NAISTビッグデータシンポジウム - バイオ久保先生
Published on: Mar 3, 2016
Transcripts - NAISTビッグデータシンポジウム - バイオ久保先生
NAIST Big Data Symposium
Single Cell Analyses for
Plant Reprogramming Study
6 March 2015
Minoru Kubo Ph.D
• 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
Big Data in Biological Science
Human Genome Project (1990 - 2003)
e.g. Genome: Gene + -ome. a set of all genes in a organism
Ome and Omics Changed Biology
Omics Targets Methods
Genomics DNA Next Generation
RNA Next Generation
Proteomics Proteins Mass Spectrometry
Metabolomics Metabolites Mass Spectrometry
Next Generation Sequencing (NGS)
Single Cell Analyses for Plant
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.
Various Cells Originate from a Zygote
Baby Stem cells Adult Differentiated cells
“ ” $
Sir. John Gurdon: Reprogramming by nuclear transfer (1962)
Dr. Shinya Yamanaka: Establishment of iPS cells (2006)
Nobel Prize in Physiology or Medicine 2012
Plants Are Easily Reprogrammed
Steward et al. (1958) Am. J. Bot.
leaf, root, flower
he Moss Physcomitrella patens!
• Genome was opened 26,610 genes).
• 84% of developmental genes were conserved in land
• ene targeting is available.
• Simple structures
Advantage of P. patens
Reprogramming Process in the Moss
a leaf cell changes to an apical stem cell after cutting.
Not All Cells Are Reprogrammed!
Expression$ f$Reprogramming$genes Stem$cell$formaUon
What’s the Difference between
Stem and Non-Stem Cells?
Single cell analysis
Single Cell Transcriptomics
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
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
sion in hESCs w
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
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Jurkat Cell Preparatio
M Ac4ManNAz resu
surface glycans (24).
10% FBS (JR Scientiﬁ
depleted medium c
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
Findings by Single Cell Analysis
Next challenge for single cell analysis
Lack of positional information
With positional information,
New information for multicellular organisms not
only at cellular level but at tissue and organ level
The Microscope with Micromanipulators
Cell Sup Extraction by Glass Capillary
0 h 24 h 36 h
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
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)