Evolutionary quantitative genetics

Quantitative genetics is a discipline that emerged in the early 20th century to understand the inheritance of continuous traits, i.e., the majority of traits of agronomic interest (yield, etc.) or evolutionary interest (life history traits, morphology). It is therefore an essential tool for understanding, modeling, and predicting natural or artificial selection and the evolution of natural systems or cultivated plants/animals. Its relevance is more topical than ever at the beginning of the 21st century, with the emergence of genomics (a factor of scientific progress, provided that not all evolutionary problems are reduced to the fiction of a few Mendelian alleles with strong effects) and the resurgence of alternative models of heredity (epigenetics) that go beyond the sequence-centered vision inherited from classical molecular biology.

The aim of the module is to provide sufficient knowledge of quantitative genetics to (i) understand the classical foundations of the discipline, manipulate key quantities (genetic variances, heritabilities, genetic correlations) and the statistical techniques used to estimate these parameters (ii) understand the power of this technique for posing and understanding fundamental or applied evolutionary problems (agronomic improvement) (iii) understand how this formalization of heredity relates to the classical Mendelian view.

1) Have a thorough understanding of basic concepts: heritability, additive/dominance genetic variance, selection gradients, response to selection, covariances between relatives.

2) Understand QTL and genetic association (GWAS) techniques 2) Know how to construct a protocol for estimating variance components and heritabilities in an experimental design

3) Know how to analyze data from controlled crossbreeding using linear models and data from natural populations using animal models.

4) Be able to understand how quantitative genetics can be used to address evolutionary questions, and understand articles that do so.

A foundation in Mendelian genetics and statistics is required, and a foundation in quantitative genetics (M1 module) is useful but not strictly necessary (refresher course during the first session for doctoral students with whom this module is shared).

Continuous assessment: 100%