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An undergraduate genome research course using "big data".

ABSTRACT: The ability to analyze large data sets ("Big Data") is an increasingly important skill in modern science. In Biochemistry, the increased volume and velocity of data is particularly evident in the rapid expansion of biological databases. We present a modular bioinformatics course to survey the analysis of genomic data for advanced undergraduates. Research activities include genome scanning for endogenous retroviruses, annotating genomic sequences and a brief exploration of programming in R. A summative poster session was used to disseminate their work. This course is amenable to remote or online instruction. Supplemental materials provided include a schedule and outline. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science on Big Data."

SUBMITTER: Bennett EN

PROVIDER: S-EPMC10458672 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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An undergraduate genome research course using "big data".

Bennett Evan N EN Page Shallee T ST

Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology 20220709 5

The ability to analyze large data sets ("Big Data") is an increasingly important skill in modern science. In Biochemistry, the increased volume and velocity of data is particularly evident in the rapid expansion of biological databases. We present a modular bioinformatics course to survey the analysis of genomic data for advanced undergraduates. Research activities include genome scanning for endogenous retroviruses, annotating genomic sequences and a brief exploration of programming in R. A sum ...[more]

PMID: 35809004

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Project description:Genetic analysis in model systems can provide a rich context for conceptual understanding of gene structure, regulation, and function. With an intent to create a rich learning experience in molecular genetics, we developed a semester-long course-based undergraduate research experience (CURE) using the CRISPR-Cas9 gene editing system to disrupt specific genes in the zebrafish. The course was offered to freshman students; nine students worked in four groups (two to three members per group) to design, synthesize, and test the nuclease activity of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/sgRNAs for targeted disruption of specific genes in the zebrafish. Each group worked with a gene with an already known mutant phenotype that can be visually scored and a gene that had not been studied in zebrafish previously. Embedded in the course were a series of workshop-styled units or tutorials, including tours to core facilities. The focus was on introducing and developing skills that could be accommodated within the span of a semester. Each group successfully cloned at least one plasmid-encoding CRISPR/sgRNA template, visually analyzed injected embryos, and performed genotyping assays to detect CRISPR-Cas9 activity. In-class discussions, a final end-of-semester written test, and group oral presentations were assessed for an understanding of the CRISPR-Cas9 system, application of the CRISPR-Cas9 system as a gene manipulation tool, and experimental methods used to create plasmid vectors and synthesize sgRNA. In addition, poster presentations were evaluated by faculty, graduate students, and senior undergraduate students at a University research exposition. Self-reflections in the form of group conversations were video recorded. All students (9/9) distinctly showed learning gains after completing the activity, but the extent of the gains was variable, as seen from results of a written test and poster presentation assessment. Qualitative analysis of evaluations and self-reporting data indicated several gains, suggesting that all students found many aspects of the CURE valuable and gained project-specific (conceptual) and transferrable skills (science process and science identity).

Dataset Information

An undergraduate genome research course using "big data".

Publications

An undergraduate genome research course using "big data".

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