Advanced Population Genetics
| ECTS (hours) | 2.5 |
| Code | HMBE2221 |
| Organization | Yannis Michalakis (yannis.michalakis@ird.fr) with the participation of T. Lenormand and 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 with elementary algebra that 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 that 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 |
| Code | HMBE225 |
| Organization | Céline Devaux (celine.devaux@umontpellier.fr) |
he 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) 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 sessions are as follows:
- Introduction to multivariate statistics and description of some classification methods
- Detailed description of principal component analysis
- Detailed description of correspondence analysis
- Brief recap of descriptive statistics and hypotheses tests
- Explicit link between multivariate and univariate analyses, using 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 |
| Level | HMBE222 |
| Oranization | Renaud Vitalis (renaud.vitalis@supagro.inra.fr) with the participation of R. Leblois |
The objectives of this course are threefold: (i) to remind students of 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.
The sessions are as follows:
- Classical inference in population genetics. F-statistics provide a useful description of genetic structure at several levels (individuals, populations, etc.). The definition of F-statistics as well as the statistical framework used to develop estimates of these parameters will be examined, and then some application examples for the inference of sex-specific demography will be provided.
- Inference of dispersal in isolation-by-distance models. Limited dispersal results in a correlation between genetic and geographic distances. How dispersal characteristics can be inferred from the analysis of genetic polymorphisms will be shown.
- Maximum-likelihood and Bayesian inference in population genetics. Modern techniques of inference in population genetics are based upon maximum-likelihood and Bayesian methods. The principles of these methods will be shown, and some application examples with the software package STRUCTURE will be provided.
- 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. The basics of coalescent theory will be developed and some application examples for the inference of population size changes will be provided.
- 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. How this information can be used to detect genomic signatures of past or on-going selection will be shown.
Hot Topics in Ecology
| ECTS (hours) | 2.5 |
| Code | HMBE2A1 |
| Oranization | Philippe JARNE (philippe.jarne@cefe.cnrs.fr) |
Format:
Each class section will cover a different topic. Each year, Philippe will suggest a number of topics, but the list will be neither binding nor exhaustive: any topic that relates to evolution is fair game. Each class session, a group of two or three people will be responsible for presenting the topic they have chosen. Each person should participate in presentations in two of the sessions. Philippe will give each group a small selection of recent papers that they will use to begin to explore the topic, or the groups will themselves propose pertinent papers. Among these, the group will distribute (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. The presentation format will be defined by the group, keeping in mind that it should open discussions. Grades will be based on Philippe’s evaluation of how students perform in the presentations, in generating discussion and in overall participation in discussions.
A sample of topics treated in previous runs of the course:
Transgenerational transmission of heritable epigenetic variation; human evolution; 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; RNA world; life in extreme environments; life on other planets?; astrobiology; 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; sexual conflict; synthetic biology; environmental DNA and applications in ecology; fast evolution and environmental change ; parallel evolution ; current species extinction ; ecological correlates of species diversification ; what’s new on the evolution of sex ; CRISPRcas in ecology and evolution.
Modeling in Ecology and Evolution
| ECTS (hours) | 2.5 |
| Code | HMBE224 |
| Organization | Guillaume Martin (Guillaume.Martin@umontpellier.fr) |
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 initiation is to show that modelling is by no means more inaccessible than other techniques in biology. The goal is to give students a feel of how a model is constructed, to be able to spot the key assumptions behind a result, and to test their validity. The course will seek to familiarize the students with several basic modelling techniques (stochastic or deterministic dynamical systems and their analysis) and tools (mathematical softwares, computer simulation).
The course will illustrate by practical work the different phases of modelling, from the formalization of the biological hypotheses to the exploitation of results
The course will be based on an initial problem, either purely hypothetical scenario or based on a given published dataset, the students will work by groups of 2 -3 and will build up the model to describe the situation at hand, analyze it mathematically and simulate it. They will work on computers and use mathematical softwares for analysis and simulations (most likely Mathematica).
As the groups will advance on their own project, we will progressively introduce tools for the study of dynamical systems (individual based simulation, stochastic models, deterministic models and their analysis).
The last sessions will be dedicated to summarize the tools and individual exercises.
Reading Papers and Seminars
| ECTS (hours) | 2 |
| Code | HMBE2A2 |
| Oranization | Oliver Kaltz (oliver.kaltz@umontpellier.fr) |
– reading papers in genetics and statistics.
In this course, we will simulate several important steps in the dissemination of scientific results. At the beginning of the course, each student will be given one article, for which this student will write a summary, present a poster and give a short oral presentation. The challenge is to get to know the paper as if it were the student’s own. This involves reading of relevant literature, but most importantly understanding (or questioning!) each and every detail of the article.
- one seminar per week (Montpellier Seminar in Evolution and Ecology = SEEM – Fridays 11h30, all seminars in english are compulsory)
Evolutionary Applications
| ECTS (hours) | 1 |
| Code | HMBE2A3 |
| Oranization | Yannis Michalakis (yannis.michalakis@ird.fr) |
The course discusses cases where evolutionary biology based implementations provide invaluable insight in applied issues such as vector control, conservation biology or fish stock management.
Grant Proposal Writing
| ECTS (hours) | 1 |
| Code | HMBE2A4 |
| Oranization | Thomas Lenormand (thomas.lenormand@cefe.cnrs.fr) & Yannis Michalakis (yannis.michalakis@ird.fr) |
This one week course will be offered at least in winter 2020 (and in following years if independent funding can be secured). It will be organized as a retreat during which students will write in small groups grant proposals on Evolutionary Biology topics.