Integration of RNA-Seq Data Analysis into Undergraduate Laboratory Teaching Modules

Undergraduate students learn about Next Generation Sequencing (NGS) platforms in courses, but often have difficulty understanding the impact of these techniques without hands-on experience analyzing actual NGS datasets.  The NSF-supported Infrastructure & Training to Bring NGS Analysis Into Undergraduate Education project focuses on streamlining RNA-sequencing (RNA-seq) data analysis using a combination of bioinformatics and wet lab workflows tailored for implementation into diverse undergraduate laboratory classroom settings. These modular workflows can be applied to a variety of novel or publicly available RNA-seq datasets.

To create a course-based undergraduate research experience focusing on NGS that complements my research program, I developed an RNA-seq dataset to identify differentially expressed genes between embryonic day 8 (E8) and E18 chicken retinas. Computational and wet lab modules analyzing this RNA-seq dataset were implemented into an upper level undergraduate Advanced Molecular Biology course. Computational modules investigated gene ontology of the dataset to identify target candidate genes for follow up analysis as well as sequence retrieval, sequence annotation and gene-specific primer design. These modules were used in conjunction with wet lab activities constructing cDNA libraries from total RNA followed by quantitative reverse transcriptase PCR (qRT-PCR) using student-designed qPCR primers. Additional computer-based modules were employed for analysis of qRT-PCR gene expression data. Lab modules and lesson plans for this and other courses are publicly available to educators via the “RNA-seq for the Next Generation” website developed by the Cold Spring Harbor Laboratory DNA Learning Center.