Transcript GCAT-SEEK - Lycoming College

The Genome Consortium on
Active Teaching Using NextGeneration Sequencing
(GCAT-SEEK)
The vision of GCAT-SEEK is for faculty
at primarily undergraduate institutions to
direct their innate passion for research
into projects of their choosing that become
the cornerstone of innovative, broadly
disseminated educational efforts that are
assessed for student learning gains, and
meet the goals of the “Vision and Change
in Undergraduate Biology Education”
dialogues published by AAAS and NSF.
Vince Buonaccorsi, Juniata College
Jeff Newman, Lycoming College
Nancy Trun, Duquesne University
Tammy Tobin, Susquehanna University
Deborah Grove, Penn State University
Abstract
Teaching Experience
Undergraduate Teaching Experience
Years in GCAT
Frequency
10
8
6
4
2
0
0
1-5
6-10
Familiarity with Assessment
Literature
30
25
20
15
10
5
0
15
Frequency
12
Frequency
Genomics and bioinformatics are dynamic fields that provide opportunities to form student-scientist partnerships at small liberal arts
colleges. Empowering undergraduate faculty with access to state-of-the-art technology and with tools to implement curricular changes
is a difficult and evolving challenge. This challenge has been successfully addressed in the last decade by the Genome Consortium
on Active Teaching (GCAT), a grass-roots consortium of undergraduate educators. GCAT provided undergraduates access to
microarray technology, and has impacted over 300 faculty and 24,000 undergraduates. A major driving factor that enticed a diverse
group of faculty to adjust their teaching strategies was the academic freedom associated with integrating their own research questions
into an active teaching approach. A new network of educators (GCAT-SEEK) was formed in July, 2011 to enable undergraduate
access to Next-Generation sequencing and functional genomics using the GCAT organizational model. The consortium now involves
over 100 faculty, postdocs, and students from over 80 institutions throughout the country. Major interest areas include genomics,
transcriptomics, and metagenomics. GCAT-SEEK aims to engage students in inquiry-based learning that is grounded in the key
concepts and competencies of modern biology, and are connected to learning objectives and assessments. In our first year we have
identified three bottlenecks that make it difficult to seamlessly integrate next-generation sequencing into undergraduate courses and
research experiences. Challenges include experimental design for the faculty member who is a novice with respect to the technology,
bioinformatics training of faculty, and identification of appropriate and effective pedagogical and assessment tools.
1-5
11-15 16-20 21-25 26-30 31-40
10
5
0
Years Teaching
6-10
Years in GCAT
1
Low
11-15
2
3
4
5
High
• Relatively experienced with respect to teaching
Examples of Student / Scientist
Partnerships in Year 1
Intellectual Merits of Network
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Anticipated Broad Impacts: This network will
provide additional educational opportunities and
resources for STEM education and improved
opportunity for students to be prepared for
graduate, technical and research careers. With
116 faculty members from 88 institutions
already members of the GCAT-SEEK network,
we anticipate impacting thousands of students
via this project, with special focus on minority
representation.
Community of enthusiastic biologists, with primary undergraduate teaching responsibilities
Intellectual synergies on experimental design, bioinformatics approach, pedagogy and assessment
Discounted runs, software
Dissemination of data, pedagogic, assessment modules
Outreach to Minority Serving Institutions
Database of barcoded metagenomic primers
Voice for student input: leadership training, presentations, participation
Cross-disciplinary interactions
Student Impact in Year 1: 28 research students, 95 students in labs
Large non-model Eukaryotic genomics
Sequence
Genome
Formulate
Specific
Question
Assemble
Genome
Literature
Search
Create a Custom
BLAST database
(Geneious) from the
assembly
Download, study
candidate gene sets
(Uniprot/Genbank/
UCSC G.Browser)
Collaborators
Standard Operating Procedure
Proposed GCAT-SEEK workshop schedule and general content.
Theme
Content
Day
Setting
1 PM
Group
NextGen
Platforms
Experimental Design
Experimental
Design
2
Breakout
Wet Lab
Sample Prep
3
Breakout
Bioinformatics
Assembly
4 AM
Breakout
Bioinformatics
Annotation /
Comparison
4 PM
Group
Assessing Student
Customizing and
Learning Gains
Using the SALG
5 AM
Group Faculty Presentations Faculty teaching
modules
5 PM
Group Student Presentations
Student
presentations
As a result of faculty/student workshops, participants will be
able to:
1. Design experiments using next-generation sequencing
technologies
2. Prepare nucleic acid samples and assess quality
3. Sequence and analyze their samples
4. Teach modules that integrate next-generation sequencing
research into the classroom, and
5. Assess student learning goals and track outcomes
Students
Identify contigs in novel genome with homology
to candidate genomes (tBlastn in Geneious)
Identify Full CDS in novel
genome using the
MAKER2 web annotation
pipeline
Extract Coding
Sequences using
Galaxy/ Apollo
A student’s phylogenetic comparison
of six uncharacterized pheromone
receptors in Sebastes rubrivinctus
(Sru) to three previously sequenced
fishes. Further analyses showed no
evidence of positive selection, which
may occur in genes important to rapid
speciation rates in the genus.
Align sequences, separate into
clusters, generate a
phylogenetic tree (Geneious)
Calculate Ka/Ks ratio to
determine positive
selection (Selecton,
Ka/Ks calculator)
Write MS
Pipeline successfully used by three students to explore
targeted gene sets in the un-annotated Sebastes rockfish
genome related to mate recognition and high speciation rates.
Large non-model
Eukaryotic
transcriptomics
Student 1
A student has successfully
installed the Linux-based
MAKER pipeline on the
GCAT-SEEK server, which
can be used by other
network members, allowing
whole genome annotations.
The MAKER web annotation
service can be used by
novice students to learn the
analysis.
Bacterial genomics:
Lycoming College
Annotation of a single scaffold
in S. rubrivinctus focused on the
TERF1 gene. Polymorphisms
in this gene may help explain
negligible senescence in
Sebastes rockfishes
Human genomics:
Putative Freshman Lab
Download
Exome Trios from
1000 Genomes DB
Isolate RNA/
Sequence
Transcriptome
Teacher
Map against Human
Ref using NextGENe
on GCAT-SEEK server
Assemble Transcriptome
Using Geneious, CLC Bio,
NextGENe
Pick a single gene and
research prognosis of
individual (HUGO DB)
Present with two other
lab mates that picked
different SNPs from
same individual:
Prognosis
Advice
Use NextGENe viewer
to examine data
Students
Sample prep and deNovo transcriptome
assembly pipeline used by a student
Who is GCAT-SEEK?
NextGen Apps of interest
MSI Institions
MSI
14%
Non
MSI
86%
Animalia
41%
Fungi
13%
Bacteria
16%
Field of Teacher/Scholars
Putative pipeline to find and interpret differences
between an individual and human reference genome.
Plantae
28%
Bacterial
Genomics
18%
Metageno
mics
20%
Pipeline successfully used by students to
annotate bacterial genomes
Filter differences
Errors
Mode of inheritance
dbNSFP
Allele fqs
Kingdoms of interest
Eukaryotic
Genomics
26%
Transcript
omics
36%
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Archaea
2%
A student’s comparative analysis of
transcriptome assembly methods. Geneious
outperformed other methods in a 454 FLX+
low coverage (3X) dataset.
A G
C G
Mom
Venn Diagrams allowing correlation of
metabolism and bacterial ecology
x
A A
A G
Dad
A A
C G
Child
Example of a screenshot and scenario of
compound heterozygosity
Number of undergraduates at school
35
30
Frequency
Bioinformatics
5%
Evolution /
Ecology
17%
Conclusions
25
20
15
10
Biochem /
Mol Bio /
Genetics
78%
5
0
1-1000
1001-5000
5001-10000
10001-20000
Number of Students
20001-30000
• 14% from Minority Serving Institutions
• Diverse organisms and applications of interest.
• Predominantly BMB/Genetics/Microbiology faculty from small PUIs
Technology Expertise
Linux Proficiency
Perl or Python Proficiency
15
10
5
0
1
Low
2
3
4
5
High
35
30
25
20
15
10
5
0
1
Low
2
3
4
Works Cited
Number of NextGen Data Sets
Analyzed
Frequency
20
Frequency
Frequency
25
5
High
30
25
20
15
10
5
0
• Relatively novice with respect to computer science or NextGen approaches
• Our standard operating protocol should facilitate growth in membership, faculty
expertise, and student training.
• Network members have diverse interests, low NextGen and bioinformatic
experience, but high teaching experience.
• Year 1 examples of genomics work illustrate relative ease of projects involving
bacteria, collaboration with research intensive universities, and commercially
supported software for novice users.
• Vision and Change in Undergraduate Biology Education: Preliminary Reports of
Conversations. July 2009.NSF-AAAS. www.visionandchange.org
Acknowledgements
0
1-5
6-10
11-15 16-20 21-25
• NSF Award # DBI-1061893
• HHMI award to Juniata College
• Juniata College: Kresge Fund, Biology Dept, Provost