Integration of RNA-Seq Data Analysis into Undergraduate Lab Teaching - - PowerPoint PPT Presentation

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Integration of RNA-Seq Data Analysis into Undergraduate Lab Teaching - - PowerPoint PPT Presentation

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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

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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

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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)

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Milestones in Genome Sequencing

  • 2000. Arabidopsis

1st Plant Genome. 135 Mbp

  • 1995. Fleischmann et al.

1st Free Living Organism

  • H. influenza 1.8 Mbp
  • 1977. Sanger et al.

1st Complete Organism Bacteriophage; 5375 bp 2001. Venter et al., IHGSC Human Genome; 2.9 Gbp

~13 years + ~$3 billion

  • 1998. 1st Multicellular Organism
  • C. elegans; 97 Mbp

*all completed using Sanger sequencing

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The Impact of “Next Generation” Sequencing

Completion of Human Genome Project (2001) Source: NHGRI

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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

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“Next Generation” Sequencing (and beyond)

Roche 454 (2007) Illumina (2009) Ion Torrent (2010) Nanopore MinION (2015)

  • Reduced cost of “Next gen” sequencing platforms have made genome-wide

analysis available to the masses

“3rd Generation!” “Next Gen” Sequencing Platforms

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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
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Main objective:

  • Assist PUI faculty to integrate authentic Next-Gen Sequence analysis

into undergraduate course work

  • RNA-sequencing (RNA-seq) analysis as vehicle

Infrastructure & Training to Bring Next-Generation Sequence Analysis into Undergraduate Education project

(PI: Dave Micklos, CSHL DNA Learning Center)

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
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Program Website

www.rnaseqforthenextgeneration.org/

  • T

eaching Resources, Virtual Training, RNA-Seq Data Sets

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Program Website

www.rnaseqforthenextgeneration.org/

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JMU Biosciences building

About James Madison University

  • Public PUI; Harrisonburg,

VA

  • ~19,000 undergraduates
  • ~60% admission rate
  • ~1,000 Biology/Biotech majors
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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

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cDNA synthesis qPCR primer design qPCR setup Gene ontology analysis Sequence retrieval RNA extrac>on For RNA-Seq RNA extrac>on for qRT-PCR Illumina RNA-Seq Retrieve SRA RNA-Seq data

(in class student ac>vi>es)

qPCR data analysis

  • r

week #1 Sequence annota>on week #2 week #3-4 week #5 Wet lab module Computa>onal module

Key:

(currently completed prior to course)

DNA Subway Green Line (Cuffdiff out)

BIO480 Course-embedded Research Modules

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Embryo Eye Retina

E8 embryo E18 embryo

Our RNA-Seq Experiment

photoreceptors (PRs) neuronal precursors

  • Question: What mRNAs are up/down regulated in the E8 chicken retina vs E18 retina?
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RNA-Seq Output: Differentially Expressed Genes

  • 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

Up regulated list Down regulated list

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  • 1,416 significant (p<0.05) down regulated genes

RNA-Seq: Cuffdiff output

Lots of candidates, what next?

  • What’s the full gene name?
  • What’s the associated function of the gene?
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cDNA synthesis qPCR primer design qPCR setup Gene ontology analysis Sequence retrieval RNA extrac>on For RNA-Seq RNA extrac>on for qRT-PCR Illumina RNA-Seq Retrieve SRA RNA-Seq data

(in class student ac>vi>es)

qPCR data analysis

  • r

week #1 Sequence annota>on week #2 week #3-4 week #5 Wet lab module Computa>onal module

Key:

(currently completed prior to course)

DNA Subway Green Line (Cuffdiff out)

Example computer-based RNA-Seq Analysis Modules

  • computer-based lab modules
  • In class or take home activities
  • 2X 20-30 min activities
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qPCR primer design qPCR setup

(in class student ac>vi>es)

qPCR data analysis Sequence annota>on week #2 week #3-4 week #5 Wet lab module Computa>onal module

Example computer-based RNA-Seq Analysis Modules

Key: www.rnaseqforthenextgeneration.org/

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  • Gene Ontology (GO): computational

classification of genes based on function

  • e.g. photoreceptors, phototransduction

Gene Ontology (GO) Analysis of Differentially Expressed Genes

1,077 up regulated genes from RNA-Seq dataset

  • In Class Activity I: Use RNA-Seq data for GO analysis and ID all up/down

regulated genes associated with the phototransduction pathway

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GO analysis using Ensembl BioMart

  • Filter associated gene names in cuffdiff output through BioMart to
  • btain full gene names and GO terms

www.ensembl.org/biomart/

Table browser currated by European Bioinformatics Institute & Wellcome Trust Sanger Institute

1,077 up regulated genes from RNA-Seq dataset

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GO analysis using Ensembl BioMart

  • Filter associated gene names in cuffdiff output through BioMart to
  • btain full gene names and GO terms

*Copy/paste list of 1,077 up regulated gene symbols to filter input window

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GO analysis using Ensembl BioMart

  • Filter associated gene names in cuffdiff output through BioMart to
  • btain full gene names and GO terms

*select attributes you want

  • utput from the filter
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GO analysis using Ensembl BioMart

  • Sort or search GO terms associated with candidate genes (ctrl F in Excel)

*Output is sortable list of selected attributes (full gene name, gene symbol, GO term)

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GO analysis using Ensembl BioMart

  • Sort to ID genes in your favorite pathway
  • e.g. “phototransduction” & “photoreceptor”
  • Next step: retrieve & annotate candidate gene sequences
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UCSC Genome Browser:

  • In Class Activity II: Use the UCSC Genome Browser to retrieve genomic & mRNA

sequence and the ApE software to annotate sequence features

Sequence Retrieval & Annotation

ApE Sequence Editor:

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UCSC Genome Browser

UCSC Genome Browser:

  • Intuitive genome browser & sequence repository for many genomes

http://genome.ucsc.edu

Sequence Retrieval: UCSC Genome Browser

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Rho genomic DNA UCSC Genome Browser

http://genome.ucsc.edu

Sequence Retrieval: UCSC Genome Browser

UCSC Genome Browser:

  • Intuitive genome browser & sequence repository for many genomes
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Rho mRNA Rho genomic DNA

http://genome.ucsc.edu

Sequence Retrieval: UCSC Genome Browser

UCSC Genome Browser:

  • Intuitive genome browser & sequence repository for many genomes
  • Next step: annotation of sequence features
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Rho genomic DNA

Sequence Annotation: A Plasmid Editor (ApE) Software

Rho mRNA

ApE Sequence editing Software:

  • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC)
  • Intuitive & versatile sequence editing software
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Rho genomic DNA

Sequence Annotation: A Plasmid Editor (ApE) Software

Rho mRNA

ApE Sequence editing Software:

  • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC)
  • Intuitive & versatile sequence editing software

*copy/paste sequences into new ApE files

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31 *annotated exon junctions in mRNA

Sequence Annotation: A Plasmid Editor (ApE) Software

ApE Sequence editing Software:

  • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC)
  • Intuitive & versatile sequence editing software

Rho genomic DNA Rho mRNA

*annotate sequence features (splice junctions, primer sequences, etc)

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Rho genomic DNA

Sequence Annotation: A Plasmid Editor (ApE) Software

ApE Sequence editing Software:

  • Freely available at biologylabs.utah.edu/jorgensen/wayned/ape/ (Mac/PC)
  • Intuitive & versatile sequence editing software

*annotated “text map” view yields intuitive sequence image

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cDNA synthesis

(completed prior to course)

qPCR primer design qPCR setup Gene ontology analysis Sequence retrieval RNA extrac>on For RNA-Seq RNA extrac>on for qRT-PCR Illumina RNA-Seq Retrieve SRA RNA-Seq data

(in class student ac>vi>es)

qPCR data analysis

  • r

week #1 Sequence annota>on week #2 Wet lab module Computa>onal module

Key:

DNA Subway Green Line (Cuffdiff out) week #3-4 week #5

My Future Directions: Expand My Course Modules

  • Bioinformatics analysis: DNA Subway Green Line
  • RNA extraction, quantification & QC wet labs
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  • 2016

Virtual Workshop : 40 additional PUI faculty to be trained

  • Program website development is ongoing

www.rnaseqforthenextgeneration.org/

Program Future Directions: Continue to Train PUI Faculty

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2014 RNA-Seq Working Group

Thanks!

  • CHSL DNA Learning Center
  • Dave Micklos, Mona Spector
  • JMU Biology + GCEMS
  • RNA-Seq Working Group
  • Scott Woody (UW-Madison)
  • Funding
  • JMU 4-VA; CHRB

contact: enkera@jmu.edu www.rnaseqforthenextgeneration.org/

CHRB