Genomics and Epigenetics of the Brain

Course Number: 02-319

This course will provide an introduction to genomics, epigenetics, and their application to problems in neuroscience. The rapid advances in single cell sequencing and other genomic technologies are revolutionizing how neuroscience research is conducted, providing tools to study how different cell types in the brain produce behavior and contribute to neurological disorders.

Analyzing these powerful new datasets requires a foundation in molecular neuroscience as well as key computational biology techniques. In this course, we will cover the biology of epigenetics, how proteins sitting on DNA orchestrate the regulation of genes. In parallel, programming assignments and a project focusing on the analysis of a primary genomic dataset will teach principles of computational biology and their applications to neuroscience. The course material will also serve to demonstrate important concepts in neuroscience, including the diversity of neural cell types, neural plasticity, the role that epigenetics plays in behavior, and how the brain is influenced by neurological and psychiatric disorders. Although the course focuses on neuroscience, the material is accessible and applicable to a wide range of topics in biology.

Academic Year: 2026-2027
Semester(s): Fall
Units: 9
Prerequisite(s): (03151 or 03121) and (03220 or 03221) and (15110 or 02201 or 15112 or 15121)
Location(s): Pittsburgh

Format

Learning Objectives

1.  be able to describe the technological advances in genomics, different classes of genomic experiments researchers conduct, and how genomics has contributed towards our understanding of biology;
2. critically evaluate primary literature that uses genomic technology to understand the brain;
3. distinguish whether genomic technology is being used to test for specific hypotheses, screen for candidate molecules, provide an annotation, or learn the basic rules underlying a biological system;
4. explain the role that epigenetics plays in gene regulation and inheritance;
5. conduct a computational analysis of genomic data, from raw output to biological conclusions, using existing genomic analysis tools at the command line;
6. conduct a statistical analysis of transcriptomic and epigenetic data using the R programming language;
7. design genomic experiments with sufficient statistical power and controls by approaching problems in biology and neuroscience from a quantitative perspective;
8. describe the molecular and functional difference between neurons, astrocytes, oligodendrocytes, and microglial cells in the brain;
9. describe how epigenetics contributes to the process of neural plasticity;
10. and describe the biological basis of neurological and psychiatric disorders and how genomic technology has contributed towards our understanding of them.