Skip to main content

Genomic Selection in Plant Breeding

  • Protocol
  • First Online:
Crop Breeding

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1145))

Abstract

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    CAS  PubMed Central  PubMed  Google Scholar 

  2. VanRaden PM, Van Tassell CP, Wiggans GR, Sonstegard TS, Schnabel RD, Taylor JF, Schenkel FS (2009) Invited review: reliability of genomic predictions for North American Holstein bulls. J Dairy Sci 92:16–24

    Article  CAS  PubMed  Google Scholar 

  3. Lorenzana RE, Bernardo R (2009) Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor Appl Genet 120:151–161

    Article  PubMed  Google Scholar 

  4. de los Campos G, Naya G, Gianola D, Crossa J, Legarra A, Manfredi E, Weigel K, Cotes JM (2009) Predicting quantitative traits with regression models for dense molecular markers and pedigrees. Genetics 182:375–385

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Asoro FG, Newell MA, Beavis WD, Scott MP, Jannink J-L (2011) Accuracy and training population design for genomic selection on quantitative traits in elite North American oats. Plant Genome 4:132–144

    Article  Google Scholar 

  6. Lorenz AJ, Smith KP, Jannink J-L (2012) Potential and optimization of genomic selection for Fusarium Head Blight resistance in six-row barley. Crop Sci 52:1609–1621

    Article  Google Scholar 

  7. Hayes BJ, Bowman PJ, Chamberlain AC, Goddard ME (2009) Invited review: genomic selection in dairy cattle: progress and challenges. J Dairy Sci 92:433–443

    Article  CAS  PubMed  Google Scholar 

  8. Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA (2010) The impact of genetic architecture on genome-wide evaluation methods. Genetics 185:1021–1031

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Habier D, Fernando R, Dekkers J (2007) The impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389–2397

    CAS  PubMed Central  PubMed  Google Scholar 

  10. Habier D, Tetens J, Seefried FR, Lichtner P, Thaller G (2010) The impact of genetic relationship information on genomic breeding values in German Holstein cattle. Genet Sel Evol 42:5

    Article  PubMed Central  PubMed  Google Scholar 

  11. Clark SA, Hickey JM, Daetwyler HD, van der Werf JHJ (2012) The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes. Genet Sel Evol 44:4

    Article  PubMed Central  PubMed  Google Scholar 

  12. de Roos APW, Hayes BJ, Goddard ME (2009) Reliability of genomic breeding values across multiple populations. Genetics 183:1545–1553

    Article  PubMed Central  PubMed  Google Scholar 

  13. Hayes BJ, Bowman PJ, Chamberlain AC, Verbyla K, Goddard ME (2009) Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genet Sel Evol 41:51

    Article  PubMed Central  PubMed  Google Scholar 

  14. Yu J, Pressoir G, Briggs WH, Bi IV, 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 

  15. Jannink J-L (2010) Dynamics of long-term genomic selection. Genet Sel Evol 42:35

    Article  PubMed Central  PubMed  Google Scholar 

  16. Bijma P (2012) Accuracies of estimated breeding values from ordinary genetic evaluations do not reflect the correlation between true and estimated breeding values in selected populations. J Anim Breed Genet 129:345–358

    Article  CAS  PubMed  Google Scholar 

  17. Sonesson AK, Woolliams JA, Meuwissen THE (2012) Genomic selection requires genomic control of inbreeding. Genet Sel Evol 44:27

    Article  PubMed Central  PubMed  Google Scholar 

  18. Heffner EL, Lorenz AJ, Jannink J-L, Sorrells ME (2010) Plant breeding with genomic selection: gain per unit time and cost. Crop Sci 50:1681–1690

    Article  Google Scholar 

  19. Endelman J (2011) Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4:250–255

    Article  Google Scholar 

  20. Wickham H (2009) ggplot2: elegant graphics for data analysis. Springer, New York

    Book  Google Scholar 

  21. Lorenz A, Chao S, Asoro F, Heffner E, Hayashi T, Iwata H, Smith K, Sorrells M, Jannink J-L (2011) Genomic selection in plant breeding: knowledge and prospects. In: Sparks DL (ed) Advances in agronomy. Academic, San Diego, CA, pp 77–123

    Google Scholar 

Download references

Acknowledgments

Funding for the data used in this chapter came from a US Department of Agriculture, National Institute of Food and Agriculture agreement, No. 2006-55606-16722 “Barley Coordinated Agricultural Project: Leveraging Genomics, Genetics, and Breeding for Gene Discovery and Barley Improvement.” Mark Newell’s contributed work was funded by “The Samuel Roberts Noble Foundation.”

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jean-Luc Jannink .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this protocol

Cite this protocol

Newell, M.A., Jannink, JL. (2014). Genomic Selection in Plant Breeding. In: Fleury, D., Whitford, R. (eds) Crop Breeding. Methods in Molecular Biology, vol 1145. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0446-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-0446-4_10

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0445-7

  • Online ISBN: 978-1-4939-0446-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics