C4/CAM: Upcoming Meetings
CAM Systems
Biology/Ecology (New
Phytologist) – July 15-18,
2014 Granlibakken
Conference Center- S. Lake
Tahoe, CA
Plant and Animal Genome
(PAG) Workshop –
Functional Genomics of C4
and CAM Photosynthesis,
January 11, 2014 (Saturday,
10:30 am)
Engineering CAM Photosynthetic Machinery
into Bioenergy Crops for Biofuels Production
in Marginal Environments
C4-CAM Plant Biology Meeting
University of Illinois, Urbana-Champaign
August 6-10, 2013
John C. Cushman – University of Nevada
Department of Energy, Office of Science, Genomic Science Program - Genomic Science:
Biosystems Design to Enable Next-Generation Biofuels: Award #DE-SC0008834.
Project Network
John Cushman
Karen Schlauch
James Hartwell
Xiaohan Yang
Tim Tschaplinski
Dave Weston
Gerald Tuskan
Jay Chen
Hong Guo
Anne Borland
Project Overview
Goal: Enhance WUE and adaptability
to hotter/drier climates of C3 species by
introducing CAM
Outcome: Develop new capabilities for
biomass production on marginal or
abandoned agricultural lands while
minimizing H2O and N inputs
http://www.globalwarmingart.com/
http://www.esrl.noaa.gov/
http://www.globalwarmingart.com/
http://climate.nasa.gov http://climate.nasa.gov
1960 2006
400
Rising Global Emissions, CO2, and Temperatures
Project Motivation
U.S. Drought Monitor August 14, 2012
Global Annual Groundwater Depletion
Source: United Nations Environment Program: 2012
Project Motivation
ORNL Biomass Program
http://www1.eere.energy.gov/library/default.aspx?page=1
New RFS demands feedstock enhancement/expansion
ALL soy/corn crop yield will displace ~6/12% of current
diesel/gasoline fuels
Waste stream capture would add another ~7%
ORNL Biomass Program
0%
USDA/DOE estimates <0.3% biofuels from arid western U.S. and
0% biomass production
Geographical Distribution of Biomass Production
ORNL Biomass Program
?
Can biomass feedstock production be expanded to more arid
areas by improving water use efficiency?
Geographical Distribution of Biomass Production
Research Question?
Can crassulacean acid metabolism
(CAM) be exploited to improve the
WUE or drought durability of (biofuel)
crops?
Existing mega-CAM species
Transfer of CAM into C3 crops
Crassulacean Acid Metabolism
C4 acid
HCO3-
Pi
CO2
Stomata Open
Stomata Closed
1° Carboxylation
Starch
PEP
PEPC
C4 acid
C3 acid
Calvin
Cycle Decarboxylation
RUBISCO DAY
NIGHT
CO2
2° Carboxylation
Physiological Consequences of CAM
Water use efficiency (WUE) is
improved 5-10-fold relative to
C4 and C3 species, respectively
The ‘CO2 pump’ of CAM
reduces photorespiration
dramatically
A more efficient RUBISCO
enzyme might improve nitrogen
use efficiency
Lüttge 2002
Robust Growth Characteristics of CAM Plants
High water use efficiency
High drought tolerance (25 mm)
Extreme heat tolerance (65°C vs. 45°C)
High light tolerance (1000 µm m-2 sec-1 PPFD)
Tolerance to UV-B irradiation
Entire shoot surface area typically
photosynthetic Borland et al. (2009) J. Exp. Bot. 60: 2879-2896.
Annual Water Demand
0
5000
10000
15000
20000
25000
30000
C3 C4 CAM
Cro
p w
ate
r d
em
an
d (
Mg
H20
ha
-1 y
ea
r-1)
Photosynthetic Pathway
Borland et al. (2009) J. Exp. Bot. 60: 2879-2896.
Above-ground Dry Biomass Productivities
Ananas comosus: ~35 Mg ha-1 year-1
Agave americana: ~42 Mg ha-1 year-1
Opuntia ficus-indica: 47-50 Mg ha-1 year-1
Nobel 1991 New Phytol. 119: 183- 205.
Annual Productivity (Above Ground)
0
10
20
30
40
50
C3C4
CAM
Ave
rag
e a
bo
ve
-gro
un
d p
rod
uctivity (
Mg
ha
-1 y
ea
r-1)
Photosynthetic Pathway
Borland et al. (2009) J. Exp. Bot. 60: 2879-2896.
Agave worldwide cultivation >500,000 ha
Large Agave species used for alcoholic beverage
production (27-38% sugar leaves/stems)
Ethanol production well developed
CAM Bioenergy Crops: Agave
Simpson et al., 2011 Global Change Biology: Bioenergy 3: 25-36. Agave americana
Agave worldwide cultivation >500,000 Ha
Large Agave species used for fiber production:
- A. sisalana (sisal) 246 x 103 Mg
- A. fourcroydes (henequin) 22 x 103 Mg
CAM Bioenergy Crops: Agave
Sisal fibers Agave sisalana
CAM Bioenergy Crops: Opuntia
Opuntia worldwide cultivation >1,000,000 ha
Large Opuntia species used for food as young
cladodes (nopalitos) and fruits (tunas) and forage
Paterson et al., (2008) Trop. Plant Biol. 1: 3-19
EPI = water index x air temperature x photosynthetic photon flux density (PPFD)
EPI predicts productivity
EPI was calculated for 87 sites in the U.S. (189 sites across the earth)
Annualized productivities of a model CAM species (Opuntia ficus-indica) were calculated
Environmental Productivity Indices (EPI) of CAM Species
Nobel (1991) Plant Cell & Environ. 14: 637-646.
Temperature Index
Water Index
PPFD Index
Temperature Index
EPI Indices Modeling of Temperature Increase
Nobel (1991) Plant Cell & Environ. 14: 637-646.
Temperature Index calculated from 10 years of daily min/max temperature data
Annualized productivities
for Opuntia ficus-indica were calculated at 2 °C, 4 °C, and 6 °C above current climate conditions
Sites with no temps below -10 °C increased by 16%, 38%, and 65%
2 °C
4 °C
6 °C
37 sites
51 sites
61 sites
CAM Species are Distributed Widely
CAM present in
~6.5% of vascular
plant species
CAM evident in more
than 35 different (10
major) plant families
Multiple independent
origins documented Silvera et al., 2010 FPB 37: 995-1010
Research Question?
Does the recurrent, independent evolution of
CAM suggest that the bar might be lower
(than C4 photosynthesis) for possible
engineering of CAM into C3 (biofuel) crops?
www.abc.net.au
Project Goals
1. Define the genetic basis of
CAM ‘modules’ in eudicot and
monocot species using
network modeling of data
derived from ‘Omics (e.g.,
transcriptomic, metabolomic)
data sets.
Opuntia ficus-indica
Agave americana
Phylogenetic Tree of Selected CAM Species
Yang Lab
Monocots
CoreEudicots
Caryophyllales
Saxifragales
Agave americana A. tequilana
A. sisalana
Kalanchoë fedtschenkoi
K. laxiflora
Opuntia ficus-indica
Mesembyranthemum crystallinum
(facultative)
Clusia minor (facultative)
Orchidaceae
Agavaceae
Phalaenopsis equestris
P. aphrodite
Cactaceae
Aizoaceae
Crassulaceae
Clusiaceae
Asparagales
Malpighiales
Sedum album (cycling)
Bromeliaceae Poales
Ananas comosus
Genomes and Transcriptomes
of Selected CAM Species
Species CAM Type
Estimated
Genome Size Transcriptome Data Reads (type) Draft Genome Data Data Source
Monocots
Agave americana Obligate 6.0 Gb 3.0 M (454), 850 M (Illumina) - X. Yang, et al., unpublished
Agave deserti Obligate 4.0 Gb 1.2 B (Illumina) - S. Gross et al., unpublished
Agave sisalana Obligate 6.4-8.5 Gb 1.5 M (454), 1.1 B (Illumina) - J. Hartwell et al., unpublished
Agave tequilana Obligate 4.0 Gb - ~30X coverage X. Yang et al., unpublished
Anana comosus Facultative 526 Mb 4.4 M (Illumina) - Ong et al., 2012
Phalaenopsis aphrodite Obligate 1.6 Gb 3.3 M (454), 290 M (Illumina) - Fu et al., 2011; Su et al., 2011
Phalaenopsis equestris Obligate 1.6 Gb 0.26 M (454), 37 M (Illumina) - Fu et al., 2011; Hsiao et al., 2011
Eudicots
Clusia minor Facultative 1.8 Gb - - A. Borland et al., unpublished
Kalanchoë fedtchenkoi Obligate 246 Mb 1.6 M (454), 900 M (SOLiD) ~60X coverage J. Hartwell et al., unpublished
Kalanchoë laxiflora Obligate 250 Mb - In progress X. Yang, et al., unpublished
Mesembryanthemum crystallinum Facultative 390 Mb 3.7 M (454), 2.4 B (Illumina) In progress J. Cushman et al., unpublished
Opuntia ficus-indica Obligate 2.8 Gb 0.6 M (454), 1.7 B (Illumina) In progress
Mallona et al., 2011; J. Cushman
et al., unpublished
Sedum album Facultative cycling 142 Mb ? (Ion Torrent™) ~46X coverage T. Michael, 2012
Agave tequilana Genome
Important obligate CAM crop
4 Gb genome (n=30) diploid
Illumina-based sequencing
completed to 30X coverage
Pac Bio-based sequencing
for assembly scaffold will be
initiated shortly
Hengfu Yin, Xiaohan Yang
Chromosome spread for
Agave. (S. Neethirajan and
J. Morrell-Falvey)
Agave sisalana Transcriptome
Important obligate CAM crop for
fiber and biofuel production
6.4 Gb genome
Roche 454 (Dark/Light) and
Illumina-based leaf development
sequencing completed
Dissection of CAM developmental
gradient along leaf axis ongoing
Phytun Bupphada, James Hartwell Poster P47
Kalanchoe laxiflora Genome
Obligate CAM model for functional
dissection of CAM
Small, short life cycle, seed producer;
transformable
146 Mb genome (n=17) diploid
Illumina-based sequencing completed
to 100X coverage; assembly at 90%
Pac Bio-based sequencing for
assembly scaffold will be initiated
shortly Hengfu Yin, Xiaohan Yang
Ice Plant Genome
Well-studied facultative CAM
halophyte model
390 Mb genome (n=9)
Illumina-based sequencing in
progress
Pac Bio-based sequencing
for assembly scaffold will be
initiated shortly
Bernie Won, Won Yim, Richard Tillett
Ice Plant Transcriptome Assembly
Hybrid assembly completed
~83% of genes
characterized (mostly from
leaf tissue)
Reference protein set Set members
(N) BLAST hit in ice plant
(%)
Eukaryotic Ultra-Conserved Orthologs 357 357 (100%)
GreenCut2 green-lineage proteins 677 675 (99%)
AVPO single-copy genes 959 947 (98%)
Arabidopsis proteome (TAIR 10) 27,416 22,740 (83%)
Won Yim, Richard Tillett Poster P49
Opuntia ficus-indica Transcriptome
Important obligate CAM crop
food and forage production
2.8 Gb genome
Illumina-based time course
sequencing in process; US vs.
water-deficit stress contrast of
mesophyll and epidermal peels.
Illumina-based C3 vs. CAM
developmental series
Jesse Mayer, Bernie Wone
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
0-2.5 2.6-5 6-10 11-15 16-20 21-25 26-30 31-35
umolH
+/gFreshW
eight
PadHeight(cm)
AcidicTitra onofOpun aficus-indica
Dawn
Dusk
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
110.00%
0 1234 56 7891011121314151617181920212223242526272829303132333435363738394041424344454647
%FreshW
eight
DaysA erWatering
rep1
rep2
rep3
Strategies for Finding CAM Genes
Developmental gradient in obligate CAM
species - “Clean System”
Hartwell Lab
1
2
3
4
5
6
CAM C3
0
50
100
150
200
250
300
350
400
450
02:00 06:00 10:00 14:00 18:00 22:00
RP
KM
Time
PPCK
C3
CAM
Strategies for Finding CAM Genes
Stress induction in facultative CAM species
– “Dirty System”
Cushman Lab CAM C3
Salt or Water Deficit Stress
TF Identification for ChIP Seq
Detailed curation and expression analysis
from microarray and Illumina data sets
followed by co-expression analysis
WTC3 WTCAM
23647 43
Bernie Won, Won Yim, Richard Tillett
Ice Plant Digital Expression Profiling
Illumina-based DEG identification of
rhythmic genes over 72 h time course (US
vs. WDS).
62
355
116
5,034 13,974 9,365
Won Yim, Richard Tillett Poster P67
TF Identification for Planned ChIP Seq
1487 putative transcription factors have been
identified.
0
20
40
60
80
100
120
140
160
180
200
AP
2/E
RF
B3 s
uperf
am
ily
BB
R-B
PC
B
ES
1
bH
LH
bZIP
C
2C
2
C2H
2
C3H
C
AM
TA
CP
P
E2F/D
P
EIL
FA
R1
GeB
P
GR
AS
G
RF
HB
H
SF
LB
D (A
S2/L
OB
) M
AD
S
MY
B s
uperf
am
ily
NA
C
NF-X
1
NF-Y
N
in-lik
e
SB
P
SR
S
TC
P
Whir
ly
WR
KY
ZF-H
D
Nu
mb
er
of
Ge
ne
s
Transcription Factor Family
Bernie Won, Won Yim, Richard Tillett Poster P67
Ice plant Transcript Mapping: Carboxylation Module
Chloroplast
Vacuole
Mitochondrion
Starch
Glycolysis
PEP MAL Malic acid
TCA Cycle
2H+
HCO3-
PEPC
CO2
CA
Stomata OPEN
Nocturnal CO2
uptake and
primary fixation
Respired CO2
MDH
H+ H+
PPi
2Pi
V-PPiase
PPCK
POH
H+ H+
ATP
ADP+Pi
V-ATPase
+ H+
Pi
OAA MAL
NADH+ NADH+
Calvin Cycle
V-MT
D D N SN SL D
0.99 **
comp23737_c1_seq21 V-ATPase V1
peripheral complex
comp23737_c1_seq21 V-ATPase V1
peripheral complex
**
1.25
comp23737_c1_seq21 V-ATPase V1
peripheral complex
**
0.93
comp23737_c1_seq21 V-ATPase V1
peripheral complex
** *
1.19
comp23737_c1_seq21 V-ATPase V1
peripheral complex
**
1.36
comp23737_c1_seq21 V-ATPase V1
peripheral complex
0.19
comp23737_c1_seq21 V-ATPase V1
peripheral complex
**
1.33
comp23737_c1_seq21 V-ATPase V1
peripheral complex
**
1.57
comp23737_c1_seq21 V-ATPase V1
peripheral complex
** **
1.00
Min Max
0.54 comp59117_c0_seq1 PEPCK
** **
D D N SN SL D
Min Max
D D N SN SL D
comp11175_c0_seq1 CA
* 2.59
2.40 comp23854_c0_seq1 PEPC
**
D D N SN SL D
D D N SN SL D
comp14442_c0_seq1 PPCK
** **
1.82
comp23866_c0_seq1 C-NAD-MDH1
* **
1.33
D D N SN SL D
comp10851_c0_seq1 AVP
-0.65 ** **
D D N SN SL D
TP
G6P
TP
Glucose
TPT
Glucose
comp2658432_c0_seq1 TPT
0.83
D D N SN SL D
comp20559_c0_seq2 PLST
1.04
D D N SN SL D
GT
G6P
GPT2
D D N SN SL D
comp11177_c0_seq1 GPT
** **
4.08
Ice plant Transcript Mapping: Dearboxylation Module
Chloroplast
Vacuole
Mitochondrion
Starch
Gluconeogenesis
PEP
MAL Malic acid
TCA Cycle
2H+
Respired CO2
ME
PPDK-RP
PYR MAL
NAD(P)H NAD(P)+
PPT
G6P
Calvin Cycle
V-TDT
Stomata CLOSED
Daytime
CO2 release
and refixation
GPT2
CO2
ATP
+ Pi
AMP
+ PPi
RUBISCO
PPDK
CO2
1.75 **
comp11165_c1_seq1 PPDK
D D N SN SL D
D D N SN SL D
comp74283_c0_seq1 TDT
** **
-1.28
comp14662_c0_seq1 PPDK-RP
* 1.40
D D N SN SL D
D D N SN SL D
comp11177_c0_seq1 GPT
** **
4.08
2.63 comp23737_c1_seq21 BASS2
** **
D D N SN SL D
** ** 0.73 comp14433_c1_seq3
NADP-ME
D D N SN SL D
Ice plant Metabolic Profiling
Chloroplast
Vacuole
Mitochondrion
TPG6P
TPG6P
Starch
Glucose
PGA
PGA
PEP
OAA
MAL MAL
Malicacid
Malicacid
OAA
MAL
FUM
PYRTCACycle
H+ H+
H+
PCRCycle
H+
ATP
ADP+Pi
Glucose
1
3
6
MAL
4
8
PYRPYR
PEP
2ATP
2ADP+Pi
CO2
RUBISCO
?
HCO3-
PEPC
CO2
PPDK
CA
NADP-ME
StomataOPENNocturnalCO2
uptakeandprimaryfixa on
StomataCLOSEDDay meCO2releaseandrefix
aon
RespiredCO2
NAD-MDH
V-ATPase
H+ H+
PPi
2Pi
V-PPiase
10
2 53
PPCKP
OH
NAD-ME
6
CO2
MAL
6
PYR
NAD-MDH
7
PYR
9
Ice plant Metabolic Profiling
MT “CAM” MT C3 WT CAM WT C3
Organic Acids and Carbohydrates
Ice plant Metabolic Profiling
Chloroplast
Vacuole
Mitochondrion
TPG6P
TPG6P
Starch
Glucose
PGA
PGA
PEP
OAA
MAL MAL
Malicacid
Malicacid
OAA
MAL
FUM
PYRTCACycle
H+ H+
H+
PCRCycle
H+
ATP
ADP+Pi
Glucose
1
3
6
MAL
4
8
PYRPYR
PEP
2ATP
2ADP+Pi
CO2
RUBISCO
?
HCO3-
PEPC
CO2
PPDK
CA
NADP-ME
StomataOPENNocturnalCO2
uptakeandprimaryfixa on
StomataCLOSEDDay meCO2releaseandrefix
aon
RespiredCO2
NAD-MDH
V-ATPase
H+ H+
PPi
2Pi
V-PPiase
10
2 53
PPCKP
OH
NAD-ME
6
CO2
MAL
6
PYR
NAD-MDH
7
PYR
9
malate
0 8 16 24 8 16 24 32 40 480 8 16 24 8 16 24 32 40 48
DT ZTDT ZT
0
0.5
1
1.5
2
2.5
3
oxaloacetate
0 8 16 24 8 16 24 32 40 480 8 16 24 8 16 24 32 40 48
DT ZTDT ZT
0
1
2
3
4
5
fumarate
0 8 16 24 8 16 24 32 40 480 8 16 24 8 16 24 32 40 48
DT ZTDT ZT
0
5
10
15
20
25
30
35
40
Cis-aconitate
α-ketoglutarate
Succinate
Fumarate
Citrate
Oxaloacetate
Isocitrate Malate
Pyruvate
WT US
WT DS
MUT US
MUT DS
Phosphoenol
pyruvate
pyruvate oxaloacetate
malate
fumarate succinate alpha-ketoglutarate
cis-aconitate isocitrate
citrate
Ice plant Metabolic Profiling
Chloroplast
Vacuole
Mitochondrion
TPG6P
TPG6P
Starch
Glucose
PGA
PGA
PEP
OAA
MAL MAL
Malicacid
Malicacid
OAA
MAL
FUM
PYRTCACycle
H+ H+
H+
PCRCycle
H+
ATP
ADP+Pi
Glucose
1
3
6
MAL
4
8
PYRPYR
PEP
2ATP
2ADP+Pi
CO2
RUBISCO
?
HCO3-
PEPC
CO2
PPDK
CA
NADP-ME
StomataOPENNocturnalCO2
uptakeandprimaryfixa on
StomataCLOSEDDay meCO2releaseandrefix
aon
RespiredCO2
NAD-MDH
V-ATPase
H+ H+
PPi
2Pi
V-PPiase
10
2 53
PPCKP
OH
NAD-ME
6
CO2
MAL
6
PYR
NAD-MDH
7
PYR
9
Ice plant Metabolic Profiling
MT “CAM” MT C3 WT CAM WT C3
Amino Acids and N-Rich Compounds
Project Goals
2. Characterize the
regulation of
‘carboxylation’,
‘decarboxylation’ and
‘stomatal control’
modules using
comparative genomics,
network/molecular
dynamics modeling,
and loss-of- function
testing.
Tissue type
Co
-exp
res
sio
n m
od
ule
ID
Dave Weston, Xioahan Yang
WGCNA Coexpression network modules for 15 different
Agave americana tissues and temporal states.
Comparative Genomics: Clustering of
Orthologous Gene Groups
Xiaohan Yang
Arabidopsis thaliana
Populus trichocarpa
Solanum tuberosum
Musa acuminata
Brachypodium distachyon
Oryza sativa
Sorghum bicolor
Zea mays
Setaria italica
Agave americana
Agave deserti
Agave tequilana
Selaginella moellendorffii
Physcomitrella patens
Chlamydomonas reinhardtii
CAM/Agave
NVP (Non-vascular
plants)
C4
C3_moncot
C3_dicot
Biological Process Enrichment in Agave
CAM
C4C3
**
Xiaohan Yang
Loss-of-function Analysis in Kalanchoë
fedtschenkoi
Rhythmic gas exchange in PPCK RNAi lines
Note loss of amplitude (amount) in PPCK RNAi
lines (green and blue); WT, Red Susie Boxall, James Hartwell Poster P69
Loss-of-function Analysis in Kalanchoë
fedtschenkoi
Reduction of PPCK activity in RNAi lines
Note loss of nocturnal kinase activity and
potentially reduced fitness in PPCK RNAi lines.
Phosphorylated PEPC PEPC
WT
PPCK1
PPCK3
2 6 10 14 18 22 2 6 10 14 18 22
Wild type PPCK RNAi
Susie Boxall, James Hartwell Poster P69 Louisa Dever….
Project Goals
3. Deploy advanced genetic
engineering technologies to
enable stacking of a large
number of transgenes to
improve transgene
persistence and to transfer
fully functional CAM ‘modules’
and ‘pathway’. In planta Gene Stacking
Henrique De Paoli, Gerald Tuskan, Xiaohan Yang
GoldenBraid: Gene Module Assembly
3a. Synthetic biology cloning system for building
genetic modules/pathways from multipartite assembly
of standard component parts:
PR (promoter), CDS (coding sequence), and TM
(terminators).
GoldenBraid Cloning System Sarrion-Perdigones et al. 2011, 2013
Enzyme A
Enzyme A
Enzyme A
Enzyme A
Enzyme A
Enzyme A Enzyme A
Enzyme A
Enzyme A Enzyme A Enzyme A Enzyme A
GoldenBraid: Gene Module Assembly
3b. Set of four
destination cloning
vectors (A) for
reiterative (braided)
cloning of multiple,
reusable gene
modules (B) using
the principle of
idempotency:
5 transcription unit
assemblies
demonstrated.
GoldenBraid Cloning System Sarrion-Perdigones et al. 2011, 2013
GoldenBraid: Gene Module Assembly
3c. Creation of
libraries of
component
elements that can
be reused.
Combinations of
different linkers and
adapters can be
used to keep the
component parts in
frame.
GoldenBraid 2.0 Cloning System Sarrion-Perdigones et al. 2013
Simplified CAM ‘Carboxylation’ Module
Mal OAA
PEP
HCO3- CO2
PEPC CA
+
NAD-MDH
PPCK
PR CDS TM EveP
R
CDS TM PR CDS TM
Eve PR CDS TM
CAM and
Succulence
Silvera et al., 2010 FPB 37: 995-1010
-30
-25
-20
-15
-10
-5
0
d13C(‰
)
PhotosynthesisType
C3
WeakCAM
StrongCAM
0
0.5
1
1.5
2
2.5
3
3.5
4
LeafThickn
ess(mm)
C3
WeakCAM
StrongCAM Survey of
173 orchid
species.
Tissue
succulence
required for
C4 acid
storage.
CAM and Succulence
Nelson and Sage, 2008
Reduced IAS is associated with (and
is likely required as an evolutionary
prerequisite) for high CAM function.
Cell size and tissue succulence are functional traits of
CAM.
CAM
C3 Reduced surface of
mesophyll exposed to
IAS (Lmes/area) limits
CO2 efflux from site of
carboxylation (Phase I
and II) and increasing
likelihood of CO2
recapture.
Can Tissue Succulence Be Engineered?
Nicolas P. et al., 2013
Can Tissue Succulence Be Engineered?
Cell size and tissue succulence in Vitis embryos are
controlled by a grape berry-specific bHLH transcription
factor that also affects expression of cell expansion genes.
Project Goals
4. To analyze the effects of
the different CAM ‘modules’
and ‘pathway’ on stomatal
control, CO2 assimilation
and transpiration rates,
WUE, and biomass yield in
Arabidopsis and Populus. Populus trichocarpa
http:rvroger.co.uk
Not represented: Section Leucoides (big leaf poplars) and Abaso (Mexican poplars).
1. Populus section Populus – aspens and White Poplar. North America, Europe, Asia.
P. tremula x alba aspen hybrid clone INRA 717 1B4 (N. Europe)
P. grandidentata – Bigtooth Aspen (N. America)
2. Populus section Aigeiros – black poplars. North America, Europe, western Asia.
P. deltoides – Eastern Cottonwood (N. America)
P. nigra – Black Poplar (Europe)
3. Populus section Tacamahaca – balsam poplars. North America, Asia.
P. maximowiczii – ‘Maximowicz' Poplar, Japanese Poplar (NE Asia)
P. trichocarpa –Black Cottonwood (Western N. America)
4. Populus section Turanga – subtropical poplars. Southwest Asia.
P. euphratica – Euphrates Poplar (SW Asia)
P. tremula x alba INRA 717 1B4
P. deltoides
P. trichocarpa
P. euphratica
P. tremula x alba INRA 717 1B4 P. tremula x alba INRA 717 1B4
P. deltoides
P. trichocarpa
P. euphratica
P. tremula x alba INRA 717 1B4
P. deltoides
P. trichocarpa
P. euphratica
P. tremula x alba INRA 717 1B4
P. deltoides
P. trichocarpa
P. euphratica
P. tremula x alba INRA717 hybrid
P. deltoides
P. trichocarpa
P. euphratica
Tuskan Lab
Leaf succulence and anatomy, cuticle
thickness, stomatal physiology, and transformability.
Candidate Populus Target Species
Project Website: CAMbiodesign.org
Home Page:
News and press releases
Publications
Events: Upcoming meetings
Position openings
Newsletter signup
Project: Research Aims
Collaborators
Data Sharing: Downloads and
supplements
Own Cloud: Internal data
sharing
KBASE: Data Analysis and Modeling
KBASE Website:
http://kbase.science.energy.org
RNA-Seq data analysis
Genome-Seq data analysis
Comparative Genomics
Coexpression networks
Regulatory network modeling
to define CAM modules
Metabolic networks
Conclusions
Can crassulacean acid metabolism (CAM)
be engineered?
Will require a more detailed understanding of the
genetic requirements and their regulation for the
carboxylation, decarboxylation and stomatal control.
Will require a more detailed understanding of the
anatomical requirements (succulence, epidermal
waxes, stomatal density and control) of CAM.
Acknowledgements
Rebecca Albion
Travis Garcia
Jungmin Ha
Jesse Mayer
Juli Petereit
Richard Tillett
Won Yim
Bernard Wone
Rick Chen
Henrique De Paoli
Nancy Engle
Lee Gunter
Sara Jawdy
Guruprasad H. Kora
Anthony Palumbo
Zackary Moore
Mark Schuster
Heather Tran
Hengfu Yin
Susie Boxall
Phaitun Bupphada
Jack Davies
Louisa Dever
Jade Weller
Jianzhuang Yao
Project Support
Department of Energy Office of Science, Genomic Science: Biosystems Design to Enable Next-
generation Biofuels: Award #DE-C0008834
National Institutes of Health INBRE (P20 RR-016464) for Omics Centers and Bioinformatics Support
Questions?
http://CAMbiodesign.org
C4/CAM: Upcoming Meetings
CAM Systems
Biology/Ecology (New
Phytologist) – July 15-18,
2014 Granlibakken
Conference Center- S. Lake
Tahoe, CA
Plant and Animal Genome
(PAG) Workshop –
Functional Genomics of C4
and CAM Photosynthesis,
January 11, 2014 (Saturday,
10:30 am)
Project Director
John C. Cushman
Task Leaders (co-PDs)
AM Borland, J-G Chen, J Hartwell, M Martin, KA Schlauch, TJ Tschaplinski, GA Tuskan, D Weston, X Yang
External Scientific Advisory Board
Dr. James Bristow – JGI
Dr. Howard Griffiths – Cambridge University
Dr. Joe Holtum – James Cook University
Dr. Rowan Sage – University of Toronto
Dr. J.A.C. Smith – Oxford University
Dr. Stan Wullschleger – ORNL
University of Nevada, Reno (UNR)
John C. Cushman
CAM Testing in
Kalanchoë,
Arabidopsis and
Populus
GA Tuskan (ORNL)
AM Borland (ORNL)
J-G Chen (ORNL)
J Hartwell (UL)
X Yang (ORNL)
Network Modeling of CAM
Modules/KBase
DJ Weston (ORNL)
J Hartwell (UL)
AM Borland (ORNL)
J-G Chen (ORNL)
JC Cushman (UNR)
H Guo (UT), G Kora (ORNL)
KA Schlauch (UNR)
X Yang (ORNL)
CAM Metabolic &
Proteomic Profiling
TJ Tschaplinski (ORNL)
JC Cushman (UNR)
J Hartwell (UL)
M Martin (ORNL)
Metabolon Inc.
CAM Discovery
RNA/DNA/ChIP Seq
X Yang (ORNL)
JC Cushman (UNR)
J Hartwell (UL)
KA Schlauch (UNR)
University of Liverpool (UL)
James Hartwell
Oak Ridge National Laboratory (ORNL)
Xiaohan Yang
Network
Organization
Plan
INTACT System for ChIP Seq
Isolation of Nuclei Tagged in specific Cell Types
(INTACT) method allows affinity-based isolation of
nuclei from specific cell types.
K. laxiflora as target model (Bernie Wone)
A B
(Deal and Henifkoff, 2010a)
Opuntia ficus-indica Transcriptome
Comparison of well-watered and 50%
RWC loss in mesophyll and over a 24 diel
timecourse (Jesse Mayer, Bernie Wone)
Illumina-based sequencing in progress.
Metabolite study samples being submitted
this week.
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
110.00%
0 1234 56 7891011121314151617181920212223242526272829303132333435363738394041424344454647
%FreshW
eight
DaysA erWatering
rep1
rep2
rep3
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
00 10 20 30 40 50
WaterPoten
al(MPa)
%lossbyfreshweight
Project
Timeline
Aim Task Description FY13 FY14 FY15 FY16 FY17
Aim 1 Task 1.1 Transcriptome (RNA-Seq) sequencing
Task 1.2 Metabolic profiling
Task 1.3 Genomic DNA preparation, sequencing,
and genome assembly (DNA-Seq)
Task 1.4 Chromatin immunoprecipitation-DNA sequencing (ChIP-Seq)
Aim 2 Task 2.1 Co-expression network modeling in CAM plants
Task 2.2 Gene regulatory network modeling
Task 2.3 Consolidating CAM module discovery by
computational simulation
Task 2.4 Validation of CAM module design via loss-of-function knock-down in K.
fedtschenkoi
Task 2.5 Testing of CAM module design using
transient and stable gene expression systems
Aim 3 Task 3.1 CAM gene module assembly
Task 3.2 Site-specific stacking of CAM modules in
Arabidopsis
Task 3.3 Site-specific stacking of CAM modules in
Populus
Aim 4 Task 4.1 Real-time RT-PCR expression analysis of transgenes
Task 4.2 Measurement of biochemical parameters
Task 4.3 CO2 assimilation, stomatal conductance
and transpiration rates
Task 4.4 Leaf carbon balance and level/mode of CAM activity
Task 4.5 Biomass productivity of transgenic plants
Arid Epiphytic Aquatic
Diverse Habitats of CAM Plants
Photos: Anne M. Borland
~7% of all plant species are CAM
Market Values of Economically Important CAM Species
Species Worldwide value
Pineapple $3.0 billion/yr
Vanilla (flavoring) $0.5 billion/yr
Orchids $9 billion/yr
Agave (tequila, sisal) $1.2 billion/yr
Opuntia (pads, fruits) >$100 million/yr
Horticultural and
Ornamentals >$100 million/yr
CAM Plants as Bioenergy Crops
1/3 earth’s surface area is arid or semi-arid
CAM species can be grown on marginal lands NOT suitable for C3 and C4 species (200-400 mm precipitation/year)
http://www.esa.int
40% of Global Land Area is Arid
Source: United Nations Environment Program: 2012
Global Dryland Degradation
Source: United Nations Environment Program: 2012
Global Annual Groundwater Depletion
Source: Gleeson et al. 2012