ADVANCED AND QUANTITATIVE GENETICS
- Scheda dell'insegnamento
- Obiettivi formativi
- Metodi didattici
- Verifica dell'apprendimento
- Altre informazioni
The purpose of the Module of Quantitative Genetics, in the frame of the integrated course in Advanced and Quantitative Genetics, is to provide the students with a detailed knowledge in the field of Quantitative Genetics, discussing the related topics from the origins to the most recent applications in this field of the new molecular technologies. Since Quantitative Genetics relies heavily on statistical techniques, many biometric approaches to evaluation of numerical data will be presented. This will allow the student to understand both the potential underlying the identification of new genes and the pitfalls due to not-so-well-understood genetics and statistical basic theory. The overall aim of this module is to provide knowledge and abilities needed for the understanding of the genetic mechanisms underlying the expression of metric traits.
The Course will make the student familiar with basic and advanced issues in Quantitative Genetics. Since its beginning, this branch of Genetics developed buttressed by statistical and biometrical aspects. It is thus necessary to provide the student with interlaced genetic and statistical knowledge. At the end of the module, the student will have the knowledge necessary to understand modern quantitative genetics, both in its theoretical and molecular aspects, with special stress on Genome Wide Analysis and Association Mapping.
At the end of the course, the Student will be able to plan experiments in the field of Quantitative Genetics and will acquire a modern understanding of the relationship gene(s)/environment(s) so as to correctly evaluate the advances in the evolutionary, biomedical and biotechnological areas and suggest solutions to related problems.
It is recommended to start the classes with a strong background in Genetics and Molecular Biology and some basics of Statistics.
Quantitative traits (QT): the first experiments, the polygenic hypothesis for quantitative inheritance. Estimating the number of loci controlling a QT. Genetic and environmental variance: the concepts of broad-sense and narrow-sense heritability, the breeder’s formula. Molecular markers and their use in identifying quantitative traits loci (QTL). Power and pitfalls of Genome Wide Analysis studies. SNPs and association mapping.
Random variables and a statistical tests. The model of Analysis of Variance (ANOVA). One-Way ANOVA: the completely randomised and the randomised block designs. Two-Ways ANOVA: the factorial design. Linear regression models, parameters estimate in linear, multiple and curvilinear regression. The use of regression for QTL identification. The χ2 test and its use in association mapping.
Normal classes will be held. In some occasions, statistical analysis of numerical examples will be done under the teacher’s guidance.
At the end of the course, the student will undergo a written examination. S/he will be presented with two questions about the “Quantitative genetics” part and two numerical exercises about the “Statistical methodologies” part. An open answer is required for the two questions, aimed at verifying the general knowledge in quantitative genetics and at using a correct scientific language. The two exercises have to be solved in order to verify the knowledge of the logic and methodological tools required for a correct evaluation of experimental data. The allotted time or the exam is 3 hours and the exam will be considered passed equal or over the 18/30 mark.
At the beginning of the course, the teacher will provide the students with a list of useful texts. If needed, the teacher will also provide short notes on selected issues. Presence to classes is strongly suggested.
The teacher will answer questions regarding the topics discussed in the course following an arrangement either by phone or e-mail. Students are kindly required not to ask bureaucratic and/or administrative question, if not really urgent. E-mail address: firstname.lastname@example.org
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