84933 - Human Genomics and Biostatistics

Learning outcomes

The aim of this course is to provide students with a general understanding of the principles and concepts of human genetics. Specific topics are: fundamentals of gene structure, human genome organization and expression; genetic variation and its functional and pathogenic consequences; molecular basis of single gene disorders and complex diseases; basic principles of DNA technologies and genetic testing. In addition students will get familiar with basic statistical methods for the analysis of biological data

Course contents

Module 1. Human genomics

• Introduction to human genetics: from Mendelian transmission to genomic medicine
• Fundamentals of gene structure, genome organization and expression, principles of gene regulation and epigenetics.
• Genetic variation: origin of DNA variation, types of genetic variants, small scale and structural variation, functional genetic variationand its pathogenic consequences. Single gene disorders: inheritance patterns, phenotype variability
• Allelic frequences in populations: Hardy Weinberg equilibrium and its applications; how allelic frequencies change.
• Identification of human disease genes. Linkage analysis and lod-score method. Mapping and identification of genetic susceptibility to complex disease. The principles of genetic association and linkage disequilibirum mapping; genome-wide association studies.
• Next generation sequencing and its applications Elements of molecular genetic testing.

Module 2. Biostatistics

• Descriptive statistics
• Probability
• Distributions
• Populations, samples, standard errors, and confidence intervals
• Statistical inference: Hypothesis testing and P-value
• Correlation and linear regression
• Non-parametric distributions
• Elements of epidemiology
• Genetic and genomic databases

Readings/Bibliography

• Genetics and Genomics in Medicine, by Tom Strachan, Judith Goodship & Patrick Chinnery (Garland Science).
• Human Molecular Genetics. Tom Strachan, Andrew Read. Fifth Edition (CRC Press, Garland Science) 2019.
  

• The analysis of biological data, by Michael Whitlock and Dolph Schluter.

Teaching methods

The course consists of 9 CFU :

Module 1: 5 CFU of frontal lectures and 1 CFU of laboratory practicals

Module 2: 1 CFU of frontal lectures and 2 CFU of computer classroom exercises

Assessment methods

Written final exam

Teaching tools

Course materals (slide presentations and exercises) will be available on the Moodle web site

https://iol.unibo.it/
Access is restricted to Bologna Unversity students enrolled in the course

Office hours

See the website of Elena Maestrini

See the website of Elena Bacchelli