single cell gene expression
Post on 19-Oct-2014
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DESCRIPTION
TRANSCRIPT
Tracking expression one cell at a time
Why do single cell analysis?
Limited Sample
Cellular Complexity
Cellular Heterogeneity
Fluidigm is different
Who wants to be average?
Many cells
Multiple genes
Quality
Flexibility
Throughput
Time
Cost
Technology
Workflow
Stories
Technology
96.96 48.48
9,216 2,304
Dynamic Array IFCs
Architecture
Nanoflex valve open
Fluid Line
Control Line
Nanoflex valve closed
Fluid Line
Fluid Line
Control Line
Cells
RT-TSA
Chip
Data
Workflow
FACS into 10 μL CellsDirect™ master mix
18 cycles
Gene expression analysis
One step RT-TSA
Transcript Specific Amplification
48/96 assay mix0.2x
PreAmp master mixSingle cell
18 cycles
Preamplified cDNA
1:5 dilution
+ +
BioMark™ has excellent correlation with the 7900
BioMark system
ABI 7900
r= 0.99
Workflow is fast and easy
Pipette Load PCR
20 mins 55/90 mins 90 mins
Sample Protocol
Vol/ sample Total VolμL μL
2x master mix 2.50 120Loading reagent 0.25 12Preamp cDNA 2.25 -Total 5
Assay Protocol
Vol/ sampleVol/ sampleμL
20x primer probe 2.5Loading reagent 2.5Total 5
Customer Stories
Targeting Pathways to Critical Cancer Stem CellsOncomed
How does BioMark perform on single cells?
48 Samples
Assays x 5Ct
Expression of 3 genes from a single cell
GSS
β Actin
MALAT1
Δ RN
Cycle
Standard Curves
Ct
pg RNA
R2= 0.99
GSSβ Actin
R2= 0.99
Correlation between RNA and cell number
RNA (pg)
β Actin
GSS
R2= 0.999
R2= 0.999
Number of cells
Single cells from pancreatic a tumour
Ct
High population
Gene assays (x3)
Low population
Ct
High population Low population
Gene 13
Cell number
Gene 2GAPDH
7900
Master mix 184 mlPrimer/probe 18 ml384 well plates 96Time 24 days
384 samples x 96 genes
Master mix 960 μlPrimer/probe 960 μl96.96 chips 4Time 1 day
384 samples x 96 genes
Resolution of cell fate decisions by Single-Cell Gene Expression Analysis from Zygote to Blastocyst
Guo, G. et al. (2010) Developmental Cell.18, 765
Resolution of cell fate decisions
BlastocystMorula8 cell4 cell2 cellZygote
NucleusInner cell mass
(ICM)
Trophectoderm (TE)
ICMPrimitive endoderm (PE)
Epiblast (EPI)
Analysis of individual single cells from blastocysts
Defining cells by gene expression patterns
Developmental progression to 3 blastocyst cell types
Developmental decisions are made at the cellular level
Decisions are affected by expression of multiple genes
How did BioMark enable this study?
Many genes in parallel
Single cell resolution over time
Multiple genes = accurate view of cellular phenotype
Parthenogenic Blastocysts Derived from Cumulus-Free In Vitro Matured Human Oocytes
McElroy, S.L. et al. (2010)PloS. 5, e10979
Natural vs. IVF
Expression of patterns ovarian factors and receptors
Calculated normalised relative quantity
Receptor
Ligand
Expression of patterns ovarian factors and receptors
Receptor
Ligand
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
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