Overview
    Standard QTL mapping is introduced as an extension of mixed model analysis of single traits in single trials. Effectively, on a genomic grid genetic covariates are fitted that represent contrasts in unobserved QTL genotype probabilities given marker information. The calculation of these genetic covariates will be explained for various types of populations: inbreeders, outbreeders and association panels. After mixed model QTL analysis for single traits in single trials, extensions will be described for multiple trials and multiple traits, where the modeling of the variance-covariance structure for trials and traits is crucial.

Learning Objectives
    By the end of the course you should be able to:

• Perform a QTL analysis for a wide array of single populations, for single and multiple environments, and single and multiple traits
  
• Use various inference procedures for assessing QTL evidence
  
• Report QTL locations and effects
  

Instruction methods
    Theory will be presented in the form of lectures. Supervised practicals will allow attendants to become familiar with the details of the actions required to perform a QTL analysis in GenStat using Windows’ dialogues and in R using source code. These practicals will also serve to learn how to interpret QTL mixed model analysis output.

Schedule

Some selected papers

• Fred A. van Eeuwijk, Marco C.A.M. Bink, Karine Chenu and Scott C. Chapman (2010) Detection and use of QTL for complex traits in multiple environments – Current Opinion in Plant Biology 13:193-205.
  
• Van Eeuwijk FA, Boer MP, et al. (2010) Mixed model approaches for the identification of QTLs within a maize hybrid breeding program Theor Appl Genet 120: 429-440.
  
• Mark Cooper - Fred A van Eeuwijk - Graeme L Hammer - Dean W Podlich (2009) Modeling QTL for complex traits: detection and context for plant breeding Current Opinion in Plant Biology, 12, 231-240.
  
• Malosetti, M., Ribaut, J. M., Vargas, M., Crossa, J., & Van Eeuwijk, F. A. (2008). A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (zea mays L.). Euphytica, 161(1-2), 241-257.
  
• Paulo M.-J., Boer MP, Huang X, Koornneef M., and FA van Eeuwijk (2008) A mixed model QTL-analysis for a complex cross population consisting of a half diallel of two-way hybrids in Arabidopsis thaliana: analysis of a simulated data. Euphytica 161:107-114.
  
• Boer MP, Wright D, Feng L, Podlich D, Luo L, Cooper M., and FA van Eeuwijk (2007) A Mixed-Model Quantitative Trait Loci (QTL) Analysis for Multiple-Environment Trial Data Using Environmental Covariables for QTL-by-Environment Interactions, With an Example in Maize. Genetics 177: 1801-1813.
  
• Malosetti, M., Van Der Linden, C. G., Vosman, B., & Van Eeuwijk, F. A. (2007). A mixed-model approach to association mapping using pedigree information with an illustration of resistance to phytophthora infestans in potato. Genetics, 175(2), 879-889.
  
• Hammer G, Cooper M, Tardieu F, Welch S, Walsh B, van Eeuwijk FA, Chapman S, Podlich D, (2006) Models for navigating biological complexity in breeding improved crop plants. Trends in Plant Science 11 (12): 1360-1385.
  
• Fred A. van Eeuwijk, Marcos Malosetti, Xinyou Yin, Paul C. Struik and Piet Stam. 2005. Statistical models for genotype by environment data; From conventional ANOVA models to eco-physiological QTL models. Australian Journal of Agricultural Research 56: 883-894.
  
• Malosetti, M., Voltas, J., Romagosa, I., Ullrich, S. E., & Eeuwijk, F. A. V. (2004). Mixed models including environmental covariables for studying QTL by environment interaction. Euphytica, 137(1), 139-145.
  
• A. T. W. Kraakman, R. E. Niks, P. M. M. M. Van den Berg, P. Stam & F. A. Van Eeuwijk 2004 Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics: 138: 435-446.