Single Cell Gene Expression
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Transcript of Single Cell Gene Expression
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Tracking expression one cell at a time
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Why do single cell analysis?
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Limited Sample
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Cellular Complexity
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Cellular Heterogeneity
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Fluidigm is different
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Who wants to be average?
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Many cells
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Multiple genes
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Quality
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Flexibility
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Throughput
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Time
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Cost
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Technology
Workflow
Stories
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Technology
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96.96 48.48
9,216 2,304
Dynamic Array IFCs
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Architecture
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Nanoflex valve open
Fluid Line
Control Line
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Nanoflex valve closed
Fluid Line
Fluid Line
Control Line
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Cells
RT-TSA
Chip
Data
Workflow
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FACS into 10 μL CellsDirect™ master mix
18 cycles
Gene expression analysis
One step RT-TSA
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Transcript Specific Amplification
48/96 assay mix0.2x
PreAmp master mixSingle cell
18 cycles
Preamplified cDNA
1:5 dilution
+ +
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BioMark™ has excellent correlation with the 7900
BioMark system
ABI 7900
r= 0.99
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Workflow is fast and easy
Pipette Load PCR
20 mins 55/90 mins 90 mins
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Sample Protocol
Vol/ sample Total VolμL μL
2x master mix 2.50 120Loading reagent 0.25 12Preamp cDNA 2.25 -Total 5
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Assay Protocol
Vol/ sampleVol/ sampleμL
20x primer probe 2.5Loading reagent 2.5Total 5
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Customer Stories
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Targeting Pathways to Critical Cancer Stem CellsOncomed
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How does BioMark perform on single cells?
48 Samples
Assays x 5Ct
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Expression of 3 genes from a single cell
GSS
β Actin
MALAT1
Δ RN
Cycle
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Standard Curves
Ct
pg RNA
R2= 0.99
GSSβ Actin
R2= 0.99
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Correlation between RNA and cell number
RNA (pg)
β Actin
GSS
R2= 0.999
R2= 0.999
Number of cells
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Single cells from pancreatic a tumour
Ct
High population
Gene assays (x3)
Low population
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Ct
High population Low population
Gene 13
Cell number
Gene 2GAPDH
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7900
Master mix 184 mlPrimer/probe 18 ml384 well plates 96Time 24 days
384 samples x 96 genes
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Master mix 960 μlPrimer/probe 960 μl96.96 chips 4Time 1 day
384 samples x 96 genes
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Resolution of cell fate decisions by Single-Cell Gene Expression Analysis from Zygote to Blastocyst
Guo, G. et al. (2010) Developmental Cell.18, 765
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Resolution of cell fate decisions
BlastocystMorula8 cell4 cell2 cellZygote
NucleusInner cell mass
(ICM)
Trophectoderm (TE)
ICMPrimitive endoderm (PE)
Epiblast (EPI)
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Analysis of individual single cells from blastocysts
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Defining cells by gene expression patterns
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Developmental progression to 3 blastocyst cell types
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Developmental decisions are made at the cellular level
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Decisions are affected by expression of multiple genes
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How did BioMark enable this study?
Many genes in parallel
Single cell resolution over time
Multiple genes = accurate view of cellular phenotype
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Parthenogenic Blastocysts Derived from Cumulus-Free In Vitro Matured Human Oocytes
McElroy, S.L. et al. (2010)PloS. 5, e10979
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Natural vs. IVF
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Expression of patterns ovarian factors and receptors
Calculated normalised relative quantity
Receptor
Ligand
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Expression of patterns ovarian factors and receptors
Receptor
Ligand
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Nuclear maturation of cumulus-free oocytes
Culture media No. of oocytes 24 h 48 h
IVM 46 41.5 50.0
SAGE 45 48.9 68.9
Supplement 98 45.9 54.1
IVM 29 72.4 75.9
SAGE 42 88.1 88.1
Supplement 51 94.1 94.1
GV: germinal vesicleMI: metaphase IVM medium + 10% SPSSAGE: IVM medium + 10% SPS, FSH, hCG, estradiolSupplement: IVM medium + 10% SPS, BDNF, estradiol, IGF-1, GDNF, FGF2, leptin
Nuclear maturation rate (%)
MI
GV
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GAPDH expression in single cells
0
5
10
15
20
9 10 11 12 13 14 15 16 17
Population 1 Population 2
Number of cells
Ct