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This is an author’s version published in:
http://oatao.univ-toulouse.fr/13751
To cite this version:
Roustan, Jean-Paul
and Senin, Pavel La transition fruit
immature/fruit mature: analyse globale des profils
transcriptomiques. (2012) In: Journee de la Recherche à
La transition fruit
immature/fruit mature:
analyse globale des profils
transcriptomiques
Jean-Paul Roustan, Pavel Senin
UMR 990 INRA/INP-ENSAT Génomique et Biotechnologie des Fruits
Autres Contributeurs:
C. Chervin, M. Zouine, E. Maza, E. Purgato, L. Su, P. Frasse, O. Berseille, M. Bouzayen
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Maturation des fruits
* Activité respiratoire :
- augmentation subite et intense
chez les fruits climactériques
- pas de changement d'intensité
chez les fruits non climactériques
* Diminution de la fermeté
* Formation de pigments
* Évolution des sucres et des acides
* Biosynthèse d’arômes
Changement physiologiques et biochimiques profonds:
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Régulation du développement des fruits
par les hormones
Éthylène
(Déclenche et module la maturation)
Auxine
(division cellulaire; inhibiteur de maturation?)
Gibbérellines
(développement du fruit)
Cytokinines
(division cellulaire)
Acide Abscissique
(dormance des graines)
•
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Régulation de la Maturation des fruits
climactériques
Éthylène
- Production autocatylique de l’éthylène
- Autonomie de maturation
Quelques fruits climactériques:
abricot, avocat, banane, kiwi, melon,
pêche, poire, pomme, tomate …
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C
Gènes de
maturation
Autres signaux
Hormonaux dont auxine
sucres
acides
Goût
Vacuole
Noyau
MATURATION
DES FRUITS
DNA
Dégradation de la paroi
Ramollissement
Arôme
Odeur
Arômes
Facteurs de Transcription
Perception
C=C H
H
H
H
Ethylene
Transduction du signal
PROGRAMME GENETIQUE
Dégradation des membranes
Couleur
Pigments
Chromoplaste
Mitochondrie
Respiration
d'après JC Pech
Crosstalk
C2H4
Autocatalytique
... 11
[)
Maturation du fruit de Tomate
Production
d’éthylène
Autocatalytique
Autoinhibition
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Influence croisée de l’éthylène et de l’auxine
au moment de la transition fruit immature/fruit mature
(stade de développement vert mature :mature green)
Transition fruit immature/fruit mature
ou
Comment le fruit acquière sa capacité à murir ?
Analyse du transcriptome de tomates traitées avec de l’éthylène ou
de l’auxine par RNASeq : séquençage quantitatif des ARN messagers
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+ Auxin
+ Ethylene
RNAseq
Control
+ Ethylene
+ Auxin
+ Auxin
+ Ethylene
Mature
Green
+ 48h
Approche d’étude et Plan d’experience
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• RNASeq – technology based on the second
generation of sequencing machines (NGS) to
catalog full collection of RNA in the cell
(a.k.a. transcriptome)
• Using this technology we are able to look at
the transcriptome snapshot inferring all
possible variations in transcription and
quantify levels of expression
RNAseq
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RNAseq experiments: workflow
1.Sampling,
RNA extraction
2. Sequencing
3.Bioinformatics
data processing
in-silico discovery
4. In-vitro &
In-vivo
validation
5 treatments
X 3 biological replicates
Illumina Hiseq2000,
PLAGe plateforme
qRT-PCR,
analyzes
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Transcripts capture with RNAseq,
sampling, sequencing
Sample RNA
Amplified
cDNA
cDNA
fragments
@HWI-ST314_0085:8:1101:10000:
CGAGTGTATAGTGAATCCCCTTTTGA
+
HHHHHHHHHHHHHHHEG########
@HWI-ST314_0085:8:1101:10000:
CTTGCATCTATCTTCAAACCAATAAAT
+
HHHHHHHHHHHHHHHHHHHHHHHH
+
@HWI-ST314_0085:8:1101:10003:
TGGAAGGAGAGAGGCCTGAGAAAC
+
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
Millions of
short reads
per sample
Reverse
transcription
+PCR
fragmentation
sequencing
We sequenced 450M reads in total: 30M x 5 samples x 3 replicates
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INSîlTUT NATIONAL POLYTECHNIQUE DE TOULOUSE
...
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==-;:::::,
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Strategies for reconstructing transcripts
from RNA-Seq reads, bionformatics
Align-then-assemble: Cufflinks, Scripture
Assemble-then-align: ABySS
Advancing RNA-Seq analysis
Brian J Haas & Michael C Zody
Not assembled =
not quantified
Ill 1111 1 1 1111 1111RNA-Seq reads
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Assemble transcripts
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Assemble transcripts
\
denovo
Align transcripts
to genome
RNA-Seq—quantitative measurement of expression through massively parallel
RNA-sequencing, Brian T. Wilhelm a,b,*, Josette-Renée Landry
Bioinformatics workflow diagram
Library
preparation
1
Sequenc
i
ng
1
Data filtering/QC
1
Read mapping to
reference genome
1
Dataset assembly
(
select
i
on of
un
i
que reads/repeat removal
,
paired end read jo
i
ning
)
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Definition ofnovel transcribed
•
regions (exons/genes)
t
Calculation of
quantitative
expression score
t
Val
i
dation of annotated spl
i
ce
sites/definition of new sites
t
Definition of UTRs
&
revision of gene structure
Cross spec
i
es
corn ar
i
sons of re
i
ons
1
Prediction of
novel ORFs
•
Prediction of
ncRNAs
(
miRNAs
,
antisense
,
etc)
•
Comparison of
A
,
B
,
C
sam
l
es
Identification of
differentially
expressed
genes
Identification of
nove
l
sample
specific transcribed
regions
Ident
i
ficat
i
on of
a
l
ternative promoters
,
terminators
,
sp
li
ce s
i
te usage
Biostatistics:
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-expressed genes “steal” more of reads
– sequencing biases
• DE analysis: is a gene significantly differentially
expressed under two conditions?
– we are working on accurate stochastic data model design
– we use Binomial, Poisson and Negative Binomial distributions
– employing Fisher Exact Test, Mann-Whitney U test, MARS.
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Control
+ Ethylene
+ Auxin
+ Auxin
+ Ethylene
Mature
Green
+48h
Expression levels comparison and
Differentially expressed genes identification
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Induction of Auxin related genes by
auxin treatment
-1
-0,5
0
0,5
1
1,5
2
2,5
3
S
lI
AA3
5
S
lI
AA1
7
S
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AA2
S
lI
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2
S
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3
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9
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6
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5
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AA9
S
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6
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7
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S
l-A
RF
9
S
l-A
RF
18
S
l-A
RF
16A
S
l-A
RF
4
S
l-A
RF
1
S
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RF
3
S
l-A
RF
5
S
l-A
RF
8A
S
l-A
RF
2B
S
l-A
RF
7B
Log(
Fold
c
ha
nge
)
+ Auxin
+ 48h
Mature
Green
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Suppression of Ethylene related
genes by auxin treatment
-5
-4
-3
-2
-1
0
1
SA
M1
SA
M2
AC
S
SA
M3
AC
O
Le
EIL2
Le
EIL3
Le
ETR
1
Le
AC
O
4
Le
EIL4
Le
EIL1
Le
EIN
2
S
lT
PR
1
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CTR
2
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AC
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5
GRL
1
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ETR
6
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4
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AC
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ETR
3
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AC
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AC
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NR
Log(
Fold
change)
+ Auxin
+ 48h
Mature
Green
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Conclusion and perspectives
• RNASeq allowed us to measure the mRNA expression
levels in tomato fruits in the presence of external
signals (hormone treatment)
• Analysis of this data identified a number of genes
actively responding to treatment, thus shedding light on
the process of the fruit ripening
• Our RNASeq experiment revealed hundreds of 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
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Contributeurs
• Laboratoire GBF
– Biologie:
• E. Purgato
• C. Chervin
• L. Su
• P. Frasse
• O. Berseille
• M. Bouzayen
• JP Roustan
– Bioinformatique / Statistique
• P. Senin
• E. Maza
• M. Zouine
•
Plateforme Plage
•
O. Boucher
•
G. Salin
•
Plateforme Bioinfo-genotoul
•
C. Klopp
•
D. Laborie
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