Module I: Human Genetics and Genomics
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.
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.