Functional genomics in Picea glauca

Functional Genomics in Picea glauca
John MacKay
Université Laval, Sciences du bois et de la forêt
University of Oxford, Plant Sciences
February 21, 2014
05/12/12
1. Conifer Genomes and their Evolution
Gymnosperms: ‘ancient’ lineages of seed plants
Shared and distinct features compared to
flowering plants (angiosperms)
*
Gymnosperms
Angiosperms
Outline
1. Transcriptional regulation and gene networks
2. Discovery and analysis of a gene associated with
resistance to the spruce budworm
Gene Catalogue & Resource Development:
Transcriptome sequencing
Rigault et al. (2011) Plant Physiology. 157: 14
In White spruce :
Sampled (Coverage)
Predicted total
Number of expressed genes
27,720*
32,720
Transcriptome (Mb) Sanger
30.15
41.75**
Next-Gen
Total
7.8
37.95
47
*85% of genes represented by FL-cDNA inserts, 40% contain complete CDS
**Predicted size of sampled transcriptome based on mRNA sequence completion & CDS analysis
Microarray: 23,853 genes
PiceaGenExpress
Raherison et al. 2012 BMC
Genomics 13: 434
Transcriptome
resequencing:
– SNP discovery
Genotyping chips:
– Linkage mapping
– Association studies
1. Transcriptional regulation and gene
netwoks
Bomal C., Duval I., Giguère I., Fortin É., Caron S., Boyle B., Séguin A., MacKay J. 2014. Opposite
action of R2R3-MYBs from different subgroups on common key genes from shikimate and
monolignol pathways in spruce. Journal of Experimental Botany, 65(2):495-508
Duval I, Lachance D, Giguère I, Bomal C, Morency M-J, Pelletier G, Boyle B, MacKay J, Séguin A.
2014. Large-scale screening of transcription factor – promoter interactions in spruce
revealed a transcriptional network involved in vascular development. Journal of
Experimental Botany, accepted for publication
1.1 - Opposite effects of MYB genes
1. Transgene expression
2. Wild-type expression
Microarray profiling
RT-qPCR
Co-expression in vascular tissues
MYB1 & MYB8
MYB14 & MYB15
Vs
33 putative targets
• Opposite correlations
• Tissue dependent
SHM4
DHS2
COMT
4CL
Shikimate path
Shikimate path
Monolignol path
Phenylpropanoid path
6
B
PtMYB14
99
PgMYB14*
53
90
PgMYB15*
PgMYB17*
PgMYB10
PtMYB21*
86
50
PtMYB10*
[1]-[2]-[3]-[4]-[5]-[6]
PtMYB5*
PgMYB5
PtMYB14
99
PtMYB16*
91
PgMYB15*
PgMYB16*
92
51
PgMYB20*
PgMYB14*
99
PgMYB19*
90
PgMYB17*
86
PgMYB18*
96
PgMYB5
PtMYB13*
68
[1]-[2]-[3]-[4]-[5]
PtMYB5*
98
PgMYB13
[1]-[2]-[5]-[6]
Os09G36730PgMYB16*
5390 PtrMYB156
PtMYB16*
78 PttMYB4a
[1]-[2]-[5]-[6]-[4]
PgMYB18*
81
77 PtrMYB221 PgMYB19*
AtMYB4
96
PgMYB20*
[1]-[2]-[4]
Vv03G01970
EgMYB1
PtMYB10* [1]-[2]-[5]-[6]-[4]
[1]-[2]-[5]-[4]
Vv04G13330PgMYB10
59
9196 Os08G43550
[1]-[2]-[5]-[6]
PtMYB21*
ZmMYB42
[1]-[2]-[5]-[6]-[4]
AtMYB7PtMYB13*
99
PgMYB13
89
AtMYB32
AtMYB6
94
PtMYB22*
[1]-[2]-[5]
AtMYB8
AtMYB7
94
[1]-[2]-[5]-[2]
PtrMYB168
74
AtMYB3 AtMYB32
[1]-[2]-[5]
Vv04G13330
[1]-[2]-[5]-[6]
Os01G65370
72
Os05G35500
[1]-[2]-[5]
Vv03G01970
Os12G07640
[1]-[2]-[6]
AtMYB4
63
Vv00G63420
100
Vv00G63420 [1]-[2]-[5]-[5]
99
Vv00G63425
Vv00G63425
PtMYB22*
[1]-[2]-[5]
85
Os09G36730
Vv00G58155
69
Vv01G04780
EgMYB1
80
Vv17G02670
Os12G07640
62
Vv17G02660 [1]-[5]
71
Os08G43550
AtMYB20
92
ZmMYB42
AtMYB13
AtMYB123
Os01G65370
86
AtMYB3R4
Os05G35500
84
100
PttMYB3R
98
PtrMYB156
100
PttMYB4a
PtMYB14
PgMYB15*
92
PgMYB14*
99
PgMYB17*
96
PgMYB5
68
PtMYB5*
PgMYB16*
53
PtMYB16*
PgMYB18*
81
77
PgMYB19*
96
PgMYB20*
PtMYB10*
PgMYB10
59
91
PtMYB21*
PtMYB13*
99
PgMYB13
PtMYB22*
AtMYB7
94
AtMYB32
Vv04G13330
Vv03G01970
AtMYB4
63
100
Vv00G63420
Vv00G63425
85
Os09G36730
EgMYB1
Os12G07640
62
71
Os08G43550
92
ZmMYB42
Os01G65370
86
Os05G35500
84
98
PtrMYB156
93
100
PttMYB4a
PtrMYB221
PtrMYB168
AtMYB3
64
AtMYB6
56
AtMYB8
99
Vv00G58155
Vv17G02670
73
Vv17G02660
95
Vv01G04780
67
AtMYB123
AtMYB20
AtMYB13
PttMYB3R
AtMYB3R4
100
99
Sg4C Sub-group 4
R2R3-MYB
B
93
.1
64
PtrMYB221
PtrMYB168
AtMYB3
AtMYB6
0.05
7
Transcriptional regulation assay
Transient assay system
Activation and repression
Promoter construct PgDHS2
35S pro
Target gene promoter
GUS reporter
NOS ter
TF vector
PgMYB8
Ubi pro
NOS ter
Ubi pro
Transcription factor
PtMYB8
NOS ter
PtMYB1
PtMYB14
GS1
spot
Ratio
Ratio
TF/no TF
TF/no TF
9.29
11.85
density
10.63
12.85
spot
density
spot
2.65
3.26
3.30
5.57
5.56
5.31
density
3.66
5.89
spot
0.21
0.15
density
0.20
0.12
0.08
0.00
0.12
0.00
PgMYB15 spot
density
Duval et al. 2014 JExB accepted
Pg4CL
Bomal et al. 2014 JExB
8
+
_
DNA Binding Assay
EMSA with MYB ACI and ACII elements from 4CL and DHS2 promoters
MYB8 protein
MYB 15 protein
9
Competitive DNA Binding Assay
EMSA with ACI element from the Pg4CL promoter
[MYB15] = [MYB8]
[MYB8] < [MYB 15]
10
Transcriptional MYB Network
CARBOHYDRATE METAB.
SHM4
SHIKIMATE PATH.
DHS2
AROMATIC A.A. PATH.
(CM1)
PHE
TYR
TRP
PgMYB8
PgMYB15
CINAMATE
ISOPRENOID PATHWAY
(TERPENES)
COMT
p-COUMARATE
MONOLIGNOLS
4CL
COUMAROYL-CoA
FLAVONOIDS
(CHS, CHI)
ANTHOCYANINS
(CHS, CHI, DFR, LDOX)
MALONYL-CoA
11
YNB
YNS
RT
AX
PR
ES
PS
Expression Profiles:
Transcription factors
and secondary cell
wall genes (RT-qPCR)
XR
XS
XS
XR
ES
PS
PR
AX
RT
YNS
YNB
1.2-Functional Profiling : Secondary Cell Wall Gene Network
MYB
NAM/NAC
II
I
0
100
12
0
100
Functional Assays
GUS marker expression following
co-transformation
PgXTH8-1
PgTUA-1
PgSABATH2
PgGASA5-1
PgLIM-1
PgHB4
PgMYB8
PgMYB1
PgCesA-3
PgCAD
Pg4CL
PgDHS2
Promoters
Transcription factors
NAC-2
NAC-3
NAC-4
NAC-5
NAC-6
NAC-7
NAC-8
05/12/12
13
Phylogenetic Tree of Plant NAC Genes
14
Secondary Cell Wall Gene Network
Transcriptional network in conifers vs Arabidopsis
15
2. Spruce Budworm Resistance
Nathalie Delvas, Melissa H. Mageroy, Geneviève Parent, Isabelle
Giguère, Halim Maaroufi, Gaby Germanos, Joerg Bohlmann, Éric
Bauce, John J. Mackay
SBW Impacts
Spruce Budworm (SBW)
– Outbreaks are very large in scale
– 55 million hectares (550,000 km2)
during last major outbreak in Québec
(1970-80s)
– Caused wood losses estimated at 380 $
millions
1800
1500
1.6+ million ha
1200
SBW infested areas
in Québec (1000 ha)
900
600
300
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Susceptible
Recovering
Dead
Resistant
Phenolic compounds associated with SBW resistance
Resistant Trees
Susceptible Trees
PICEIN
PICEOL
1-(4-(beta-D-glucopyranosyloxy)phenyl)ethan-1-one
4-hydroxyacetophenone
PUNGENIN
« PUNGENOL »
1-(4-(beta-D-glucopyranosyloxy)-4hydroxyacetophenone
3,4-hydroxyacetophenone
Delvas, N., Bauce, É., Labbé, C., Ollevier, T., Bélanger, R. Phenolic compounds that confer resistance to spruce
budworm. Entomol. Exper. Applic. 141, 35-44 (2011).
Piceol and Pungenol Decrease Larval Survival
90
Rate of survival to L6
80
70
60
50
40
30
20
10
0
control
Control diet
piceol
1 X 1x piceol
2 X 2x pungenol
1 X 1xpungenol
2 X 2x pi1+Xpu 1x pi2+ Xpu 2x
Piceol
Pungenol
Piceol + Pungenol
Delvas, N., Bauce, É., Labbé, C., Ollevier, T., Bélanger, R. Phenolic compounds that confer resistance to spruce
budworm. Entomol. Exper. Applic. 141, 35-44 (2011).
Microarray analyses
Sampling June 17, 2010
7 susceptible trees and 7 resistant
trees (14 trees total)
A
B
C
3 samples per tree (A, B, C)
Microarray: Oligonucleotide chip,
23,834 genes
Additional samples collected in
August 2010 (for RT-PCR)
PgbGlu-1 Gene: Differential Expression
22
PgbGlu-1 Gene: Differential Expression
RT-qPCR determination of spliced PgbGlu-1 RNA level
Mature test trees
R
N-R
23
PgbGlu-1 Gene: Differential Expression
Based on PiceaGenExpress database
Raherison et al. 2012 BMC Genomics 13: 434
24
Previously Proposed Biosynthesis pathway
General phenylpropanoid pathway
Phenylalanine
Cinnamic acid
R: H, 4-Coumaric acid
R: OH, Caffeic acid
R: H, 4-Coumaroyl-CoA
R: OH, Caffeoyl-CoA
R: H, OH
Proposed: from Negrel and Javel Phytochem. 71, 751–
759 (2010)
?
R: H, Piceol
R: OH, Pungenol
?
?
Pathway Revised
SBW Resistance Mechanism
Glycosylation
(glysosyl transferase)
Transport to the vacuole
b-glucosidase
(tonoplastic)
Gene expression is a determinant of
susceptibility and resistance
Gene and compounds to develop:
• Novel breeding strategies for SBW
resistance
• Vulnerability assessment of existing stands
Concluding Remarks
1. Gene networks: other approaches are being used, e.g.
eQLT analysis, co-expression modules, and integrated
with current results
2. Insect resistance gene: heritability and SBW resistance
experiments planned based on breeding population
results
3. Functional insights are being developed by using
comparative transcriptome and functional profiling
4. Next steps for developing an understanding of genome
function: integrate diverse types analyses
Acknowledgements:
SMarTForests Team Members
•
•
•
Project Leaders: John MacKay, Jörg Bohlmann
Project Investigators: Jean Beaulieu, Jean Bousquet, Gary Bull, Janice Cooke, Nancy
Gélinas, Nathalie Isabel, Steven Jones, Kermit Ritland, Armand Séguin, Alvin Yanchuk
Project Managers: Sophie Laviolette, Carol Ritland
Transcriptome and Genome Research (MacKay lab)
•
•
•
•
Students: Elie Raherison , Jukka-Pekka Verta, Nathalie Delvas, Guillaume Tessier,
Mebarek Lamara, Gaby Germanos, Élise Fortin
Postdocs: Claude Bomal, Patrick Lenz, Julien Prunier, Geneviève Parentr
Research assistants: Sébastien Caron, Pier-Luc Poulin , Brian Boyle, Isabelle Giguère,
Collaborators: Éric Bauce, Philippe Rigault, Christian Landry
Funding:
–
–
–
–
Genome Canada, Genome Québec, B-C, Alberta
Canadian Forest Service, Canadian Wood Fiber Center
Canadian Fondation for Innovation, NSERC of Canada
Fonds de Recheche du Québec – Nature et technologies
Thank you