2012) Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers. Crop Sci 52:707–719CrossRefGoogle Scholar
  9. Cools HJ, Fraaije BA (2008) Are azole fungicides losing ground against Septoria wheat disease? Resistance mechanisms in Mycosphaerella graminicola. Pest Manag Sci 64:681–684CrossRefPubMedGoogle Scholar
  10. Crossa J, de Los Campos G, Pérez P et al (2010) Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713–724CrossRefPubMedPubMedCentralGoogle Scholar
  11. Daetwyler H, Pong-Wong R, Villanueva B, Woolliams JA (2010) The impact of genetic architecture on genome-wide evaluation methods. Genetics 185:1021–1031CrossRefPubMedPubMedCentralGoogle Scholar
  12. Deutscher Wetterdienst (2018) ein außergewöhnliches Wetterjahr mit vielen Rekorden. https://www.dwd.de/DE/presse/pressemitteilungen/DE/2018/20181228_deutschlandwetter_jahr2018.pdf?__blob=publicationFile&v=3. Accessed 01 Feb 2019
  13. Draeger R, Gosman N, Steed A et al (2007) Identification of QTLs for resistance to Fusarium head blight, DON accumulation and associated traits in the winter wheat variety Arina. Theor Appl Genet 115:617–625CrossRefPubMedGoogle Scholar
  14. Duchemin SI, Legarra A, Baloche G et al (2012) Genomic selection in the French Lacaune dairy sheep breed. J Dairy Sci 95:2723–2733CrossRefPubMedGoogle Scholar
  15. Endelman JB (2011) Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4:250–255CrossRefGoogle Scholar
  16. Fisher RA (1921) On the “probable error” of a coefficient of correlation deduced from a small sample. Metron 1:1–32Google Scholar
  17. Fones H, Gurr S (2015) The impact of Septoria tritici blotch disease on wheat: an EU perspective. Fungal Genet Biol 79:3–7CrossRefPubMedPubMedCentralGoogle Scholar
  18. Gianola D, van Kaam JB (2008) Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits. Genetics 178:2289–2303CrossRefPubMedPubMedCentralGoogle Scholar
  19. Gianola D, Fernando RL, Stella A (2006) Genomic-assisted prediction of genetic value with semiparametric procedures. Genetics 173:1761–1776CrossRefPubMedPubMedCentralGoogle Scholar
  20. Gilmour A, Gogel B, Cullis B, Thompson R, VSN International Hemel Ltd, Hempstead (2009) ASReml user guide release 3.0. http://www.vsni.co.uk. Accessed 3 March 2017
  21. Goddard M, Hayes B (2007) Genomic selection. J Anim Breed Genet 124:323–330CrossRefPubMedGoogle Scholar
  22. González-Camacho J, de los Campos G, Pérez P et al (2012) Genome-enabled prediction of genetic values using radial basis function neural networks. Theor Appl Genet 125:759–771CrossRefPubMedPubMedCentralGoogle Scholar
  23. Gower J (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53:325–338CrossRefGoogle Scholar
  24. Hallauer A, Miranda JB (1981) Quantitative genetics in maize breeding. Iowa State University Press, Iowa CityGoogle Scholar
  25. Han S, Utz H, Liu W et al (2016) Choice of models for QTL mapping with multiple families and design of the training set for prediction of Fusarium resistance traits in maize. Theor Appl Genet 129:431–444CrossRefPubMedGoogle Scholar
  26. Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME (2009) Invited review: genomic selection in dairy cattle: progress and challenges. J Dairy Sci 92:433–443CrossRefPubMedGoogle Scholar
  27. Heffner EL, Sorrells ME, Jannink JL (2009) Genomic selection for crop improvement. Crop Sci 49:1–12CrossRefGoogle Scholar
  28. Heffner EL, Lorenz AJ, Jannink JL, Sorrells ME (2010) Plant breeding with genomic selection: gain per unit time and cost. Crop Sci 50:1681–1690CrossRefGoogle Scholar
  29. Heffner EL, Jannink JL, Sorrells ME (2011a) Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Genome 4:65–75CrossRefGoogle Scholar
  30. Heffner EL, Jannink JL, Iwata H, Souza E, Sorrells ME (2011b) Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci 51:2597–2606CrossRefGoogle Scholar
  31. Herter CP, Ebmeyer E, Kollers S, Korzun V, Würschum T, Miedaner T (2018) Accuracy of within-and among-family genomic prediction for Fusarium head blight and Septoria tritici blotch in winter wheat. Theor Appl Genet 132:1121–1135.  https://doi.org/10.1007/s00122-018-3264-6 CrossRefPubMedGoogle Scholar
  32. Hess D, Shaner G (1987) Effect of moisture and temperature on development of Septoria tritici blotch in wheat. Phytopathology 77:215–219CrossRefGoogle Scholar
  33. Jannink J-L, Lorenz A, Iwata H (2010) Genomic selection in plant breeding: from theory to practice. Brief Funct Genom 9:166–177CrossRefGoogle Scholar
  34. Jiang Y, Reif JC (2015) Modelling epistasis in genomic selection. Genetics 201:115CrossRefGoogle Scholar
  35. Jiang G, Wu Z, Huang D (1993) Effects of recurrent selection for resistance to scab (Gibberella zeae) in wheat. Euphytica 72:107–113CrossRefGoogle Scholar
  36. Juliana P, Singh R, Singh P et al (2017) Comparison of models and whole-genome profiling approaches for genomic-enabled prediction of Septoria tritici blotch, Stagonospora nodorum blotch, and tan spot resistance in wheat. Plant Genome 10:1–16CrossRefGoogle Scholar
  37. Klahr A, Zimmermann G, Wenzel G, Mohler V (2007) Effects of environment, disease progress, plant height and heading date on the detection of QTLs for resistance to Fusarium head blight in an European winter wheat cross. Euphytica 154:17–28CrossRefGoogle Scholar
  38. Kollers S, Rodemann B, Ling J et al (2013a) Whole genome association mapping of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.). PLoS ONE 8:e57500CrossRefPubMedPubMedCentralGoogle Scholar
  39. Kollers S, Rodemann B, Ling J et al (2013b) Genetic architecture of resistance to Septoria tritici blotch (Mycosphaerella graminicola) in European winter wheat. Mol Breed 32:411–423CrossRefGoogle Scholar
  40. Kutcher HR, Johnston AM, Bailey KL, Malhi SS (2011) Managing crop losses from plant diseases with foliar fungicides, rotation and tillage on a Black chernozem in Saskatchewan, Canada. Field Crop Res 124:205–212CrossRefGoogle Scholar
  41. Lehermeier C, Krämer N, Bauer E et al (2014) Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction. Genetics 198:3–16CrossRefPubMedPubMedCentralGoogle Scholar
  42. Lorenz A, Smith K (2015) Adding genetically distant individuals to training populations reduces genomic prediction accuracy in barley. Crop Sci 55:2657–2667CrossRefGoogle Scholar
  43. Lu Q, Lillemo M, Skinnes H et al (2013) Anther extrusion and plant height are associated with Type I resistance to Fusarium head blight in bread wheat line ‘Shanghai-3/Catbird’. Theor Appl Genet 126:317–334CrossRefPubMedGoogle Scholar
  44. Massman JM, Jung H-JG, Bernardo R (2013) Genomewide selection versus marker-assisted recurrent selection to improve grain yield and stover-quality traits for cellulosic ethanol in maize. Crop Sci 53:58–66CrossRefGoogle Scholar
  45. McGill R, Tukey JW, Larsen WA (1978) Variations of box plots. Am Stat 32:12–16Google Scholar
  46. Meuwissen T, Hayes B, Goddard M (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829PubMedPubMedCentralGoogle Scholar
  47. Michel S, Ametz C, Gungor H, Epure D, Grausgruber H, Löschenberger F, Buerstmayr H (2016) Genomic selection across multiple breeding cycles in applied bread wheat breeding. Theor Appl Genet 129:1179–1189CrossRefPubMedPubMedCentralGoogle Scholar
  48. Miedaner T, Voss HH (2008) Effect of dwarfing genes on Fusarium head blight resistance in two sets of near-isogenic lines of wheat and check cultivars. Crop Sci 48:2115–2122CrossRefGoogle Scholar
  49. Miedaner T, Gang G, Geiger H (1996) Quantitative-genetic basis of aggressiveness of 42 isolates of Fusarium culmorum for winter rye head blight. Plant Dis (USA) 80:500–504CrossRefGoogle Scholar
  50. Miedaner T, Wilde F, Steiner B, Buerstmayr H, Korzun V, Ebmeyer E (2006) Stacking quantitative trait loci (QTL) for Fusarium head blight resistance from non-adapted sources in an European elite spring wheat background and assessing their effects on deoxynivalenol (DON) content and disease severity. Theor Appl Genet 112:562–569CrossRefPubMedGoogle Scholar
  51. Miedaner T, Wilde F, Korzun V, Ebmeyer E, Schmolke M, Hartl L, Schön CC (2009) Marker selection for Fusarium head blight resistance based on quantitative trait loci (QTL) from two European sources compared to phenotypic selection in winter wheat. Euphytica 166:219–227CrossRefGoogle Scholar
  52. Miedaner T, Risser P, Paillard S, Schnurbusch T, Keller B, Hartl L, Holzapfel J, Korzun V, Ebmeyer E, Utz HF (2012) Broad-spectrum resistance loci for three quantitatively inherited diseases in two winter wheat populations. Mol Breed 29:731–742CrossRefGoogle Scholar
  53. Miedaner T, Zhao Y, Gowda M et al (2013) Genetic architecture of resistance to Septoria tritici blotch in European wheat. BMC Genom 14:858CrossRefGoogle Scholar
  54. Mirdita V, He S, Zhao Y et al (2015a) Potential and limits of whole genome prediction of resistance to Fusarium head blight and Septoria tritici blotch in a vast Central European elite winter wheat population. Theor Appl Genet 128:2471–2481CrossRefGoogle Scholar
  55. Mirdita V, Liu G, Zhao Y et al (2015b) Genetic architecture is more complex for resistance to Septoria tritici blotch than to Fusarium head blight in Central European winter wheat. BMC Genom 16:430CrossRefGoogle Scholar
  56. Morota G, Gianola D (2014) Kernel-based whole-genome prediction of complex traits: a review. Front Genet 5:363PubMedPubMedCentralGoogle Scholar
  57. Nakaya A, Isobe SN (2012) Will genomic selection be a practical method for plant breeding? Ann Bot 110:1303–1316CrossRefPubMedPubMedCentralGoogle Scholar
  58. Piepho H-P, Möhring J (2007) Computing heritability and selection response from unbalanced plant breeding trials. Genetics 177:1881–1888CrossRefPubMedPubMedCentralGoogle Scholar
  59. Piepho H-P, Williams E, Fleck M (2006) A note on the analysis of designed experiments with complex treatment structure. HortScience 41:446–452CrossRefGoogle Scholar
  60. Pirgozliev SR, Edwards SG, Hare MC et al (2003) Strategies for the control of Fusarium head blight in cereals. Eur J Plant Pathol 109:731–742CrossRefGoogle Scholar
  61. Poland J, Rutkoski J (2016) Advances and challenges in genomic selection for disease resistance. Annu Rev Phytopathol 54:79–98CrossRefPubMedGoogle Scholar
  62. R Core Team (2017) R: a language and environment for statistical computing. Retrieved from R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. Accessed 12 July 2017
  63. Resende M, Muñoz P, Resende M et al (2012) Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190:1503–1510CrossRefPubMedPubMedCentralGoogle Scholar
  64. Risser P, Ebmeyer E, Korzun V, Hartl L, Miedaner T (2011) Quantitative trait loci for adult-plant resistance to Mycosphaerella graminicola in two winter wheat populations. Phytopathology 101:1209–1216CrossRefPubMedGoogle Scholar
  65. Rutkoski J, Heffner E, Sorrells M (2011) Genomic selection for durable stem rust resistance in wheat. Euphytica 179:161–173CrossRefGoogle Scholar
  66. Rutkoski J, Benson J, Jia Y, Brown-Guedira G, Jannink J, Sorrells M (2012) Evaluation of genomic prediction methods for Fusarium head blight resistance in wheat. Plant Genome 5:51–61CrossRefGoogle Scholar
  67. Rutkoski J, Poland J, Singh R et al (2014) Genomic selection for quantitative adult plant stem rust resistance in wheat. Plant Genome 7:1441–1448CrossRefGoogle Scholar
  68. Rutkoski J, Singh RP, Huerta-Espino J, Bhavani S, Poland J, Jannink JL, Sorrells ME (2015) Genetic gain from phenotypic and genomic selection for quantitative resistance to stem rust of wheat. Plant Genome.  https://doi.org/10.3835/plantgenome2014.10.0074 CrossRefGoogle Scholar
  69. Sallam AH, Smith KP (2016) Genomic selection performs similarly to phenotypic selection in barley. Crop Sci 56:1–11CrossRefGoogle Scholar
  70. Schmolke M, Zimmermann G, Buerstmayr H et al (2005) Molecular mapping of Fusarium head blight resistance in the winter wheat population Dream/Lynx. Theor Appl Genet 111:747–775CrossRefPubMedGoogle Scholar
  71. Snijders C, Perkowski J (1990) Effects of head blight caused by Fusarium culmorum on toxin content and weight of wheat kernels. Phytopathology 80:566–570CrossRefGoogle Scholar
  72. Spindel J, Begum H, Akdemir D, Collard B, Redoña E, Jannink J, McCouch S (2016) Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement. Heredity 116:395–408CrossRefPubMedPubMedCentralGoogle Scholar
  73. Srinivasachary, Gosman N, Steed A, Hollins T, Bayles R, Jennings P, Nicholson P (2009) Semi-dwarfing Rht-B1 and Rht-D1 loci of wheat differ significantly in their influence on resistance to Fusarium head blight. Theor Appl Genet 118:695CrossRefPubMedGoogle Scholar
  74. Stram D, Lee J (1994) Variance components testing in the longitudinal mixed effects model. Biometrics 50:1171–1177CrossRefPubMedGoogle Scholar
  75. Tinker N, Fortin M, Mather D (1993) Random amplified polymorphic DNA and pedigree relationships in spring barley. Theor Appl Genet 85:976–984CrossRefPubMedGoogle Scholar
  76. Torriani SFF, Brunner PC, McDonald BA, Sierotzki H (2009) QoI resistance emerged independently at least 4 times in European populations of Mycosphaerella graminicola. Pest Manag Sci 65:155–162CrossRefPubMedGoogle Scholar
  77. VanRaden PM, Van Tassell C, Wiggans G, Sonstegard T, Schnabel R, Taylor J, Schenkel F (2009) Invited review: reliability of genomic predictions for North American Holstein bulls. J Dairy Sci 92(1):16–24CrossRefPubMedGoogle Scholar
  78. Von der Ohe C, Ebmeyer E, Korzun V, Miedaner T (2010) Agronomic and quality performance of winter wheat backcross populations carrying non-adapted Fusarium head blight resistance QTL. Crop Sci 50:2283–2290CrossRefGoogle Scholar
  79. Voss HH, Holzapfel J, Hartl L et al (2008) Effect of the Rht-D1 dwarfing locus on Fusarium head blight rating in three segregating populations of winter wheat. Plant Breed 127:333–339CrossRefGoogle Scholar
  80. Wang S, Wong D, Forrest K et al (2014) Characterization of polyploid wheat genomic diversity using a high-density 90, 000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796CrossRefPubMedPubMedCentralGoogle Scholar
  81. Whittaker J, Thompson R, Denham M (2000) Marker-assisted selection using ridge regression. Genet Res 75:249–252CrossRefPubMedGoogle Scholar
  82. Wilde F, Korzun V, Ebmeyer E, Geiger HH, Miedaner T (2007) Comparison of phenotypic and marker-based selection for Fusarium head blight resistance and DON content in spring wheat. Mol Breed 19:357–370CrossRefGoogle Scholar
  83. Willyerd KT, Li C, Madden L, Bradley V, Bergstrom CA, Sweets GC, McMullen LE et al (2012) Efficacy and stability of integrating fungicide and cultivar resistance to manage Fusarium head blight and deoxynivalenol in wheat. Plant Dis 96:957–967CrossRefPubMedGoogle Scholar
  84. Wolc A, Stricker C, Arango JS et al (2011) Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model. Genet Sel Evol 43(1):5CrossRefPubMedPubMedCentralGoogle Scholar
  85. Wright S (1978) Evolution and genetics of populations, variability within and among natural populations, vol 4. The University of Chicago Press, Chicago, p 91Google Scholar
  86. Würschum T, Abel S, Zhao Y (2014) Potential of genomic selection in rapeseed (Brassica napus L.) breeding. Plant Breed 133:45–51CrossRefGoogle Scholar
  87. Würschum T, Maurer H, Weissmann S, Hahn V, Leiser W (2017) Accuracy of within-and among-family genomic prediction in triticale. Plant Breed 136:230–236CrossRefGoogle Scholar
  88. Yuen GY, Schoneweis SD (2007) Strategies for managing Fusarium head blight and deoxynivalenol accumulation in wheat. Int J Food Microbiol 119:126–130CrossRefPubMedGoogle Scholar
  89. Zhang X, Pérez-Rodríguez P, Semagn K et al (2015) Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs. Heredity 114:291CrossRefPubMedGoogle Scholar
  90. Zhao Y, Gowda M, Liu W et al (2012) Accuracy of genomic selection in European maize elite breeding populations. Theor Appl Genet 124:769–776CrossRefPubMedGoogle Scholar
  91. Zhong S, Dekkers JC, Fernando RL et al (2009) Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a barley case study. Genetics 182:355–364CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.State Plant Breeding InstituteUniversity of HohenheimStuttgartGermany
  2. 2.KWS LOCHOW GmbHBergenGermany

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