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Quantitative Evolutionary Genetics

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M2_E36_QuantitativeGenetics_schedule2021_2022

Biology Master, ENS
Bio-M2_E36 | Quantitative Evolutionary Genetics
Year and Semester : M2 | S1
Duration : 60 hours
First and last day of class : December 6th-17th, 2021
Hours : 9:00-12:00 | 14:00-17:00
Maximum class size : 20 students
This course is open to external students. Contact : H. Teotónio

Coordination

Henrique Teotónio, ENS
Pierre de Villemereuil, EPHE
Alain Charcosset, INRAE

Credits

6 ECTS

Keywords

Heritability and resemblance between relatives | Components of genetic and phenotypic variances | Selection differentials | Intensities and gradients | G-matrix | M-matrix | gamma-matrix | Polygenic and infinitesimal models | Animal model.

Course prerequisites

Students will have the background in population genetics and quantitative genetics, and a keen interest in the mathematical foundations of evolutionary theory. Students will further have a basic understanding of statistical inference and computer programming.

Course objectives and description

Aims : This is an advanced graduate course in quantitative genetics as applied to understand the evolution of complex traits, those traits whose expression is conditional on environment and on many genes. The students will learn how to partition and estimate the several components of phenotypic and genetic (co)variation, as well as define and estimate (multivariate) selection gradients. We will discuss the Robertson-Price identity and Fisher’s fundamental theory of natural selection.
Specific topics will include understanding natural selection and genetic drift in experimental and natural populations, evolution of phenotypic plasticity and robustness, inbreeding and outbreeding depression, genomic prediction of complex trait values (including humans) and genomic selection, among others.
Organisation : In the mornings lectures and seminars will be given by the coordinators and invited faculty, in the afternoons there will be computer projects on data analysis and numerical simulations of complex trait evolution.

Assessment

Students will be evaluated based on their attendance and active participation in the lectures and seminars (accounting for 30% of the final grade), completion of computer projects (30%) and a written exam (60%).

Course material

Lecture and computer practical handouts will be provided to the students.

Suggested readings in relation with the module content

• Barton, N. H. and P. D. Keightley (2002). "Understanding quantitative genetic variation." Nat Rev Genet 3(1) : 11-21.
• Hill, W. G. (2010). "Understanding and using quantitative genetic variation." Philos Trans R Soc Lond B Biol Sci 365(1537) : 73-85.
• Lynch, M. and B. Walsh (1998). Genetics and Analysis of Quantitative Traits. Sunderland, Sinauer Associates, Inc.
• Roff, D. (1997). Evolutionary Quantitative Genetics. New York, Chapman & Hall.
• Walsh, B. and M. Lynch (2018). Evolution and Selection of Quantitative Traits. Sunderland, Sinauer Associates, Inc.