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. Lab Practicals

Module 3. 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

Module 2: 1 CFU 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 Marta Viggiano

See the website of Elena Bacchelli