ArticleJournal of microbiology & biology education2026
A course-based undergraduate research experience (CURE) designed for modern genetics and biodiversity courses using a classroom benchtop sequencer.
Article in Journal of microbiology & biology education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Modern genetics increasingly relies on genomic data sets to address medical, ecological, and evolutionary questions. Investigating these questions requires a diverse set of core competencies in wet-lab techniques, data analysis, and bioinformatics. We describe the design and implementation of a nine-week course-based undergraduate research experience (CURE) embedded within an upper-level Genetics Laboratory course. This CURE exposed students to contemporary wet-lab and analytical techniques related to genomic sequencing and biodiversity analysis. Each student began with an intact biological specimen and independently completed DNA extraction, quantification, library preparation, and sequencing using Oxford Nanopore Technologies. Students were subsequently trained in basic bioinformatic and phylogenetic analyses. To simulate an authentic research experience, students worked with real research samples, engaged in iterative data evaluation, and were responsible for troubleshooting and planning next steps. Data analysis was student-driven; not all students participated in all aspects of the analysis, allowing for individual ownership and specialization. Modules on quantitative reasoning and scientific communication were integrated into the curriculum to ensure consistent development of key skills. This CURE focused on understudied groups of trematodes (Platyhelminthes), with uncertain taxonomic placement, providing an opportunity to explore species discovery, marker selection, intra- vs. interspecific variation and zoonotic disease transmission. "Teaching-Research Synergy" is central to this curriculum, which is adaptable to other study systems and can be leveraged to support a faculty's research program. We present findings from two iterations of this CURE and discuss how student-generated data can contribute meaningfully to faculty-led research.
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