CHI TIẾT NGHIÊN CỨU …
Tiêu đề
Big data to the bench: Transcriptome analysis for undergraduates
Tác giả
Procko C.; Morrison S.; Dunar C.; Mills S.; Maldonado B.; Cockrum C.; Peters N.E.; Huang S.-S.C.; Chory J.
Năm xuất bản
2019
Source title
CBE Life Sciences Education
Số trích dẫn
1
DOI
10.1187/cbe.18-08-0161
Liên kết
Tóm tắt
Next-generation sequencing (NGS)-based methods are revolutionizing biology. Their prevalence requires biologists to be increasingly knowledgeable about computational methods to manage the enormous scale of data. As such, early introduction to NGS analysis and conceptual connection to wet-lab experiments is crucial for training young scientists. However, significant challenges impede the introduction of these methods into the undergraduate classroom, including the need for specialized computer programs and knowledge of computer coding. Here, we describe a semester-long, course-based undergraduate research experience at a liberal arts college combining RNA-sequencing (RNA-seq) analysis with student-driven, wet-lab experiments to investigate plant responses to light. Students derived hypotheses based on analysis of RNA-seq data and designed follow-up studies of gene expression and plant growth. Our assessments indicate that students acquired knowledge of big data analysis and computer coding; however, earlier exposure to computational methods may be beneficial. Our course requires minimal prior knowledge of plant biology, is easy to replicate, and can be modified to a shorter, directed-inquiry module. This framework promotes exploration of the links between gene expression and phenotype using examples that are clear and tractable and improves computational skills and bioinformatics self-efficacy to prepare students for the “big data” era of modern biology. © 2019 C. Procko et al. CBE-Life Sciences Education.
Từ khóa
Tài liệu tham khảo
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Nơi xuất bản
American Society for Cell Biology
Hình thức xuất bản
Article
Open Access
All Open Access; Gold Open Access; Green Open Access
Nguồn
Scopus