Title: A semester-long collaborative research based genomics course
using a previously unsequenced nematode
Theresa M. Grana1*, David Toth2†
Affiliations:
1
Department of Biological Sciences, University of Mary Washington
2
Department of Computer Science, Centre College
*Jepson Science Center, 1301 College Ave., Fredericksburg, VA 22401, tgrana@umw.edu
†600 West Walnut Street, Danville, KY 40422
Type of Manuscript: CourseSource Lesson Manuscript
Funding & Conflict of Interest Statement: Funding for the development of this course came from
GCAT-SEEK (which is/has been funded by NSF grants #DBI-1248096 and #DBI-1061893 and
HHMI), and the UMW Center for Teaching Excellence and Innovation
Our course will not be taught until Fall 2015, so we have greyed out questions that we are not
able to answer at this time.
Conflict of interest exists when an author, reviewer or editor has financial, personal, or professional
relationships that could inappropriately bias or compromise his or her actions. For example, if the
authors of a Lesson are assessing the effectiveness of the Lesson, a conflict of interest exists. The
presence OR absence of perceived conflicts must be addressed on a Conflict of Interest
Notification on the manuscript’s title page.
List of Tables, Figures and Supplemental Material: Please list the Figures, Tables and Supplemental
materials associated with the Lesson.
Table 1: Course Schedule
Supplemental materials:
S1 Syllabus
S2 Lab manual
S3 Course assignments and activities
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Abstract Page
Undergraduate students in this upper-level course participate in a genomics research project.
Providing all students with an independent research experience is challenging, but in this course
students participate collaboratively in an original research project to sequence and characterize a
previously unsequenced nematode genome. Each student will contribute independently to
genome analysis and then the work of all students will be aggregated into a potential publication.
During the first third of the course, students learn basic genome assembly, annotation, and
comparative genomics; and discuss a series of relevant research articles. Students then formally
propose a comparative genomics question, develop a small project, and then use genomics tools
to address their research question, analyze and contextualize their results, and finally present their
research findings. We have designed modules of this course so that they can be readily be adapted
by other instructors or be used over several semesters, so that many students could contribute to
this genome project. A blog and database will be developed to track progress on the genome.
Thus, many students across institutions and over a period of several years can participate in a
collaborative original research project, to obtain the benefits of the deep learning that comes with
research and to experience the collaborative nature of modern science.
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Article Context Page: To make the submission
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answers during the submission process). Choose all
applicable options that effectively describe the
conditions IN WHICH THE LESSON WAS
TAUGHT. Modifications to expand the usability of
the Lesson will be addressed later in the text.
**Please delete this page prior to submission.
**Not all categories will pertain to your article,
in those cases, please select ‘N/A’ when
submitting on the website.
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Course
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Biochemistry
Cell Biology
Developmental Biology
Genetics
Microbiology
Molecular Biology
Introductory Biology
Bioinformatics (We added this
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Lesson Length
o Portion of one class period
o One class period
o Multiple class periods
o One term (semester or quarter)
o One year
o Other

Key Scientific Process Skills
o Reading research papers
o Reviewing prior research
o Asking a question
o Formulating hypotheses
o Designing/conducting
experiments
o Predicting outcomes
o Gathering data/making
observations
o Analyzing data
o Interpreting results/data
o Displaying/modeling results/data
o Communicating results

Pedagogical Approaches
o Think-Pair-Share
o Brainstorming
o Case Study
o Clicker Question
o Collaborative Work
o One Minute Paper
o Reflective Writing
o Concept Maps
o Strip Sequence
o Computer Model
o Physical Model
o Interactive Lecture
o Pre/Post Questions
o Other
o Computational approaches
(We added this choice because it was not
choice because it was not an option)

Course Level
o Introductory
o Upper Level
o Graduate
o High School
o Other

Class Type
o Lecture
o Lab
o Seminar
o Discussion Section
o On-line
o Other

Audience
o Life Sciences Major
o Non-Life Science Major
o Non-Traditional Student
o 2-year College
o 4-year College
o University
o Other
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Class Size
o 1 – 50
51 – 100
101+
an option)

Bloom’s Cognitive Level (based on
learning objectives & assessments)
3
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Foundational: factual knowledge
& comprehension
Application & Analysis
Synthesis/Evaluation/Creation

Principles of how people learn
o Motivates student to learn material
o Focuses student on the material to
be learned
o Develops supportive community
of learners
o Leverages differences among
learners
o Reveals prior knowledge
o Requires student to do the bulk
of the work

Vision and Change Core Concepts
o Evolution
o Structure and Function
o Information flow, exchange and
storage
o Pathways and transformations of
energy and matter
o Systems

Vision and Change Core Competencies
o Ability to apply the process of
science
o Ability to use quantitative
reasoning
o Ability to use modeling and
simulation
o Ability to tap into the
interdisciplinary nature of
science
o Ability to communicate and
collaborate with other disciplines
o Ability to understand the
relationship between science and
society

Key Words: List 3 – 10 key words that are
relevant for the Lesson (e.g. mitosis;
meiosis; reproduction; egg; etc.)
o genome analysis
o nematode
o computational biology
o next-gen sequencing
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Scientific Teaching Context Page
Learning Goal(s):
Students will:
 Understand how biological information is encoded in a genome and how genomes are
studied.
 Develop approaches to solving biological problems using Bioinformatics.
 Recognize the importance of computational power and approaches in data analysis and
organization.
 Work in areas outside of your own areas of expertise in biology and computing, gaining
the knowledge and skills you need as you go along.
 Be willing to use trial and error to figure out how different bioinformatics software
works.
 Become comfortable with the open-ended nature of biological problems.
Learning Objective(s):
Students will:
 Describe how a genome is sequenced and how decisions are made about data quality and
genome annotation.
 Develop a research question and investigate that question using bioinformatics tools.
 Be able to accurately and efficiently extract genetic and genomic data from public
databases, taking in to consideration the limitations of available data.
 Employ good science & computing practices, including maintaining an online record of
their work, managing files, and backing up their work.
 Effectively communicate with others about complex biological problems and work
collaboratively with others.
 Read and interpret primary literature in bioinformatics.
 Critically evaluate your own experiments and those of others.
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Main Text
Begin the Lesson text on a new page. Include the following sections:
1. Introduction: The introduction should provide the origin and rationale for the design of the Lesson and
provide enough background information to allow the reader to evaluate the Lesson without
referring to extensive outside material. For complex topics, a Science Behind the Lesson article
may be simultaneously submitted with the Lesson, so that potential instructors will have
sufficient information to implement the Lesson.
Beginning in fall 2014, all UMW biology majors will be required to participate in a researchintensive (RI) course where they i) learn techniques used in contemporary biological research, ii) develop
a research proposal, iii) complete the research project they design. To keep up with demand the
department will need to offer five to six RI courses per year. An RI bioinformatics course using our own
sequencing data will allow students to ask and answer questions about genome evolution, learn modern
techniques, and also be manageable for instructors with heavy teaching loads. Thus, adding this genome
sequencing and analysis RI course will benefit biology majors at UMW.
Nematodes are one group of multicellular eukaryotes with simple body plans, relatively small
genome, and a growing body of well-annotated genomic information. This course will focus on the
sequencing of a nematode species in the R. axei group known by its strain name JU1783. Nematodes in
this group have reproductive strategies similar to many animal parasitic nematodes, and are thus of
interest for animal/human medicine. In addition, other nematodes in this group are being sequenced by
other laboratories (the Andre Pires-da Silva lab, for example), opening up opportunities for comparative
genomics between sister species. These nematodes are also being phenotypically characterized by
researchers in Diane Shakes lab at the College of William and Mary, opening up opportunities for
dialogue between these labs and students in my course.
The introduction should also explain:
 Intended Audience: Describe the intended student population for the Lesson, including level
and major affiliation. For example: first-year students, biology majors, non-majors, advanced
biology students, etc. Upper-level biology majors. There will be ~16 students per course.
 Learning time: Indicate the approximate class or lab time required for the Lesson, keeping in
mind potential alternate Lesson timelines that may also be described in the modifications
section. This course will meet in 2 hour blocks three times per week all semester.
 Pre-requisite student knowledge: Describe the knowledge and skills that students should have
before using this Lesson. Prerequisite knowledge may include both science process skills and
background content knowledge. Only students who have completed both cell biology, general
genetics, and the sophomore-level research process course will be able to enroll. Students
interested in molecular biology, solving problems, and computation will most enjoy the
course. Students who want to pursue research or academic medicine may benefit the most.
2. Scientific Teaching Themes: Explain how the Lesson relates to the Scientific Teaching Themes of:
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Active Learning: How will students actively engage in learning the concepts? List and/or
explain the active learning strategies that are used in the Lesson. For example, activities could
include think-pair-share, clicker questions, group discussion, debate, etc. Include both inclass and out-of-class activities. Group and class wide discussions will regularly be used to
regroup, and clarify material. Students will practice genome assembly using a small genome
and then do an assembly on a large genome that has never been studied before. They will also
carry out their own research projects.
Assessment: How will teachers measure learning? How will students self-evaluate their
learning? List and/or explain the kinds of assessment tools used to measure how well students
achieved the learning objectives. For example, assessments might be clicker questions, forced
choice questions, exams, posters, etc. Formative assessment will take place throughout the
semester via class worksheets and homework assignments. The Classroom Undergraduate
Research Experience survey
(https://www.grinnell.edu/academics/areas/psychology/assessments/cure-survey) will be used
to assess pre- and post-course attitudes. The projects will be graded and assessed via
department rubrics developed for our “Research Intensive” designated learning outcomes.
Formative assessment of project proposals, journal club assignments, and draft reports will
help students formulate good research questions and a final formal research paper.
Inclusive Teaching: How is the Lesson designed to include all participants and acknowledge
the value of diversity in science? List and/or explain how the Lesson is inclusive and how it
leverages diversity in the classroom and beyond. For example, the lesson may use multiple
senses and provide examples of scientists from different backgrounds. All students in the
course will develop a research proposal and complete a research project, regardless of
previous research experience.
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3. Lesson Plan: Provide a detailed description of the Lesson that is sufficiently complete and detailed to
enable another teacher to replicate it. You may need/want to include subsections such as: preclass preparation and in-class script. A Table containing a recommended timeline for the class
should be included. As needed, expand upon aspects of scientific teaching that are particularly
highlighted in the Lesson. As appropriate, provide examples of formative and/or summative
assessments and related rubrics. List materials that are necessary or useful for teaching the
Lesson, whether they are provided as supplementary materials or as links to other websites.
We will teach this course in fall 2015 and are just learning how to do genomics ourselves, so our lesson
plan is not ready yet. Working course schedule:
Week
1 Introduction to
genomes
2
Introduction to
reading journal
articles
Assembly
preparation
3
Assembly &
Annotation
practice
4
Assembly &
Annotation
practice
5
Assembly &
Annotation,
Comparative
Genomics
6
Annotation
7
Project proposals
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Topic/Activity
Examine online genomic data, gene
structure, discuss where this
information comes from, how it is
used, etc. Prepare to build our own
genome! (pre-modules)
Primer on genomic DNA isolation
Journal Club
Challenges & theory – assembly
exercises on paper
Linux access & tutorial; file type
Journal Club
Practice day 1– Data Quality and
Error Correction
Practice day 2 – Assembly using
SOAPdenovo2 walk them through
beginning, they finish and compare
results 1X, and 10X
Practice day 3 – Repeat masking
Practice day 4 – Whole genome
analysis
Journal Club
Homework
Extract info from Wormbase &
UCSC Genome Browser
Journal Article: introducing
genomics
More Linux at home following a
video of Dave’s design
Journal Article: best practices for
assembly, plan assembly settings
Practice 100X
Can they assemble a simple
genome?
Journal Article(s) Comparative
genomics
Data Quality and Error Correction
Assembly using SOAPdenovo2 (one
run? or many?). Repeat masking,
Stacks SNP finding
Journal Article(s) Comparative
genomics
Comparative Genomics using CoGe
Whole Genome Analysis
Research Questions & Literature
Search; Literature workshop
annotations ongoing?
formulate a good research question
Project proposal development
Begin projects
peer review project proposals
instructor review project proposals
short annotated bibliography,
methods section
Spring Break
9 Projects
Generate and analyze project data
10 Projects
Generate and analyze project data
work on projects in class and at
home
work on projects in class and at
home
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11 Projects
Interpret and contextualize results
12 Projects
Write Manuscript
13
14
15
16
Draft Manuscript
Write Manuscript
Finalize Manuscripts
Work on Presentations
Deliver Presentations
Final Manuscript
write results and begin discussion
generate figures
re-write introduction (from
proposal); re-write methods (from
proposal)
tie aspects of manuscript together
due at final exam time
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4. Teaching Discussion: Share your observations about the Lesson’s effectiveness in achieving the stated
learning goals and objectives, student reactions to the Lesson, and your suggestions for possible
improvements or adaptations to different courses or student populations.
N/A
 Subheadings: can be included within the sections above to increase readability and clarity.
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Acknowledgments
Begin the Acknowledgements on a new page. The acknowledgements can be multiple
paragraphs.

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
GCAT-SEEK (supported training, and sequencing costs)
Mary Kayler (UMW) for curricular and lesson advice.
The UMW Center for Teaching Excellence and Innovation for supporting our
Interdisciplinary project.
Andre Pires daSilva and Diane Shakes for collaborting on the selection and
characterization of strain JU1783.
959 genomes/Mark Blaxter for calling for the sequencing of 959 nematode genomes
and providing a place for researchers to corrodinate sequencing projects.
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References We are just listing references in categories since the text of our plan will be significantly revised in
the next two years. Similarly, we will put references in the correct format once we have taught the course.
Science Education References
Recommendations from the NSF, AAAS, The National Academes (BIO2010), Council on Undergraduate
Research, Vision & Change.
Genomics Course References
Jennifer C. Drew, Eric W. Triplett, “Whole Genome Sequencing in the Undergraduate Classroom:
Outcomes and Lessons from a Pilot Course.” 9(3-11), Journal of Microbiology & Biology Education, May
2008.
Buonaccorsi VP, Boyle MD, Grove D, Praul C, Sakk E, Stuart A, Tobin T, Hosler J, Carney SL, Engle MJ,
Overton BE, Newman JD, Pizzorno M, Powell JR, Trun N. (2011) GCAT- SEEKquence: Genome Consortium
for Active Teaching of undergraduates through increased faculty access to next-generation-sequencing
data. CBE Life Sciences Education. 10:342-345.
Michael D. Boyle “Shovel-ready” Sequences as a Stimulus for the Next Generation of Life Scientists
JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION, May 2010
General Genome Analysis References (References and exercises put together by Vince for the
Eukaryotic Genomics Modules)
Timothy L. Bailey, Mikael Boden, Fabian A. Buske, Martin Frith, Charles E. Grant3, Luca Clementi, Jingyuan
Ren, Wilfred W. Li and William S. Noble. MEME SUITE: tools for motif discovery and searching. Nucl. Acids
Res. (2009) 37 (suppl 2): W202-W208. doi: 10.1093/nar/gkp335
MA Beer, S Tavazoie. Predicting gene expression from sequence. Cell 117 (2), 185-198
De Santa F1, Barozzi I, Mietton F, Ghisletti S, Polletti S, Tusi BK, Muller H, Ragoussis J, Wei CL, Natoli G. A
large fraction of extragenic RNA pol II transcription sites overlap enhancers. PLoS Biol. 2010 May
11;8(5):e1000384. doi: 10.1371/journal.pbio.1000384.
Margaret C.W. Ho, Benjamin J. Schiller, Sara E. Goetz and Robert A. Drewell Non-genic transcription at
the Drosophila bithorax complex – functional activity of the dark matter of the genome (2009), Int. J. Dev.
Biol. 53, 459-468;
Kenney DR, Schatz MC, Salzberg SL. 2010. Quake:quality-aware detection and correction of sequencing
errors. Genome Biology 11:R116.
Cantarel B, Korf I, Robb SMC, Parra G, Ross E, Moore B, Holt C, Sanchez Alvarado A, Yandell M.
2008.MAKER: An Easy-to-use Annotation Pipeline Designed for Emerging Model Organism Genomes.
Genome Research 2008 18: 188-96.
Holt C, Yandell M. 2011. MAKER2: an annotation pipeline and genome-database management tool for
second-generation genome projects. BMC Bioinfo 12:491
Kenney DR, Schatz MC, Salzberg SL. 2010. Quake:quality-aware detection and correction of sequencing
errors. Genome Biology 11:R116.
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Kim TK1, Hemberg M, Gray JM, Costa AM, Bear DM, Wu J, Harmin DA, Laptewicz M, Barbara-Haley K,
Kuersten S, Markenscoff-Papadimitriou E, Kuhl D, Bito H, Worley PF, Kreiman G, Greenberg ME.
Widespread transcription at neuronal activity-regulated enhancers Nature. 2010 May 13;465(7295):182-7.
doi: 10.1038/nature09033. Epub 2010 Apr 14
Marcais G, Kingsford C. 2011. A fast, lock-free approach for efficient parallel counting of occurrences of
k-mers. Bioinformatics. 27:764-770.
Miller JR, Koren S, Sutton G. Assembly algorithms for next-generation sequencing data. Genomics 2010.
95:315-27; PMID:20211242. http://dx.doi.org/10.1016/j.ygeno.2010.03.00
Nematode Genome References
Todd W Harris, Igor Antoshechkin, Tamberlyn Bieri, Darin Blasiar, Juancarlos Chan, Wen J Chen, Norie De
La Cruz, Paul Davis, Margaret Duesbury, Ruihua Fang, Jolene Fernandes, Michael Han, Ranjana Kishore,
Raymond Lee, Hans-Michael Müller, Cecilia Nakamura, Philip Ozersky, Andrei Petcherski, Arun
Rangarajan, Anthony Rogers, Gary Schindelman, Erich M Schwarz, Mary Ann Tuli, Kimberly Van Auken,
Daniel Wang, Xiaodong Wang, Gary Williams, Karen Yook, Richard Durbin, Lincoln D Stein, John Spieth,
Paul W Sternberg. WormBase: a comprehensive resource for nematode research. Nucleic acids research
38 (suppl 1), D463-D467 185
2010
Gerstein MB, Lu Z, Van Nostrand E, Cheng C, Arshinoff B, Liu T, et al. Integrative Analysis of the
Caenorhabditis elegans Genome by the modENCODE Project. Science 2010; 330:1775-87;
PMID:21177976; http://dx.doi.org/10.1126/science.1196914
Steven G Kuntz, Erich M Schwarz, John A DeModena, Tristan De Buysscher, Diane Trout, Hiroaki Shizuya,
Paul W Sternberg, Barbara J Wold. Multigenome DNA sequence conservation identifies Hox cis-regulatory
elements. Genome research 18 (12), 1955-1968 2008
Sujai Kumar, Georgios Koutsovoulos, Gaganjot Kaur and Mark Blaxter. “Towards 959 nematode
genomes.” 1:1(42-50) Worm. March 2012.
Mitreva M1, Jasmer DP, Zarlenga DS, Wang Z, Abubucker S, Martin J, Taylor CM, Yin Y, Fulton L, Minx P,
Yang SP, Warren WC, Fulton RS, Bhonagiri V, Zhang X, Hallsworth-Pepin K, Clifton SW, McCarter JP,
Appleton J, Mardis ER, Wilson RK. The draft genome of the parasitic nematode Trichinella spiralis. Nat
Genet. 2011 Mar;43(3):228-35. doi: 10.1038/ng.769. Epub 2011 Feb 20.
Missal et al. (2006), Prediction of structured non-coding RNAs in the genomes of the nematodes
Caenorhabditis elegans and Caenorhabditis briggsae Journal of Experimental Zoology Part B: Molecular
and Developmental Evolution, 379-392. Volume 306B, Issue 4, pages 379–392, 15 July 2006
Ali Mortazavi, Erich M. Schwarz, Brian Williams, et. al. “Scaffolding a Caenorhabditis nematode genome
with RNA-seq. 20(12):1740-7 Genome Research, December 2010.
Ross JA1, Koboldt DC, Staisch JE, Chamberlin HM, Gupta BP, Miller RD, Baird SE, Haag ES. Caenorhabditis
briggsae recombinant inbred line genotypes reveal inter-strain incompatibility and the evolution of
recombination. 2011 Jul;7(7):e1002174. doi: 10.1371/journal.pgen.1002174. Epub 2011 Jul 14., PLoS
Genet. 7, e1002174
Erich M Schwarz, Pasi K Korhonen, Bronwyn E Campbell, Neil D Young, Aaron R Jex, Abdul Jabbar, Ross S
Hall, Alinda Mondal, Adina C Howe, Jason Pell, Andreas Hofmann, Peter R Boag, Xing-Quan Zhu, T Ryan
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Gregory, Alex Loukas, Brian A Williams, Igor Antoshechkin, C Titus Brown, Paul W Sternberg, Robin B
Gasser. The genome and developmental transcriptome of the strongylid nematode Haemonchus
contortus. Genome Biology 14 (8), R89 2013
Paul W Sternberg, Erich Schwarz, Ali Mortazavi, Adler Dillman, Mihoko Kato. Obtaining and using
nematode genome sequences. Journal of Nematology 42 (3), 270-270 2010
Wenick AS, Hobert O. Genomic cis-regulatory architecture and trans-acting regulators of a single
interneuron-specific gene battery in C. elegans. Dev Cell. 2004 Jun;6(6):757-70.
Begin the References on a new page.
* Cite references in the text using superscript Arabic numbers. Use commas to separate multiple
citation numbers. Superscript numbers are placed outside periods and commas and inside colons and
semicolons.
1. Begin the reference list on a new page. The reference list is comprehensive and spans the text, figure
captions and materials.
2. Number references in the order in which they appear in the text. Follow ASM style and abbreviate
names of journals according to the journals list in NCBI. List all authors and/or editors up to 6; if
more than 6, list the first 3 followed by “et al.” Note: Journal references should include the issue
number in parentheses after the volume number.
Examples of reference style:
1. Knight JK, Wood WB. 2005. Teaching more by lecturing less. Cell Biol Educ. 4(4):298-310.
2. Samford University. How to get the most out of studying: A video series.
www.samford.edu/how-to-study/. Accessed August 20, 2013.
3. Handelsman J, Miller S, Pfund C. 2006. Scientific Teaching. New York, NY:W.H. Freeman.
3. Please add notes to the end of the reference list; do not mix in references with explanatory notes.
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