La transition fruit immature/fruit mature: analyse globale des ... - ensat

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Sep 29, 2013 (4 years and 3 months ago)

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La transition fruit
immature/fruit mature:
analyse
globale des profils
analyse
globale des profils
transcriptomiques
S
Jean-Paul Roustan, Pavel
S
enin
Autres Contributeurs:
UMR 990 INRA/INP-ENSAT Génomique et Biotechnologie des Fruits
C. Chervin, M. Zouine, E. Maza, E. Pur
g
ato, L. Su, P. Frasse, O. Berseille, M. Bouza
y
en
Maturation des fruits
Chan
g
ement
p
h
y
siolo
g
i
q
ues et biochimi
q
ues
p
rofonds:
* Activité respiratoire :
-au
g
mentation subite et intense
gpygqqp
g
chez les fruits climactériques
-pas de changement d'intensité
chez les fruits non climactériques
chez les fruits non climactériques
* Diminution de la fermeté
* Formation de pigments
* Élti d t d id
* É
vo
l
u
ti
on
d
es

sucres

e
t d
es

ac
id
es
* Biosynthèse d’arômes
Régulation du développement des fruits
par les hormones
par les hormones
Éthylène (Déclenche et module la maturation)
Auxine (division cellulaire; inhibiteur de maturation?)
Gibbérellines (développement du fruit)
Cytokinines
(division cellulaire)
Cytokinines
(division cellulaire)
Acide Abscissique
(dormance des graines)
Régulation de la Maturation des fruits
cli
m
actéri
q
ues
mqu
Éthlè
Éth
y

ne
-Production autocatylique de l’éthylène
-
Autonomie de maturation
-
Autonomie de maturation
Q
uel
q
ues fruits climactéri
q
ues:
Qqq
abricot, avocat, banane, kiwi, melon,

pêche, poire, pomme, tomate …
MATURATION
DES FRUITS
Odeur
Arômes
Perception
Ethylene
Autres signaux
Hormonaux dont auxine
Goût
C=CC=C
HHH
H
HHHH
Ethylene
Goût
Transduction du signal
C2H4
Autocatalytique
C
sucres
acides
Arôme
Crosstalk
C
Vacuole
Noyau
Facteurs de Transcription
Couleur
Pigments
Respiration
Gènes de
maturation
DNA
PROGRAMME GENETIQUE
Dégradation des membranes
Chromoplaste
Mitochondrie
Dégradation de la paroi
Ramollissement
d'après JC Pech
Maturation du fruit de Tomate
AutocatalytiqueAutoinhibition
Production
d’éthylène
Transition fruit immature/fruit mature
ou
Comment le fruit acquière sa capacité à murir ?
fl ié d l’éhlè d l’i
Comment le fruit acquière sa capacité à murir ?
I
n
fl
uence

cro
i
s
é
e
d
e
l’é
t
h
y

ne

et
d
e
l’
aux
i
ne

au moment de la transition fruit immature/fruit mature
(
stade de dévelo
pp
ement vert mature :mature
g
reen
)
(ppg)
Analyse du transcriptome de tomates traitées avec de l’éthylène ou
de l’auxine par RNASeq: séquençage quantitatif des ARN messagers
Approched’étudeet Plan d’experience
Mature
Green
Green
+ 48h
Control
+
Ethylene
+ Auxin
+ Auxin
RNAseq
Control
+
Ethylene
+ Auxin
+ Ethylene
RNAseq
RNAse
q
•RNASeq–technology basedon the second
f
h (NG)
q
generationo
f
sequencingmac
h
ines
(NG
S
)
to

catalogfull collection of RNA in the cell
(
aka

transcriptome
)
(
a
.
k
.
a
.

transcriptome
)
Usin
this
tchnl
bl t lk
t

Usin
g
this
t
e
chn
o
l
ogy

weare

a
bl
e
t
o
l
oo
k
a
t
the transcriptomesnapshotinferringall
possible variations in transcription and
possible variations in transcription and
quantifylevelsof expression
RNAseqexperiments: workflow
1.Sampling,
RNA extraction
2. Sequencing
5 treatments
Illumina Hiseq2000
3.Bioinformatics
X 3 biologicalreplicates
Illumina Hiseq2000
,

PLAGeplateforme
3.Bioinformatics
data processing
in-silicodiscovery
4. In-vitro &
In-vivo
validation
qRT-PCR,
analyzes
analyzes
Transcripts capture with RNAseq,
sampling sequencing
sampling
,
sequencing
Sample RNA
Amplified
cDNA
cDNA
fragments
Millions of
short reads
per sample
cDNA
fragments
@HWI-ST314_0085:8:1101:10000:
CGAGTGTATAGTGAATCCCCTTTTGA
+
HHHHHHHHHHHHHHHEG########
@HWI-ST314_0085:8:1101:10000:
CTTGCATCTATCTTCAAACCAATAAAT
per sample
Reverse
i
CTTGCATCTATCTTCAAACCAATAAAT
+
HHHHHHHHHHHHHHHHHHHHHHHH
+
@HWI-ST314_0085:8:1101:10003:
TGGAAGGAGAGAGGCCTGAGAAAC
+
HHHHHGHHHFHGHHHHHHHHHHH
transcription
+PCR
fragmentation
sequenc
i
ng
HHHHHGHHHFHGHHHHHHHHHHH
@HWI-ST314_0085:8:1101:10004:
TCCGGTTACATTCTTAAACCCAACCG
+
@CC@CDEDECDFEFEE8DBEFBCFD8C
@HWI-ST314_0085:8:1101:10005:
CCAAAATAAAGAAAACATTCAACTCA
+
GD>FFD:5869%<2'++,:9.C<;@;<<A:-
@HWI-ST314_0085:8:1101:10008:
CTGCAAGATAGAATTCCTTACATTCTT
+
HHHHHHHFHHHHHFHHHHHHHHHH
@HWI-ST314_0085:8:1101:10008:
CTGGGTTTCTTTGTTTCCGGAGTTTTTC
Wesequenced450M readsin total: 30M x 5 samplesx 3 replicates
Strategies for reconstructing transcripts
from RNA
-
Seq
reads,
bionformatics
from RNA
Seq
reads
,

bionformatics
Not assembled =
not quantified
Align-then-assemble: Cufflinks, Scripture
Assemble-then-align: ABySS
Advancing RNA-Seqanalysis
BrianJ Haas & Michael C Zody
Bioinformatics workflow diagram
RNA-Seq—quantitative measurement of expression through massively parallel
RNA-sequencing, Brian T. Wilhelm a,b,*, Josette-Renée Landry
Biostatistics:
data normalization and significance test
data normalization and significance test
•Normalization by account for technical errors/bias:
–different library sizes: different numbers of reads
–different gene lengths; limited read capacity: highly-
ex
p
ressed
g
enes “steal” more of reads
pg
–sequencing biases

DE analysis: is a gene significantly differentially
DE analysis: is a gene significantly differentially
expressed under two conditions?
–we are working on accurate stochastic data model design
Biil Pi d Ni Biil diibi
–we

use
Bi
nom
i
a
l
,
P
o
i
sson

an
d N
egat
i
ve
Bi
nom
i
a
l di
str
ib
ut
i
ons
–employing Fisher Exact Test,Mann-Whitney U test, MARS.
Expression levels comparison and
Differentiall
y
ex
p
ressed
g
enes identification
Mature
Green
Green
+48h
Control
+
Ethylene
+ Auxin
+ Auxin
Control
+
Ethylene
+ Auxin
+ Ethylene
Induction of Auxinrelatedgenesby
auxin
treatment
auxin
treatment
25
3
Mature
Gr
ee
n
2
2
.
5
e
)
+ Auxin
+ 48h
Grn
1
1.5
oldchang
e
0
0.5
Log(F
-0.5
SlIAA35
SlIAA17
SlIAA2
SlIAA12
SlIAA13
SlIAA29
SlIAA16
SlIAA1
SlIAA15
SlIAA9
SlIAA36
SlIAA8
SlIAA4
SlIAA27
SlIAA3
Sl-ARF9
Sl-ARF18
Sl-ARF16A
Sl-ARF4
Sl-ARF1
Sl-ARF3
Sl-ARF5
Sl-ARF8A
Sl-ARF2B
Sl-ARF7B
-1
Suppression of Ethylenerelated
genes
by
auxin
treatment
genes
by
auxin
treatment
1
R
-
1
0
SAM1
SAM2
ACS
SAM3
ACO
LeEIL2
LeEIL3
LeETR1
LeACO4
LeEIL4
LeEIL1
LeEIN2
SlTPR1
LeCTR2
LeACO5
GRL1
LeETR6
LeCTR1
LeACO1
LeACO3
ETR
LeETR4
EIL
L
eACS1B
L
eACS1A
ACS
LeETR3
LeACS2
LeACS4
N
R
-2
1
L
L
o
ldchange)
Mature
-3
Log(F
o
+ Auxin
+ 48h
Green
-5
-4
Conclusion and perspectives
•RNASeqallowedus to measure the mRNA expression
levels in tomato fruits in the
p
resence of external
p
signals (hormone treatment)
•Anal
y
sis of this data identified a number of
g
enes
il di h hddi lih
yg
act
i
ve
l
y

respon
di
ng

to

treatment,

t
h
us

s
h
e
ddi
ng
li
g
h
t

on

the process of the fruit ripening
O
RNAS
it ld hdd f

O
ur

RNAS
eqexper
i
men
t
revea
l
e
d h
un
d
re
d
s

o
f
new

transcripts (genes and RNA) in tomato which were
previously un-annotated
•We identified a need and started a development of
robust statistical methods for DE genes identification
Contributeurs
•Laboratoire GBF
–Biolo
g
ie:
•Plateforme Plage
•O. Boucher
•G. Salin
g
•E. Purgato
•C. Chervin
•L. Su
•P
. Frass
e
. Frass
•O. Berseille
•M. Bouzayen
•JP Roustan
•PlateformeBioinfo-genotoul
–Bioinformatique / Statistique
•P. Senin
•E. Maza
M Zi
•C. Klopp
•D. Laborie

M
.
Z
ou
i
ne