Big Data to the Bench: Transcriptome Analysis for Undergraduates

Item request has been placed! ×
Item request cannot be made. ×
  Processing Request
  • Source:
    CBE - Life Sciences Education, v18 n2 Article 19 Jun 2019. 11 pp.
  • Accession Number:
    http://dx.doi.org/10.1187/cbe.18-08-0161
  • Language:
    English
  • Publication Type:
    Journal Articles; Reports - Research
  • Additional Information
    • Author(s):
    • Availability:
      American Society for Cell Biology. 8120 Woodmont Avenue Suite 750, Bethesda, MD 20814-2762. Tel: 301-347-9300; Fax: 301-347-9310; e-mail: ascbinfo@ascb.org; Website: http://www.ascb.org
    • Peer Reviewed:
      Y
    • ISSN:
      1931-7913
    • Subject Terms:
    • Abstract:
      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.
    • Abstract:
      As Provided
    • Number of References:
      -1
    • Sponsoring Agency:
      National Institutes of Health (DHHS)
    • Sponsoring Agency:
      National Science Foundation (NSF)
    • Contract Number:
      1F32GM101876
    • Contract Number:
      5R35GM122604
    • Contract Number:
      DBI0735191
    • Contract Number:
      DBI1265383
    • Physical Description:
      11
    • Education Level:
      Higher Education; Postsecondary Education
    • Journal Code:
      SEP2019
    • Publication Date:
      2019
    • Accession Number:
      EJ1217730
  • Citations
    • ABNT:
      PROCKO, C. et al. Big Data to the Bench: Transcriptome Analysis for Undergraduates. CBE - Life Sciences Education, [s. l.], v. 18, n. 2, 2019. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428. Acesso em: 5 dez. 2019.
    • AMA:
      Procko C, Morrison S, Dunar C, et al. Big Data to the Bench: Transcriptome Analysis for Undergraduates. CBE - Life Sciences Education. 2019;18(2). http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428. Accessed December 5, 2019.
    • APA:
      Procko, C., Morrison, S., Dunar, C., Mills, S., Maldonado, B., Cockrum, C., … Chory, J. (2019). Big Data to the Bench: Transcriptome Analysis for Undergraduates. CBE - Life Sciences Education, 18(2). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428
    • Chicago/Turabian: Author-Date:
      Procko, Carl, Steven Morrison, Courtney Dunar, Sara Mills, Brianna Maldonado, Carlee Cockrum, Nathan Emmanuel Peters, Shao-shan Carol Huang, and Joanne Chory. 2019. “Big Data to the Bench: Transcriptome Analysis for Undergraduates.” CBE - Life Sciences Education 18 (2). http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428.
    • Harvard:
      Procko, C. et al. (2019) ‘Big Data to the Bench: Transcriptome Analysis for Undergraduates’, CBE - Life Sciences Education, 18(2). Available at: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428 (Accessed: 5 December 2019).
    • Harvard: Australian:
      Procko, C, Morrison, S, Dunar, C, Mills, S, Maldonado, B, Cockrum, C, Peters, NE, Huang, SC & Chory, J 2019, ‘Big Data to the Bench: Transcriptome Analysis for Undergraduates’, CBE - Life Sciences Education, vol. 18, no. 2, viewed 5 December 2019, .
    • MLA:
      Procko, Carl, et al. “Big Data to the Bench: Transcriptome Analysis for Undergraduates.” CBE - Life Sciences Education, vol. 18, no. 2, June 2019. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428.
    • Chicago/Turabian: Humanities:
      Procko, Carl, Steven Morrison, Courtney Dunar, Sara Mills, Brianna Maldonado, Carlee Cockrum, Nathan Emmanuel Peters, Shao-shan Carol Huang, and Joanne Chory. “Big Data to the Bench: Transcriptome Analysis for Undergraduates.” CBE - Life Sciences Education 18, no. 2 (June 1, 2019). http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428.
    • Vancouver/ICMJE:
      Procko C, Morrison S, Dunar C, Mills S, Maldonado B, Cockrum C, et al. Big Data to the Bench: Transcriptome Analysis for Undergraduates. CBE - Life Sciences Education [Internet]. 2019 Jun 1 [cited 2019 Dec 5];18(2). Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1217730&custid=s8280428