Course information

Course title
Introduction to Evolutionary Quantitative Genetics
University / Organization
Transmitting Science
Els Hostalets de Pierola, Barcelona
Academic level
Both Msc and PhD
Course director
Course lecturer(s)
Dr. Erik Postma (University of Exeter, United Kingdom) Dr. Jesús Martínez-Padilla (Universidad de Oviedo, Spain)
Course aim
The rate and direction of adaptive evolution critically depends on the additive genetic variances and covariances underlying the traits subject to selection. As a consequence, understanding the genetic basis of complex morphological, life-history, physiological, ornamental and behavioural traits is crucial if we are to understand their evolutionary potential, and the evolutionary process in general. Quantitative genetics uses the phenotypic resemblance among related individuals to infer the role of genes and the environment in shaping phenotypic variation. Depending on the species, we can use data obtained from breeding experiments in captivity (e.g. insects), or from individual-based monitoring programs in the wild (e.g. birds and mammals). Especially the latter has benefited greatly from the application of animal model methodology, originally developed in animal breeding to identify individuals of high genetic merit. By simultaneously using the resemblance among all individuals in the pedigree, these methods provide more precise and accurate estimates of genetic and non-genetic variance components (heritabilities and genetic correlations). Furthermore, they allow for the estimation of individual-level genetic effects (breeding values), and thereby the inference of evolution. In this course we will cover everything from basic quantitative genetic theory and statistics to advanced mixed model-based approaches. You will learn how to estimate genetic variances and covariances in wild and captive populations, and how to test for evolutionary change. Along the way, you will be exposed to the main software packages, and the R packages MCMCglmm and ASReml-R in particular, and you will learn about their strengths and weaknesses. You are strongly encouraged to bring your own data (if you have it), which you will be able to work on during the course and which will allow you to put the theory into practice.
Course contents / programme
Monday, April 9th, 2018. Introduction into quantitative genetics. Morning: Quantitative genetic theory. From single loci with two alleles to the infinitesimal model. Additive and non-additive genetic variance. Quantifying relatedness and inbreeding. Heritability and genetic correlations. Evolvability. Basic statistics. Correlation. Regression. ANOVA. Estimating heritabilities, Part I. Parent-offspring regression. Fullsib/halfsib analysis. Afternoon: Practical. Simulate data on parents and offspring. Estimate heritabilities using parent-offspring regression and ANOVA. Tuesday, April 10th, 2018. Mixed models, pedigrees and animal models. Morning: Advanced statistics. Mixed models. Estimating heritabilities, Part II. Mixed model analysis of halfsib data. Practical. Analyse simulated data with mixed model (continuation of Monday afternoon). Afternoon: Pedigree reconstruction. Observational and marker-based. Pedigree errors. Software. Descriptive statistics. Visualisation. Analysis of own (or simulated) data. Wednesday, April 11th, 2018. The animal model. Morning: Estimating heritabilities, Part III. The animal model. Software. Practical. Animal model tutorials ASReml-R and/or MCMCglmm. Afternoon: Analysis of own (or simulated) data. Thursday, April 12th, 2018. Advanced topics. Morning: Multivariate models. G matrix estimation. Genotype-environment interactions. Intersexual genetic correlations. Random regression. Breeding values. Prediction. Inferring evolution. Afternoon: Analysis of own (or simulated) data. Friday, April 13th, 2018. Morning: Presentations. Literature Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, Prantice Hall, Harlow, United Kingdom, 4th Edition. Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits, Sinauer, Sunderland, MA, United States. Kruuk LEB (2004) Estimating genetic parameters in natural populations using the ‘animal model’. Phil Trans R Soc Lond B, 359: 873-890. Kruuk LEB, Slate J, Wilson AJ (2008) New answers for old questions: The evolutionary quantitative genetics of wild animal populations. Annu Rev Ecol Evol Syst, 39: 525-548. Wilson AJ, Réale D, Clements MN, Morrissey MM, Postma E, Walling CA, Kruuk LEB, Nussey DH (2010) An ecologist’s guide to the animal model. J Anim Ecol, 79: 13-26. Charmantier A, Garant D, Kruuk LEB (2014) Quantitative genetics in the wild, Oxford University Press, Oxford, United Kingdom.
Required Knowledge and preparation
Teaching methods
Course type
Consecutive days
Online course
Duration (net days)
April 9th-13th, 2018
Course fee
Direct e-mail to register
Paper submission required?
Logo of institution
front approval