title: Applying association mapping and genomic selection to the dissection of key traits in elite European wheat.
abstract: 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.
authors.affiliation: The John Bingham Laboratory, NIAB, Huntingdon Road, Cambridge, CB3 0LE, UK, alison.bentley@niab.com.
authors.forename: Alison R
authors.initials: AR
authors.lastname: Bentley
authors.forename: Marco
authors.initials: M
authors.lastname: Scutari
authors.forename: Nicolas
authors.initials: N
authors.lastname: Gosman
authors.forename: Sebastien
authors.initials: S
authors.lastname: Faure
authors.forename: Felicity
authors.initials: F
authors.lastname: Bedford
authors.forename: Phil
authors.initials: P
authors.lastname: Howell
authors.forename: James
authors.initials: J
authors.lastname: Cockram
authors.forename: Gemma A
authors.initials: GA
authors.lastname: Rose
authors.forename: Tobias
authors.initials: T
authors.lastname: Barber
authors.forename: Jose
authors.initials: J
authors.lastname: Irigoyen
authors.forename: Richard
authors.initials: R
authors.lastname: Horsnell
authors.forename: Claire
authors.initials: C
authors.lastname: Pumfrey
authors.forename: Emma
authors.initials: E
authors.lastname: Winnie
authors.forename: Johannes
authors.initials: J
authors.lastname: Schacht
authors.forename: Katia
authors.initials: K
authors.lastname: Beauchêne
authors.forename: Sebastien
authors.initials: S
authors.lastname: Praud
authors.forename: Andy
authors.initials: A
authors.lastname: Greenland
authors.forename: David
authors.initials: D
authors.lastname: Balding
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Mackay
mesh_terms: D001947:Breeding; D002874:Chromosome Mapping; D005602:France; D056726:Genetic Association Studies; D005819:Genetic Markers; D005828:Genetics, Population; D023281:Genomics / Q000379:methods*; D005838:Genotype; D005858:Germany; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D015233:Models, Statistical; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D014908:Triticum / Q000235:genetics*; D006113:United Kingdom
chemical_list: D005819:Genetic Markers