Evolutionary Quantitative Genetics

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

The goal of this module is to provide students with a sufficient foundation in quantitative genetics to (i) understand the classical foundations of the discipline, work with key quantities (genetic variances, heritabilities, genetic correlations), and apply statistical techniques for estimating these parameters; (ii) understand the power of this technique for formulating and understanding fundamental or applied evolutionary problems (agricultural breeding), and (iii) understand how this formalization of inheritance relates to the classical Mendelian view.

1) Have a thorough understanding of the basic concepts: heritabilities, additive and dominance genetic variances, selection gradients, response to selection, and covariances among related individuals

2) Understand QTL and genome-wide association study (GWAS) techniques 2) Know how to develop a protocol for estimating variance components and heritabilities in an experimental design

3) Be able 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 to understand articles that do so.

A basic understanding of Mendelian genetics and statistics is required, and a basic understanding of quantitative genetics (M1 module) is helpful but not strictly necessary (a refresher session will be provided during the first class for Doctoral School students who are taking this module as part of a joint program).

Comprehensive ongoing assessment: 100%