Loyola Genomics Facility
Michael J. Zilliox
Loyola Genomics Facility
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Loyola Genomics Facility (Google
“Loyola Genomics”)
genomics.luc.edu
Research Channel in Loyola Wired
Ion Torrent Personal Genome
Machine
2 Illumina MiSeq Sequencers
Gina Kuffel- Lab Manager
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Funding:
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P01- Nishimura
R01- Le Poole
R56- Brubaker
P20- Wolfe
RFC- Hutchens
Astellas
Kimberly-Clark
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Collaborating Facilities
• University of Chicago
– Illumina microarrays
– RNA-Seq
• Notre Dame
– RNA-Seq
– Proteomics
• Johns Hopkins
– Affymetrix microarrays
Protocols
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Amplicon Sequencing
– Variant analysis
– 16S rRNA sequencing
(microbiome, virome, fungiome)
Whole Genome Sequencing
– Bacterial genomes
– Viral genomes
Gene Expression Analysis
– Affymetrix, Illumina bead arrays,
Illumina RNA-Seq, NanoString,
bacterial RNA-seq,
– miRNA-seq
Beyond Heatmaps
Classic Gene Expression Analysis
Classic Gene Expression Analysis
Control
Experimental Sample
New Gene Expression Analysis
Experimental Sample
Control
No Change
New Gene Expression Analysis
Experimental Sample
Control
No Change
Why???
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Determine the components of normal cells
Discover genes missed due to variation
Find genes that are potentially co-regulated
Discover biomarkers/make clinical predictions
Example 1- Naive, Normal
Components
Human Immune Cell Transcriptomes
Cell Type
Broadly
Expressed
N
Genes
ImmuneExpressed specific
3212
1319
0
CD8+ T cells
4
4510
68
CD4+ T cells
9
4083
37
B cells
4
5066
192
CD14+
monocytes
13
3652
42
Alveolar
macrophages
11
4465
178
Human Naïve CD8+ T Cell
3
10
277
1453
400
138
61
263
222
149
263
15
16 1132
14 404
51
1. Nucleolus 5. Rough ER*
9. Mitochondrion
2. Nucleus
6. Golgi apparatus 10. Vacuole
3. Ribosome 7. Cytoskeleton
11. Cytosol
4. Vesicle
8. Smooth ER*
12. Lysosome
*Rough ER and Smooth ER are combined
13. Centriole
14. Plasma membrane
15. Extracellular region
16. Unannotated
Image from Wikimedia Commons: Authors MesserWoland and Szczepan1990
Proteome Comparison
B Cells
CD4 T Cells
CD8 T Cells
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10
−5
Unexpressed
Unexpressed
Expressed
Expressed
Barcode Value
Barcode Value
−10
−5
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−10
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0
Proteomics Value
0
Proteomics Value
0
−5
−10
Proteomics Value
5
5
5
10
10
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Unexpressed
Expressed
Barcode Value
Example 2- Discover genes
missed due to variation
Finding Variable Genes
12
10
2
4
6
8
Log2 Fluorescence
10
8
6
4
2
Log2 Fluorescence
12
14
MAL2
14
CD82
Chromophobe
Control (Dap)
Oncocytoma
Control (Dap)
Chromophobe
Control (Dap)
Oncocytoma
Control (Dap)
Classic Analysis
321
Classic
781
547
Barcode
Example 3- Find genes that are
potentially co-regulated
New Gene Expression Analysis
Control
Enhancer?
Up-regulated
Transcription Factor?
No Change
Experimental Sample
Example 4- Discover Biomarkers
Biomarker Discovery
Normal
Tumor
Gene 1- Up-regulated 2 fold
Gene 2- Off in whole cell/On in tumor
Survival
William Adams
Models
Hazard Ratio
95% CI
Model 1
P value
0.01
Spectrin
4.29
1.60-11.51
0.004
CAND1
0.99
0.26-3.82
0.99
HNRDL
1.20
0.30-4.89
0.80
Stage III and IV
(vs. I and II)
4.11
0.91-18.67
0.07
Spectrin
3.43
1.37-8.57
0.01
Model 2
Model 3
<0.001
ECE
4.08
1.62-10.26
0.003
Spectrin
4.57
1.85-11.29
0.001
William Adams
Model 4
Spectrin
3.85
1.52-9.76
0.004
Stage III and IV
(vs I and II)
2.71
0.55-13.30
0.22
ECE
3.23
1.24-8.40
0.02
Acknowledgements
Loyola University
Loyola Microbiome
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•Linda Brubaker
•Alan Wolfe
•Meghan Pearce
•Krystal Thomas-White
•Katherine Radek
Gina Kuffel
Michael Nishimura
David Murray
Jose Guevara-Patino
Susan Zelisko
Shiayin Yang
William Adams
Carol Bier-Laning
Others
MUSC
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Chrystal Paulos
Jake Bowers
Shikhar Mehrotra
Mark Rubinstein
Elizabeth Garrett-Mayer
• Rafael Irizarry
• Matt McCall
• Harris Jaffee
Barcode website: Google “Gene Expression Barcode”
barcode.luhs.org
The End