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Page 1: Making Sense Out of Transcriptome Integrative Bioinformatic Approaches Anil Jegga, D.V.M., M.S. Division of Biomedical Informatics Cincinnati Children’s

Making Sense Out of Transcriptome

Integrative Bioinformatic Approaches

Anil Jegga, D.V.M., M.S.Division of Biomedical Informatics

Cincinnati Children’s Hospital Medical CenterDepartment of Pediatrics

University of Cincinnati College of MedicineEmail: [email protected]

Homepage: http://anil.cchmc.org

Page 2: Making Sense Out of Transcriptome Integrative Bioinformatic Approaches Anil Jegga, D.V.M., M.S. Division of Biomedical Informatics Cincinnati Children’s

Acknowledgements• Jing Chen*• Siva Gowrisankar• Vivek Kaimal• Amit Sinha*• Mrunal Deshmukh• Nishanth

Vepachedu• Divya Sardana

• Scott Tabar• Eric Bardes• Bruce Aronow

Page 3: Making Sense Out of Transcriptome Integrative Bioinformatic Approaches Anil Jegga, D.V.M., M.S. Division of Biomedical Informatics Cincinnati Children’s

Annotation DatabasesGene Ontology, Pathways

DNA RepairXRCC1OGG1ERCC1MPG…..

AngiogenesisHIF1AANGPT1VEGFKLF5….

Gene lists associated with similar function/process/pathway

Genome-wide PromotersPutative Regulatory

SignaturesE2FRB1MCM4FOSSIVA…..

PDX1GLUT2PAX4PDX1IAPP….

p53CDKN1ACTSDCASPDDB2….

Expression Profile - Gene Lists

Enrichment Analysis

ObservedExpected

E2FRB1MCM4FOS…

AngiogenesisHIF1AANGPT1VEGF…..

DNA RepairXRCC1OGG1ERCC1MPG….

P53CTSDCASPDDB2….

Random Distribution

Significant Enrichment

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• Gene Ontology• Pathways• Phenotype/Disease

Association• Protein Domains• Protein Interactions• Expression in other

tissues/experiments

I have a list of co-expressed mRNAs (Transcriptome)….Now what?

• Known transcription factor binding sites (TFBS)• Conserved• Non-conserved

• Unknown TFBS or Novel motifs• Conserved• Non-conserved

• MicroRNAs

2. Identify the underlying biological theme

1. Identify putative shared regulatory elements

Give a man a fish and you feed him for a day.Teach a man to fish and you feed him for a lifetime

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Biological question: Are co-expressed genes co-regulated?

Gene Regulatory Networks (GRNs)

Do they share cis-elements or TFBSs?Are there any significant common

motifs within the promoter regions?

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Genome Browser Gateway choices:1. Select Clade2. Select genome/species: You can search only one species at a time3. Assembly: the official backbone DNA sequence4. Position: location in the genome to examine or search term (gene symbol,

accession number, etc.)5. Image width: how many pixels in display window; 5000 max6. Configure: make fonts bigger + other options

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1. Select “refFlat” under “table”

2. Ensure that “region” is “genome”

3. Click on “paste list”

1. Paste the gene symbols2. Remember it is case-sensitive:

• Human: all upper case (e.g. XRCC1)• Mouse: lower case (first letter upper case.

E.g. Xrcc1)

Enter number of bp you want to analyze/download

Select the output format as “custom track”

Describe your track

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Try GTF output too

1. Select “Variation and Repeats” under “Group”

2. Click on “create” under “intersection”

Change the “group” to “Custom Tracks” and select the appropriate “track” and “table”

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One drawback with this output is it doesn’t tell you which SNPs are in the upstream region of which gene. However, since the positions of SNPs are included, you can compare them with the gene coordinates and figure it out .

Genome Browser view that lists all the SNPs lying within the upstream 1 kb (the region we queried) region of one of the genes analyzed.

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You need to have a login account; contact [email protected]

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DiRE: http://dire.dcode.org

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http://www.cisreg.ca/oPOSSUM/

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http://genometrafac.cchmc.org

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Biological question: Are co-expressed genes functionally

similar?

Functional Networks

Do they share same GO terms or pathways?

Are there any significant enriched terms within a group of gene list?

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http://david.abcc.ncifcrf.gov/

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You can compare multiple lists!

http://www.pantherdb.org/

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ToppGene – General Schema

http://toppgene.cchmc.org

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TOPPGene - Data Sources1. Gene Ontology: GO and NCBI Entrez Gene2. Mouse Phenotype: MGI (used for the first time for

human disease gene prioritization)3. Pathways: KEGG, BioCarta, BioCyc, Reactome,

GenMAPP, MSigDB4. Domains: UniProt (Pfam, Interpro,etc.)5. Interactions: NCBI Entrez Gene (Biogrid, Reactome,

BIND, HPRD, etc.)6. Pubmed IDs: NCBI Entrez Gene7. Expression: GEO8. Cytoband: MSigDB9. Cis-Elements: MSigDB10. miRNA Targets: MSigDB

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http://www.fatigo.org

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http://vortex.cs.wayne.edu/projects.htm

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• My NCBI: Can create/store queries; Set mail options to receive new articles on your chosen queries/subjects

• PubMed Limits: Useful to refine your queries and get more appropriate results

• Preview/Index: You can customize (intersect, etc.) your previous queries

• My NCBI: Can create/store queries; Set mail options to receive new articles on your chosen queries/subjects

• PubMed Limits: Useful to refine your queries and get more appropriate results

• Preview/Index: You can customize (intersect, etc.) your previous queries


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