Applying association mapping and genomic selection to the dissection of key traits in elite European wheat

Alison Bentley, Marco Scutari, Nick Gosman, Sebastien Faure, Felicity Bedford, Phil Howell, James Cockram, Gemma Rose, Toby Barber, Jose Irigoyen, Richard Horsnell, Claire Pumfrey, Emma Winnie, Johannes Schacht, Katia Beauchêne, Sebastien Praud, Andy Greenland, David Balding, Ian Mackay*

*Corresponding author for this work

Research output: Contribution to journalArticle

52 Citations (Scopus)

Abstract

KEY MESSAGE: We show the application of association mapping and genomic selection for key breeding targets using a large panel of elite winter wheat varieties and a large volume of agronomic data. The heightening urgency to increase wheat production in line with the needs of a growing population, and in the face of climatic uncertainty, mean new approaches, including association mapping (AM) and genomic selection (GS) need to be validated and applied in wheat breeding. Key adaptive responses are the cornerstone of regional breeding. There is evidence that new ideotypes for long-standing traits such as flowering time may be required. In order to detect targets for future marker-assisted improvement and validate the practical application of GS for wheat breeding we genotyped 376 elite wheat varieties with 3,046 DArT, single nucleotide polymorphism and gene markers and measured seven traits in replicated yield trials over 2 years in France, Germany and the UK. The scale of the phenotyping exceeds the breadth of previous AM and GS studies in these key economic wheat production regions of Northern Europe. Mixed-linear modelling (MLM) detected significant marker-trait associations across and within regions. Genomic prediction using elastic net gave low to high prediction accuracies depending on the trait, and could be experimentally increased by modifying the constituents of the training population (TP). We also tested the use of differentially penalised regression to integrate candidate gene and genome-wide markers to predict traits, demonstrating the validity and simplicity of this approach. Overall, our results suggest that whilst AM offers potential for application in both research and breeding, GS represents an exciting opportunity to select key traits, and that optimisation of the TP is crucial to its successful implementation.

Original languageEnglish
Pages (from-to)2619-33
Number of pages15
JournalTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Volume127
Issue number12
Early online date2 Oct 2014
DOIs
Publication statusPrint publication - Dec 2014
Externally publishedYes

Bibliographical note

© Springer-Verlag Berlin Heidelberg 2014

Keywords

  • Breeding
  • Chromosome Mapping
  • France
  • Genetic Association Studies
  • Genetic Markers
  • Genetics, Population
  • Genomics/methods
  • Genotype
  • Germany
  • Linkage Disequilibrium
  • Models, Genetic
  • Models, Statistical
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci
  • Triticum/genetics
  • United Kingdom

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    Bentley, A., Scutari, M., Gosman, N., Faure, S., Bedford, F., Howell, P., Cockram, J., Rose, G., Barber, T., Irigoyen, J., Horsnell, R., Pumfrey, C., Winnie, E., Schacht, J., Beauchêne, K., Praud, S., Greenland, A., Balding, D., & Mackay, I. (2014). Applying association mapping and genomic selection to the dissection of key traits in elite European wheat. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 127(12), 2619-33. https://doi.org/10.1007/s00122-014-2403-y