Overview:

This course provides hands-on training in microbial transcriptomics, guiding students through the complete RNA-seq workflow, from bacterial RNA extraction and library preparation through Oxford Nanopore long-read sequencing of both cDNA and direct RNA, while addressing the unique challenges of working with prokaryotic samples. Students will build practical bioinformatics skills, writing and troubleshooting Linux and R scripts (with AI-assisted debugging) to process sequencing data, and learn to interpret differential gene expression results through gene ontology and KEGG pathway analysis.

Learning Objectives:

1. Describe the steps for RNA-seq workflow, from sample preparation to differential gene expression (DEG) analysis.
2. Identify appropriate controls for different experimental conditions when designing an RNA-sequencing experiment..
3. Write and execute Linux and R scripts to process sequencing data, using AI tools to troubleshoot errors.
4. Analyze long-read sequencing data of both cDNA and Direct-RNA.
5. Interpret DEG data by using bacterial gene ontology (GO) and KEGG pathway analysis.
6. Evaluate RNA-seq workflows and long-read NGS approaches for a given experiment.
7. BIT 595 Only: Design and justify a research proposal that applies transcriptomics to address a relevant biological question

Lecture Topics: 

• Introduction to Omics approaches
• Transcriptomics and Next-Generation Sequencing 
• RNA-seq workflow and library preparation methods
• Prokaryotic-specific challenges with RNA-seq
• Nanopore/long-read sequencing technologies
• Comparison of cDNA and direct RNA sequencing
• Transcriptomic experimental design and controls
• Differentially expressed gene (DEG) analysis and KEGG pathway mapping
• Research applications of microbial transcriptomics

Lab Topics:

• Microbial RNA extractions, preservation, and processing
• cDNA-PCR and Direct-RNA sequencing with Nanopore
• Sequencing read filtering, alignment, and data processing
• Analysis and interpretation of transcriptomic data using metabolic pathway mapping and gene ontology networks