Next-generation teaching: a template for bringing genomic and bioinformatic tools into the classroom

Scott Hotaling; Brittany L. Slabach; David W. Weisrock

doi:10.1080/00219266.2017.1357650

Next-generation teaching: a template for bringing genomic and bioinformatic tools into the classroom

Scott Hotaling, Brittany L. Slabach, David W. Weisrock

Biology

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

The recent increase in accessibility and scale of genetic data available through next-generation sequencing (NGS) technology has transformed biological inquiry. As a direct result, the application and analysis of NGS data has quickly become an important skill for future scientists. However, the steep learning curve for applying NGS technology to biological questions, including the complexity of sample preparation for sequencing and the analysis of large data sets, are deterrents to the integration of NGS into undergraduate education. Here, we present a course-based undergraduate research experience (CURE) designed to aid in overcoming these limitations through NGS investigations of prokaryotic diversity. Specifically, we use 16S rRNA sequencing to explore patterns of diversity stemming from student-directed hypothesis development. This CURE addresses three learning objectives: (1) it provides a forum for experimental design hypothesis generation, (2) it introduces modern genomic tools through a hands-on experience generating an NGS data-set, and (3) it provides students with an introductory experience in bioinformatics.

Original language	English
Pages (from-to)	301-313
Number of pages	13
Journal	Journal of Biological Education
Volume	52
Issue number	3
DOIs	https://doi.org/10.1080/00219266.2017.1357650
State	Published - Jul 3 2018

Bibliographical note

Funding Information:
We thank the staff at the UK Advanced Genetic Technology Center for their assistance and guidance in library preparation and data generation. This CURE was funded by a Kentucky Biomedical Research Infrastructure Network grant (#5P20GM103436-15) to Arnold J. Stromberg of the UK Department of Statistics and Ramona Stone for her help administering the grant. D.W.W. was funded through a National Science Foundation grant (DEB-1355000) during the development of this teaching exercise. We thank Rachel Holsinger, Lynn Hotaling, Karla Lightfield, and two anonymous reviewers for helpful comments that improved the final manuscript. We also thank the participants of the 2014, 2015, and 2016 iterations of this educational experience – without their enthusiasm, patience, and willingness to try a new approach, its development would not have been possible. We would also like to acknowledge Seth Taylor and Devin Klaserner for their invaluable logistical and computational support.

Funding Information:
This work was supported by the Kentucky Biomedical Research Infrastructure Network and National Science Foundation [grant number DEB# 1355000].

Publisher Copyright:
© 2017, © 2017 Royal Society of Biology.

Keywords

CURE
Prokaryotic diversity
STEM
next-generation sequencing
undergraduate education

ASJC Scopus subject areas

Education
Agricultural and Biological Sciences (all)

Access to Document

10.1080/00219266.2017.1357650

Cite this

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abstract = "The recent increase in accessibility and scale of genetic data available through next-generation sequencing (NGS) technology has transformed biological inquiry. As a direct result, the application and analysis of NGS data has quickly become an important skill for future scientists. However, the steep learning curve for applying NGS technology to biological questions, including the complexity of sample preparation for sequencing and the analysis of large data sets, are deterrents to the integration of NGS into undergraduate education. Here, we present a course-based undergraduate research experience (CURE) designed to aid in overcoming these limitations through NGS investigations of prokaryotic diversity. Specifically, we use 16S rRNA sequencing to explore patterns of diversity stemming from student-directed hypothesis development. This CURE addresses three learning objectives: (1) it provides a forum for experimental design hypothesis generation, (2) it introduces modern genomic tools through a hands-on experience generating an NGS data-set, and (3) it provides students with an introductory experience in bioinformatics.",

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Next-generation teaching: a template for bringing genomic and bioinformatic tools into the classroom

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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