Introduction to Microbiome Analysis

Catalog description

The development of next-generation sequencing (NGS) technologies was initially spurred by the desire for a human genome sequence, but these tools are now essential to all areas of biology. The amount of data produced by NGS allows us to ask questions about processes that occur across genomes, communities, and even landscapes. In particular, NGS has revolutionized the study of environmental microbiology, allowing us to investigate the thousands of microbial "species" that co-occur in a given environment, even though most of these microorganisms have not been captured or observed in culture. The entire complement of microorganisms (and their genes) that occur in a particular environment is frequently referred to as the "microbiome" of that environment. The field of microbiome research is evolving rapidly, which means that there are many opportunities to contribute to exciting new discoveries. However, this fast pace of change has made it difficult to properly prepare students for microbiome-focused graduate work. In this course, students will learn about the development of NGS techniques, as well as recent applications of NGS to natural and agricultural soil systems, including how these tools can be used to understand both targeted and unintentional human-induced changes to microbiomes. Students will also develop the ability to interpret microbiome-related literature and to work with NGS data using freely available software. In the second assignment, students will explore additional software not used in class, in order to learn how to learn to use unfamiliar bioinformatics tools. This course is intended for students with very little background in programming or bioinformatics, but with a strong understanding of microbiology, molecular biology, and/or ecology. At the conclusion of this course, students will be able to: - Interpret microbiome terminology and figures. - Understand and present a summary of a microbiome-based journal article. - Analyze microbiome-based high-throughput sequencing data using freely available software. - Apply microbiome analysis tools to unknown data. - Express their interpretation of microbiome data in oral, written, and graphical contexts.