This study was initiated based on the observation that most students struggle to understand the relationships between genes, proteins, and traits. To address this issue, we developed a bioinformatics-based teaching-learning program designed to help students learn about such causal relationships through genomic data analysis. The primary objective of the developed program is to improve students’ ability to explain molecular biological concepts related to the association between gene expression and trait manifestation. Using bioinformatics tools, students engage in data collection, analysis, visualization, and data interpretation over three sessions. In the first session, ResFinder is used to compare the genomes of three bacterial strains and to analyze for the presence of the antibiotic resistance gene BlaZ. Next, Clustal Omega and GeneMarkS are used to visualize differences between the nucleotide and amino acid sequences of BlaZ of two strains. Finally, students analyze the relationship between mRNA codons and amino acid sequences using an Excel-based visualization tool and explore how changes in nucleotide sequences can affect resulting amino acid. This program is designed to support understanding of the causal relationships among genes, proteins, and traits, while engaging students in authentic scientific inquiry that requires higher-order thinking, thereby fostering data literacy competency.
Kim et al. (Sun,) studied this question.