Advanced Population Genetics
ECTS (hours) | 2.5 (24) |
Level | M1 and higher |
Teachers | Y. Michalakis, T. Lenormand & G. Martin |
The objective of this course is to provide the theoretical background for understanding, and potentially being able to use and apply the principles of how selection will affect the evolution of populations. Y. Michalakis describes the basics of selection theory and shows how with elementary algebra it is possible to derive some fundamental results in Population Genetics, such as Fisher’s Fundamental Theorem. He also gives an introduction to mutation-selection balance and two-locus theory. The latter topics are put in perspective in the courses by T. Lenormand on the evolution of sexual reproduction, migration and local adaptation. T. Lenormand also presents the theory which allows understanding the dynamics of adaptation. G. Martin’s courses explain how stochastic effects interact with selection to influence the fate of adaptive mutations.
Advanced Statistics
ECTS (hours) | 2.5 (24) |
Level | |
Teachers | C. Devaux |
The course scans through both multivariate and univariate (linear models) analyses; and aims at providing students with (i) solid mathematical and theoretical background, (ii) insights into protocol and model building and (iii) and knowledge for accurate interpretation of data. At the end of the course, students are well aware of many classical models in ecology and evolution and some estimation methods, and can thus autonomously build their own experimental designs and analyze their own data. The eight sessions are as follows:
- introduction to multivariate statistics and description of some classification methods
- detailed description of principal component analysis
- detailed description correspondence analysis
- brief recap of descriptive statistics and hypotheses tests
- explicit link between multivariate and univariate analyses, using the multiple regression
- building simple ANOVAs and make a posteriori validation tests and group differences
- building ANOVAs with complications, such as random factors and non-independence
- insights into model selection, and discussion of students own data and models
Genetic Data Analysis
ECTS (hours) | 2.5 (24) |
Level | M1 and higher |
Teachers | R. Vitalis & R. Leblois |
The objectives of this course are threefold (i) to recall the theoretical bases of some essential concepts of population genetics theory; (ii) to detail some “classical” inference methods (e.g., F-statistics) and more “modern” approaches (based, e.g., on coalescent theory); (iii) to show how demographic history may be inferred from the analysis of genetic polymorphisms.
- Day 1: Classical inference in population genetics. F-statistics provide a useful description of genetic structure at several levels (individuals, populations, etc.). We will examine the definition of F-statistics as well as the statistical framework used to develop estimates of these parameters, and then provide some application examples for the inference of sex-specific demography.
- Day 2: Inference of dispersal in isolation-by-distance models. Limited dispersal results in a correlation between genetic and geographic distances. We will show how dispersal characteristics can be inferred from the analysis of genetic polymorphisms.
- Day 3: Maximum-likelihood and Bayesian inference in population genetics. Modern techniques of inference in population genetics are based upon maximum-likelihood and Bayesian methods. We will show the principles of these methods, and provide some application examples with the software package STRUCTURE.
- Day 4: Coalescent theory. Coalescent theory provides a conceptual framework for the study of genetic variation in populations, and is the source of essential tools for making inference about population evolutionary history. We will develop the basics of coalescent theory and provide some application examples for the inference of population size changes.
- Day 5: Measuring selection from gene frequency data. The recent advent of high throughput sequencing and genotyping technologies makes it possible to produce, easily and cost-effectively, large amounts of relevant information for the characterization of population genetic diversity, even for species for which a detailed knowledge of the genome structure is not yet available. We will show how this information can used to detect genomic signatures of past or on-going selection.
Hot Topics in Ecology
ECTS (hours) | 2.5 (24) |
Level | M1 and higher |
Teachers | D. McKey |
Format:
Each class session, a group of three people (exceptionally two) will be responsible for that session’s topic. (Each person should participate in leading two of the sessions.) I will give each group a small selection of recent papers that they will use to begin to explore the topic (or the groups will find these themselves). Among these (or other papers the group finds during its exploration), the group will suggest (one week before the class session) one-two papers that everyone should read before class. The group will be responsible for presenting the topic to the rest of the class and leading discussion of it. The group presentation should explain why the topic is interesting and present the state of the art, outlining points of controversy and defining big open questions.
Topics treated in previous runs of the course:
- Transgenerational transmission of heritable epigenetic variation
- Cultural evolution
- Cultural group selection
- Comparative studies of agriculture in protists, animals and humans
- Darwinian agriculture: what can artificial selection do that natural selection cannot?
- Species diversity and ecosystem functioning: what relationships?
- Spatial self-organization in ecosystems: processes and consequences
- Origin of life
- Life in extreme environments
- Life on other planets?
- Pleistocene overkill, ecological anachronisms and Pleistocene Park
- Evolution within individuals: diplontic selection; cancer and evolution
- The human microbiome: microbial ecology of the human gut
- Neutral theory of biodiversity in community ecology: Hubbell 10 years onwards
- Sexual conflict
Topics for the current year’s run are still to be defined, and students are welcome to play a very active role in this.
Modeling in Ecology and Evolution
ECTS (hours) | 2.5 (24) |
Level | M1 and higher |
Teachers | S. Maurice |
Modelling is a methodology that is frequently used in biological sciences nowadays, in particular in ecological and evolutionary studies. However, models usually frighten students. The aim of this course is to show that modelling is by no means inaccessible. Hence, we aim to familiarize the students with several modelling techniques, so that they can use them in their future work and such that they can better understand theoretical papers.
Instead of presenting an exhaustive panel of techniques, we chose to have the students work by themselves on some examples. The course will thus illustrate by practical work the different phases of modelling, since the formalisation of the biological hypotheses to the exploitation of results.
The students will work, alone or by two, on computers. We will tackle two problems, one in ecology and one in evolutionary biology. These problems will allow us to introduce several kinds of modelling and to use several programming techniques under R. The work plan is as follows:
- Global introduction (3h):
- The different kinds of models
- How to choose between several models?
- How to confront models to data?
- Sex-ratio evolution (12h):
- formalizing the question
- game theory approach (derivative calculus, equation solving…)
- simulation of data (random numbers drawing) and test by maximum-likelihood
- Sex-ratio evolution with an explicit genetic determination of sex-ratio (equation iteration)
- Metapopulation dynamics (10h):
- formalizing the question
- deterministic approach (differential equations: analytic resolution and numerical resolution, stability of steady states…)
- stochastic approach (linear algebra, Monte Carlo simulations)
Writing scientific papers in English and French as a foreign language
ECTS (hours) | 1 |
Level | M1 and higher |
Teachers | M. Hochberg |
“What you need to know to be effective in writing and publishing your work”
The practical work will provide training in several important ways, including scientific expression, manuscript structure, and the process of writing manuscripts. Students will do either independent or team-based assignments. I will start each day with between 30 minutes and 1 hour of lecture.
- Day 1: Key parts of a manuscript. Attracting potential readers to one’s work means being able to effectively write titles, abstracts and choose keywords that will catch the attention of both specialists and the wider scientific community. Students will be given short manuscripts to read, and will be asked to write titles, an abstract, and keywords.
- Day 2: Understand manuscript structure. Part of the strategy for writing manuscripts is to understand what makes a written manuscript work. In this project, the students will be given a manuscript that has been cut into pieces, asked to reassemble this “puzzle”, and explain their logic.
- Day 3: Scientific expression. Write a paper. The students will be confronted with a figure and legend, and be asked to write a short manuscript about the contents.