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1. NAIST Big Data Symposium
Single Cell Analyses for
Plant Reprogramming Study
6 March 2015
Minoru Kubo Ph.D
Humanophilic Project
NAIST
Topics
• Big Data in Biological Science
– Human Genome Project
– Ome and Omics changed Biology
– Next Generation Sequencing (NGS)
• Single Cell Analyses for Plant Reprogramming Study
– What’s Cell?
– What’s Reprogramming?
– Difference of Reprogramming between Animals and Plants
– he Moss Physcomitrella patens
– Why Single Cell Analysis?
– y interest

2. Big Data in Biological Science
Human Genome Project (1990 - 2003)
DNA $
3G$base$pairs$(30 /person$
Budget:$$$3billion$(30 $
Period:$15$years$
(gene) (genome)
e.g. Genome: Gene + -ome. a set of all genes in a organism
Aome:$ $

3. Ome and Omics Changed Biology
-omics: $
Omics Targets Methods
Genomics DNA Next Generation
Sequencing (NGS)
Transcriptomics
(Transcriptome)
RNA Next Generation
Sequencing (NGS)
Proteomics Proteins Mass Spectrometry
(MS)
Metabolomics Metabolites Mass Spectrometry
(MS)
0$
5000$
10000$
15000$
20000$
25000$
30000$
1987$$
1990$$
1993$$
1996$$
1999$$
2002$$
2005$$
2008$$
2011$$
2014$$
Number'of'Papers'
Published'year
Metabolomics$
Proteomics$
Transcriptome$
Genomics$
“omics”'papers'in'PubMed
~4.Mar.2015
Next Generation Sequencing (NGS)
By$HiSeq2500$(illumina)
MiSeq$(illumina)
• 120G$bases$(40x$human$genome)/$day$
• Short$read$(36A250$bases/read)$
• 4G$reads/run$
• $1,000/person$(by$HiSeq$X)$
• Various$applicaUon$(DNA,$RNA,$DNAAprotein$
interacUon$etc.)
Big$data $

4. Single Cell Analyses for Plant
Reprogramming Study
Cell : A Unit of Organisms
• Segmented by membranes (or cell walls).
• A set of the genome (DNA).
• H. sapiens is composed of 6x1013 cells.
• Categorized into 260-270 cell types.
• Derived from one egg cell.
.net

5. Various Cells Originate from a Zygote
Neuron
Lens
Skin
Stomach
Intestine
Lever
Pancreas
Heart
Blood
Bone
Muscle
Zygote
Baby Stem cells Adult Differentiated cells
ES cell
In animals
What’s “Reprogramming”?
“ ” $
$
$
$
Sir. John Gurdon: Reprogramming by nuclear transfer (1962)
Dr. Shinya Yamanaka: Establishment of iPS cells (2006)
Nobel Prize in Physiology or Medicine 2012

6. Plants Are Easily Reprogrammed
Steward et al. (1958) Am. J. Bot.
Differentiated Cells
leaf, root, flower
Reprogramming
Stem cell
Animals Plants
4 genes
(Yamanaka factors)
Wounding
he Moss Physcomitrella patens!
• Genome was opened 26,610 genes).
• 84% of developmental genes were conserved in land
plants
• ene targeting is available.
• Simple structures
Advantage of P. patens

7. Reprogramming Process in the Moss
Physcomitrella patens
a leaf cell changes to an apical stem cell after cutting.
Not All Cells Are Reprogrammed!
Expression$ f$Reprogramming$genes Stem$cell$formaUon

8. What’s the Difference between
Stem and Non-Stem Cells?
Non-stem cells
Stem cells
$
Single cell analysis
Single Cell Transcriptomics
RNA
RNA
https://www.fluidigm.com/products/c1-system
Problems How to get RNA from single cell for NGS?
NGS mRNA 1 ng
Step 1. RNA → DNA
Step 2. Amplification
0.05-0.4 pg of mRNA/ cell

9. efficient transfer of nanoliter bolus material. Finally, the affinity
capture, purification, and concentration process enables the
quantitative analysis of all generated products, a dramatic im-
provement over the use of a traditional cross-injector (28) or
single-cell analys
sion in hESCs w
differentiation in
based on our pre
reactor (22), ou
studies of express
level, once impro
processes are full
offers many exci
ation in gene ex
Materials and M
Additional procedur
Bioprocessor Fabrica
previous nucleic aci
pneumatic manifold
lithographically defi
borofloat 100-mm g
the manifold was d
dimethylsiloxane (P
sides of the 254-␮m
improve PDMS-glass
the manifold and th
The reactor/chan
glass wafer. Fluidic c
on the front side and
chambers along with
on the back side and
resistance temperat
diamond drilled. To
sputter deposited w
photolithographical
30-␮m-wide RTD e
channel wafer was a
a programmable va
To form the rem
wafer was sputter-d
by electroplating 6 ␮
serpentine resistive
by anisotropically et
Jurkat Cell Preparatio
(Nalge–Nunc Interna
Invitrogen) containi
␮M Ac4ManNAz resu
surface glycans (24).
10% FBS (JR Scientifi
depleted medium c
synchronization. Fre
before the analysis
containing 1% FBS
(5Ј-phos-GTA ACG A
The cells were then
introduction into th
Fig. 4. Gene expression and silencing at the single-cell level. (A) Represen-
tative gene expression electropherograms from individual Jurkat cells (1). A
single wild-type cell with primers targeting GAPDH (200 bp) and 18S rRNA (247
bp) generates 2 strong peaks migrating at 160 s and 185 s, respectively (2). A
single cell electroporated with siRNA directed at GAPDH mRNA shows only a
single peak for 18S rRNA. (B) Gene expression of GAPDH for Jurkat cells
treated with GAPDH siRNA relative to normal untreated cells. GAPDH expres-
sion has been normalized to a control 18S rRNA for comparison. Experiments
from 8 individual cells show GAPDH mRNA levels at 0, 5, 50, 1, 48, 0, 5, and 0%
of normally untreated Jurkat cells. However, a representative bulk measure-
ment from 50 cells shows GAPDH expression at 21 Ϯ 4%. When no cell is
captured on the pad there is no amplification. Similarly, a PCR control with no
reverse transcriptase shows no amplification. (C) Histogram of the number of
events for siRNA treated cells shows that there are 2 distinct populations of
cells whose expression levels are very distinct from the population average.
Why Single Cell Analysis?
Singl cell Toriello$et$al.$(2008)$PNAS
wo$expression$paerns$were$found$at$ he$single$cell$level.
velage$of$50$cells
RNA
Findings by Single Cell Analysis
Heterogeneity
$
Xi$(log10(RPKM+1))
Piras$et$al.$(2014)$Sci$Rep$
Fluctuation
$
Guo$et$al.$(2010)$Dev$Cell
Gene$expression$(log2)

10. Next challenge for single cell analysis
Lack of positional information
With positional information,
Cell lineage
Cell-Cell Interaction
New information for multicellular organisms not
only at cellular level but at tissue and organ level
The Microscope with Micromanipulators

11. Cell Sup Extraction by Glass Capillary
bd
c
My Interests
0 h 24 h 36 h
a
12 h
b
a
d
c
b
a
d
c
b
a
d
c
Single cell transcriptome data:
40 cells x 4 cell positions x 4 time points x 26,610 genes
• Identification of reprogramming genes
• Confirmation of border point of stem and non-stem cells
• Detection of cell-cell interaction during reprogramming
• Validation of theory “stochastic” and “elite” model
Basic Logic of Multicellular Organisms

12. Acknowledgements
Prof. Dr. Mitsuyasu Hasebe (NIBB)
Prof. Dr. Ralf Reski (Univ. Freiburg)
Prof. Dr. Taku Demura (NAIST)
Dr. Takashi Murata (NIBB)
Dr. Yosuke Tamada (NIBB)
Dr. Akihiro Imai (NIBB)
Dr. Tomoaki Nishiyama (Kanazawa Univ.)
Dr. Daniel Lang (Univ. Freiburg)
Dr. Olaf Faustmann (Eppendorf)
s. Ritsuko Okamoto (NAIST)