IIT Madras, July 2011

1. Inference of gene expression regulation
by miRNA using MiRaGE method
Y­h. Taguchi/Dept.Phys.,Chuo Univ.
Jun Yasuda /School Med.,Tohoku Uinv.

2. Three Topics:
Inference of transfection of miRNA to human
lung cancer cell
Inference of gene regulation via miRNA in
murine medulloblastoma
Identification of critical miRNAs for ES
stemness during differentiation to neuronal
cells

3. Regulation of gene expression via miRNA
Computer oriented prediction
(uncertain)
Target genes genome
microRNA mRNA
microRNA mRNA 3

4. miRNA target gene list
Gene8
Gene7
Gene6
Gene5
Gene4
Gene3
Gene2
Gene1
simple seed match
(Virtual)
miRNA1 ○×○○○○××
miRNA2 ○×○○××○○
Prediction miRNA3 ×○○×○○××
miRNA4 ○○○×○○××
VS
Human lung cancer
Murine medulloblastoma
gene1 Murine ES cell
gene2 miRNA1
Real
gene3
4

5. Control Treated
Gather the information of miRNA targets
Compare the expressions of targets for each
miRNAs (see Next Slides)
Calculate False Discovery Rate
Generate ranking
5

6. MiRaG
miRNA Targets E Down P­value FDR
miR­a 54 3 0.5 0.4
miR­b 120 54 0.0001 0.005
miR­c 36 1 0.5 0.7
... ... ... ... ...
miR­X 60 18 0.001 0.007
Reject miR­a & c because the FDR > 0.05
Filtrate with miRNA expression profiles
Ranking 6

7. Topics 1
Inference of transfection of miRNA to human
lung cancer cell

8. Gene expression by
Array: Agilent
at
One and three days
after transfection of
Mir­107, mir­185, and let­7a.
log(xg[miRNA]) vs log(xg[Control])
xg: gene expression
Target gene list: simple seed match
ICIC2011, LNBI in press. (2011/8/11­14)

9. Transfected miRNA
mir­107 mir­185 let­7a
time replicate 1 replicate 2 replicate 1 replicate 2 replicate 1 replicate 2
day1 1[1st] 1[1st] 7[1st] 9[1st] 2[1st] 2[1st]
day3 1[1st] 0[­­­] 0[1st] 0[­­­] 1[1st] 1[1st]
Numbers of significant miRNAs.
The ranks of transfected micriRNAs are shown in
square brackets.
Transfected miRNAs are
correctly identified by MiRaGE
method.

10. Topics 2
Inference of gene regulation via miRNA in
murine medulloblastoma

11. Materials
(established at Tastuo Noda group)
P6＝6 days after birth, normal but growing
P6
P30＝30 days after birth, normal and not
P30
growing
MB＝a few month after birth, malignant
MB
neoplasm
30% of the Ptc1 +/­ mice suffers from MB.
11

12. mRNA/miRNA expression by
Array: Agilent
at
P6, P30 and MB
log(xg[mRNA/miRNA:MB or P6])
vs
log(xg[mRNA/miRNA:P30])
xg: mRNA/miRNA expression
12
Target gene list: simple seed match

13. t test for miRNA expression
log(xg[miRNA:P6/MB]) vs log(miRNA:xg[P30])
of considered miRNA(*)
(*) each miRNA is measured by multiple probe
13

14. t test for miRNA target genes (MiRaGE method)
log(xg[mRNA:P6/MB]) – log(xg[mRNA:P30])
in target genes of considered miRNA
V
S
log(xg[mRNA:P6/MB]) – log(xg[mRNA:P30])
in target genes of
any of other miRNA
14

15. selected by
miRNA miRNA expression / MiRaGE
miRNA P30<MB
1 mmu-miR-25 1 1
target gene P30>MB
2 m m u-m iR-466i-5p 1 1
3 mmu-miR-92a 0.75 1
4 mmu-miR-19a 1 0.69 miR­17~92 cluster family
5 mmu-miR-19b 1 0.69 members are ranked in top 5
members
6 m m u-m iR-3082-5p 1 0.56 by combination of MiRaGE
7 m m u-m iR-130a 1 0.5 methods and miRNA
8 m m u-m iR-130b 1 0.5 expression profiling.
9 m m u-m iR-15b 1 0.5
10 m m u-m iR-2861 1 0.5
11 m m u-m iR-3096-5p 1 0.5
12 m m u-m iR-32 0.5 1
13 m m u-m iR-322 1 0.5
14 m m u-m iR-721 1 0.5
15 m m u-m iR-149* 0.5 0.88
16 m m u-m iR-3081* 1 0.38
17 m m u-m iR-574-5p 1 0.31
18 m m u-m iR-669n 0.5 0.81 suggested contribution to
15
19 m m u-m iR-1187 1 0.25
cancer formation

16. selected by
miRNA P30>MB
miRNA miRNA expression / MiRaGE
m m u-m iR-100 1 1
target gene P30<MB
m m u-m iR-126-3p 1 1
mmu-miR-29c 1 1 Some of the neuron­
mmu-miR-376a 1 1 specific miRNAs and
specific miRNA
m m u-m iR-451 1 1 tumor­suppressive
m m u-m iR-99b 1 1 miRNAs seem to contribute
miRNAs
m m u-m iR-136* 1 0.9375
to the gene expression
m m u-m iR-299* 0.75 1
profiles of P30.
mmu-miR-26a 1 0.5
mmu-miR-26b 1 0.5
mmu-miR-29a 0.5 1
mmu-miR-7a-1* 1 0.5
m m u-m iR-3107 1 0.4375
m m u-m iR-340-5p 1 0.3125
m m u-m iR-369-5p 1 0.3125
mmu-let-7a 1 0.25
tumor­suppressive miRNAs
mmu-let-7e 1 0.25
mmu-let-7g 1 0.25 neuron­specific miRNAs
16
mmu-let-7i 1 0.25

17. selected by
miRNA miRNA expression / MiRaGE
miRNA P30<P6
1 mmu-miR-106b 1.00 1.00
target gene P30>P6
2 m m u-m iR-130a 1.00 1.00
3 m m u-m iR-130b 1.00 1.00
4 m m u-m iR-15b 1.00 1.00 miR­17~92, mir­106b­
5 mmu-miR-17 1.00 1.00 25,mir­106a­363
6 mmu-miR-20a 1.00 1.00 cluster family members are
7 mmu-miR-20b 1.00 1.00 ranked in top 5 by
8 m m u-m iR-301b 1.00 1.00 combination of MiRaGE
9 m m u-m iR-322 1.00 1.00 methods and miRNA
10 m m u-m iR-721 1.00 1.00 expression profiling.
11 mmu-miR-93 1.00 1.00
12 m m u-m iR-542-3p 1.00 0.94
13 m m u-m iR-3081* 1.00 0.88
14 m m u-m iR-335-3p 1.00 0.88
15 m m u-m iR-199a-5p 1.00 0.81
16 m m u-m iR-199b* 1.00 0.81
17 mmu-miR-19a 1.00 0.81
17
18 mmu-miR-1 9 b 1.00 0.81

18. selected by
miRNA miRNA expression / MiRaGE miRNA P30>P6
m m u-m iR-29c 1.00 1.00 target gene P30<P6
mmu-miR-376a 1.00 1.00
m m u-m iR-451 1.00 1.00
Some of the neuron­
mmu-let-7b 1.00 0.94
specific miRNAs and
specific miRNA
mmu-let-7e 1.00 0.94
tumor­suppressive
mmu-let-7g 1.00 0.94
miRNAs seem to contribute
miRNAs
mmu-let-7i 1.00 0.94
m m u-m iR-98 1.00 0.94
to the gene expression
profiles of P30.
m m u-m iR-126-3p 0.75 1.00
m m u-m iR-299* 0.75 1.00
m m u-m iR-29a 0.75 1.00
mmu-let-7a 0.75 0.94
m m u-m iR-3070b-3p 1.00 0.69
m m u-m iR-138 1.00 0.63
m m u-m iR-3107 1.00 0.56
m m u-m iR-181a-1* 0.50 1.00 tumor­suppressive miRNAs
mmu-let-7d 0.50 0.94
neuron­specific miRNAs
18
m m u-m iR-1937b 0.25 1.00

19. MiRaGE method + miRNA expression
successfully pick up biologically important
miRNAs. Further (wet) experiments which
supress miRNA expression with tiny LNA is
now planed.
If it is successful, our method can find miRNAs
which control tumor formation.
Published in IPSJ Technical report,
2011­SIGBIO­25, No5, pp.1­6
19

20. Topics 3
Identification of critical miRNAs for ES
stemness during differentiation to neuronal
cells

21. Materials:
Gene expression data is downloaded from GEO by the
Gene expression
accession number GSE11523, “Defining Developmental
Potency and Cell Lineage Trajectories by Expression
Profiling of Differentiating Mouse ES Cells”.
In this study, among those, data for the differentiation from
ES cells to neuronal cells are used.
In parallel, we analyzed the difference of miRNA
expression profiles between 2 datasets from ES cells and
6 datasets from mature neuronal tissues(*) and listed up
the ES cell specific miRNAs.
*) http://www.mirz.unibas.ch/cloningprofiles/

22. m iRNAs
m m u-m iR-200b
ratio
1.00
miRNA ES> Neuronal Cell
>
m m u-m iR-200c (+) 1.00 target gene ES< Neuronal Cell
<
m m u-m iR-23a 1.00
m m u-m iR-23b 1.00
mmu-miR-291a-3p 1.00
mmu-miR-429 1.00
mmu-miR-294 0.98
mmu-miR-295 0.98
m m u-m iR-302a (+) 0.98
m m u-m iR-302b (+) 0.97
m m u-m iR-302d (+) 0.97
m m u-m iR-199a-5p 0.94
m m u-m iR-141 0.69
m m u-m iR-200a 0.69
m m u-m iR-409-3p 0.67
m m u-m iR-369-3p (+) 0.36
m m u-m iR-96 0.11
m m u-m iR-674 0.08
Mallanna, S.K., and Rizzino., A.(2010)
m m u-m iR-467b 0.06

23. Our method identified critical miRNAs for ES
stemness including iPS inducing miRNAs (marked
with “+”in the previous slide) recently reported by
Miyoshi, et al.(2011, Cell Stem Cell).
Published in IPSJ Technical report,
2011­BIO­25, No.38, pp.1­ 2

24. miRNA is short non­coding RNA which
regulate many biological processes ranging
from cancer formation to differentiation.
We have proposed a new method, MiRaGE,
MiRNA Ranking by Gene Expression, which
assists to discriminate which miRNA really
regulate target genes.
Since there are some technical method which
suppress miRNA machinery, it can also be a
drug candidates related to several biological
processes.

25. Acknowledgements:
We thank Drs. Tetsuo Noda and
Katsuyuki Yaginuma for
providing reagents (Topics 2).
These works were supported by
KAKENHI (23300357) .

26. S e rve r w ill b e s o o n a va ila b le a t:
h ttp ://w w w .g ra n u la r.c o m /MiRa G E.h tm l
e -m a il: ta g @ g ra n u la r.c o m