Integration of RNA-Seq Data Analysis into Undergraduate Lab Teaching Modules Ray Enke Ph.D. James Madison University Department of Biology Harrisonburg VA Plant & Animal Genome Conference: XXIV
Talk Overview 1. Intro to the Infrastructure & Training to Bring Next-Generation Sequence Analysis into Undergraduate Education project (in progress) 2. Examples from my course-embedded RNA-Seq analysis teaching modules (in progress) 2
Milestones in Genome Sequencing 1995 . Fleischmann et al. 1977 . Sanger et al. 1998 . 1 st Multicellular Organism 1 st Free Living Organism 1 st Complete Organism C. elegans ; 97 Mbp H. influenza 1.8 Mbp Bacteriophage; 5375 bp *all completed using Sanger sequencing 2001 . Venter et al., IHGSC 2000 . Arabidopsis Human Genome; 2.9 Gbp 1 st Plant Genome. ~13 years + ~$3 billion 135 Mbp 3
The Impact of “Next Generation” Sequencing Completion of Human Genome Project (2001) Source: NHGRI
The Impact of “Next Generation” Sequencing advent of “Next Gen” sequencing (2007) • 10K fold reduction in sequencing cost over 4 yrs (2007-2011) Source: NHGRI
“Next Generation” Sequencing (and beyond) Roche 454 (2007) Illumina (2009) Ion Torrent (2010) Nanopore MinION (2015) “Next Gen” Sequencing Platforms “3 rd Generation!” • Reduced cost of “Next gen” sequencing platforms have made genome-wide analysis available to the masses
Infusing Next-Generation Sequence Analysis into Undergraduate Education Barriers to integrating authentic genomics analysis into PUI curriculum: • Cost prohibitive to generate data sets at many PUIs • Complex bioinformatics analysis & advanced computing capabilities • Limited instructor resources for training
Infrastructure & Training to Bring Next-Generation Sequence Analysis into Undergraduate Education project (PI: Dave Micklos, CSHL DNA Learning Center) Main objective: • Assist PUI faculty to integrate authentic Next-Gen Sequence analysis into undergraduate course work - RNA-sequencing (RNA-seq) analysis as vehicle Infrastructure: provided by the iPlant Collaborative Data storage space • High performance computing power • Intuitive bioinformatics web interfaces designed for non-experts • Faculty Training: Summer workshops for bioinformatics training • Development & dissemination of teaching materials • -Summer 2014 Workshop: 11 PUI faculty trained -Summer 2015 Workshops: 33 PUI faculty trained -Upcoming Summer 2016 Workshop: ~40 PUI faculty to be trained
Program Website www.rnaseqforthenextgeneration.org/ • T eaching Resources, Virtual Training, RNA-Seq Data Sets
Program Website www.rnaseqforthenextgeneration.org/
About James Madison University • Public PUI; Harrisonburg, VA • ~19,000 undergraduates • ~60% admission rate • ~1,000 Biology/Biotech majors JMU Biosciences building
BIO480 Advanced Molecular Biology • Junior/senior level course • 18 students/section • 4 credit lecture/lab course -4 hours/week • 3 sections/year (~50 students) • ~50% have lab research experience other than classes • Developed & incorporated RNA-Seq analysis modules in fall 14 & spring 15 semesters
BIO480 Course-embedded Research Modules (currently completed prior to course) (in class student ac>vi>es) week #1 week #2 week #3-4 week #5 RNA extrac>on For RNA-Seq RNA extrac>on cDNA qPCR setup for qRT-PCR synthesis Illumina qPCR data RNA-Seq Gene ontology qPCR primer analysis analysis design DNA Subway or Green Line (Cuffdiff out) Retrieve SRA Sequence Sequence RNA-Seq data retrieval annota>on Wet lab Computa>onal Key: module module 13
Our RNA-Seq Experiment Embryo Eye Retina E8 neuronal precursors embryo E18 photoreceptors (PRs) embryo • Question: What mRNAs are up/down regulated in the E8 chicken retina vs E18 retina?
RNA-Seq Output: Differentially Expressed Genes Down regulated list Up regulated list • Question: What mRNAs are up/down regulated in the E8 chicken retina vs E18 retina? • Answer: A lot! -1,077 up regulated -1,416 down regulated 15
RNA-Seq: Cuffdiff output • 1,416 significant (p<0.05) down regulated genes Lots of candidates, what next? • What’s the full gene name? • What’s the associated function of the gene? 16
Example computer-based RNA-Seq Analysis Modules (currently completed prior to course) (in class student ac>vi>es) week #1 week #2 week #3-4 week #5 RNA extrac>on For RNA-Seq RNA extrac>on cDNA qPCR setup for qRT-PCR synthesis Illumina qPCR data RNA-Seq Gene ontology qPCR primer analysis analysis design DNA Subway or Green Line (Cuffdiff out) Retrieve SRA Sequence Sequence RNA-Seq data retrieval annota>on computer-based lab modules • In class or take home activities • Wet lab Computa>onal Key: 2X 20-30 min activities • module module 17
Example computer-based RNA-Seq Analysis Modules (in class student ac>vi>es) www.rnaseqforthenextgeneration.org/ week #2 week #3-4 week #5 qPCR setup qPCR data qPCR primer analysis design Sequence annota>on Wet lab Computa>onal Key: module module 18
Gene Ontology (GO) Analysis of Differentially Expressed Genes 1,077 up regulated genes from RNA-Seq dataset • Gene Ontology (GO) : computational classification of genes based on function -e.g. photoreceptors, phototransduction • In Class Activity I : Use RNA-Seq data for GO analysis and ID all up/down regulated genes associated with the phototransduction pathway 19
GO analysis using Ensembl BioMart 1,077 up regulated genes from RNA-Seq dataset www.ensembl.org/biomart/ Table browser currated by European Bioinformatics Institute & Wellcome Trust Sanger Institute • Filter associated gene names in cuffdiff output through BioMart to obtain full gene names and GO terms 20
GO analysis using Ensembl BioMart *Copy/paste list of 1,077 up regulated gene symbols to filter input window • Filter associated gene names in cuffdiff output through BioMart to obtain full gene names and GO terms 21
GO analysis using Ensembl BioMart *select attributes you want output from the filter • Filter associated gene names in cuffdiff output through BioMart to obtain full gene names and GO terms 22
GO analysis using Ensembl BioMart *Output is sortable list of selected attributes (full gene name, gene symbol, GO term) • Sort or search GO terms associated with candidate genes (ctrl F in Excel) 23
GO analysis using Ensembl BioMart • Sort to ID genes in your favorite pathway -e.g. “phototransduction” & “photoreceptor” • Next step: retrieve & annotate candidate gene sequences 24
Sequence Retrieval & Annotation UCSC Genome Browser: ApE Sequence Editor: • In Class Activity II : Use the UCSC Genome Browser to retrieve genomic & mRNA sequence and the ApE software to annotate sequence features 25
Sequence Retrieval: UCSC Genome Browser UCSC Genome Browser http://genome.ucsc.edu UCSC Genome Browser: • Intuitive genome browser & sequence repository for many genomes 26
Sequence Retrieval: UCSC Genome Browser Rho genomic DNA UCSC Genome Browser http://genome.ucsc.edu UCSC Genome Browser: • Intuitive genome browser & sequence repository for many genomes 27
Sequence Retrieval: UCSC Genome Browser Rho mRNA Rho genomic DNA http://genome.ucsc.edu UCSC Genome Browser: • Intuitive genome browser & sequence repository for many genomes • Next step: annotation of sequence features 28
Sequence Annotation: A Plasmid Editor (ApE) Software Rho mRNA Rho genomic DNA ApE Sequence editing Software: • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC) • Intuitive & versatile sequence editing software 29
Sequence Annotation: A Plasmid Editor (ApE) Software Rho mRNA Rho genomic DNA *copy/paste sequences into new ApE files ApE Sequence editing Software: • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC) • Intuitive & versatile sequence editing software 30
Sequence Annotation: A Plasmid Editor (ApE) Software Rho mRNA Rho genomic DNA *annotate sequence features (splice junctions, primer sequences, etc) *annotated exon junctions in mRNA ApE Sequence editing Software: • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC) • Intuitive & versatile sequence editing software 31
Sequence Annotation: A Plasmid Editor (ApE) Software Rho genomic DNA *annotated “text map” view yields intuitive sequence image ApE Sequence editing Software: • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC) • Intuitive & versatile sequence editing software 32
My Future Directions: Expand My Course Modules (completed prior to course) (in class student ac>vi>es) week #1 week #2 week #3-4 week #5 RNA extrac>on For RNA-Seq RNA extrac>on cDNA qPCR setup for qRT-PCR synthesis Illumina qPCR data RNA-Seq Gene ontology qPCR primer analysis analysis design DNA Subway or Green Line (Cuffdiff out) Retrieve SRA Sequence Sequence RNA-Seq data retrieval annota>on Bioinformatics analysis: DNA Subway Green Line • RNA extraction, quantification & QC wet labs • Wet lab Computa>onal Key: module module 33
Recommend
More recommend
