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Implementation and assessment of a yeast orphan gene research project: involving undergraduates in authentic research experiences and progressing our understanding of uncharacterized open reading frames

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Saccharomyces cerevisiae was the first eukaryotic organism to be sequenced; however, little progress has been made in recent years in furthering our understanding of all open reading frames (ORFs). From October 2012 to May 2015 the number of verified ORFs had only risen from 75.31% to 78%, while the number of uncharacterized ORFs had decreased from 12.8% to 11% (representing > 700 genes still left in this category; http://www.yeastgenome.org/genomesnapshot). Course‐based research has been shown to increase student learning while providing experience with real scientific investigation; however, implementation in large, multi‐section courses presents many challenges. This study sought to test the feasibility and effectiveness of incorporating authentic research into a core genetics course, with multiple instructors, to increase student learning and progress our understanding of uncharacterized ORFs. We generated a module‐based annotation toolkit and utilized easily accessible bioinformatics tools to predict gene function for uncharacterized ORFs within the Saccharomyces Genome Database (SGD). Students were each assigned an uncharacterized ORF, which they annotated using contemporary comparative genomics methodologies, including multiple sequence alignment, conserved domain identification, signal peptide prediction and cellular localization algorithms. Student learning outcomes were measured by quizzes, project reports and presentations, as well as a post‐project questionnaire. Our results indicate that the authentic research experience had positive impacts on students' perception of their learning and their confidence to conduct future research. Furthermore, we believe that creation of an online repository and adoption and/or adaptation of this project across multiple researchers and institutions could speed the process of gene function prediction. Copyright © 2015 John Wiley & Sons, Ltd.
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Keywords: bioinformatics; course-based research; genetics; orphan genes

Document Type: Research Article

Publication date: February 1, 2016

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