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Hyper-lignified root systems as a carbon sink in Arabidopsis thaliana Nye, Adrienne Juliana 2009

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HYPER‐LIGNIFIED
ROOT
SYSTEMS
AS
A
CARBON
SINK
IN
ARABIDOPSIS
THALIANA
  by ADRIENNE JULIANA NYE B. Sc., The University of Victoria, 2005  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Plant Science)  
 
 
 
 
  
  
 
  THE
UNIVERSITY
OF
BRITISH
COLUMBIA
 
 (Vancouver)
 
 
 
 
 
 October
2009
 
 ©
Adrienne
Juliana
Nye,
2009
  Abstract
  
 Lignified
 plant
 cell
 walls
 represent
 an
 immense
 carbon
 sink
 to
 offset
 rising
 atmospheric
 carbon
 dioxide
 (CO2)
 due
 to
 the
 chemical
 stability
 and
 structural
 diversity
 of
 the
 bonds
 formed
 between
 lignin
 subunits,
 making
 it
 the
 slowest
 decomposing
 component
 of
 dead
 vegetation.
 This
 thesis
 explores
 the
 feasibility
 of
 increasing
 lignin
 deposition
 in
 roots
 through
 overexpression
 of
 SND1
 (Secondary
 Wall
Associated
NAC
Domain
Protein
1),
a
key
transcriptional
activator
involved
in
 regulating
secondary
wall
biosynthesis
in
fibres,
under
the
control
of
two
different
 putative
root‐specific
promoters,
4‐coumarate:CoA
ligase
1
(4CL1)
and
glutathione
 S‐transferase‐tau
 class
 19
 (GSTU19).
 Transgenic
 plants
 were
 analyzed
 at:
 1)
 the
 molecular
level
(transcription
of
lignin
pathway
genes
and
regulatory
transcription
 factors
 (TFs)
 involved
 in
 cell
 wall
 biosynthesis),
 2)
 the
 chemical
 level
 (lignin
 content)
 and
 3)
 the
 plant
 growth
 and
 development
 level
 (phenotyping
 and
 microscopy).
 
 Results
 showed
 that:
 i)
 SND1
 was
 overexpressed
 in
 a
 tissue‐specific
 manner
 in
 roots,
 ii)
 SND1
 overexpression
 caused
 an
 upregulation
 of
 its
 previously
 known
 direct
 downstream
 targets,
 iii)
 SND1
 overexpression
 did
 not
 result
 in
 a
 modification
 of
 indicative
 lignin
 biosynthetic
 pathway
 genes
 in
 roots,
 iv)
 plants
 overexpressing
SND1
in
roots
generally
produced
plants
with
decreased
total
lignin
 content,
 v)
 plants
 overexpressing
 SND1
 in
 roots
 generally
 showed
 an
 increase
 in
 lateral
root
density,
and
vi)
seed
traits,
plant
growth
and
development,
plant
height
 and
lignin
deposition
patterns
in
roots
remained
unaltered.

Misregulation
of
SND1
 in
roots
did
not
result
in
the
predicted
increase
in
lignin
deposition
patterns
in
this
 organ.
  
  ii
  Table
of
Contents
 Abstract.......................................................................................................................................ii
 Table
of
Contents ................................................................................................................... iii
 List
of
Tables ............................................................................................................................. v
 List
of
Figures...........................................................................................................................vi
 Abbreviations .........................................................................................................................vii
 Acknowledgements............................................................................................................. viii
 Research
and
material
contributions.....................................................................................viii
 Support
and
guidance .....................................................................................................................ix
 1.
 Introduction ...................................................................................................................... 1
 1.1
 Global
climate
change
and
mitigating
global
carbon
emissions ............................1
 1.1.1
 The
global
carbon
cycle
and
the
role
of
plants
as
terrestrial
carbon
sinks ............3
 1.1.2
 Increasing
agricultural
soil
carbon
stocks
through
carbon
sequestration .............4
 1.1.3
 Root‐derived
soil
carbon ..............................................................................................................7
 1.1.4
 Arabidopsis
thaliana
as
a
model
organism............................................................................8
 1.2
 Secondary
cell
walls
and
the
importance
of
lignin
in
vascular
plant

biology...9
 1.2.1
 Lignin
biosynthesis ......................................................................................................................12
 1.2.2
 Lignin
as
a
carbon
sink ...............................................................................................................16
 1.2.3
 Lignin
modification
via
the
monolignol
biosynthetic
pathway ................................17
 1.3
 Transcription
factors
as
tools
for
metabolic
engineering
in
plants................... 17
 1.3.1
 The
role
of
transcription
factors
in
the
regulation
and
modification
of
lignin

 
 biosynthesis.....................................................................................................................................18
 1.4
 Root­specific
and
inducible
gene
expression
systems............................................ 23
 1.4.1
 Herbicidal
safeners
as
inducers
of
root‐specific
gene
expression...........................26
 1.5
 Project
rationale
and
thesis
objectives........................................................................ 27
 2.
 Materials
and
Methods ............................................................................................... 30
 2.1
 Organ­specific
expression
of
candidate
gene
and
promoters.............................. 30
 2.2
 Cis­element
analysis
of
candidate
promoters............................................................ 31
 2.3
 Preparation
of
the
4CL1pro­SND1
gene
expression
constructs
and

transgenic
 
 plants ....................................................................................................................................... 31
 2.4
 Preparation
of
the
GSTU19pro­SND1
gene
expression
constructs
and

 
 transgenic
plants ................................................................................................................. 35
 2.5
 Molecular
analysis
of
transgenic
plants ...................................................................... 38
 2.5.1
 Reverse
transcription‐PCR
of
direct
downstream
targets
of
SND1 ........................38
 2.5.2
 Reverse
transcription‐PCR
of
lignin
biosynthetic
pathway
enzymes ....................39
 2.6
 Determination
of
lignin
content
in
transgenic
plants
overexpressing

SND1. 40
 2.6.1
 Plant
growth
conditions.............................................................................................................40
 2.6.2
 Rapid,
micro
scale,
acetyl
bromide‐based
method
for
lignin
content
analysis..41
 2.6.3
 Klason
lignin
or
72%
(v/v)
H2SO4
acid
procedure
and
carbohydrate
analysis .42
 2.7
 Starch
analysis...................................................................................................................... 43
 2.8
 Phenotypic
analysis
of
transgenic
plants .................................................................... 44
 2.8.1
 Seed
phenotyping..........................................................................................................................44
 2.8.2
 Root
growth
and
lateral
root
density ...................................................................................44
 2.8.3
 Plant
growth
and
height.............................................................................................................45
 2.8.4
 Microscopy.......................................................................................................................................45
 
  iii
  3.
 Results .............................................................................................................................. 47
 3.1
 Organ­specific
expression
of
candidate
gene
and
promoters.............................. 47
 3.2
 Cis­regulatory
element
analysis
of
candidate
promoters...................................... 51
 3.3
 SND1
overexpression
in
transgenic
plants ................................................................. 55
 3.4
 Molecular
analysis
of
transgenic
plants
overexpressing
SND1 ........................... 56
 3.5
 Determination
of
lignin
content
in
transgenic
plants
overexpressing


SND1 59
 3.5.1
 Determination
of
lignin
content
in
transgenic
plants
overexpressing
SND1
by

 
 rapid
micro‐scale
acetyl
bromide
method .........................................................................59
 3.5.2
 Cellulose,
starch
and
Klason
lignin
analysis ......................................................................60
 3.6
 Phenotypic
analysis
of
transgenic
plants
overexpressing
SND1 ......................... 63
 3.6.1
 Seed
phenotyping..........................................................................................................................63
 3.6.2
 Root
growth
and
lateral
root
density ...................................................................................64
 3.6.3
 Plant
growth
and
height.............................................................................................................66
 3.6.4
 Microscopy.......................................................................................................................................68
 4.
 Discussion ....................................................................................................................... 71
 5.
 Conclusions
and
Future
Directions ........................................................................ 98
 Bibliography.........................................................................................................................103
 Appendices ...........................................................................................................................112
 Appendix
A.
 Primary
sequences
of
gene
expression
constructs ..............................112
 Appendix
B.
 Cis­acting
DNA
regulatory
element
analysis
of
At4CL1
and
AtGSTU19
 
 promoters...........................................................................................................116
 Appendix
C.
 Primer
sequences ............................................................................................119
 Appendix
D.
 Media,
Buffers
and
Reagent
Stocks............................................................121
 Appendix
E.
 One­way
analysis
of
variance
(ANOVA)
for
average
seed
weight



and
 
 lateral
root
density..........................................................................................123
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  iv
  List
of
Tables
 
  Table
1.
 
 
 
 Table
2.

 
 
 
 Table
3.
 
 
 
 Table
4.

 
 
 
 Table
5.
 
 
 
 Table
6.

 
 
 
 Table
7.

 
 
 
 Table
8.

 
 
  Candidate
genes
whose
promoters
have
the
potential
to
drive
root­
 specific
transgene
expression.............................................................................48
 Cis­acting
DNA
regulatory
elements
located
2000
bp
upstream
of
the

 transcription
start
site
of
At4CL1
(At1g51680).............................................53
 Cis­acting
DNA
regulatory
elements
located
2000
bp
upstream
of
the

 transcription
start
site
of
AtGSTU19
(At1g78380).......................................54
 Cell
wall
composition
of
roots
from
empty
vector
and
transgenic
lines

 overexpressing
SND1.............................................................................................62
 Summary
of
cis­acting
regulatory
DNA
elements
associated
with
root­
 specific
gene
expression.......................................................................................78
 Cis­acting
DNA
regulatory
element
analysis
of
At4CL1,
2000bp

 
 upstream
of
the
transcription
start
site........................................................116
 Cis­acting
DNA
regulatory
element
analysis
of
AtGSTU19,
2000bp

 upstream
of
the
transcription
start
site........................................................117
 List
of
all
primer
sequences
used
for
PCR,
reverse
transcription­PCR

 and
sequencing......................................................................................................119
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  v
  List
of
Figures
 
  Figure
1.
 
 Figure
2.
 
 Figure
3.
 
 Figure
4.
 
 
 
 Figure
5.


 
 
 
 Figure
6.
 
 
 
 Figure
7.
 
 
 
 Figure
8.

 
 
 
 Figure
9.
 
 
 
 Figure
10.
 
 
 
 Figure
11.
 
 
 
 Figure
12.
 
 
 
 Figure
13.

 
 
 
 Figure
14.

 
 
 
 Figure
15.
  Monolignols
and
Lignin.........................................................................................13
  Figure
16.
 
 
 
 Figure
17.

 
 
  One­way
ANOVA
statistical
analysis
to
determine
differences
in


 average
seed
weight
between
genotypes......................................................123
  
  The
Phenylpropanoid
Pathway..........................................................................15
 Phylogenetic
tree
of
five
closely
related
NAC
domain
proteins...............19
 Schematic
diagram
of
the
SND1
overexpression
constructs
in

 
 pPZP211......................................................................................................................33
 Genevestigator
heat
map
of
candidate
genes
whose
promoters

 have
the
potential
to
drive
root­specific
transgene
expression..............49
 Organ­specific
expression
of
candidate
gene
and
promoters
from

 four­week­old
Arabidopsis
plants......................................................................51
 Transcriptional
analysis
of
T2
generation
plants
overexpressing

 SND1
using
RTPCR...................................................................................................55
 Transcriptional
analysis
of
transcription
factors
known
to
be

 
 direct
targets
of
SND1.............................................................................................57
 Reverse
transcription­PCR
analysis
of
genes
involved
in
lignin

 
 biosynthesis...............................................................................................................58
 Lignin
content
in
transgenic
Arabidopsis
plants
overexpressing

 
 SND1.............................................................................................................................60
 Seed­related
phenotypes
of
T3
generation
seeds
from
transgenic

 and
empty
vector
constructs...............................................................................64
 Primary
root
extension,
lateral
root
formation
and
number
of

 lateral
roots
per
cm
(lateral
root
density)
of
14­day­old
seedlings.......66
 Plant
growth
and
height
time­course
experiment
for
transgenic

 Plants
overexpressing
SND1
and
empty
vector
lines..................................67
 Wax­embedded
root­hypocotyl
cross
sections
of
SND1
overexpressors

 and
empty
vector
control
lines...........................................................................69
 Auto­fluorescence
of
lignin
in
root­hypocotyl
cross­sections..................70

  One­way
ANOVA
statistical
analysis
to
determine
differences
in


 average
number
of
lateral
roots
between
genotypes...............................124
  
 
  vi
  Abbreviations
 
  4CL
 4‐coumarate:CoA
ligase
  HCT
 p‐hydroxycinnamoyl‐CoA:
 quinate/shikimate
4‐ hydroxycinnamoyltransferase
 KNAT
 Knotted1‐like
TALE
 homeodomain
protein
 LB
 Luria‐Bertani
 LRD
 lateral
root
density
  4CL1
 4‐coumarate:CoA
ligase
1
 6xHis
 hexameric
histidine
tag
 ANACO12
 Arabidopsis
NAC
domain
 containing
protein
12
 ARF
 auxin
response
factor
 ASF‐1
 nuclear
activating
sequence‐1‐ binding
factor
 ATAF
1/2
 arabidopsis
transcription
 activation
factor
 bp
 base
pair
 C
 carbon
 C3H
 C4H
 CAD
 CCR
  LRP
 lateral root primordium 
 Mya
 million
years
ago
 mRNA
 messenger
RNA
  4‐coumarate‐3‐hydroxylase
 cinnamate‐4‐hydroxylase
 cinnamyl
alcohol
dehydrogenase
 cinnamoyl‐CoA‐reductase
  CCoAOMT
 caffeoyl‐CoA
3‐O‐ methyltransferase
 cDNA
 complementary

 deoxyribonucleic
acid
 CDS
 coding
sequence
 CO2
 carbon
dioxide
 CoA
 coenzyme
A
 COMT
 caffeic
acid/5‐ hydroxyconiferaldehyde
O‐ methyltransferase
 CUC2
 cup‐shaped
cotyledon
2
 DNA
 deoxyribonucleic
acid
 F5H
 ferulate‐5‐hydroxylase
 G
 guaiacyl
(lignin)
  RNA
 RT
 S
 SND1
  GHGs
 GPI
 GSH
 GSTU19
  
  
  MS
 Murashige
and
Skoog
 MYB
 v‐myb
myeloblastosis
viral
 oncogene
homolog
(avian)
 NAC
 NAM,
ATAF1/2
and
CUC2
 NAM
 no
apical
meristem
 
 
 NST1
 NAC
secondary
wall
thickening
 promoting
factor
1

 NST2
 NAC
secondary
wall
thickening
 promoting
factor
2
 NST3
 NAC
secondary
wall
thickening
 promoting
factor
3
 OD
 optical
density
 ORF
 open
reading
frame
 PAL
 phenylalanine
ammonia‐lyase
 PCR
 polymerase
chain
reaction
  greenhouse
gases
 glycosylphosphatidylinositol
 glutathione
 glutathione
S‐transferase‐tau
 class
19
 Gt
 gigatonnes
 GUS
 beta‐glucuronidase
 H
 hydroxyphenyl
(lignin)
  SOC

 SIC
 SURE
 TF
  ribonucleic
acid
 reverse
transcription
 syringyl
(lignin)
 Secondary
Wall
Associated
NAC
 Domain
Protein
1
 soil
organic
carbon
 soil
inorganic
carbon
 sulfur‐responsive
element

 transcription
factor
  UGT
 UDP‐glucosyltransferase
 VND6
 Vascular‐related
NAC‐Domain
6

 VND7
 Vascular‐related
NAC‐Domain
7

  vii
  Acknowledgements
 Research
and
material
contributions
 I
 would
 like
 to
 begin
 by
 expressing
 my
 sincerest
 gratitude
 to
 my
 supervisor,
 Dr.
 Brian
Ellis,
who
has
proven
to
be
an
exceptional
mentor
in
guiding
me
through
my
 master’s
 degree.
 His
 warm
 and
 approachable
 nature,
 along
 with
 his
 exceedingly
 brilliant
 contributions,
 thoughtful
 insights
 and
 endless
 encouragement
 throughout
 my
research,
has
inspired
me
to
grow
and
develop
on
both
a
personal
and
academic
 level.
 
 This
 work
 would
 not
 have
 been
 possible
 without
 the
 guidance,
 ideas,
 suggestions
and
support
offered
by
my
committee
members,
Dr.
Leonard
Foster
and
 Dr.
 James
 Kronstad,
 whose
 time
 and
 energy
 devoted
 to
 improving
 my
 research
 project
is
 deeply
 appreciated.
 
I
acknowledge
Dr.
Patrick
von
Aderkas
and
 the
 late
 Yousuf
 Ebrahim
 for
 recognizing
 my
 potential
 and
 encouraging
 me
 to
 pursue
 this
 master’s
 degree.
 
 In
 addition,
 I
 would
 like
 to
 thank
 Margaret
 Ellis,
 our
 lovely
 lab
 manager,
for
her
excellent
ordering
skills,
organizational
prowess
and
commitment
 to
 ensuring
 that
 lab
 affairs
 run
 smoothly.
 
 I
 am
 indebted
 to
 my
 student
 and
 lab
 colleagues,
 Hardy
 Hall,
 QingNing
 Zeng,
 Apurva
 Bhargava,
 Ankit
 Walia,
 Doris
 Vong,
 Jia
 Cheng,
 JinSuk
 Lee,
 Earl
 Alikpala,
 and
 Dr.
 Jun
 Chen
 for
 their
 endless
 patience,
 moral
support
and
generous
friendship
offered
while
teaching
me
new
techniques,
 answering
 my
 many
 questions
 and
 allowing
 me
 above
 all
 to
 be
 myself.
 
 Their
 contribution
 to
 stimulating
 conversations
 over
 coffee
 and
 shared
 meals,
 company
 during
 long
 hours
 poured
 over
 gels
 and
 petri
 dishes,
 priceless
 involvement
 in
 several
lab
adventures
and
eventful
musical
collaborations,
made
my
time
pass
by
 here
in
somewhat
of
a
bliss,
providing
me
with
memories
to
last
a
lifetime.
I
would
  
  viii
  like
 to
 recognize
 the
following
 people
for
 their
invaluable
 contributions
 to
 helping
 me
 complete
 my
thesis
research:
Jim
Guo
of
 the
Chen
 Lab
for
 devoting
his
time
 to
 teach
me
how
to
use
the
microscope,
Zorica
Kotur
of
the
Glass
Lab
for
her
help
and
 guidance
with
the
hydroponics,
Julia
Nowak
of
the
Cronk
Lab
for
aiding
me
with
the
 hand
 sectioning,
 staining
 and
 microscopy
 of
 my
 transgenic
 plant
 lines,
 Dr.
 Sarah
 McKim
 of
 the
 Haughn
 Lab
 for
 assistance
 with
 the
 wax
 embedding
 protocol,
 microtome
 sectioning
 and
 staining
 of
 my
 transgenic
 plant
 lines,
 Lifang
 Zhao
 for
 providing
me
with
the
pPZP211
empty
vector
seed
lines,
Xue
Feng
Chang
(Harry)
of
 the
Beatson
Lab
at
BCIT
for
his
immense
involvement
in
the
acetyl
bromide
lignin
 analysis,
 Vicki
 Maloney
 of
 the
 Mansfield
 Lab
 for
 her
 amazing
 contribution
 to
 the
 Starch
and
Klason
lignin
analyses,
and
to
Paul
Lee
(undergraduate
in
the
Ellis
Lab)
 for
 his
 enthusiasm
 and
 painstaking
 commitment
 to
 helping
 me
 with
 seed
 phenotyping,
germination
assays
and
RNA
extractions
in
the
summer
of
2009.


  Support
and
guidance
 
 A
very
heartfelt
thanks
goes
out
to
my
Mom
and
Dad
for
their
immeasurable
love,
 generosity,
encouragement
and
financial
support
throughout
my
life.
Their
selfless
 acts
of
kindness
and
tireless
ability
to
provide
me
with
whatever
I
need,
constantly
 remind
 me
 to
 remain
 humble
 and
 be
 grateful
 for
 everything
 that
 is
 given
 to
 me.

 Without
providing
me
with
the
safe
and
loving
environment
needed
for
growth
and
 self‐discovery
as
I
was
growing
up
to
the
hour‐long
phone
conversations
and
visits
 home
throughout
my
degree,
I
would
not
be
who
I
am
today
and
for
that
am
forever
 in
their
debt.

I
feel
honoured
to
share
my
genes
(and
my
birth
date)
with
my
sister,
 Gabrielle,
whose
love
and
support
always
seem
to
show
up
at
exactly
the
right
time.




 
  ix
  Her
 belief
 in
 me
 and
 my
 ability
 to
 succeed
 throughout
 my
 graduate
 studies
 have
 given
 me
 the
 strength
 to
 pull
 through
 to
 the
 end.
 
 I
 would
 like
 to
 convey
 a
 very
 special
 message
 to
 all
 my
 friends,
 who
 have
 made
 my
 time
 here
 both
 memorable
 and
delectably
fun.

To
the
ones
who
were
there
through
all
the
ups
and
downs,
ins
 and
outs,
who
listened
when
I
needed
to
vent,
who
lifted
me
up
when
I
was
down
 and
who
provided
me
with
the
courage
I
needed
to
deal
with
everyday
life,
I
raise
 my
glass
to
you!
 
 Finally,
I
would
like
to
dedicate
this
thesis
to
my
late
grandmother,
Anyu,
for
always
 believing
in
me
but
more
importantly
showing
me,
by
example,
what
it
means
to
be
 a
true
Survivor.

I
am
deeply
grateful
for
the
contribution
she
has
made
to
my
life
as
 a
caregiver,
friend
and
kindred
spirit.

Her
life
has
inspired
me
in
more
ways
than
I
 can
express;
she
was
the
embodiment
of
strength,
self‐empowerment
and
above
all
 grace.

Her
love,
wisdom
and
spirituality
have
always
taught
me
to
be
true
to
myself,
 a
theme
that
has
become
the
driving
force
behind
all
that
I
do,
all
that
I
am
and
is
 ultimately
what
propels
me
forward
into
the
future,
with
no
regrets.





  
  x
  1.
  Introduction
  1.1
  Global
climate
change
and
mitigating
global
carbon
emissions
  
 Our
 planet
 is
 habitable
 due
 to
 its
 proximity
 to
 the
 sun
 and
 to
 the
 layer
 of
 gases
 surrounding
it,
which
we
have
come
to
know
as
our
atmosphere
(Karl
&
Trenberth,
 2003).
 
 
 This
 natural
 greenhouse
 effect
 results
 from
 the
 presence
 of
 a
 particular
 combination
of
atmospheric
gases
including
nitrogen,
oxygen,
argon,
carbon
dioxide
 (CO2)
and
other
trace
gases
(Karl
&
Trenberth
2003).


These
gases
act
as
a
sort
of
 insulating
 blanket,
 trapping
 solar
 energy
 as
 heat
 and
 regulating
 average
 global
 surface
temperatures
within
a
range
suitable
for
life
to
evolve
(Li
et
al.
2009).


 
 Life
 on
 Earth
 as
 we
 know
 it
 relies
 greatly
 on
 the
 balance
 of
 these
 important
 greenhouse
 gases
 (GHGs).
 
 Through
 both
 human
 endeavors
 and
 natural
 fluxes
 through
the
Earth
system,
it
is
now
acknowledged
that
atmospheric
CO2
levels
have
 increased
 about
 35%
 since
 the
 early
 ages
 of
 industrialization
 (Karl
 &
 Trenberth
 2003;
 Millard
 et
 al.
 2007).
 
 What’s
 more,
 is
 that
 roughly
 half
 of
 the
 CO2
 released
 since
the
Industrial
Revolution
remains
in
the
atmosphere
while
the
other
half
has
 been
sequestered
in
the
ocean
as
well
as
terrestrial
ecosystems
(Karl
&
Trenberth
 2003;
Millard
et
al.
2007;
Raven
&
Karley
2006).

It
has
been
hypothesized
that
one
 result
 of
 this
 increase
 in
 GHGs
 (atmospheric
 CO2,
 methane
 and
 nitrous
 oxide)
 is
 a
 pattern
 of
 climate
 change
 phenomena
 that
 includes
 but
 is
 not
 limited
 to:
 rises
 in
 global
 surface
 temperatures,
 increased
 occurrence
 of
 extreme
 weather
 events,
 increased
 incidence
 and
 intensity
 of
 wild
 fires,
 shifting
 of
 ecosystems,
 rising
 sea
  
  1
  levels
 and
 changes
 in
 disease
 transmission
 dynamics
 (Lal
 2008).
 
 In
 addition,
 anthropogenic
 activities
 such
 as
 deforestation,
 fossil
 fuel
 combustion,
 altered
 land
 use
 through
 urbanization,
 wetland
 draining,
 soil
 cultivation
 and
 biomass
 burning
 have
 also
 had
 a
 large‐scale
 impact
 on
 terrestrial
 surface
 characteristics
 and,
 by
 extension,
on
climate
change
(Lal
2008;
Karl
&
Trenberth,
2003).

As
a
result,
there
 is
 growing
 interest
 in
 stabilizing
 increases
 in
 GHGs
 with
 the
 goal
 of
 mitigating
 the
 risks
associated
with
global
climate
change
(Lal
2008).

An
introduction
to
all
of
the
 mitigation
 strategies
 proposed
 for
 lowering
 GHG
 emissions
 is
 beyond
 the
 scope
 of
 this
 thesis;
 therefore,
 only
 those
 related
 to
 carbon
 (CO2)
 emissions
 will
 be
 mentioned.
 
 The
 reason
 being
 that
 of
 all
 the
 GHGs
 contributing
 to
 global
 climate
 change,
CO2,
next
to
water
vapour,
is
considered
one
of
the
most
important
(Malhi
et
 al.
2002).



 
 There
are
currently
three
broad
categories
of
mitigation
strategies
and
practices
for
 lowering
 CO2
 emissions:
 (i)
 to
 reduce
 global
 energy
 use,
 (ii)
 to
 reduce
 emissions,
 and
(iii)
to
enhance
removal
via
carbon
sequestration
(Lal
2008;
Smith
et
al.
2008).


 The
 last
 of
 these
 approaches
 has
 garnered
 the
 attention
 of
 both
 scientists
 and
 politicians
 as
 an
 effective
 strategy
 for
 mitigating
 GHG
 emissions
 (Mondini
 &
 Sequi
 2008).
 
 As
 a
 result
 of
 this
 interest,
 four
 main
 types
 of
 carbon
 sequestration
 have
 been
 proposed:
 ocean
 storage,
 geological
 storage,
 biomass
 storage
 and
 mineral
 carbonation
 (Oelkers
 &
 Cole
 2008).
 In
 conclusion,
 carbon
 sequestration
 is
 by
 no
 means
 instantaneous
 and
 consideration
 must
 be
 given
 to
 the
 fact
 that
 strategies,
 practices
and
techniques
take
time
to
develop
and
implement.


  
  2
  
 1.1.1 The
global
carbon
cycle
and
the
role
of
plants
as
terrestrial
carbon
sinks

 
 In
 order
 to
 develop
 workable
 strategies
 for
 mitigating
 global
 climate
 change
 we
 must
first
understand
how
the
global
carbon
(C)
cycle
works
(Lal
2008).

The
global
 C
cycle
is
typically
thought
of
as
an
interconnected
flow
of
C
through
four
principal
 reservoirs:

the
terrestrial
biosphere,
the
oceans,
fossil
carbon
and
the
atmosphere

 (Schimel
 1995;
 Oelkers
 &
 Cole,
 2008).
 
 
 
 In
 the
 terrestrial
 biosphere,
 a
 number
 of
 organisms
 (cyanobacteria,
 green
 algae
 and
 land
 plants)
 have
 specialized
 mechanisms
 that
 allow
 for
 absorption
 of
 CO2
 into
 their
 cells.
 
 With
 the
 addition
 of
 water
 and
 energy
 from
 solar
 radiation,
 they
 use
 photosynthesis
 to
 chemically
 convert
 CO2
 to
 carbohydrates
 (Black
 1973).
 
 Conversely,
 CO2
 and
 energy
 can
 be
 released
from
terrestrial
ecosystems
by
the
process
of
respiration.

This
involves
the
 metabolic
 breakdown
 of
 C‐based
 organic
 molecules
 primarily
 into
 gaseous
 CO2,
 among
other
byproducts.

Every
year,
respiration
returns
almost
half
of
the
CO2
that
 is
 absorbed
 by
 photosynthesis
 to
 the
 atmosphere
 (Falkowski
 et
 al.
 2000;
 Black
 1973).
 The
 movement
 of
 atmospheric
 C
 through
 photosynthesis,
 respiration,
 and
 back
 to
 the
 atmosphere
 is
 considerable,
 and
 this
 flux
 produces
 notable
 annual
 fluctuations
in
atmospheric
CO2
concentrations
(Falkowski
et
al.
2000).

 
 Photosynthetic
organisms
play
a
significant
role
in
the
global
C
cycle
and
over
time,
 significant
amounts
of
C
can
be
stored
or
released
from
terrestrial
biomes
(Schimel
 1995).
 
 For
 example,
 changes
 in
 land
 use
 can
 greatly
 contribute
 to
 carbon
 source/sink
 dynamics,
 as
 demonstrated
 by
 the
 accumulation
 of
 C
 in
 the
 living
 
  3
  tissues
of
new
plant
growth
and
within
the
soil
of
regenerating
forests
following
the
 abandonment
 of
 agricultural
 lands,
 causing
 a
 net
 decrease
 in
 contributions
 to
 atmospheric
CO2
concentrations
(Schimel
1995).



In
other
words,
as
atmospheric
 CO2
 increases,
 terrestrial
 plants
 can
 become
 a
 potential
 sink
 for
 anthropogenic
 carbon
 (Falkowski
 et
 al.
 2000).
 
 These
 net
 returns
 and
 losses
 (or
 fluxes)
 of
 C
 between
 the
 four
 previously
 mentioned
 C
 reservoirs
 are
 known
 as
 the
 global
 C
 budget
 (Schimel
 1995).
 
 Although
 terrestrial
 ecosystems
 have
 the
 potential
 to
 mitigate
 rising
 atmospheric
 CO2
 levels
 in
 the
 coming
 decades,
 there
 is
 still
 considerable
 uncertainty
 surrounding
 how
 these
 ecosystems
 will
 respond
 to
 the
 combined
effects
of
higher
CO2
concentrations,
 higher
temperatures,
and
changes
in
 soil
 dynamics
 (Falkowski
 et
 al.
 2000).
 
 In
 order
 to
 predict
 how
 these
 sources
 and
 sinks
 will
 behave
 in
 the
 future,
 it
 is
 crucial
 that
 we
 enhance
 our
 understanding
 of
 how
 plants
 will
 respond
 to
 the
 foreseeable
 increases
 in
 human‐derived
 CO2
 emissions
(Lal
2008;
Raven
&
Karley
2006).


 1.1.2
 Increasing
agricultural
soil
carbon
stocks
through
carbon
sequestration

 
 Since
ratification
of
the
Kyoto
Protocol,
most
C
mitigation
strategies
have
focused
on
 the
use
of
C
sinks
(natural
or
manmade
carbon
reservoirs)
as
a
form
of
C
offset,
and
 this
 focus
 has
 increased
 general
 awareness
 of
 carbon
 sink
 significance
 (Lal
 2008).


 In
 attempting
 to
 balance
 the
 global
 C
 budget,
 future
 economic
 growth
 would
 be
 based
on
a
‘carbon
neutral’
strategy,
or
rather
a
‘no
net
increase’
in
atmospheric
C
 (Lal
2008).

Therefore,
of
interest
to
those
involved
with
the
Kyoto
Protocol
is
any
 mitigation
practice
that
increases
C
input
via
photosynthesis
or
slows
the
return
of
 stored
 C
 via
 respiration
 or
 fire
 (Smith
 et
 al.
 2008).
 
 These
 strategies
 consequently
 
  4
  offer
the
potential
to
‘sequester’
C
or
build
C
‘sinks’
and
will
likely
be
a
focal
point
 for
 future
 approaches
 to
 mitigating
 climate
 change
 (Smith
 et
 al.
 2008).
 
 In
 short,
 carbon
sequestration
is
the
process
by
which
the
terrestrial
C
sink
generates
a
net
 removal
of
CO2
from
the
atmosphere.
 
 The
capture,
transport
and
final
deposition
of
carbon,
via
carbon
sequestration,
are
 largely
 dependent
 upon
 a
 complex
 set
 of
 biochemical
 and
 chemical
 processes
 (Oelkers
 &
 Cole
 2008).
 
 
 More
 specifically,
 sequestering
 C
 represents
 a
 metabolic
 dead
end,
inhibiting
its
reusability
by
terminating
its
physiological
activity
(Millard
 et
al.
2007),
and
more
securely
storing
it
in
other
more
long‐lived
C
reservoirs
(Lal
 2004).


 
 In
 the
 face
 of
 increasing
 carbon
 emissions,
 particular
 emphasis
 is
 being
 placed
 on
 this
process
of
carbon
sequestration
(Lal
2008).


For
example,
roughly
a
third
of
the
 terrestrial
 land
 surface
 is
 dominated
 by
 agricultural
 lands
 (crops
 or
 planted
 pastures)
whose
soils
are
capable
of
acting
as
either
carbon
sources
or
sinks
(Smith
 et
al.
2008).

Of
the
~2500
gigatons
(Gt)
of
worldwide
soil
C,
there
is
roughly
1550
 Gt
of
soil
organic
carbon
(SOC)
and
950
Gt
of
soil
inorganic
carbon
(carbonates)
(Lal
 2004).
 
 Furthermore,
 the
 global
 soil
 C
 pool
 is
 considerable
 compared
 to
 the
 atmospheric
C
pool
of
760
Gt
and
the
biotic
pool
of
560
Gt,
(Lal
2004).

However,
soil
 carbon
 sequestration
 is
 a
 trickier
 long‐term
 strategy
 for
 climate
 mitigation
 as
 opposed
 to
 reducing
 carbon
 emissions,
 given
 that
 it
 could
 be
 difficult
 to
 measure
 and
verify
the
amount
of
carbon
sequestered
below
ground
(Mondini
&
Sequi
2008).

  
  5
  Nevertheless,
 strategies
 to
 improve
 soil
 carbon
 stocks
 are
 appealing
 as
 part
 of
 an
 integrated
 sustainability
 approach
 since
 enhanced
 agricultural
 management
 often
 brings
with
it
an
array
of
other
desirable
environmental
and
economic
outcomes
in
 addition
 to
 mitigating
 climate
 change
 (Mondini
 &
 Sequi
 2008;
 Smith
 and
 Falloon,
 2005).
 
 
 Lal
 (2008)
 summarizes
 these
 soil
 C
 sequestration
 benefits
 as
 including
 enhanced
soil
quality,
improved
soil
productivity,
decreased
risk
of
soil
erosion
and
 sedimentation,
 and
 reduced
 water
 contamination
 and
 eutrophication.
 These
 potential
 outcomes
 also
 demonstrate
 that
 soil
 C
 sequestration
 could
 represent
 an
 approach
 to
 attain
 food
 security
 (Johnson
 et
 al.
 2007).
 
 In
 addition
 to
 both
 environmental
and
economic
benefits,
C
sequestration
is
attractive
for
one
another
 reason:
 it
 is
 likely
 to
 be
 the
 most
 cost‐effective
 and
 feasible
 method
 to
 lower
 atmospheric
 CO2
 levels
 within
 the
 first
 20–30
 years
 that
 it
 is
 implemented,
 thus
 effectively
 buying
 time
 while
 other
 technologies
 aimed
 directly
 at
 reducing
 GHG
 emissions
 are
 developed
 (Mondini
 &
 Sequi
 2008).
 
 
 However,
 yearly
 increases
 in
 SOC
 can
 only
 be
 sustained
 perhaps
 for
 50–100
 years,
 at
 which
 point
 increases
 in
 SOC
 are
 likely
 to
 slow
 and
 ultimately
 cease
 as
 the
 soil
 reaches
 a
 new
 equilibrium.


 This
emphasizes
the
point
that
C
sequestration
may
even
be
a
reversible
process
if
 suitable
soil
management
practices
are
not
maintained
(Lal

2004;
Mondini
&
Sequi
 2008).
 
 Given
the
sizeable
amount
of
global
carbon
contained
within
agricultural
soils,
it
is
 not
 surprising
 that
 the
 possibility
 of
 partially
 offsetting
 fossil‐fuel
 emissions
 by
 sequestering
 excess
 atmospheric
 C
 within
 these
 soils
 is
 now
 being
 strongly
  
  6
  advocated
 (West
 &
 Marland
 2002).
 
 Unfortunately,
 fossil‐fuel
 emissions
 over
 the
 next
 100
 years
 are
 anticipated
 to
 greatly
 exceed
 even
 the
 maximum
 amount
 of
 carbon
 that
 could
 potentially
 be
 sequestered.
 
 Therefore,
 carbon
 sequestration
 should
simply
be
seen
as
a
modest
contribution
to
a
much
larger
mitigation
plan
and
 not
as
a
replacement
for
the
development
of
new
energy
supplies,
improved
energy
 use
strategies
and
technological
innovations
required
to
stabilize
concentrations
of
 atmospheric
CO2
(Malhi
et
al.
2002).
 1.1.3
 Root‐derived
soil
carbon
 
 In
 terrestrial
 plants,
 the
 rhizosphere
 (the
 soil
 that
 immediately
 surrounds
 a
 plant
 root)
 encompasses
 the
 complex
 chemical,
 physical,
 and
 biological
 interactions
 between
roots
and
their
surrounding
environment
(Bais
et
al.
2006).

Plant
roots
are
 actively
involved
in:
soil‐microbe
interactions,
the
secretion
of
compounds
required
 for
 pathogen
 defense
 and
 absorption
 of
 soil
 nutrients.
 
 Roots
 also
 play
 a
 role
 in
 protecting
 above
 ground
 tissues
 from
 acidic
 conditions,
 heavy
 metals
 and
 drought
 (Koyama
et
al.
2005).

Studies
have
shown
that
soil
C
is
predominantly
composed
of
 root
 C
 and
 that
 within
 the
 organic
 soil
 horizons,
 root‐derived
 soil
 organic
 C
 generally
 decreases
 with
 depth
 (Jobbágy
 &
 Jackson
 2001;
 Rasse
 et
 al.
 2005).
 In
 natural
 ecosystems,
 root‐derived
 SOC
 is
 almost
 entirely
 a
 result
 of
 materials
 released
from
the
roots
of
natural
vegetation
or
crops
during
growth,
such
as
root
 exudates,
 sloughed
 off
 root
 tips
 and
 cells,
 mucilage
 and
 by
 decomposition
 of
 dead
 roots
 (Subedi
 at
 al.
 2006).
 
 There
 is
 still
 considerable
 debate
 over
 the
 amount
 of
 plant
 root
 C
 that
 contributes
 to
 the
 total
 C
 pool
 in
 the
 terrestrial
 biosphere.

 According
 to
 Robinson
 (2007),
 the
 best
 approximation
 of
 the
 root
 carbon
 pool
 is
 
  7
  270–280 Pg
 of
 the
 total
 terrestrial
 biome
 C
 pool
 of
 650 Pg
 (Subedi
 at
 al.
 2006).
 
 A
 global
root
C
reservoir
this
large
has
implications
for
land
C
sinks
as
a
response
to
a
 rise
 in
 atmospheric
 CO2.
 For
 instance,
 excess
 levels
 of
 CO2
 can
 stimulate
 photosynthesis
leading
to
an
estimated
20%
increase
in
plant
production,
which
in
 turn
could
enhance
soil
C
input
thus
increasing
soil
C
sequestration
(De
Graaff
et
al.
 2007).
 Moreover,
 this
 increase
 in
 SOC
 could
 thereby
 counterbalance
 the
 rise
 in
 atmospheric
CO2
(De
Graaff
et
al.
2007).


Conversely,
an
increase
in
input
of
SOC
due
 to
increased
rhizodeposition
and
root
litter
can
have
a
profound
influence
on
plant
 productivity
and
root
growth
(Subedi
at
al.
2006).

It
is
worth
noting
that
more
in‐ depth
 measurement
 of
 the
 impacts
 of
 root‐derived
 SOC
 from
 crop
 systems
 could
 make
invaluable
contributions
to
our
study
of
C
dynamics,
the
global
C
budget
and
C
 sequestration
(Subedi
at
al.
2006).

 1.1.4
 Arabidopsis
thaliana
as
a
model
organism

 
 Arabidopsis
 thaliana,
 also
 known
 as
 thale
 cress
 or
 mouse‐ear
 cress,
 is
 a
 small
 flowering
 plant
 widely
 used
 as
 a
 model
 organism
 in
 plant
 biology
 research.
 Arabidopsis
is
a
member
of
the
mustard
family
(Brassicaceae),
which
includes
many
 familiar
agricultural
species
such
as
broccoli,
cabbage,
turnip,
rapeseed,
cauliflower,
 brussels
 sprouts
 and
 radish.
 Arabidopsis
 itself
 is
 not
 of
 any
 major
 agricultural
 importance,
 but
 it
 is
 intensively
 used
 as
 a
 model
 organism
 for
 studies
 in
 genetics
 and
 molecular
 biology
 and
 is
 a
 close
 relative
 of
 canola,
 a
 major
 transgenic
 crop
 in
 Canadian
 agriculture.
 
 Arabidopsis
 can
 produce
 numerous
 self‐progeny
 in
 a
 relatively
 short
 time
 period,
 and
 it
 has
 very
 limited
 growth
 space
 requirements,
 which
means
that
large
populations
can
be
easily
grown
in
a
greenhouse
or
indoor
 
  8
  growth
 chamber.
 
 It
 has
 a
 relatively
 small,
 genetically
 tractable
 and
 sequenced
 genome
 that
 can
 be
 manipulated
 through
 genetic
 engineering
 more
 rapidly
 and
 easily
than
any
other
plant
genome
(About
Arabidopsis
2008;
Arabidopsis
thaliana
 2009).
  1.2
 
  Secondary
cell
walls
and
the
importance
of
lignin
in
vascular
plant
 biology

  
 Plant
 cell
 walls
 have
 many
 important
 functions
 such
 as,
 providing
 mechanical
 strength,
 regulating
 cell
 expansion
 and
 cell
 cohesion,
 water
 conduction
 and
 pathogen
 defense
 (Knox
 2008).
 
 The
 carbon‐based
 polymers,
 cellulose,
 hemicellulose,
 pectin
 and
 lignin,
 are
 what
 form
 the
 strong,
 but
 flexible
 macromolecular
 complexes
 of
 the
 cell
 walls
 of
 higher
 plants
 
 (Weng
 et
 al.
 2008).


 Cellulose,
 hemicellulose
 and
 pectin
 are
 the
 main
 carbohydrates
 comprising
 the
 growing
primary
cell
wall,
while
cellulose,
xylan,
other
hemicelluloses
and
lignin
are
 the
major
contributors
to
secondary
cell
walls
(Weng
et
al.
2008).

These
major
cell
 wall
components
are
variable
in
their
composition
and
relative
abundance,
and
the
 final
 combination
 in
 any
 given
 tissue
 often
 depends
 on
 the
 species,
 growing
 site,
 climate,
age
and
part
of
the
plant
(Ko
et
al.

2009).


 
 The
composition
of
cell
wall
components
can
be
distinguished
based
on
the
ground
 tissues
that
they
are
composed
of:
i.e.
parenchyma,
collenchyma,
and
sclerenchyma.

 Parenchyma
 and
 collenchyma
 cells,
 which
 possess
 primary
 cell
 walls,
 provide
 structural
 support
 in
 regions
 of
 the
 plant
 body
 that
 are
 still
 growing
 whereas
 sclerenchyma
tissue
has
both
primary
cell
walls
 and
thickened
secondary
cell
walls.

  
  9
  For
example,
specialized
cells
involved
in
structural
support
and
water
conduction,
 such
as
fibres,
are
composed
primarily
of
sclerenchyma
(Zhong
et
al.
2006;
Burk
et
 al.
2001;
Rogers
et
al.
2005;
Boerjan
et
al.
2003).

The
ability
to
resist
the
forces
of
 gravity
 and/or
 tension
 associated
 with
 the
 pull
 of
 the
 water
 column
 due
 to
 transpiration
 (involved
 in
 transporting
 water
 and
 solutes
 over
 long
 distances)
 comes
 from
 the
 evolution
 of
 these
 specialized
 cells,
 which
 provide
 mechanical
 support
to
regions
of
the
plant
body
that
have
ceased
elongation
(Rogers
et
al.
2005;
 Boerjan
 et
 al.
 2003).
 
 A
 defining
 feature
 of
 these
 cells
 is
 the
 secondary
 cell
 wall,
 which
 is
 formed
 in
 a
 highly
 coordinated
 manner
 by
 successive
 encrustation
 and
 deposition
 of
 the
 various
 cell
 wall
 constituents
 (Ko
 et
 al.
 
 2009).
 
 
 Lignin
 fills
 the
 spaces
 between
 cellulose
 and
 hemicellulose,
 where
 it
 is
 covalently
 linked
 to
 the
 hemicellulose
 and
 crosslinked
 to
 other
 plant
 polysaccharides
 (Weng
 et
 al.
 2008).

 The
 secondary
 cell
 wall
 polysaccharides
 are
 highly
 hydrophilic
 and
 are
 easily
 permeable
 to
 water
 whereas
 lignin
 is
 more
 hydrophobic.
 
 Lignification
 of
 the
 secondary
 cell
 wall
 thus
 waterproofs
 the
 cell
 wall
 and
 facilitates
 the
 transport
 of
 water
and
solutes
through
the
vascular
system
(Boerjan
et
al.
2003).

In
summary,
 lignified
secondary
cell
walls
are
essential
for
the
function
of
structurally
supportive
 and
conductive
xylem
tissues.

 
 Cell
 wall
 lignification
 emerged
 in
 the
 plant
 kingdom
 about
 430
 million
 years
 ago
 (Mya)
 and
 is
 considered
 to
 be
 a
 relatively
 recent
 process
 in
 the
 evolution
 of
 photosynthetic
organisms,
which
developed
approximately
2000
Mya
(Boerjan
et
al.
 2003).
 
 The
 ability
 to
 produce
 lignin
 is
 thought
 to
 have
 been
 crucial
 for
 the
  
  10
  adaptation
of
aquatic
plants
to
a
terrestrial
environment
where
they
were
likely
to
 face
 critical
 new
 stresses
 including
 UV
 radiation,
 desiccation
 and
 attack
 by
 established
and
diverse
communities
of
soil
microbes
(Emiliani
et
al.
2009).


In
fact,
 deposition
of
lignin
or
rather
the
synthesis
of
monolignols,
has
been
shown
to
play
 an
 essential
 role
 in
 the
 assembly
 of
 cell
 wall
 appositions
 (CWAs),
 also
 known
 as
 papillae,
 which
 provide
 a
 primary
 means
 of
 defense
 against
 pathogens
 that
 are
 attempting
to
penetrate
the
cell
wall
(Bhuiyan
et
al.
2009).


 
 The
 study
 of
 phenylpropanoid
 metabolism
 (the
 pathway
 responsible
 for
 the
 lignin
 biosynthesis
as
well
as
some
other
important
secondary
metabolic
compounds)
has
 been
 a
 central
 theme
 in
 plant
 biochemistry.
 In
 addition
 to
 lignin
 formation,
 the
 contributions
to
plant
fitness
of
many
phenylpropanoid
pathway
intermediates
and
 end
products
such
as
antioxidants,
ultra‐violet
protectants,
phytoalexins,
pigments,
 aroma
 compounds
 and
 antiherbivory
 compounds,
 emphasizes
 the
 importance
 of
 this
 metabolic
 system
 (Humphreys
 &
 Chapple
 2002).
 
 Moreover,
 the
 phenylpropanoid
 pathway
 represents
 an
 essential
 and
 ubiquitous
 metabolic
 trait
 amongst
land
plants,
since
it
supplies
vital
compounds
such
as
lignin
(essential
for
 vascularization
and
xylem
formation
as
well
as
structural
support
and
stem
rigidity
 out
of
water),
and
flavonoids
(essential
for
reproductive
biology
and
for
protection
 against
 UV
 via
 pigment
 accumulation,
 for
 deterring
 microbial
 attack
 and
 for
 modulating
 symbiotic
 plant‐microbe
 interactions
 by
 production
 of
 anti‐microbial
 compounds
such
as
phytoalexins,
and
signaling
flavonoids)
(Emiliani
et
al.
2009).
  
  11
  1.2.1
 Lignin
biosynthesis

 
 The
 coordinated
 expression
 of
 numerous
 genes
 is
 required
 for
 the
 biosynthesis,
 assembly
 and
 deposition
 of
 both
 primary
 and
 secondary
 cell
 wall
 components,
 including
the
determining
structural
and
chemical
specificity
of
lignified
secondary
 walls

(Boudet
et
al.
2003).
Lignin
is
a
racemic
aromatic
polymer
that
results
from
 the
oxidative
combination
of
three
p‐hydroxycinnamyl
alcohol
monomers
known
as
 monolignols
 (p‐coumaryl,
 coniferyl
 and
 sinapyl
 alcohols)
 whose
 structure
 differ
 only
in
the
number
of
methoxyl
groups
present
in
their
aromatic
rings
(Fig.
1
(A))
 (Goujon
et
al.
2003).

While
lignins
tend
to
be
dominated
by
these
three
monolignol
 components,
 there
 are
 several
 additional
 monomers
 that
 are
 sometimes
 found
 in
 lignin
 polymers.
 
 Many
 naturally
 occuring
 plant
 species
 contain
 lignins
 derived
 in
 part
from
these
other
monomers,
in
addition
to
trace
amounts
of
units
formed
from
 incomplete
 or
 secondary
 reactions
 that
 occur
 during
 monolignol
 biosynthesis
 (Boerjan
et
al.
2003).

  
  12
  
 Figure
1.

Molecular
structures
of
the
three
main
monolignols
and
of
a
putative
 lignin
 polymer.
 (A)
 Three
 traditional
 lignin
 precursors
 (p­coumaryl
 alcohol,
 coniferyl
 alcohol,
 sinapyl
 alcohol)
 (Monolignol
 2008)
 and
 (B)
 a
 hypothetical
 lignin
 polymer
(What
Is
Wood?
2009)
 
 Initially,
 carbon
 flux
 is
 redirected
 from
 primary
 metabolism
 to
 phenylpropanoid
 biosynthesis
through
three
enzyme‐catalyzed
reactions
(PAL,
C4H
and
4CL;
Fig.
2)
 which
 transform
 L‐phenylalanine
 into
 p­coumaroyl
 CoA.
 
 The
 latter
 serves
 as
 the
 entry‐point
 for
 the
 two
 main
 downstream
 
 branch
 pathways,
 monolignol
 and
 flavonoid
 biosynthesis
 (Ferrer
 et
 al.
 2008).
 
 The
 synthesis
 of
 monolignols
 involves
 consecutive
hydroxylations
of
the
aromatic
ring,

phenolic
O‐methylation
and

side‐ chain
 carboxyl
 conversion
 to
 an
 alcohol
 group
 ultimately
 forming
 the
 p‐coumaryl,
 coniferyl
 and
 sinapyl
 alcohols
 (Boerjan
 et
 al.
 2003;
 Boudet
 A.‐M.
 2000).
 
 These
  
  13
  monolignols
respectively
give
rise
to
p­hydroxyphenyl
(H),
guaiacyl
(G)
and
syringyl
 (S)
 lignin
 residues
 within
 the
 lignin
 polymer
 (Fig.
 2)
 (Grima‐Pettenati
 &
 Goffner
 1999;
 Vanholme
 et
 al.
 2008).
 To
 produce
 the
 final
 intricate
 and
 interconnected
 lignin
complex
(Fig.
1
(B)),
the
monomeric
residues
are
exported
to
the
extracellular
 space
 (apoplast)
 where
 oxidative
 enzymes
 catalyze
 the
 formation
 of
 free
 radical
 derivativs
 of
 the
 monomers.
 
 The
 radicals
 are
 then
 coupled
 to
 the
 growing
 lignin
 polymer
forming
either
carbon–carbon
or
ether
bonds
(Boudet
A.‐M.
2000;
Grima‐ Pettenati
&
Goffner
1999;
Vanholme
et
al.
2008).



 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  14
  
 
  
 
 
 
 Figure
 2.
 The
 Phenylpropanoid
 Pathway.
 PAL,
 phenylalanine
 ammonia‐lyase;
 C4H,
cinnamate‐4‐hydroxylase;
C3H,
4‐coumarate‐3‐hydroxylase;
COMT,
caffeic
acid
 3‐O‐methyltransferase;
 CCoAOMT,
 caffeic
 acid/5‐hydroxyconiferaldehyde
 O‐ methyltransferase;
F5H,
ferulate‐5‐hydroxylase;
4CL,
p‐coumaroyl:CoA
ligase;
HCT,
 p‐hydroxycinnamoyl‐CoA:
 quinate
 shikimate
 p‐hydroxycinnamoyltransferase;
 CCR,
 cinnamoyl‐CoA‐reductase;
 CAD,
 cinnamyl
 alcohol
 dehydrogenase;
 UGT,
 UDP‐ glucosyltransferase.
(Besseau
et
al.
2007
(Figure);
Vanholme
et
al.
2008
(Caption))
 
 
 
  15
  1.2.2
 Lignin
as
a
carbon
sink

 
 In
 addition
 to
 their
 many
 important
 biological
 functions,
 lignified
 plant
 cell
 walls
 represent
a
large
proportion
of
plant
biomass
in
the
terrestrial
biosphere
and
thus
 an
 immense
 carbon
 sink
 (Boudet
 et
 al.
 2003).
 
 Next
 only
 to
 cellulose,
 lignin
 is
 the
 second
most
abundant
biopolymer
on
earth
(Boudet
et
al.
2003;
Grima‐Pettenati
&
 Goffner
1999;
Humphreys
&
Chapple
2002).

Over
1.4x1012
kg
of
C
is
sequestered
in
 terrestrial
plant
material
each
year
(Battle
et
al.
2000)
with
lignin
constituting
about
 30%
 of
 that
 total
 (Humphreys
 &
 Chapple
 2002).
 
 Research
 interest
 in
 lignin
 biosynthesis
and
lignin
deposition
has
been
motivated
by
the
multiple
roles
played
 by
lignin
in
plant
biology,
including
management
of
abiotic
and
biotic
stress,
water
 conduction,
 cell
 differentiation,
 and
 carbon
 partitioning,
 all
 of
 which
 have
 both
 industrial
 and
 agricultural
 importance
 (Boudet
 et
 al.
 2003;
 Humphreys
 &
 Chapple
 2002).
 
 An
 important
 aspect
 of
 lignin
 that
 impacts
 lignocellulosic
 biomass
 utilization,
 in
 both
 industry
 and
 agriculture,
 stems
 from
 the
 variable
 and
 stable
 cross‐linking
of
the
various
cell
wall
components,
which
minimizes
the
accessibility
 of
 cellulose
 and
 hemicellulose
 to
 degradative
 enzymes
 (Bhuiyan
 et
 al.
 2009).
 
 Not
 only
 is
 the
 capacity
 of
 lignin
 to
 resist
 degradation
 largely
 due
 to
 its
 unique
 polymeric
structure,
but
this
structure’s
distinct
arrangement
and
representation
of
 monomeric
 units
 varies
 widely
 among
 species,
 individuals
 and
 even
 within
 cell
 types
of
the
same
plant
(Weng
et
al.
2008).

In
essence,
the
combination
of
chemical
 stability
 and
 structural
 diversity
 of
 the
 bonds
 formed
 between
 lignin
 subunits
 is
 sufficient
 to
 prevent
 complete
 degradation
 of
 the
 polymer
 by
 any
 single
 enzyme
 (Weng
et
al.
2008).

This
stability
highlights
the
potential
for
lignin
to
act
as
a
long‐  
  16
  lived
 C
 reservoir,
 and
 by
 extension,
 to
 serve
 as
 a
 vehicle
 increased
 carbon
 storage
 and
sequestration.
 1.2.3
 Lignin
modification
via
the
monolignol
biosynthetic
pathway
 
 The
 past
 twenty
 years
 of
 research
 has
 led
 to
 significant
 insight
 into
 lignin
 biosynthesis,
particularly
through
the
use
of
reverse
genetics
approaches
in
which
 expression
of
genes
encoding
individual
monolignol
and
phenylpropanoid
pathway
 enzymes
has
been
altered
(Vanholme
et
al.
2008).
Generally
speaking,
in
transgenic
 plants,
 the
 downregulation
 of
 PAL,
 C4H,
 4CL,
 HCT,
 C3H,
 CCoAOMT,
 CCR,
 and,
 to
 a
 smaller
degree,
CAD,
has
been
shown
to
have
a
major
influence
on
lignin
content
as
 well
 as
 the
 ratios
 of
 H,
 G
 and
 S
 lignin,
 although
 these
 outcomes
 are
 often
 accompanied
 by
 other,
 undesirable
 pleiotropic
 impacts
 on
 plant
 growth,
 morphology
or
chemistry
(Anterola
&
Lewis
2002;
Vanholme
et
al.
2008).

  1.3
  Transcription
factors
as
tools
for
metabolic
engineering
in
plants
  
 Transcriptional
 regulation
 is
 an
 important
 mechanism
 by
 which
 metabolic
 pathways
and
assembly
of
cell
wall
components
in
plants
is
controlled
(Broun
2004;
 Zhong
&
Ye,
2007).
Transcription
factors
(TFs)
are
regulatory
proteins
that
modify
 the
 expression
 of
 specific
 sets
 of
 genes
 by
 interacting
 with
 the
 transcriptional
 machinery,
 including
 chromatin
 remodeling
 proteins
 and/or
 other
 transcription
 factors
 involved
 in
 transcription
 through
 sequence‐specific
 DNA
 binding
 and
 protein–protein
interactions
(Broun
2004).

In
other
words,
these
proteins
are
able
 to
 recognize
 and
 bind
 specific
 sequences
 in
 the
 promoter
 regions
 of
 their
 target
 genes,
 thereby
 subsequently
 activating
 or
 repressing
 entire
 metabolic
 or
  
  17
  developmental
 processes.
 
 This
 often
 occurs
 by
 mediation
 of
 either
 an
 increase
 or
 decrease
 of
 the
 encoded
 mRNA
 by
 acting
 as
 activators
 or
 repressors
 of
 gene
 expression
 (Broun
 2004;
 Arce
 et
 al.
 2008).
 
 The
 role
 of
 transcription
 factors
 in
 coordinated
 metabolic
 regulation
 is
 of
 great
 interest
 in
 metabolic
 engineering
 because
 of
 their
 ability
 to
 control
 both
 cellular
 processes
 and
 multiple
 pathway
 steps
necessary
for
metabolite
accumulation
(Broun
2004;
Petersen,
2007).

Unlike
 alterations
 in
 single‐enzyme
 expression,
 the
 use
 of
 TFs
 for
 metabolic
 engineering
 has
 the
 potential
 to
 generate
 more
 complex
 phenotypes
 in
 transgenic
 plants,
 as
 a
 result
 of
 simultaneous
 modification
 of
 different
 transcriptionally‐regulated
 pathways
(Tyo
et
al.
2007).

 1.3.1
 The
role
of
transcription
factors
in
the
regulation
and
modification
of
lignin
 
 biosynthesis
 
 Lignin
 synthesis
 and
 deposition
 requires
 strict
 spatial
 and
 temporal
 regulation
 of
 processes
occurring
during
plant
growth
and
development
(Boudet
A.‐M.
2007).

So
 far,
 numerous
 studies
 suggest
 that
 several
 features
 of
 cellular
 structure
 and
 metabolism,
  such
  as
  the
  cytoskeleton,
  phosphoinositide
  signaling,
  glycosylphosphatidylinositol
(GPI)‐anchored
proteins,
hormones,
and
the
supply
of
 sugar
nucleotides,
must
all
be
integrated
as
part
of
the
regulation
of
secondary
cell
 wall
biosynthesis
and
lignin
deposition
(Zhong
&
Ye
2007).


 
 Although
many
of
the
genes
encoding
enzymes
involved
in
lignin
biosynthesis
have
 been
characterized,
little
is
known
about
the
molecular
mechanisms
underlying
the
 coordinated
 expression
 of
 these
 genes
 (Weng
 et
 al.
 2008).
 
 However,
 the
 study
 of
  
  18
  global
 patterns
 of
 gene
 expression
 by
 high‐throughput
 technologies
 has
 recently
 revealed
 some
 additional
 features
 of
 the
 various
 regulatory
 networks
 through
 which
this
metabolic
pathway
is
controlled
(Broun
2004).
For
example,
comparative
 transcriptome
 analyses
 in
 xylem
 cells
 of
 Arabidopsis
 plants
 undergoing
 secondary
 growth
have
identified
a
range
of
upregulated
genes
(specifically
NAC
and
MYB
TFs)
 involved
 in
 secondary
 cell
 wall
 formation,
 and
 these
 have
 provided
 an
 initial
 glimpse
 of
 the
 complex
 networks
 of
 TFs
 controlling
 this
 process
 (Ko
 et
 al.
 2007;
 Weng
et
al.
2008;
Zhong
&
Ye
2007;
Zhong
et
al.
2008).



A
group
of
closely
related
 NAC
 domain
 proteins
 in
 Arabidopsis
 thaliana
 (Fig.
 3),
 including
 ANAC043/NST1
 (NAC
 Secondary
 Wall
 Thickening
 Promoting
 Factor
 1),
 ANAC066/NST2,
 ANAC012/NST3/SND1
 (Secondary
 Wall
 Associated
 NAC
 Domain
 Protein
 1),
 VND6
 (Vascular‐related
 NAC‐Domain
 6),
 and
 VND7
 are
 now
 known
 to
 be
 major
 transcriptional
regulators
of
secondary
wall
biosynthesis
in
various
supporting
cell
 types
in
plant
tissues
that
have
ceased
elongation
(Zhong
et
al.
2008).



  
 Figure
3.
Phylogenetic
analysis
of
five
closely
related
NAC
domain
proteins
in
 Arabidopsis
thaliana
involved
in
regulating
secondary
cell
wall
biosynthesis
in
 various
 supporting
 cell
 types.
 
 The
 full‐length
 coding
 sequences
 (CDS)
 were
 aligned
 using
 the
 CLUSTAL
 W
 program
 and
 the
 phylogenetic
 tree
 was
 constructed
 by
 neighbor‐joining
 methods.
 
 The
 GenBank
 accession
 numbers
 for
 the
 used
 sequences
are
represented
as
follows:
ANACO12/NST3/SND1
(NM_103011);
NST1
 (NM_130243);
NST2


 (NM_116056);
 VND6
 (NM_125632);
 VND7
 (NM_105851)
and
CUC3
(NM_106292).
 
  
  19
  SND1
 and
 NST1
 are
 proposed
 to
 function
 in
 a
 redundant
 manner
 to
 control
 development
 of
 secondary
 walls
 in
 fibres
 while
 VND6
 and
 VND7,
 respectively,
 are
 proposed
to
regulate
metaxylem
and
protoxylem
differentiation
in
vessels
(Zhong
et
 al.
 2008;
 Mitsuda
 et
 al.
 2007).
 
 In
 anther
 endothecium
 cells,
 NST1
 and
 NST2
 were
 shown
to
function
redundantly
in
regulating
secondary
wall
thickening
(Mitsuda
et
 al.
 2005).
 
 
 Overexpression
 of
 these
 NAC
 genes
 results
 in
 ectopic
 deposition
 of
 secondary
walls
in
cells
not
normally
reinforced
with
lignin,
while
inhibition
of
their
 functions
 via
 dominant
 repression
 or
 knockout
 results
 in
 secondary
 walls
 with
 reduced
thickening
in
the
mutant
plants
(Zhong
et
al.
2008).

These
secondary
 wall
 NACs
are
proposed
to
act
through
a
cascade
of
downstream
 TFs,
which
in
turn
lead
 to
 the
 activation
 of
 secondary
 wall
 biosynthetic
 genes
 including
 SND2,
 SND3,
 MYB20,
 MYB42,
 MYB43,
 MYB46,
 MYB52,
 MYB54,
 MYB58,
 MYB63,
 MYB69,
 MYB85,
 MYB103,
 and
 KNAT7
 (a
 Knotted1‐like
 homeodomain
 protein),
 are
 regulated
 by
 SND1
(Zhong
et
al.
2006;
Zhong
et
al.
2008;
Zhong
et
al.
2007a;
Zhong
et
al.
2007b;
 Zhou
et
al.
2009;
Zhong
&
Ye
2007).
 
 Previous
 studies
 by
 Zhong
 et
 al.
 (2006)
 have
 shown
 that
 SND1
 is
 expressed
 specifically
 in
 interfascicular
 fibres
 and
 xylary
 fibres
 of
 stems.
 
 Constitutive
 overexpression
 of
 SND1
 resulted
 in
 activation
 of
 the
 expression
 of
 secondary
 wall
 biosynthetic
genes,
leading
to
massive
deposition
of
secondary
walls
in
cells
that
are
 normally
not
lignified
(Zhong
et
al.
2006).

An
activator
is
defined
in
the
literature
as
 a
 DNA‐binding
 protein
 that
 regulates
 one
 or
 more
 genes
 by
 increasing
 the
 rate
 of
 transcription.

Ko
et
al.
(2007)
showed
that
SND1
gene
expression
was
localized
to
  
  20
  the
 procambium
 region
 of
 inflorescence
 stems
 and
 roots.
 
 They
 confirmed
 the
 function
 of
 SND1
 as
 a
 transcriptional
 activator
 but
 also
 found
 that
 ectopic
 overexpression
 of
 35S::SND1
 plants
 in
 Arabidopsis
 noticeably
 suppressed
 secondary
 wall
 deposition
 in
 the
 xylary
 fibre.
 
 Moreover,
 they
 observed
 a
 slight
 increase
in
cell‐wall
thickness
in
xylem
vessels
which
suggested
that
SND1
might
act
 as
a
negative
regulator
of
secondary
wall
thickening
in
xylary
fibres.

In
contrast
to
 activators,
a
negative
regulator
is
defined
in
the
literature
as
any
regulator
that
acts
 to
 prevent
 transcription
 or
 translation.
 In
 addition
 to
 the
 elucidation
 of
 SND1
 as
 a
 major
transcriptional
activator
of
secondary
wall
biosynthesis,
Zhong
et
al.
(2007b)
 demonstrated
 that
 the
 Arabidopsis
 thaliana
 MYB46
 transcription
 factor
 is
 a
 direct
 target
of
SND1.

They
showed
that
dominant
repression
of
MYB46
caused
 a
severe
 decrease
in
the
secondary
wall
thickening
of
fibres
and
vessels
while
overexpression
 of
this
gene
resulted
in
the
activation
 of
the
cellulose,
xylan,
and
lignin
 biosynthetic
 pathways,
 which
 concurrently
 led
 to
 ectopic
 deposition
 of
 secondary
 walls
 in
 cells
 not
 normally
 lignified.
 
 Overexpression
 of
 MYB46
 caused
 an
 upregulation
 in
 gene
 expression
 among
 particular
 genes
 involved
 in
 the
 synthesis
 of
 all
 three
 major
 secondary
cell
wall
components
(Weng
et
al.
2008;
Zhong
et
al.
2007b;
Zhong
et
al.
 2008).

Furthermore,
the
expression
of
two
secondary
wall–associated
transcription
 factors,
 MYB85
 and
 KNAT7,
 was
 highly
 upregulated
 by
 MYB46
 overexpression
 demonstrating
 that
 MYB46
 is
 possibly
 another
 major
 player
 in
 the
 transcriptional
 network
 involved
 in
 regulating
 secondary
 wall
 biosynthesis
 in
 Arabidopsis
 (Zhong
 et
al.
2007b).


In
addition,
Zhou
et
al.
(2009)
demonstrated
that
overexpression
 of
 MYB58
 and
 MYB63
 resulted
 in
 specific
 activation
 of
 lignin
 biosynthetic
 genes
 and
  
  21
  simultaneous
ectopic
deposition
of
lignin
in
cells
not
normally
lignified.

MYB58
was
 able
to
directly
activate
 the
expression
of
lignin
biosynthetic
genes
and
a
secondary
 wall–associated
laccase
(LAC4)
gene.

Furthermore,
the
SND1
homologs
NST1,
NST2,
 VND6,
and
VND7
as
well
as
the
SND1
downstream
target,
MYB46,
were
also
shown
 to
regulate
the
expression
of
MYB58
and
MYB63.

Their
results
suggest
that
MYB58
 and
 MYB63
 are
 transcriptional
 activators
 of
 lignin
 biosynthesis
 specifically
 within
 the
 SND1‐mediated
 transcriptional
 network
 regulating
 secondary
 cell
 wall
 formation.
 
 Lastly,
 a
 recent
 high‐throughput
 study
 using
 whole‐transcriptome
 analyses
 by
 Ko
 et
 al.
 (2009)
 provided
 insight
 into
 the
 regulatory
 relationship
 of
 a
 group
 of
 transcription
 factors
 upregulated
 by
 MYB46,
 uncovering
 a
 speculative
 regulatory
network
with
intricate
cross
communication.

 
 Recently,
another
study
identified
a
novel
CCCH‐type
zinc
finger
protein,
AtC3H14,
 as
 a
 potential
 master
 regulator
 of
 secondary
 wall
 biosynthesis
 operating
 downstream
 of
 MYB46
 (Ko
 et
 al.
 2009).
 
 These
 studies
 suggest
 that
 SND1,
 MYB46
 and
 C3H14,
 act
 as
 key
 regulators
 of
 secondary
 cell
 wall
 deposition
 through
 their
 demonstrated
 ability
 to
 turn
 on
 the
 entire
 cellulose,
 xylan,
 and
 lignin
 biosynthetic
 pathways
in
transgenic
plants
(Zhong
et
al.
2008).

In
conclusion,
this
model
of
over‐ arching
regulation
of
secondary
cell
wall
biosynthesis
by
SND1,
MYB46
and
C3H14,
 along
with
the
discovery
of
other
TFs
upregulated
by
these
master
regulator
genes,
 has
provided
an
initial
glimpse
into
the
regulatory
networks
controlling
secondary
 cell
wall
formation
(Zhong
et
al.
2007a;
Zhong
et
al.
2007b;
Zhou
et
al.
2009).


 
  
  22
  As
 mentioned
 earlier,
 the
 amount
 of
 global
 carbon
 contained
 within
 agricultural
 soils,
 offers
 the
 potential
 to
 partially
 offset
 fossil‐fuel
 emissions
 by
 sequestering
 excess
atmospheric
C
in
the
roots
within
these
soils
(West
&
Marland
2002;
Subedi
 et
al.
2006).
Given
the
potential
for
lignin
to
act
as
a
C
sink
in
below‐ground
tissues,
 the
recent
identification
of
specific
TFs
involved
in
regulating
lignin
deposition
is
an
 important
 discovery.
 
 
 Single‐enzyme
 modifications
 that
 have
 led
 to
 changes
 in
 lignin
 content
 and/or
 the
 ratios
 of
 H,
 G
 and
 S
 lignin
 (Anterola
 &
 Lewis
 2002;
 Vanholme
 et
 al.
 2008)
 that
 are
 generally
 unsuitable
 for
 metabolic
 engineering
 in
 current
crop
systems,
due
to
their
severe
pleiotropic
phenotypes.

However,
specific
 TFs
that
are
involved
in
the
regulation
of
lignin
biosynthetic
pathway
genes
may
be
 important
 candidates
 for
 developing
 transgenic
 plants
 with
 enhanced
 levels
 of
 lignin
 in
 their
 roots
 for
 the
 purpose
 of
 improved
 soil
 carbon
 sequestration
 (Vijaybhaskar
et
al.
2008).

  1.4
  Root‐specific
and
inducible
gene
expression
systems
  
 Identification
 of
 suitable
 tissue‐specific
 and
 inducible
 promoter
 systems
 to
 drive
 target
gene
expression
is
another
important
step
in
developing
plants
that
have
the
 potential
 to
 increase
 below‐ground
 carbon
 sticks.
 
 Normally,
 ectopic
 gene
 expression
in
plants
is
achieved
by
using
a
broadly
active
and
constitutive
promoter
 such
 as
 the
 Cauliflower
 Mosaic
 Virus
 (CaMV)
 35S
 promoter
 
 (Brand
 et
 al.
 2006).

 However,
ubiquitous
and
constitutive
gene
expression
can
often
be
lethal
or
lead
to
 severe
defects
if
the
gene
being
overexpressed
is
of
vital
importance
to
normal
plant
 development.
 
 Therefore,
 the
 choice
 of
 promoter
 and
 inducible
 expression
 system
 often
 determines
 both
 the
 range
 of
 tissues
 and
 organs
 in
 which
 the
 gene
 can
 be
 
  23
  expressed,
in
addition
to
the
specific
developmental
stage
in
which
gene
expression
 can
be
induced
(Moore
et
al.
2006;
Brand
et
al.
2006).


Root‐specific
promoters,
for
 example,
 would
 be
 of
 particular
 interest
 in
 plant
 biotechnology
 for
 genetically
 engineering
 improved
 tolerance
 to
 salt
 and
 water
 stress,
 resistance
 against
 root
 pathogens,
improved
uptake
of
nutrients
and
carbon
sequestration
(Vijaybhaskar
et
 al.
2008;
Maizel
&
Weigel
2004).

 
 The
 organ
 and
 tissue
 types
 in
 higher
 plants,
 are
 both
 temporally
 and
 spatially
 controlled
 through
 the
 selective
 expression
 of
 specific
 parts
 of
 the
 genome,
 in
 different
 cells,
 over
 the
 organisms
 entire
 life
 cycle
 (Ma
 et
 al.
 2005).
 
 With
 the
 development
of
high
throughput
technologies,
such
as
DNA
microarrays,
there
has
 been
a
substantial
effort
made
in
recent
years
to
identify
and
determine
the
relative
 abundance
 of
 transcripts
 expressed
 within
 each
 organ
 or
 tissue
 type
 (Ma
 et
 al.
 2005).

The
ability
of
microarrays
to
measure
the
individual
transcript
level,
for
tens
 of
thousands
of
genes
in
parallel,
provides
a
way
to
analyze
gene
expression
levels
 among
 different
 cell
 types,
 tissues
 and
 even
 along
 developmental
 gradients
 (Ma
 et
 al.
 2005;
 Birnbaum
 et
 al.
 2003).
 
 Furthermore,
 a
 global
 map
 of
 gene
 expression
 patterns
 within
 an
 organ,
 such
 as
 the
 root,
 can
 identify
 genes
 whose
 expression
 is
 localized
 to
 particular
 areas,
 thus
 relating
 the
 activity
 of
 individual
 genes,
 or
 co‐ regulated
 sets
 of
 genes,
 to
 tissue
 specialization
 and
 even
 cell
 fate
 (Birnbaum
 et
 al.
 2003).

Birnbaum
et
al.
(2003)
mapped
global
gene
expression
to
15
different
zones
 of
 the
 developing
 root
 corresponding
 to
 both
 cell
 types
 and
 tissues
 at
 progressive
 developmental
 stages.
 
 Their
 data,
 as
 well
 as
 additional
 publicly
 available
  
  24
  microarray
 data
 from
 experiments
 conducted
 in
 other
 plant
 organs,
 allow
 plant
 biologists
to
identify
candidate
genes
involved
 in
specific
cell
types
within
the
root.

 By
the
same
token,
this
data
could
reveal
genes
whose
promoters
may
be
useful
in
 driving
root‐specific
transgene
expression.
 
 The
 ability
 to
 turn
 on
 gene
 expression
 both
 spatially
 and
 temporally
 offers
 the
 ability
 to
 fine‐tune
 ectopic
 gene
 expression
 without
 compromising
 the
 viability
 of
 the
organism
or
the
function
of
the
organ
being
altered.
However,
since
it
may
not
 be
possible
to
easily
identify
genes
whose
expression
is
truly
restricted
to
the
time
 and
place
of
interest,
researchers
have
also
sought
“inducible”
gene
promoters;
i.e.
a
 promoter
whose
transcriptional
activity
is
determined
by
the
presence
(or
absence)
 of
 a
 specific
 chemical
 or
 physical
 induction
 stimulus.
 
 In
 principle,
 this
 allows
 expression
 of
 a
 transgene
 to
 be
 restricted
 to
 a
 given
 developmental
 stage
 for
 a
 specific
 duration.
 
 So
 far
 there
 have
 been
 several
 inducible‐expression
 systems
 described
in
the
literature,
generally
falling
into
three
broad
categories
based
on
the
 nature
 of
 the
 “inducer”:
 Chemical‐inducible,
 hormone‐inducible
 and
 temperature‐ inducible.



 
 Since
 the
 early
 1990s,
 several
 transactivated
 and
 chemical‐inducible
 gene
 expression
 systems
 have
 been
 developed
 based
 on
 transcriptional
 de‐repression,
 inactivation,
 and
 activation
 of
 the
 gene
 of
 interest,
 as
 reviewed
 in
 Moore
 et
 al.
 (2006).

In
the
most
popular
hormone‐inducible
systems,
the
regulatory
domains
of
 the
rat
glucocorticoid
receptor,
the
human
estrogen
receptor
and
an
insect
ecdysone
  
  25
  receptor
have
been
used
to
construct
chimeric
transactivation
systems
whose
gene
 expression
 activities
 are
 controlled
 by
 the
 use
 of
 specific
 hormones
 or
 chemically
 similar
 compounds
 (Zuo
 et
 al.
 2001;
 Moore
 et
 al.
 2006).
 
 
 Alternatively,
 the
 molecular
 responses
 to
 environmental
 temperature
 changes
 that
 have
 evolved
 throughout
 living
 systems
 has
 led
 to
 cold
 tolerance
 and
 heat
 shock
 phenomena.

 These
 phenomena
 have
 in
 turn
 contributed
 to
 the
 development
 of
 temperature‐ inducible
 gene
 regulation
 (TIGR)
 systems
 (Weber
 et
 al.
 2003).
 
 Lastly,
 a
 further
 development
towards
a
more
stringent
control
of
transgene
expression
is
the
use
of
 inducible
 promoters,
 which
 are
 activated
 by
 the
 application
 of
 a
 specific
 chemical
 stimulus
(Tang
et
al.
2004).

Chemical‐inducible
systems
are
appealing
compared
to
 alternatives
 because
 they
 are
 generally
 dormant
 in
 the
 absence
 of
 the
 inducer,
 allowing
 a
 greater
 level
 of
 flexibility.
 
 This
 in
 combination
 with
 an
 appropriate
 tissue‐specific
 promoter
 to
 control
 the
 chemically‐responsive
 gene
 product
 can
 increase
 the
 specificity
 of
 target
 gene
 expression
 by
 restricting
 it
 to
 particular
 organs,
tissues
or
cell
types
at
a
desired
point
in
time
(Tang
et
al.
2004).

Chemicals
 that
 have
 been
 used
 to
 regulate
 transgene
 expression
 include
 the
 antibiotic
 tetracycline,
 the
 steroids
 dexamethasone
 (dex)
 and
 estradiol,
 copper,
 ethanol,
 benzothiadiazol
 (the
 inducer
 of
 pathogen‐related
 proteins),
 the
 insecticide
 methoxyfenozide
and
herbicide
safeners
(Tang
et
al.
2004).
 1.4.1
 Herbicidal
safeners
as
inducers
of
root‐specific
gene
expression
 
 Herbicidal
 safeners
 are
 chemicals
 that
 increase
 herbicide
 tolerance
 and
 protect
 monocot
crops
from
herbicide
burn
(DeRidder
&
Goldsbrough
2006;
De
Veylder
et
 al.
 1997;
 DeRidder
 et
 al.
 2002).
 Detoxification
 of
 these
 xenobiotics
 in
 plants
 is
 an
 
  26
  important
process
involving
three
enzyme‐catalyzed
phases.

Phase
one
begins
with
 the
 oxidation,
 reduction,
 or
 hydrolysis
 reactions
 catalyzed
 by
 cytochrome
 P450‐ dependent
monooxygenases
(De
Veylder
et
al.
1997;
DeRidder
et
al.
2002).

Phase
 two
 involves
 the
 conjugation
 of
 the
 newly
 formed
 functional
 group
 with
 a
 hydrophilic
substance
such
as
sugars
or
the
tripeptide
glutathione
(GSH).

The
GSH
 conjugation
 reaction
 is
 catalyzed
 by
 a
 class
 of
 enzymes
 known
 as
 glutathione
 S‐ transferases
(GSTs),
which
essentially
“tag”
these
molecules
for
excretion
or
storage.

 In
 the
 final
 phase,
 these
 conjugates
 are
 recognized
 by
 appropriate
 transporters
 (such
 as
 ATP‐binding
 cassette
 transporters)
 and
 are
 then
 either
 excreted
 into
 the
 apoplast
or
sequestered
in
the
vacuole
(DeRidder
et
al.
2002).



 
 In
monocots,
it
was
found
that
herbicide
tolerance
can
be
markedly
enhanced
using
 herbicide
safeners,
although
this
phenomenon
is
less
effective
dicotyledenous
crops
 (DeRidder
 et
 al.
 2002).
 
 Nevertheless,
 in
 Arabidopsis,
 a
 tau‐class
 GST
 (AtGSTU19)
 was
shown
to
respond
to
safeners
in
a
manner
similar
to
that
observed
in
monocot
 plants,
 and
 to
 do
 so
 in
 a
 tissue‐specific
 manner.
 
 In
 response
 to
 the
 safener
 benoxacor
 (and
 to
 a
 lesser
 extent
 fenclorim)
 GSTU19
 mRNA
 levels
 were
 increased
 30‐fold
 in
 roots
 compared
 to
 a
 relatively
 negligable
 4‐fold
 increase
 in
 shoots

 (DeRidder
&
Goldsbrough
2006).


  1.5
  Project
rationale
and
thesis
objectives
  
 It
is
important
that
we
learn
how
plants
will
respond
to
the
anticipated
increases
in
 anthropogenic
 carbon
 emissions
 over
 the
 coming
 decades
 given
 their
 vital
 role
 in
 the
global
carbon
cycle
(Lal
2008).
This
information
is
critical
to
understanding
the
 
  27
  effects
of
global
climate
change
on
our
ecosystems
and
is
required
to
assess
the
role
 of
 plant
 life
 in
 carbon
 sequestration
 (Raven
 &
 Karley
 2006).
 Plants
 offer
 the
 potential
 to
 play
 a
 significant
 role
 in
 carbon
 sequestration,
 a
 process
 by
 which
 atmospheric
 CO2
 can
 be
 transferred
 to,
 and
 securely
 stored
 in
 more
 long‐lived
 C
 reservoirs
(Lal
2004;
Millard
et
al.
2007).


 
 The
 overall
 aim
 of
 my
 M.Sc.
 research
 was
 to
 design
 and
 engineer
 transgenic
 Arabidopsis
plants
with
enhanced
levels
of
lignin
in
their
roots.

If
successful,
these
 plants
could
then
offer
the
potential
to
increase
soil
carbon
stocks
if
implemented
in
 crop
systems
such
as
canola
or
soybean.


 
 Lignin
is,
after
cellulose,
the
second
most
abundant
terrestrial
biopolymer
and
offers
 the
 potential
 to
 increase
 soil
 carbon
 stocks
 due
 to
 its
 ability
 to
 resist
 degradation
 (Humphreys
 &
 Chapple
 2002;
 Weng
 et
 al.
 2008).
 
 Lignin
 biosynthesis
 and
 accumulation
is
a
highly
localized
and
regulated
process
that
requires
strict
spatial
 and
 temporal
 control
 of
 the
 processes
 occurring
 during
 normal
 plant
 growth
 and
 development.


The
past
twenty
years
of
research
have
led
to
the
identification
and
 characterization
of
many
different
lignin
biosynthetic
and
regulatory
genes
involved
 in
the
biosynthesis
of
monolignols,
control
of
the
many
genes
involved
in
catalyzing
 the
reactions
of
the
lignin
biosynthetic
pathway,
ultimately
leading
to
secondary
cell
 wall
deposition
(Anterola
&
Lewis
2002;
Vanholme
et
al.
2008).


 
 Specifically,
the
objectives
of
my
project
were:
  
  28
  1. To
 identify
 suitable
 genes
 for
 overexpression
 that
 would
 result
 in
 ectopic
 deposition
of
lignin
 2. To
 identify
 suitable
 promoters
 needed
 to
 drive
 root‐specific
 expression
 of
 the
transgene
 3. To
 identify
 inducible
 systems
 that
 may
 be
 used
 to
 turn
 on
 gene
 expression
 spatially
and
temporally

 4. To
 engineer
 gene
 expression
 constructs
 designed
 to
 enhance
 lignin
 deposition
in
Arabidopsis
roots
 5. To
analyze
transgenic
plants
for
relevant
phenotypes

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  29
  2.
  Materials
and
Methods
  2.1
  Organ‐specific
expression
of
candidate
gene
and
promoters
  
 Wild
 type
 Arabidopsis
 thaliana
 (Columbia
 ecotype)
 seeds
 were
 surface
 sterilized
 using
20%
bleach
solution
and
several
washes
of
dH2O,
sown
in
(Sunshine
Mix
#5,
 Sun
 Gro
 Horticulture
 Canada
 Ltd.,
 Seba
 Beach,
 Alberta,
 Canada)
 and
 grown
 in
 a
 chamber
for
a
16hr
light/8hr
dark
photoperiod.

Root,
stem,
leaf
and
flower
tissue
 was
harvested
from
four‐week‐old
plants,
frozen
in
liquid
nitrogen
and
stored
at
‐ 80˚C
for
later
use.
For
semi‐quantitative
RT‐PCR
analyses
of
the
At4CL1,
AtGSTU19
 and
 AtSND1
 genes,
 total
 RNA
 (1µg)
 was
 extracted
 from
 frozen
 tissue
 using
 the
 RNeasy
Plant
Mini
Kit
(Qiagen)
and
the
purified
RNA
treated
with
DNase
I
to
remove
 any
 potential
 genomic
 DNA
 contamination
 before
 use
 for
 cDNA
 synthesis.
 
 RNA
 concentration
was
measured
using
a
NanoDrop
ND‐1000
Spectrophotometer
at
an
 OD
 of
 260nm.
 
 cDNA
 was
 made
 via
 reverse
 transcription
 using
 qScript™
 cDNA
 SuperMix
(Quanta
Biosciences),
according
to
the
specifications
of
the
manufacturer.

 PCR
(polymerase
chain
reaction)
was
performed
in
a
25µl
reaction
containing
10x
 PCR
 Buffer,
 2mM
 MgCl2,
 0.2mM
 dNTPs,
 0.1µl
 Taq
 DNA
 polymerase,
 0.5µl
 cDNA
 template
 and
 0.5µl
 each
 of
 forward
 and
 reverse
 primers.
 
 The
 following
 program
 was
used:

 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 54°C
 72°C

 72°C

 4°C

  Time
 3
minutes
 30
seconds
 30
seconds
 1
minute
 10
minutes
 Pause
  
  
  30
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  RT‐PCR
was
repeated
three
times
on
two
biological
replicates,
and
identical
results
 were
obtained.
Primers
designed
to
amplify
fragments
of
these
native
genes
can
be
 found
in
Table
8
in
Appendix
C
(1,
2,
3,
4,
21
and
22).
The
expression
level
of
the
β‐ Actin8
 gene
 was
 used
 as
 an
 internal
 control
 (Table
 8;
 29
 and
 30).
 
 Samples
 were
 visualized
on
1%
agarose
gels
stained
with
SYBR
Safe
DNA
gel
stain
(Invitrogen).
 Differentially
 expressed
 PCR
 products
 were
 analyzed
 using
 the
 Image
 J
 (1.42)
 (ImageJ:
Image
Processing
and
Analysis
in
Java)
program
to
compare
the
expression
 levels
 of
 each
 transcript.
 The
 Image
 J
 program
 calculates
 the
 area
 and
 pixel
 value
 statistics
of
user‐defined
selections.

  2.2
  Cis‐element
analysis
of
candidate
promoters
  
 In
order
to
investigate
the
promoter
regions
of
the
4CL1
(At1g51680)
and
GSTU19
 (At1g78380)
genes
for
common
cis‐acting
root‐specific
regulatory
elements,
500bp,
 1000bp,
2000bp
and
3000bp
regions
upstream
of
the
transcription
start
sites
were
 analyzed
 using
 the
 PLACE
 (Plant
 Cis‐acting
 Regulatory
 DNA
 Elements)
 database
 (Higo
 et
 al.
 1999).
 
 Putative
 regulatory
 elements
 that
 could
 contribute
 to
 root‐ specific
 expression
 were
 identified
 from
 previously
 published
 literature
 (Vijaybhaskar
et
al.
2008)
and
results
for
the
2000bp
analysis
is
listed
in
Appendix
B
 (Tables
6
and
7).
  2.3
 
  Preparation
of
the
4CL1pro‐SND1
gene
expression
constructs
and
 transgenic
plants
  
 A
 1224bp
 fragment
 containing
 the
 4CL1
 (At1g51680)
 promoter
 was
 amplified
 via
 tailed‐PCR
 from
 Arabidopsis
 (Columbia
 ecotype)
 wild
 type
 genomic
 DNA.
 
 The
 reaction
 was
 carried
 out
 in
 a
 25µl
 reaction
 containing
 10x
 HiFi
 PCR
 Buffer,
 2mM
 
  31
  MgCl2,
 0.2mM
 dNTPs,
 0.1µl
 HiFi
 Taq
 polymerase,
 1.0µl
 wild
 type
 genomic
 DNA
 template
 and
 0.5µl
 each
 of
 forward
 and
 reverse
 primers
 (Table
 8
 (Appendix
 C);
 5
 and
6)
according
to
the
following
program:
 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 54°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 1
minute
20
seconds
 10
minutes
 Pause
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  
 The
 forward
 primer
 (5'‐GGGCACGˇAATTCTTTTCGGTCTCTAATACCTCC‐3')
 contained
 an
 EcoRI
  site
  (underlined
  and
  bolded)
  and
  the
  reverse
  primer
  (5'‐  CACGAGGˇGATCCGˇGTNACCCCGCˇGGCTGAAGGAAACAGGAGTTGTATC‐3')
 contained
 restriction
  sites
 for
 BamHI
 (GˇGATCC),
 BstEII
 (GˇGTNACC)
 and
 SacII
 (CCGCˇGG)
 (underlined
 and
 bolded)
 respectively.
 
 Following
 enzyme
 digestion
 with
 EcoRI
 and
 BamHI
 the
 promoter
 fragment
 (4CL1pro)
 was
 ligated
 into
 the
 pPZP211
 Agrobacterium
 binary
 vector
 (Hajdukiewicz
 et
 al.
 1994).
 
 The
 SND1
 (At1g32770)
 open
 reading
 frame
 (ORF)
 was
 amplified
 from
 a
 pDG2
 plasmid
 (obtained
 from
 Apurva
 Bhargava,
 Ellis
 lab)
  containing
  the
  SND1
  cDNA
  using
  GAGCTCCCGCˇGGATGGCTGATAATAAGGTCAATCTTTCG‐3’)
  enzyme
  site
  (underlined
  and
  bolded)
  a
  forward
  primer
  (5’‐  containing
 a
 SacII
 restriction
 and
  a
  reverse
  primer
  GGGTGTGˇGATCCATGATGATGATGATGATGTCATACAGATAAATGAAGAAGTGGGTC‐3’)
  (5’‐  containing
  a
BamHI
site
(underlined
and
bolded)
and
a
HIS
x6
tag
(bolded).

PCR
was
carried
 out
 in
 a
 25µl
 reaction
 containing
 10x
 HiFi
 PCR
 Buffer,
 2mM
 MgCl2,
 0.2mM
 dNTPs,
 0.1µl
 HiFi
 Taq
 polymerase,
 0.5µl
 cDNA
 template
 and
 0.5µl
 each
 of
 forward
 and
 reverse
primers.

Conditions
for
SND1
amplification
were
as
follows:
  
  32
  Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 58°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 1
minute
18
seconds
 10
minutes
 Pause
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  
 After
digestion
with
BamHI
and
SacII
the
SND1
ORF
fragment
was
inserted
into
the
 pPZP211
 vector
 (Hajdukiewicz
 et
 al.
 1994)
 already
 containing
 the
 4CL1pro
 fragment.
The
recombinant
plasmid
(4CL1pro­SND1;
Fig.
4)
was
sequenced
(Applied
 Biosystems,
NAPS
Unit,
UBC,
Vancouver,
Canada)
using
the
standard
M13
primers,
 transferred
 into
 Agrobacterium
 tumefaciens
 strain
 GV3101
 by
 heat
 shock
 method
 and
then
used
to
transform
Arabidopsis
wild
type
plants
via
the
floral
dip
method.

 The
complete
primary
sequence
of
4CL1pro­SND1
can
be
found
in
Appendix
A.
 +,-.*&  !"#$%& '()#*&  /(,**& !"#$%&'(')*&+  ,-.$+  0121344& 56748&90:&&  !"#$%&'/,-.$+0+123$+4%++  +,-.*&  !"#$%& '()#*&  /(,**& 5,67$8%&'(')*&+  ,-.$+  0121344& 56748&90:&&  5,67$8%&'/,-.$+0+1993+4%++ 
 
 Figure
 4.
 
 Schematic
 diagram
 of
 the
 SND1
 overexpression
 constructs
 in
 pPZP211.
 Separate
 SND1
 overexpression
 constructs
 are
 driven
 by
 the
 4CL1
 and
 GSTU19
 promoters,
 respectively
 (left
 to
 right
 the
 constructs
 are
 5’
 to
 3’).
 Both
 constructs
 contain
 EcoRI,
 SacII
 and
 BamHI
 restriction
 enzyme
 sites
 as
 well
 as
 a
 6xHis
tag
at
the
3’
end
(complete
primary
sequences
may
be
found
in
Appendix
A).
 Genomic
 DNA
 was
 extracted
 from
 kanamycin‐resistant
 (50µg/ml)
 T1
 generation
  plants
and
PCR
used
to
confirm
the
presence
of
the
transgene.
PCR
was
carried
out
  
  33
  in
a
25µl
reaction
containing
10x
PCR
Buffer,
2mM
MgCl2,
0.2mM
dNTPs,
0.1µl
Taq
 DNA
polymerase,
1.0µl
cDNA
template
and
0.5µl
each
of
4CL1pro
forward
(Table
8
 (Appendix
 C);
 5)
 and
 SND1
 reverse
 primers
 (Table
 8
 (Appendix
 C);
 10)
 using
 the
 following
program:
 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 59.2°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 2
minute
30
seconds
 10
minutes
 Pause
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  
 
T1
 generation
 lines
 containing
 the
 transgene
 were
 harvested
 and
 T2
 generation
 seeds
 screened
 on
½
Murashige
 and
Skoog
 (MS)
media
plates
containing
 50µg/ml
 kanamycin.
 
 I
 selected
 12
 plants/line
 showing
 a
 1:3
 segregation
 ratio
 indicating
 a
 single
 insertion
 event
 and
 planted
 them
 in
 soil
 (Sunshine
 Mix
 #5,
 Sun
 Gro
 Horticulture
 Canada
 Ltd.,
 Seba
 Beach,
 Alberta,
 Canada),
 where
 they
 were
 grown
 under
 16hr
 light/8hr
 dark
 photoperiod.
 
 In
 addition,
 12
 plants/line
 were
 also
 transferred
to
½
MS
media
and
roots
harvested
at
three
weeks
for
analysis
of
SND1
 overexpression
 using
 RT‐PCR.
 
 Total
 RNA
 (385ng
 and
 1µg
 starting
 material)
 was
 extracted
 from
 frozen
 tissue
 using
 the
 RNeasy
 Plant
 Mini
 Kit
 (Qiagen)
 and
 the
 purified
 RNA
 treated
 with
 DNase
 I
 to
 remove
 any
 potential
 genomic
 DNA
 contamination
 before
 use
 for
 cDNA
 synthesis.
 
 RNA
 concentration
 was
 measured
 using
 a
 NanoDrop
 ND‐1000
 Spectrophotometer
 at
 an
 OD
 of
 260nm.
 
 cDNA
 was
 made
 via
 reverse
 transcription
 using
 SuperScript™
 II
 RT
 (Invitrogen)
 and
 OligodT
 (Invitrogen),
 according
 to
 the
 specifications
 of
 the
 manufacturer.
 
 All
 PCR
 and
 RT‐  
  34
  PCR
reactions
were
visualized
on
1%
agarose
gels
stained
with
SYBR
Safe
DNA
gel
 stain
(Invitrogen).
 
 Seeds
from
8
lines
showing
SND1
overexpression
were
harvested
and
screened
for
 homozygosity
on
½
MS
media
plates
containing
50µg/ml
kanamycin.

Of
the
twelve
 T3
 homozygous
 sub‐lines
 identified,
 seven
 were
 planted
 in
 soil
 (Sunshine
 Mix
 #5,
 Sun
 Gro
 Horticulture
 Canada
 Ltd.,
 Seba
 Beach,
 Alberta,
 Canada)
 and
 grown
 under
 16hr
 light/8hr
 dark
 photoperiod.
 
 Seeds
 were
 harvested
 at
 approximately
 eight
 weeks
and
used
for
subsequent
analyses.
  2.4
 
  Preparation
of
the
GSTU19pro‐SND1
gene
expression
constructs
and
 transgenic
plants
  
 A
1402bp
fragment
containing
the
GSTU19
(At1g78380)
promoter
was
amplified
via
 tailed‐PCR
 from
 Arabidopsis
 (Columbia
 ecotype)
 wild
 type
 genomic
 DNA.
 The
 reaction
 was
 carried
 out
 in
 a
 25µl
 reaction
 containing
 10x
 HiFi
 PCR
 Buffer,
 2mM
 MgCl2,
 0.2mM
 dNTPs,
 0.1µl
 HiFi
 Taq
 polymerase,
 1.0µl
 wild
 type
 genomic
 DNA
 template
and
0.5µl
each
of
forward
and
reverse
primers

according
to
the
following
 program:
 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 56°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 1
minute
20
seconds
 10
minutes
 Pause
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  
 The
 forward
 primer
 (5'‐GGGTCTGˇAATTCGCTACGTGTCGTGAGATATCG‐3')
 contained
 an
 EcoRI
 
  site
  (underlined
  and
  bolded)
 35
  and
  the
  reverse
  primer
  (5'‐  CACGAGGˇGATCCGˇGTNACCCCGCˇGGTGTTACGATCGCTAAAGCTCAC‐3')
  contained
 restriction
  sites
 for
 BamHI
 (GˇGATCC),
 BstEII
 (GˇGTNACC)
 and
 SacII
 (CCGCˇGG)
 (underlined
 and
 bolded)
 respectively.
 Following
 enzyme
 digestion
 with
 EcoRI
 and
 BamHI
 the
 promoter
 fragment
 (GSTU19pro)
 was
 ligated
 into
 the
 pPZP211
 Agrobacterium
 binary
vector
(Hajdukiewicz
et
al.
1994).


 
 As
previously
described
in
section
2.3,
the
SND1
amplicon
was
digested
with
BamHI
 and
 SacII
 and
 inserted
 into
 the
 pPZP211
 vector
 (Hajdukiewicz
 et
 al.
 1994)
 containing
 the
 GSTU19pro
 fragment.
 The
 recombinant
 plasmid
 (GSTU19pro­SND1;
 Fig.
 4)
 was
 sequenced
 
 (Applied
 Biosystems,
 NAPS
 Unit,
 UBC)
 using
 the
 standard
 M13
 primers,
 transferred
 into
 Agrobacterium
 tumefaciens
 strain
 GV3101
 by
 heat
 shock
method
and
then
used
to
produce
transgenic
Arabidopsis
plants
via
the
floral
 dip
 method.
 The
 complete
 primary
 sequence
 of
 GSTU19pro­SND1
 can
 be
 found
 in
 Appendix
A.

Genomic
DNA
was
extracted
from
kanamycin‐resistant
(50µg/ml)
T1
 generation
plants
and
PCR
used
to
confirm
the
presence
of
the
transgene.

PCR
was
 carried
out
in
a
25µl
reaction
containing
10x
PCR
Buffer,
2mM
MgCl2,
0.2mM
dNTPs,
 0.1µl
 Taq
 DNA
 polymerase,
 1.0µl
 cDNA
 template
 and
 0.5µl
 each
 of
 GSTU19pro
 forward
(Table
8
(Appendix
C);
7)
and
SND1
reverse
primers
(Table
8
(Appendix
C);
 10).

PCR
conditions
were
as
follows:
 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 58°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 2
minute
30
seconds
 10
minutes
 Pause
  
  
  36
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  T2
generation
plants
were
screened
on
½
MS
media
containing
50μg/ml
kanamycin,
 treated
with
100µM
benoxacor
for
24
hours
and
checked
for
SND1
overexpression
 using
RT‐PCR.

I
planted
12
plants/line,
showing
a
1:3
segregation
ratio
indicating
 one
 insertion
 event
 were
 planted,
 in
 soil
 (Sunshine
 Mix
 #5,
 Sun
 Gro
 Horticulture
 Canada
Ltd.,
Seba
Beach,
Alberta,
Canada)
and
grew
them
under
16hr
light/8hr
dark
 photoperiod.

I
transferred
10
plants
per
line
to
½
MS
media
and
roots
harvested
at
 three
 weeks
 for
 analysis
 of
 SND1
 overexpression
 using
 RT‐PCR.
 
 Total
 RNA
 (1µg
 starting
material)
was
extracted
from
frozen
tissue
using
the
RNeasy
Plant
Mini
Kit
 (Qiagen)
 and
 the
 purified
 RNA
 treated
 with
 DNase
 I
 to
 remove
 any
 potential
 genomic
DNA
contamination
before
use
for
cDNA
synthesis.

RNA
concentration
was
 measured
 using
 a
 NanoDrop
 ND‐1000
 Spectrophotometer
 at
 an
 OD
 of
 260nm.

 cDNA
was
made
via
reverse
transcription
using
SuperScript™
II
RT
(Invitrogen)
and
 OligodT
 (Invitrogen),
 according
 to
 the
 specifications
 of
 the
 manufacturer.
 
 All
 PCR
 and
RT‐PCR
reactions
were
visualized
on
1%
agarose
gels
stained
with
SYBR
Safe
 DNA
gel
stain
(Invitrogen).

 Seeds
from
eight
lines
showing
SND1
overexpression
were
harvested
and
screened
 for
homozygosity
on
½
MS
media
plates
containing
50µg/ml
kanamycin.

Of
the
22
 T3
 homozygous
 sub‐lines
 identified,
 eight
 were
 planted
 in
 soil
 (Sunshine
 Mix
 #5,
 Sun
 Gro
 Horticulture
 Canada
 Ltd.,
 Seba
 Beach,
 Alberta,
 Canada)
 and
 grown
 under
 16hr
 light/8hr
 dark
 photoperiod
 at
 22°C.
 
 Seeds
 were
 harvested
 at
 approximately
 eight
weeks
and
used
for
subsequent
analyses.
  
  37
  2.5
  Molecular
analysis
of
transgenic
plants
  2.5.1
 Reverse
transcription‐PCR
of
direct
downstream
targets
of
SND1
 
 Roots
and
shoots
(aerial
tissue
in
seedlings
that
does
not
include
stems)
from
two‐ week‐old
plants
grown
on
½
MS
media
were
harvested
and
frozen
in
liquid
nitrogen
 from
 three
 different
 T3
 lines
 for
 each
 construct
 as
 well
 as
 two
 different
 empty
 vector
 control
 lines.
 
 Total
 RNA
 (1µg
 starting
 material)
 was
 extracted
 from
 frozen
 tissue
using
the
RNeasy
Plant
Mini
Kit
(Qiagen)
and
the
purified
RNA
treated
with
 Dnase
I
to
remove
any
potential
genomic
DNA
contamination
before
use
for
cDNA
 synthesis.
 
 RNA
 concentration
 was
 measured
 using
 a
 NanoDrop
 ND‐1000
 Spectrophotometer
at
an
OD
of
260nm.

I
made
cDNA
via
reverse
transcription
using
 SuperScript™
 II
 RT
 (Invitrogen)
 and
 OligodT
 (Invitrogen),
 according
 to
 the
 specifications
 of
 the
 manufacturer.
 
 PCR
 was
 performed
 in
 order
 to
 amplify
 four
 known
downstream
targets
of
SND1
(SND3,
MYB46,
MYB103
and
KNAT7)
as
well
as
 SND1
itself.

Primers
used
can
be
found
in
Table
8
of
Appendix
C
(13,
14,
15,
16,
17,
 18,
 19,
 20,
 21
 and
 22)
 and
 the
 PCR
 reaction
 carried
 out
 in
 a
 Biometra
 Tpersonal
 thermocycler.
 The
 reaction
 was
 25µl
 and
 contained
 10x
 PCR
 Buffer,
 2mM
 MgCl2,
 0.2mM
 dNTPs,
 0.1µl
 Taq
 polymerase,
 0.5µl
 cDNA
 template
 and
 0.5µl
 each
 of
 the
 appropriate
forward
and
reverse
primers
according
to
the
following
program:
 Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 54°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 50
seconds
 10
minutes
 Pause
  
  
  38
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  All
 PCR
 and
 RT‐PCR
 reactions
 were
 visualized
 on
 1%
 agarose
 gels
 stained
 with
 SYBR
Safe
DNA
gel
stain
(Invitrogen).

The
PCR
reaction
was
repeated
three
times
 yielding
similar
results.
 2.5.2
 Reverse
transcription‐PCR
of
lignin
biosynthetic
pathway
enzymes
 Roots
and
shoots
(aerial
tissue
in
seedlings
that
does
not
include
stems)
from
two‐ week‐old
 plants
 were
 harvested
 and
 frozen
 in
 liquid
 nitrogen
 from
 three
 different
 T3
lines
for
each
construct
as
well
as
two
different
empty
vector
control
lines
grown
 on
½
MS
media.

Total
RNA
(1µg
starting
material)
was
extracted
from
frozen
tissue
 using
the
Rneasy
Plant
Mini
Kit
(Qiagen)
and
the
purified
RNA
treated
with
Dnase
I
 to
remove
any
potential
genomic
DNA
contamination
before
use
for
cDNA
synthesis.

 RNA
concentration
was
measured
using
a
NanoDrop
ND‐1000
Spectrophotometer
 at
an
OD
of
260nm.

I
made
cDNA
via
reverse
transcription
using
SuperScript™
II
RT
 (Invitrogen)
 and
 OligodT
 (Invitrogen),
 according
 to
 the
 specifications
 of
 the
 manufacturer.
 
 PCR
 was
 performed
 to
 amplify
 4CL1
 (At1g51680),
 CCR1
 (At1g15950)
 and
 COMT1
 (At5g54160);
 specific
 enzymes
 involved
 in
 the
 lignin
 biosynthetic
pathway.

The
primers
for
these
enzymes
along
with
the
Actin8
control
 can
be
found
in
Table
8
(Appendix
C;
23‐30).

The
PCR
reaction
was
carried
out
in
a
 Biometra
 Tpersonal
 thermocycler.
 The
 reaction
 was
 20µl
 and
 contained
 2x
 MangoMix
(Bioline),
0.5µl
cDNA
template
and
0.5µl
each
of
the
appropriate
forward
 and
reverse
primers
according
to
the
following
program:
 
 
  
  39
  Step
 1
 2
 3
 4
 5
 6
  Temperature
 94°C
 94°C
 54°C
 72°C

 72°C

 4°C

  Time
 5
minutes
 30
seconds
 30
seconds
 30
seconds
 10
minutes
 Pause
  Cycle
 
 
 
 Step
4→2
x
35
cycles
  
 All
 PCR
 and
 RT‐PCR
 reactions
 were
 visualized
 on
 1%
 agarose
 gels
 stained
 with
 SYBR
Safe
DNA
gel
stain
(Invitrogen).

The
PCR
reaction
was
repeated
in
triplicate
 yielding
similar
results.
  2.6
 
  Determination
of
lignin
content
in
transgenic
plants
overexpressing
 SND1
  2.6.1
 Plant
growth
conditions
 
 T3
generation
transgenic
and
empty
vector
lines
were
grown
hydroponically
in
an
 open‐top
liquid
culture
system.

Plastic
cylinders
that
were
1.5‐cm
in
diameter
were
 cut
from
the
tops
of
disposable
10mL
pipette
tips
were
lined
with
wire
mesh,
filled
 with
coarse
sand,
topped
off
with
fine
sand
and
placed
in
a
0.64‐cm‐thick
Styrofoam
 platform
specifically
cut
and
fitted
to
float
on
7L
of
hydroponic
nutrient
medium
in
 an
8L
plastic
basin.

Each
platform
contained
25
holes
(diameter
1.6
cm),
into
which
 were
fitted
the
plastic
cylinders.
Two
to
four
seeds
were
sown
in
each
cylinder
and
 germinated
 in
 dH2O
 for
 the
 first
 ten
 days,
 then
 transferred
 to
 aerated
 complete
 nutrient
 solution
 at
 pH
 6.1
 (1/10
 Johnson;
 see
 Appendix
 D).
 
 Nutrient
 solutions
 were
 replaced
 weekly,
 light
 was
 provided
 from
 fluorescent
 tubes
 (150
 E
 m–2
 s–1)
 and
 the
 walk‐in
 environment
 chamber
 was
 maintained
 under
 the
 following
 conditions:
 light/dark,
 8/16
 h;
 24/20°C;
 relative
 humidity
 =
 70%;
 photon
 flux
 of
 150
to
200
uE
m‐2
s‐1.

Roots
from
both
constructs
were
harvested
at
eight
weeks,
 
  40
  GSTU19pro­SND1
 lines
 treated
 for
 24hrs
 with
 100µM
 Benoxacor
 and
 tissue
 was
 stored
at
‐80°C
for
later
use.
 2.6.2
 Rapid,
micro
scale,
acetyl
bromide‐based
method
for
lignin
content
analysis

 Lignin
content
was
measured
using
a
modified
acetyl
bromide
method
to
enable
the
 rapid
microscale
determination
of
lignin
content
in
Arabidopsis
as
outlined
in
Chang
 et
al.
(2008).

Samples
(roots
from
~10‐20
plants)
 were
dried
overnight
in
a
40°C
 oven
and
ground
using
a
microball
mill
at
80‐mesh
then
transferred
to
vials,
placed
 in
a
vacuum
drying
oven
at
40°C
for
48hrs
and
then
into
a
P2O5
desiccator
overnight.


 Approximately
0.10g
(±0.01g)
of
oven‐dried
sample
was
weighed
and
transferred
to
 a
large
test
tube
by
adding
water.

Tubes
(containing
the
sample
plus
water)
were
 then
 placed
 in
 a
 65°C
 water
 bath
 for
 30
 minutes
 and
 vortexed
 at
 10
 minute
 intervals.

Samples
were
then
hot
filtrated
using
a
Millipore
filter
with
preweighed
 D47mm
(0.45µm)
nylon
membrane.


Samples
were
washed
roughly
25
times
with
 2mL
dH2O
using
a
glass
pipette.


Subsequent
washes
entailed:
25x1mL
of
ethanol,

 25x1mL
acetone
and
25x1mL
of
diethyl
ether.


Membranes
were
removed
carefully
 and
 transferred
 to
 preweighed
 aluminum
 pans
 and
 placed
 into
 a
 vacuum
 drying
 oven
at
40°C
for
48hrs
and
then
into
the
P2O5
desiccator
overnight.


Weights
were
 recorded
 and
 difference
 for
 extracted
 weights
 obtained.
 
 Samples
 were
 then
 transferred
to
new
vials.

Approximately
5.00mg
(±1.00mg)
of
oven‐dried
extracted
 sample
(times
three
replicates
per
line)
was
weighed
and
transferred
to
a
sealable
 glass
test
tube.


Samples
were
digested
with
1.0mL
of
25%
acetyl
bromide
in
acetic
 acid.

Tubes
were

capped
and
placed
in
a
70°C
water
bath
for
30
minutes,
vortexing
  
  41
  every
10
minutes.


Samples
were
then
cooled
and
stored
on
ice
for
a
minimum
of
 five
minutes
up
to
two
hours.

Acetic
acid
(5mL)
was
added
to
the
tubes
containing
 the
samples,
vortexed
and
centrifuged
to
spin
down
any
precipitate.

Subsequently,
 300µL
of
sample
mixture
was
transferred
to
a
quartz
cuvette
followed
by
400µL
of
 1.5M
NaOH,
300µL
of
0.5M
H2NOH⋅HCL
and
1.5mL
of
acetic
acid
for
a
total
volume
 of
2.5mL.

Absorbance
was
measured
at
280nm
against
a
blank
and
recorded.


 2.6.3
 Klason
lignin
or
72%
(v/v)
H2SO4
acid
procedure
and
carbohydrate
analysis
 
 Samples
were
dried
at
40°C
overnight
and
ground
using
a
microball
mill
at
80‐mesh
 then
transferred
to
vials
and
stored
in
the
desiccator
until
used.

Approximately
0.2g
 of
 sample
 was
 weighed
 into
 a
 test
 tube
 and
 its
 mass
 recorded.
 
 The
 separation
 reaction
 was
 carried
 out
 by
 adding
 3mL
 of
 72%
 (w/w)
 H2SO4
 to
 the
 weighed
 samples
and
mixing
with
a
glass
rod
every
10
minutes
for
two
hours.

Contents
of
 tubes
were
completely
transferred
to
serum
bottles
and
sealed
with
septa.

Samples
 were
 then
 autoclaved
 along
 with
 the
 sugar
 control
 (Appendix
 D)
 for
 one
 hour
 at
 121oC.


 
 For
 the
 insoluble
 lignin
 analysis,
 bottles
 were
 allowed
 to
 cool
 before
 filtering
 through
 a
 pre‐weighed
 Medium
 Coarseness
 (M)
 sintered‐glass
 crucible.
 
 The
 crucible
 solids
 were
 washed
 by
 filtering
 through
 200mL
 warm
 deionized
 water
 followed
 by
 drying
 overnight
 at
 105oC.
 
 To
 complete
 the
 retentate
 analysis,
 after
 filtration,
crucibles
containing
the
insoluble
lignin
were
weighed
and
recorded.

In
 order
 to
 determine
 the
 final
 weight
 (dry
 mass)
 of
 insoluble
 lignin,
 total
 crucible
  
  42
  weight
 (crucible
 and
 insoluble
 lignin)
 was
 subtracted
 from
 the
 weight
 of
 the
 pre‐ weighed
empty
crucible.

For
the
acid
soluble
lignin
filtrate
analysis
the
absorbance
 at
205
nm
was
determined
using
a
quartz
cuvette.

 
 For
the
carbohydrate
analysis
used
to
determine
hemicellulose
content,
the
filtrate
 from
 the
 autoclaved
 samples
 was
 retained.
 The
 sugar
 analysis
 of
 the
 filtrate
 required
 the
 preparation
 of
 a
 1mL
 sample
 for
 HPLC
 by
 weight
 using
 ~950
 mg
 hydrolysate
+
50
mg
of
fucose
standard
(Appendix
D).



  2.7
  Starch
analysis
  
 Roughly
 25‐50mg
 of
 dried
 ground
 tissue
 per
 sample
 (in
 duplicate)
 (see
 Klason
 analysis
protocol
for
drying
and
grinding
protocol)
was
weighed
into
a
10mL
glass
 culture
 tube.
 
 Following
 this,
 5mL
 of
 4%
 H2SO4
 was
 added
 to
 each
 tube,
 gently
 vortexed,
then
autoclaved
for
3½
minutes.
Samples
were
cooled
and
gently
spun
for
 five
minutes
at
500rpm
to
pellet
the
insoluble
matter.

The
supernatant
containing
 the
glucose
fraction
was
retained
and
the
pellet
discarded.

Samples
were
prepared
 for
 HPLC
 by
 adding
 fucose
 and
 filtered.
 Using
 the
 glucose
 standards
 (Appendix
 D)
 and
regression
analysis,
the
amount
of
glucose
in
the
HPLC
vial
was
calculated
and
 then
 back
 calculated
 to
 determine
 how
 much
 glucose
 the
 entire
 sample
 released.

 The
glucose
content
was
used
to
determine
the
relative
cellulose
composition
of
the
 samples
analyzed.
 
  
  43
  2.8
  Phenotypic
analysis
of
transgenic
plants
  2.8.1
 Seed
phenotyping
 
 The
average
weight
per
seed
was
determined
by
weighing
six
samples
of
100
seeds
 per
 line
 and
 the
 average
 seed
 number
 per
 silique
 was
 measured
 by
 counting
 the
 number
of
seeds
in
each
of
30
siliques.

Silique
length
was
determined
by
measuring
 30
 siliques
 for
 each
 transgenic
 line.
 
 For
 the
 germination
 assay,
 28‐36
 seeds
 from
 two
 transgenic
 lines
 per
 construct
 and
 two
 empty
 vector
 controls
 were
 surface
 sterilized
using
70%
and
95%
ethanol,
dried
and
then
sown
on
½
MS
media.

Plates
 were
kept
in
the
dark
at
4°C
for
four
days
then
placed
in
a
walk
in
growth
chamber
 under
16hr
light
and
8hr
dark.
Germinants
were
counted
24
hours
later
and
every
 12
hours
after
that
up
to
48
hours.


A
one‐way
Analysis
of
Variance
(ANOVA)
was
 performed
in
the
statistical
environment
'R'
(http://www.bioconductor.org/)
using
 the
 function
 'aov'**
 with
 the
 balanced
 linear
 model
 function
 'lm',
 and
 contrasts
 made
upon
8
levels
for
seed
weight
(A‐7,
B‐5,
D‐2,
F‐5,
F‐7,
G‐8,
EV40,
EV41)
and
5
 levels
 for
 lateral
 root
 density
 (A‐7,
 B‐5,
 F‐7,
 G‐7,
 EV40)
 (see
 section
 2.8.2
 below)
 (Chambers
et
al.
2002).

 2.8.2
 Root
growth
and
lateral
root
density
 
 After
cold
treatment
for
two
days
at
4°C,
surface
sterilized
seeds
were
individually
 pipetted
out
in
a
single
row
at
a
seed
density
of
15
seeds
per
plate
at
the
top
of
petri
 dishes
containing
1.2%
agar
in
½
MS
media.


Plants
were
grown
vertically
in
a
walk
 in
growth
chamber
at
16hrs
light/8hrs
dark
for
14
days.

I
measured
20
seedlings
of
 similar
 length
 (to
 account
 for
 different
 germination
 times)
 per
 genotype
 and
  
  44
  recorded
both
the
root
length
and
number
of
lateral
roots.

GSTU19pro­SND1
lines
 were
treated
for
24hrs
with
100µM
benoxacor.
 2.8.3
 Plant
growth
and
height

 
 Transgenic
and
empty
vector
control
seeds
were
surface
sterilized
with
20%
bleach
 solution
 for
 20
 minutes
 and
 rinsed
 several
 times
 with
 distilled
 water
 then
 germinated
 on
 ½
 MS
 plates
 then
 transferred
 to
 soil
 (Sunshine
 Mix
 #5,
 Sun
 Gro
 Horticulture
 Canada
 Ltd.,
 Seba
 Beach,
 Alberta,
 Canada)
 and
 placed
 in
 a
 growth
 chamber
at
16hrs
light/8hrs
dark
photoperiod.

Plants
were
photographed
weekly
 with
 a
 Nikon
 Coolpix
 E3200
 digital
 camera
 to
 track
 plant
 height
 over
 a
 six
 week
 period.
 2.8.4
 Microscopy
 
 Fresh
sections
of
the
lower
and
mid
part
of
the
stem
as
well
as
a
5mm
section
of
the
 root‐hypocotyl
 (portion
 of
 the
 hypocotyl
 below
 the
 soil
 surface),
 from
 both
 transgenic
and
empty
vector
lines,
grown
as
above,
were
obtained
using
a
fine
razor
 blade
 and
 stained
 with
 Phloroglucinol‐HCl.
 
 Sectioned
 were
 placed
 in
 water
 on
 a
 slide
and
visualized
using
a
Leica
DM
6000B
fitted
with
a
Leica
DFC350
Fx
camera.
 
 
 In
addition,
5mm
sections
of
root‐hypocotyl
from
both
transgenic
and
empty
vector
 lines
were
fixed
in
20mL
vials
using
a
mix
of
ethanol,
acetic
acid,
formaldehyde
and
 water
 (Appendix
 D)
 then
 dehydrated
 with
 50%,
 60%,
 70%,
 85%,
 95%
 and
 100%
 ethanol.
 
 Tissues
 were
 then
 cleared
 to
 allow
 for
 paraffin
 permeation
 with
 100%
 ethanol
 and
 then
 25%
 xylene:75%
 ethanol,
 50%
 xylene:50%
 ethanol,
 75%
  
  45
  xylene:25%
ethanol
and
100%
xylene.

Infiltration
was
achieved
slowly
in
order
to
 preserve
 the
 morphology
 of
 the
 tissue
 by
 incubating
 overnight
 with
 a
 mixture
 of
 100%
 xylene
 and
 Paraplast®
 plus
 (Sigma)
 embedding
 chips.
 
 The
 vials
 were
 incubated
at
42°C
for
one
hour
to
melt
the
Paraplast®
chips
and
then
incubated
at
 60°C
for
at
least
four
hours.

The
xylene/wax
mixture
was
then
replaced
with
100%
 molten
 Paraplast®
 embedding
 media
 and
 exchanged
 twice
 a
 day
 for
 three
 days
 (total
 of
 six
 wax
 changes).
 
 Wax
 moulds
 were
 made
 by
 pouring
 the
 hot
 wax
 and
 tissue
 into
 petri
 dishes,
 which
 were
 then
 stored
 at
 4°C
 for
 later
 use.
 
 Paraffin
 wax
 embedded
 tissues
 were
 individually
 mounted
 on
 wooden
 blocks
 and
 sectioned
 using
a
rotary
microtome
(Microm
HM
325).
The
10
µm
sections
were
heat
fixed
to
 glass
 slides,
 used
 for
 phloroglucinol‐HCl
 staining
 and
 lignin
 autofluorescence
 (UV
 360±40nm)
and
visualized
using
a
Leica
DM
6000B
microscope
fitted
with
a
Leica
 DFC350
Fx
camera.

 
 
 
 
 
 
 
 
 
 
  
  46
  3.
  Results

  3.1
  Organ‐specific
expression
of
candidate
gene
and
promoters
  
 Genes
involved
in
regulating
cell
fate
in
all
major
root
tissues
have
been
previously
 described
 in
 Arabidopsis
 (Birnbaum
 &
 Benfey,
 2004).
 
 Birnbaum
 et
 al.
 (2003)
 developed
 a
 method
 that
 measured
 high‐resolution
 spatial
 and
 temporal
 gene
 expression
 profiles
 for
 more
 than
 22,000
 genes
 throughout
 the
 Arabidopsis
 root.

 Using
 an
 Affymetrix
 ATH1
 GeneChip,
 they
 mapped
 gene
 expression
 in
 15
 different
 root
zones
(endodermis,
endodermis
and
cortex,
epidermal
atrichoblasts
and
lateral
 root
 cap)
 that
 relate
 to
 cell
 types
 and
 tissues
 at
 progressive
 developmental
 stages
 (stage
1,
2
and
3)
(Birnbaum
et
al.
2003).


 
 To
 identify
 candidate
 root‐specific
 genes,
 I
 mined
 the
 Birnbaum
 microarray
 gene
 expression
 data
 set
 for
 genes
 expressed
 in
 either
 the
 stele
 or
 endo‐cortex,
 whose
 relative
 probe
 intensity
 values
 were
 between
 1500
 and
 5000
 for
 those
 two
 cell
 types.

Based
on
this
gene
expression
data,
suitable
candidate
genes
were
selected
 whose
 promoters
 had
 the
 potential
 to
 drive
 root‐specific
 transgene
 expression,
 as
 summarized
in
Table
1.
 
 Genes
 found
 within
 these
 specified
 parameters
 were
 then
 checked
 via
 Genevestigator
 (Genevestigator,
 2008)
 for
 their
 relative
 expression
 in
 root
 compared
to
other
plant
organs
and
tissues
(Fig.
5).


 
 
  
  47
  2328.20 1533.40 2447.19 2130.62 2036.62 1951.80 1679.18 2388.33 2491.67 3077.48 2206.00 1950.50 4566.83 2935.53 2053.33 2233.24 3069.37 2554.28 3571.20 1663.77 2674.72 1851.13 2841.93 3409.25 3422.04 2004.04 2681.04 2429.96 4228.00 2328.73 1946.76 3069.00 3452.06 2944.01 2644.99 2355.48 3075.62 3795.65 2107.32 2228.69  48
  1985.63 1909.86 2381.70 2273.26 2179.20 1963.30 2039.91 1943.89 2569.18 2927.79 1991.44 1677.77 4659.56 3228.73 1862.41 2006.88 2209.25 2819.90 3955.22 1775.90 2787.03 1797.13 2374.53 4073.49 2955.32 2042.08 2993.99 2577.25 4343.62 2305.95 2496.27 2943.20 3172.00 3190.15 2461.02 2290.24 2804.01 4195.35 1603.56 2017.78  e3  co  rte  xe  nd  o  st ag  e2 st ag o nd  co  rte  xe  nd rte co  4187.95 3911.02 2262.39 1991.17 1815.69 1970.78 1915.47 2080.07 2949.11 3306.27 2688.84 1996.96 1712.47 2929.31 2240.15 2910.17 3232.28 2174.89 1540.72 1629.61 2358.48 1842.36 3271.57 4092.73 3367.03 2008.53 3476.60 2690.26 2731.18 2509.98 1927.94 3280.20 2905.62 1917.17 2588.76 2170.68 3456.93 2060.36 4080.73 2174.81  
 
  xe  st a e st el  4072.65 2485.74 2722.15 2934.41 2192.35 2439.48 2069.35 2173.63 3133.28 3992.49 2961.10 2691.84 4278.17 3639.66 2758.95 3067.99 4034.32 3461.86 2940.98 1834.42 3894.37 2265.78 4425.77 4162.22 3875.63 2631.03 3714.33 3191.61 4219.88 3661.73 2503.74 3539.86 3965.86 2990.13 3147.32 2318.31 3860.32 3816.35 3218.08 2377.96  o  3 ge  2 ge st a e st el  Gene ID AT5G11740 AT1G02500 AT5G08690 AT5G19760 AT5G64350 AT5G64400 AT5G44340 AT5G42980 AT3G62290 AT3G55440 AT3G48140 AT4G37830 AT4G33865 AT4G27960 AT4G11150 AT4G09000 AT4G05320 AT4G01850 AT1G18080 AT3G52300 AT3G17390 AT3G09820 AT3G02230 AT1G13440 AT1G78380 AT1G49140 AT1G07890 AT1G65930 AT1G56075 AT1G78040 AT1G79550 AT1G04410 AT2G36530 AT1G09640 AT1G22840 AT1G08830 AT2G16850 AT2G47110 AT2G30870 AT2G33040  st el  e  st a  ge  1  st ag  e1  Table
 1.
 
 Candidate
 genes
 whose
 promoters
 have
 the
 potential
 to
 drive
 root­ specific
 transgene
 expression.
 These
 values
 are
 based
 on
 microarray
 hybridization
 signals,
 which
 have
 no
 units.
 
 Values
 for
 each
 of
 the
 40
 candidate
 genes
 expressed
 in
 two
 cell
 types
 (stele
 and
 endo‐cortex)
 along
 three
 stages
 of
 development
are
summarized.


 
  3473.40 3096.00 2649.31 3130.84 2345.83 2453.85 2513.89 1769.15 3230.76 3798.29 2673.10 2315.44 4365.03 4003.20 2502.42 2757.02 2903.80 3821.87 3257.23 1958.06 4057.89 2199.68 3697.89 4973.17 3347.04 2680.97 4147.88 3385.06 4335.28 3625.91 3210.46 3394.76 3644.12 3240.13 2928.41 2254.10 3519.41 4218.23 2448.79 2152.92  3571.74 4871.20 2201.85 2124.47 1942.81 1982.39 2326.97 1693.00 3040.86 3145.46 2427.32 1717.73 1747.24 3221.90 2031.87 2615.20 2326.51 2401.06 1706.39 1739.45 2457.51 1788.62 2733.51 4890.14 2907.81 2046.65 3882.40 2853.33 2805.87 2485.43 2472.13 3145.74 2669.89 2077.46 2408.70 2110.56 3151.65 2277.33 3105.22 1969.00  
  ABC  Figure
5.

Genevestigator
heat
map
of
candidate
genes
whose
promoters
have
 the
 potential
 to
 drive
 root­specific
 transgene
 expression.
 
 The
 diagram
 represents
a
global
expression
map
depicting
major
patterns
of
gene
activity
among
 candidate
 genes
 listed
 in
 Table
 1,
 in
 different
 plant
 organs
 and
 tissues
 (Genevestigator,
 2009).
 Columns
 on
 the
 right
 represent
 two
 candidate
 promoters
 (A=GSTU19
 and
 B=4CL1)
 and
 one
 candidate
 gene
 (C=SND1)
 for
 engineering
 gene
 expression
constructs
to
enhance
levels
of
lignin
in
the
roots
of
transgenic
plants.


  
  49
  Based
 on
 these
 results,
 one
 candidate
 gene,
 GSTU19,
 was
 selected
 for
 further
 analysis.


For
the
second
candidate
gene,
4CL1,
previous
studies
have
showed
high
 levels
 of
 4CL1
 gene
 expression
 in
 seedling
 roots,
 as
 demonstrated
 by
 analysis
 of
 transgenic
 Arabidopsis
 plants
 containing
 the
 4CL1
 or
 4CL2
 promoter
 fused
 to
 the
 beta‐glucuronidase
 (GUS)
 reporter
 gene.
 
 These
 GUS
 reporter
 plants
 show
 developmentally
regulated
GUS
expression
in
the
xylem
tissues
of
both
the
root
and
 shoot,
 although,
 At4CL1::GUS
 lines
 showed
 root‐specific
 expression
 in
 seedlings
 (Soltani
et
al.
2006).

In
order
to
confirm
these
results
and
validate
the
potential
of
 these
 candidates
 to
 drive
 root‐specific
 expression,
 the
 activity
 of
 both
 candidate
 promoters
were
checked
using
semi‐quantitative
reverse
transcription
(RT)‐PCR
in
 flower,
leaf,
stem
and
roots
of
four‐week‐old
plants
(Fig.
6).


Results
confirmed
that
 GSTU19
is,
in
fact,
expressed
at
a
noticeably
higher
level
in
roots
compared
to
other
 plant
organs.

However,
4CL1,
showed
only
a
negligible
increase
in
expression
in
the
 roots
of
four‐week‐old
plants
as
compared
to
other
tissues.

Although
these
results
 showed
 4CL1
 to
 be
 less
 promising
 for
 root‐specific
 transgene
 expression,
 it
 was
 retained
 as
 a
 candidate,
 based
 on
 the
 earlier
 published
 data.
 
 In
 addition,
 SND1
 showed
expression
in
stems
but
no
detectable
expression
in
other
organs
(Figs.
5
&
 6).
 
 
 Along
 with
 previous
 publications
 on
 the
 role
 of
 SND1
 in
 regulating
 lignin
 biosynthesis,
 the
 combined
 data
 shown
 supports
 the
 use
 of
 these
 candidate
 promoters
in
producing
transgenic
plants
with
higher
levels
of
lignin
in
their
roots.

 In
 addition
 to
 the
 endogenous
 root‐specificity
 of
 the
 GSTU19
 gene,
 the
 previous
 studies
in
Arabidopsis
showing
the
increased
root‐specific
expression
of
GSTU19
in
 response
 to
 the
 herbicide
 safeners,
 benoxacor
 and
 fenclorim
 (DeRidder
 &
  
  50
  Goldsbrough
 2006),
 suggested
 that
 the
 GSTU19
 promoter
 could
 be
 useful
 as
 a
 chemical‐inducible
root‐specific
gene
expression
system.

  12(34567'81269:;<;=>'' ("  !"#$%&"'(")"'*+,-"../0)'  '" &" %" $" #" !" )*+,#-./01234" )*+,#-.5367" )*+,#-.*839" )*+,#-.:118"  12?@A6'81269B6C;=>'' #!"  <"  -" !"#$%&"'(")"'*+,-"../0)'  !"#$%&"'(")"'*+,-"../0)'  123DE6'81269<F::=>' -" ;" (" '" &" %" $" #"  <" ;" (" '" &" %" $" #"  !"  !" *>?#./01234"  *>?#.5367"  *>?#.*839"  *>?#.:118"  &=5#./01234"  &=5#.5367"  &=5#.*839"  &=5#.:118"  
 Figure
 6.
 Organ­specific
 gene
 expression
 of
 candidate
 gene
 and
 root­specific
 promoters
 from
 four­week­old
 Arabidopsis
 plants.
 
 Semi‐quantitative
 reverse
 transcription
 (RT)‐PCR
 analysis
 showing
 the
 relative
 gene
 expression
 of
 SND1,
 GSTU19
and
4CL1
in
flower,
leaf,
stem
and
root
tissues.
Expression
of
the
Act8
gene
 was
used
as
both
an
internal
control
and
loading
control.

RT‐PCR
was
carried
out
in
 triplicate
on
two
biological
replicates.

Differentially
expressed
PCR
products
were
 analyzed
 using
 the
 Image
 J
 (1.42)
 (ImageJ:
 Image
 Processing
 and
 Analysis
 in
 Java)
 program
to
compare
the
expression
levels
of
each
transcript.
  
 3.2
  Cis‐regulatory
element
analysis
of
candidate
promoters
  
 Several
 tissue‐specific
 cis‐acting
 regulatory
 elements
 have
 been
 previously
 described;
 ACGTROOT1
 (Salinas
 et
 al.
 1992),
 ROOTMOTIFTAPOX1
 (Elmayan
 &
 Tepfer
 1995),
 WUSATAg
 (Kamiya
 et
 al.
 2003),
 OSE1ROOTNODULE
 (Vieweg
 et
 al.
 
  51
  
  2004),
 OSE2ROOTNODULE
 (Vieweg
 et
 al.
 2004),
 RAV1AAT
 (Kagaya
 et
 al.
 1999),
 ASF1MOTIFCAMV
 (Klinedinst
 et
 al.
 2000),
 SURECOREATSULTR11
 (Maruyama‐ Nakashita
et
al.
2005),
SP8BFIBSP8BIB
(Ishiguro
&
Nakamura
1992),
ARFAT
(Inukai
 et
 al.
 2005),
 TELO
 (Tremousaygue
 et
 al.
 1999)
 and
 SORLIP1AT
 (Jiao
 et
 al.
 2005).





 To
 investigate
 possible
 root‐specific
 elements
 in
 the
 promoters
 of
 my
 candidate
 genes,
 2kb
 regions
 of
 the
 4CL1
 and
 GSTU19
 promoters
 were
 analyzed
 using
 the
 PLACE
(Plant
Cis‐acting
Regulatory
DNA
Elements)
database
(Higo
et
al.
1999).

In
 addition
 to
 the
 TATA‐box
 and
 CAAT‐box
 (core
 promoter
 sequences
 required
 to
 properly
 initiate
 transcription),
 this
 analysis
 revealed
 the
 presence
 of
 many
 elements
 that
 could
 possibly
 be
 related
 to
 root‐specific
 expression.
 
 The
 cis‐ regulatory
elements
for
4CL1
are
summarized
in
Table
2
and
include
all
of
the
root
 expression‐associated
 motifs
 mentioned
 above,
 with
 the
 exception
 of
 the
 ACGTROOT1,
 TELO
 and
 SORLIP1AT
 elements.
 
 Similarly,
 as
 shown
 in
 Table
 3,
 the
 GSTU19
promoter
contained
all
the
previously
described
root
expression‐associated
 motifs
 with
 the
 exception
 of
 the
 ACGTROOT1
 and
 TELO
 elements.
 
 It
 should
 be
 noted
that
the
frequency
of
any
given
cis‐regulatory
motif
sequence
occurring
in
the
 promoter
 region
 by
 random
 chance
 may
 be
 calculated
 based
 on
 the
 nucleotide
 frequency
that
could
occur
within
a
2kb
promoter
region,
assuming
that
nucleotides
 are
arranged
at
random.

The
elements
that
were
of
doubtful
statistical
significance
 in
the
in
silico
GSTU19
promoter
analysis,
are
demarcated
by
an
asterisk
(Table
3).

 It
is
important
to
note
that
the
sizes
of
the
promoter
fragments
that
were
amplified
 for
 the
 transgenic
 constructs
 (4CL1pro
 (1224bp)
 and
 GSTU19pro
 (1402bp)),
 were
 slightly
less
then
the
2kb
regions
analyzed
in
PLACE
but
contained
at
the
very
least
  
  52
  one
of
each
of
the
root
expression‐associated
elements
found
in
the
2kb
fragments
 analyzed.


 Table
2.
Cis­acting
DNA
regulatory
elements
located
2000
bp
upstream
of
the
 transcription
 start
 site
 of
 At4CL1
 (At1g51680).
 The
 high
 frequency
 regulatory
 elements
 are
 shown
 first
 as
 well
 as
 the
 number
 of
 times
 the
 element
 appears
 on
 both
 the
 (+)
 and
 (‐)
 strands
 (actual
 frequency).
 The
 third
 column
 represents
 the
 number
 of
 times
 that
 a
 motif
 could
 occur
 at
 random
 assuming
 all
 four
 nucleotides
 are
 represented
 equally,
 given
 the
 number
 of
 base
 pairs
 in
 the
 sequence
 (i.e.
 1:4x,
 where
 x
 is
 the
 number
 of
 base
 pairs
 in
 the
 motif
 sequence),
 in
 the
 2kb
 promoter
 region
 analyzed.
 This
 number
 gives
 an
 indication
 of
 the
 number
 of
 elements
 that
 would
 need
 to
 appear
 in
 the
 promoter
 (on
 a
 single
 strand)
 in
 order
 for
 the
 over‐ represented
motif
to
be
statistically
significant,
based
on
the
statistical
frequency
of
 occurrence
of
that
sequence.


 
 Statistical
frequency
 of
occurrence
in
the
 Putative
root
motif
 Sequence
 Actual
frequency
 2kb
promoter
 fragment
analyzed
 ROOTMOTIFTAPOX1
  ATATT
  1.95:2000
  13+;
16‐
  RAV1AAT
  CAACA

  1.95:2000
  6+;
1‐
  ASF1MOTIFCAMV*
  TGACG

  1.95:2000
  2+;
2‐
  OSE2ROOTNODULE
  CTCTT
  1.95:2000
  4+
  OSE1ROOTNODULE
  AAAGAT
  0.488:2000
  2+;
1‐
  SURECOREATSULTR11
  GAGAC
  1.95:2000
  3‐
  SP8BFIBSP8BIB
  TACTATT
  0.122:2000
  2‐
  ARFAT
  TGTCTC
  0.5:2000
  1+
  WUSATAg
  TTAATAG
  0.122:2000
  1‐
  *Sequence
of
doubtful
statistical
significance
 
 
 
 
 
 
  
  53
  
 Table
3.
Cis­acting
DNA
regulatory
elements
located
2000
bp
upstream
of
the
 transcription
start
site
of
AtGSTU19
(At1g78380).
The
high
frequency
regulatory
 elements
 are
 shown
 first
 as
 well
 as
 the
 number
 of
 times
 the
 element
 appears
 on
 both
 the
 (+)
 and
 (‐)
 strands
 (actual
 frequency).
 The
 third
 column
 represents
 the
 number
 of
 times
 that
 a
 motif
 could
 occur
 at
 random
 assuming
 all
 four
 nucleotides
 are
 represented
 equally,
 given
 the
 number
 of
 base
 pairs
 in
 the
 sequence
 (i.e.
 1:4x,
 where
 x
 is
 the
 number
 of
 base
 pairs
 in
 the
 motif
 sequence),
 in
 the
 2kb
 promoter
 region
 analyzed.
 This
 number
 gives
 an
 indication
 of
 the
 number
 of
 elements
 that
 would
 need
 to
 appear
 in
 the
 promoter
 (on
 a
 single
 strand)
 in
 order
 for
 the
 over‐ represented
motif
to
be
statistically
significant,
based
on
the
statistical
frequency
of
 occurrence
of
that
sequence.


 
 
 
 Statistical
frequency
 of
occurrence
in
the
 Putative
root
motif
 Sequence
 Actual
frequency

 2kb
promoter
 fragment
analyzed
 ROOTMOTIFTAPOX1
  ATATT
  1.95:2000
  6+;
8‐
  OSE1ROOTNODULE
  AAAGAT
  0.488:2000
  1+;
5‐
  OSE2ROOTNODULE
  CTCTT
  1.95:2000
  4+;
2‐
  ASF1MOTIFCAMV
  TGACG

  1.95:2000
  3+;
2‐
  RAV1AAT*
  CAACA

  1.95:2000
  2+;
2‐
  SORLIP1AT
  GCCAC
  1.95:2000
  4+
  SURECOREATSULTR11*
  GAGAC
  1.95:2000
  1+;
1‐
  ARFAT
  TGTCTC
  0.488:2000
  1+
  SP8BFIBSP8BIB
  TACTATT
  0.122:2000
  1‐
  WUSATAg
  TTAATAG
  0.122:2000
  1+
  
 *Sequence
of
doubtful
statistical
significance
 
 
 
  
  54
  3.3
  SND1
overexpression
in
transgenic
plants
  
 Two
 gene
 expression
 constructs
 (GSTU19pro­SND1
 and
 4CL1pro­SND1)
 were
 engineered
 by
 PCR
 amplification
 and
 ligation
 of
 the
 GSTU19
 and
 4CL1
 promoters
 and
 SND1
 ORF
 with
 the
 pPZP211
 Agrobacterium
 binary
 vector.
 
 These
 constructs
 were
 then
 introduced
 into
 Arabidopsis
 plants
 using
 Agrobacterium‐mediated
 transformation.
 PCR
 analysis
 of
 genomic
 DNA
 was
 used
 to
 select
 T1
 generation
 kanamycin‐resistant
 transgenic
 lines
 by
 confirming
 the
 presence
 of
 the
 transgene.
 Roots
 from
 three‐week‐old
 T2
 generation
 kanamycin‐resistant
 transgenic
 lines
 were
 subsequently
 analyzed
 using
 RT‐PCR
 to
 determine
 whether
 the
 SND1
 transgene
was
being
overexpressed.

The
RT‐PCR
analysis
detected
overexpression
 of
SND1,
compared
to
wild
type,
in
~90%
of
the
lines
analyzed
for
both
constructs,
  .T .2 E2 E3 E4 F3 F4 F5 F7 F8 G -8 H -3  W  W  .T .1 A1 A7 C -5 W .T B- .2 5 B8 C -2 D -1 D -2 D -6 D -7  as
shown
in
Figure
7.

  SND1 Act8  !"#$%&'()*"+,%-  ./0%'()*"+,%-  
 
 Figure
 7.
 Transcriptional
 analysis
 of
 T2
 generation
 plants
 overexpressing
 SND1
using
RT­PCR.


Total
RNAs
were
isolated
from
three‐week–old
root
tissue
of
 10
 independent
 transgenic
 plant
 lines
 from
 each
 construct
 as
 well
 as
 wild
 type
 control
 plants.
 GSTU19pro­SND1
 lines
 were
 induced
 with
 100µM
 benoxacor
 on
 ½
 MS
solid
media
for
twenty‐four
hours
prior
to
RNA
extraction.
Actin8
was
used
as
an
 internal
and
loading
control
as
shown
by
comparable
expression
levels.
 
 
 These
lines
represent
a
mixture
of
both
homozygous
and
heterozygous
individuals;
 therefore,
 among
 the
 T2
 generation
 lines
 showing
 overexpression,
 12
 sub‐lines
  
  55
  were
 screened
 for
 homozygosity.
 
 Twenty‐two
 kanamycin‐resistant
 homozygous
 sub‐lines
were
identified
for
GSTU19pro­SND1
and
twelve
for
4CL1pro­SND1.

These
 T3
 generation
 transgenic
 lines,
 homozygous
 for
 a
 single
 active
 T‐DNA
 insert,
 were
 used
 for
 further
 experiments
 to
 determine
 the
 possible
 effects
 of
 SND1
 overexpression.
  3.4
  Molecular
analysis
of
transgenic
plants
overexpressing
SND1
  
 Given
the
recent
identification
of
SND1
as
a
master
transcriptional
switch
activating
 the
developmental
program
of
secondary
cell
wall
biosynthesis
and
as
an
activator
 of
several
transcription
factors
that
are
involved
in
that
process
(Zhong
et
al.
2006;
 Zhong
et
al.
2008),
I
predicted
that
SND1
overexpression
would
result
in
an
increase
 in
expression
of
direct
targets
of
SND1,
such
as
MYB46,
SND3,
MYB103
and
KNAT7.

 Reverse
 transcription
 PCR
 analysis
 of
 these
 direct
 targets
 was
 conducted
 for
 two
 reasons:
1)
to
determine
whether
the
secondary
cell
wall
gene
regulatory
networks
 previously
described
were
present
and
functional
in
roots,
and
2)
to
investigate
the
 root‐specificity
 of
 the
 constructs.
 
 As
 shown
 in
 Figure
 8,
 SND1
 was
 found
 to
 be
 upregulated
in
both
roots
and
shoots
(aerial
tissue
in
seedlings
that
does
not
include
 stems)
compared
to
empty
vector
control
lines.

In
contrast,
the
other
transcription
 factors
(TFs)
analyzed
showed
negligible
changes
in
gene
expression
in
shoots
but
 showed
a
more
noticeable
increase
in
gene
expression
in
roots.

Given
that
these
TFs
 are
 normally
 preferentially
 expressed
 in
 stems
 (Zhong
 et
 al.
 2006;
 Zhong
 et
 al.
 2008),
 this
 data
 provides
 evidence
 that
 the
 SND1
 overexpression
 constructs
 are
 behaving
in
a
root‐preferential
manner
and
that
SND1
overexpression
results
in
an
 increase
in
gene
expression
of
its
direct
targets.


 
  56
  !"#$%&"'(")"'*+,-"../0)'  1234'  !005' 16005'  123D#  +!"!#  @0)5-0#E.6005' ?@A4,-0;1234E.6005'  &!"!#  (1894:,-0;1234E.6005'  *!"!# %!"!#  @0)5-0#E-005'  )!"!# $!"!#  ?@A4,-0;1234E-005'  (!"!#  (1894:,-0;1234E-005'  !"!#  +!"!#  (1894:,-0;1234'<3;=>'  !"#$%&"'(")"'*+,-"../0)'  '!"!#  ?@A4,-0;1234'<B;C>'  FGH4JD#  !"#$%&"'(")"'*+,-"../0)'  !"#$%&"'(")"'*+,-"../0)'  !"#$%&"'(")"'*+,-"../0)'  *7'  &!"!# *!"!# %!"!# )!"!# $!"!# (!"!# !"!#  +!"!#  (%!"!# ($!"!# (!!"!# '!"!# &!"!# %!"!# $!"!# !"!#  FGH?I##  &!"!# *!"!# %!"!# )!"!# $!"!# (!"!# !"!#  $*!"!#  K2L8C#  $!!"!# (*!"!# (!!"!# *!"!# !"!#  
 Figure
8.
Transcriptional
analysis
of
transcription
factors
known
to
be
direct
 targets
of
SND1.
Three‐week‐old
T3
generation
Arabidopsis
seedlings
grown
on
½
 MS
 solid
 medium
 and
 GSTU19pro­SND1
 lines
 treated
 for
 24
 hours
 with
 benoxacor
 (100
µM).

Total
RNA
was
extracted
from
roots
(R)
and
shoots
(S)
of
transgenic
and
 empty
 vector
 lines.
 Transcription
 factors
 were
 analyzed
 using
 RT‐PCR.
 Actin8
 was
 used
 as
 an
 internal
 and
 loading
 control
 as
 shown
 by
 comparable
 levels.
 Differentially
 expressed
 PCR
 products
 were
 analyzed
 using
 the
 Image
 J
 (1.42)
 (ImageJ:
Image
Processing
and
Analysis
in
Java)
program
to
compare
the
expression
 levels
 of
 each
 transcript
 relative
 to
 the
 Actin8
 control.
 SND1
 (At1g32770);
 SND3
 (At1g28470);
MYB46
(At5g12870);
MYB103
(At1g63910);
KNAT7
(At1g62990).

 
 
 To
 determine
 whether
 the
 result
 of
 the
 ectopic
 gene
 expression
 of
 these
 TFs
 specifically
 influences
 lignin
 biosynthesis
 in
 roots,
 RT‐PCR
 analysis
 was
 also
 performed
on
genes
encoding
three
indicative
lignin
biosynthetic
pathway
enzymes
 (4CL1,
CCR
and
COMT),
as
shown
in
Figure
9.


  
  57
  A-7 Root  A-7 Shoot  G-8 Root  G-8 Shoot  EV Root  EV Shoot  '&!"  !"#$%&"'(")"'*+,-"../0)'  '%!" '$!" '#!" '!!" &!" %!" $!" #!" !"  A-7 Root  A-7 Shoot  G-8 Root  G-8 Shoot  EV Root  EV Shoot  
  
 Figure
 9.
 Reverse
 transcription
 PCR
 analysis
 of
 genes
 involved
 in
 lignin
 biosynthesis.
 
 Three‐week‐old
 T3
 generation
 Arabidopsis
 seedlings
 grown
 on
 ½
 MS
 solid
 medium
 and
 GSTU19pro­SND1
 lines
 treated
 for
 24
 hours
 with
 benoxacor
 (100
µM).

Total
RNA
was
extracted
from
roots
(R)
and
shoots
(S)
of
transgenic
and
 empty
vector
lines.

Act8
was
used
as
an
internal
and
loading
control
as
shown
by
 comparable
 levels.
 Differentially
 expressed
 PCR
 products
 were
 analyzed
 using
 the
 Image
J
(1.42)
(ImageJ:
Image
Processing
and
Analysis
in
Java)
program
to
compare
 the
expression
levels
of
each
transcript
relative
to
the
Act8
control.

 
 In
 contrast
 to
 the
 results
 for
 expression
 of
 the
 secondary
 cell
 wall‐related
 TFs,
 I
 observed
 no
 difference
 in
 gene
 expression
 among
 the
 lignin
 biosynthetic
 genes
 or
 among
 tissue
 types
 compared
 to
 empty
 vector
 controls.
 
 
 This
 data
 suggests
 that
 unlike
the
previously
described
constitutive
overexpression
of
SND1,
which
showed
 ectopic
 deposition
 of
 lignified
 secondary
 walls
 in
 normally
 non‐sclerenchymatous
 cells
 of
 flowers,
 leaves
 and
 stems
 (Zhong
 et
 al.
 2006),
 overexpression
 of
 SND1
 in
  
  58
  roots
 had
 no
 influence
 on
 the
 expression
 of
 genes
 encoding
 certain
 key
 lignin
 biosynthetic
enzymes.
  3.5
 
  Determination
of
lignin
content
in
transgenic
plants
overexpressing

 SND1
  3.5.1
 Determination
of
lignin
content
in
transgenic
plants
overexpressing
SND1
by
 
 rapid
micro‐scale
acetyl
bromide
method
 
 To
 determine
 total
 lignin
 content,
 several
 methods
 and
 techniques
 have
 been
 developed
and
adapted
in
order
to
quantitatively
determine
total
lignin
content
and
 composition
 in
 plant
 tissues
 (Hatfield
 &
 Fukushima
 2005).
 
 To
 analyze
 total
 lignin
 content
(w/w)
in
the
roots
of
transgenic
plants
overexpressing
SND1,
I
first
used
a
 rapid
micro‐scale
method
as
outlined
in
 Chang
et
al.
(2008).

This
acetyl
bromide‐ based
 lignin
 micro‐scale
 assay
 was
 primarily
 developed
 to
 provide
 a
 rapid
 yet
 sensitive
method
of
determining
lignin
concentration,
using
small
amounts
of
plant
 material.
 
 This
 method
 is
 useful
 for
 small
 samples
 whose
 size
 is
 unsuitable
 for
 procedures
 that
 rely
 on
 the
 production
 and
 gravimetric
 measurement
 of
 an
 insoluble
lignin
residue,
such
as
the
Klason
lignin
analysis.


 
 Based
on
the
previous
studies
that
had
shown
SND1
to
be
a
master
transcriptional
 switch
activating
the
developmental
program
of
secondary
cell
wall
biosynthesis
in
 fibres,
 I
 predicted
 that
 the
 overexpression
 of
 SND1
 and
 its
 direct
 target
 genes
 in
 roots
 would
 cause
 an
 increase
 in
 total
 lignin
 content
 (Zhong
 et
 al.
 2006).

 Unexpectedly,
 my
 analysis
 of
 roots
 of
 the
 transgenic
 SND1
 overexpression
 lines,
 showed
 a
 47%
 and
 40%
 decrease
 in
 total
 lignin
 content
 in
 both
 GSTU19pro­SND1
 overexpression
 lines
 (A‐7
 and
 B‐5
 respectively)
 and
 a
 46%
 decrease
 in
 lignin
 
  59
  content
 in
 one
 of
 the
 two
 4CL1pro­SND1
 overexpression
 lines
 (G‐8)
 (Fig.
 10),
 compared
 to
 the
 roots
 of
 empty
 vector
 control
 plants.
 
 The
 second
 4CL1pro­SND1
 overexpression
line
analyzed
(F‐5)
showed
no
obvious
change
in
lignin
content
(1%
 decrease)
 compared
 to
 the
 empty
 vector
 control.
 
 This
 result
 appears
 to
 be
 correlated
 with
 the
 lack
 of
 altered
 gene
 expression
 among
 the
 lignin
 biosynthetic
 genes
observed
in
these
same
genotypes
(Fig.
9).

 
 $!"!#  !"#$%&$&"'(&)*&)"+,-,."  ,"!#  /$%&$&"0(&)*&)"  -.(#  +"!#  /.+#  *"!#  01234# 567389#  )"!# ("!#  :.*#  '"!#  ;.(#  &"!# %"!#  01234# 567389# <;6=8>?#  $"!# !"!#  Figure
 10.
 Lignin
 content
 in
 transgenic
 Arabidopsis
 plants
 overexpressing
 SND1.
 Percent
 lignin
 content
 (w/w),
 determined
 by
 the
 rapid
 microscale
 acetyl
 bromide
 method,
 in
 empty
 vector
 control
 and
 transgenic
 Arabidopsis
 plants
 expressing
 the
 4CL1pro­SND1
 (Grey)
 and
 GSTU19pro­SND1
 (Red)
 constructs.
 Control
 plants
 contain
 pPZP211.
 Error
 bars
 indicate
 standard
 error
 from
 three
 technical
replicates
(control
and
transgenic
lines
are
T3
generation).
 3.5.2
 Cellulose,
starch
and
Klason
lignin
analysis
 
 Because
SND1
has
been
shown
to
be
a
master
transcriptional
switch
activating
the
 developmental
 program
 of
 overall
 secondary
 cell
 wall
 biosynthesis
 in
 fibres,
 as
 opposed
 to
 just
 lignin
 biosynthesis,
 I
 reasoned
 that
 the
 decrease
 in
 lignin
 content
 
  60
  and
 lack
 of
 change
 in
 expression
 of
 genes
 encoding
 lignin
 biosynthetic
 enzymes,
 could
 be
 a
 result
 of
 carbon
 being
 reallocated
 to
 a
 different
 area
 of
 carbon
 metabolism.


 
 Plants
 use
 photosynthesis
 to
 chemically
 convert
 CO2
 to
 carbohydrates,
 such
 as
 cellulose
and
starch.


Cellulose
is
an
important
component
of
the
cell
walls
of
higher
 plants
 and
 the
 world's
 most
 abundant
 organic
 polymer,
 serving
 as
 another
 major
 carbon
sink
in
plants
(similar
to
lignin)
(Delmer
&
Haigler
2002).

One
other
major
 plant
 carbon
 sink
 is
 the
 other
 major
 glucan,
 starch
 (α‐1,4‐glucan
 with
 α‐1,6
 branches).
 
 As
 leaves
 (sources
 that
 export
 carbon)
 and
 storage
 organs
 (sinks
 that
 import
 carbon)
 expand,
 they
 enlarge
 and
 deposit
 their
 cellulose
 in
 their
 primary
 walls
before
the
developmental
transition
that
leads
to
starch
deposition
(Delmer
&
 Haigler
2002).



While
the
ratio
of
cellulose
to
other
cell
wall
polymers
can
change
 considerably,
 until
 recently
 it
 was
 not
 clear
 from
 the
 publicly
 available
 literature
 whether
 carbon
 flux
 in
 plants
 with
 altered
 lignin
 biosynthetic
 pathways
 directly
 altered
 other
 carbon‐polymer
 synthetic
 pathways
 (Delmer
 &
 Haigler
 2002).


 Studies
 have
 now
 shown
 that
 alterations
 in
 lignin
 deposition
 can
 cause
 relative
 cellulose
 content
 to
 increase,
 as
 a
 result
 of
 these
 perturbations
 (Coleman
 et
 al.
 2008).
 To
 test
 my
 carbon
 reallocation
 hypothesis,
 I
 analyzed
 both
 cellulose
 and
 starch
 content
 (in
 addition
 to
 insoluble
 lignin
 content).
 
 
 The
 carbohydrate
 analysis
 provided
an
indirect
measure
of
the
cellulose
(quantified
as
glucose
monomers)
and
 other
 wall
 pollysacharides
 (pectin
 and
 hemicellulose),
 (quantified
 as
 other
 sugars
  
  61
  such
 as
 rhamnose,
 fucose,
 arabinose,
 xylose,
 mannose
 and
 galactose
 monomers)
 content
of
transgenic
lines
overexpressing
SND1
(Table
4).


These
results
showed
a
 29%
decrease
in
cellulose
content
and
26%
decrease
in
hemicellulose
content
in
the
 GSTU19pro­SND1
 line
 (D‐2)
 compared
 to
 the
 empty
 vector
 control.
 
 The
 4CL1pro­ SND1
 line
 (G‐8)
 showed
 a
 slight
 decrease
 of
 3.5%
 in
 cellulose
 content
 and
 a
 negligible
1.5%
decrease
in
hemicellulose
content.


Furthermore,
the
Klason
lignin
 analysis
 revealed
 a
 23%
 decrease
 in
 lignin
 content
 in
 the
 GSTU19pro­SND1
 overexpression
 line
 (D‐2)
 compared
 to
 the
 control,
 which
 was
 consistent
 with
 the
 decrease
in
lignin
content
found
for
GSTU19pro­SND1
lines
analyzed
using
the
acetyl
 bromide‐based
method.

Conversely,
the
4CL1pro­SND1
line
(G‐8)
showed
less
then
 a
0.1%
increase
in
lignin
content
compared
to
the
empty
vector
control,
a
nominal
 amount.
 
 This
 line,
 when
 analyzed
 by
 the
 acetyl
 bromide
 based
 method,
 showed
 a
 46%
decrease
in
lignin
content
as
described
in
the
previous
section.

Although
the
 4CL1pro­SND1
 (G‐8)
 line
 showed
 different
 results
 when
 analyzed
 using
 two
 different
methods,
the
results
shown
here
using
the
Klason
procedure
are
similar
to
 the
other
4CL1pro­SND1
line
(F‐5)
analyzed
using
the
acetyl‐bromide
based
method.

 Table
4.
Cell
wall
composition
of
roots
from
empty
vector
and
transgenic
lines
 overexpressing
 SND1.
 Numbers
 represent
 milligrams
 of
 cellulose,
 hemicellulose
 and
lignin
per
100
milligrams
of
initial
dry
weight.


Absolute
values
shown
are
from
 a
single
biological
replicate.
  
  
  
  62
  
  3.6
  Phenotypic
analysis
of
transgenic
plants
overexpressing
SND1
  3.6.1
 Seed
phenotyping
 
 It
 is
 desirable
 to
 avoid
 pleiotropic
 effects
 that
 might
 result
 from
 constitutive
 overexpression
 of
 target
 genes
 in
 agricultural
 systems,
 which
 is
 why
 the
 ability
 to
 drive
 transgene
 expression
 in
 a
 location‐specific
 and
 controlled
 manner
 is
 important.
 
 
 I
 wished
 to
 determine
 whether
 the
 transgenic
 plants
 overexpressing
 SND1,
 displayed
 any
 phenotypes
 that
 might
 reflect
 an
 impact
 of
 transgene
 expression
 on
 normal
 plant
 growth
 and
 development.
 
 As
 one
 measure
 of
 overall
 growth
 and
 productivity,
 I
 decided
 to
 analyze
 seed‐related
 traits.
 
 My
 transgenic
 plants
overexpressing
SND1
did
not
show
significant
deviations
from
control
plants
 (empty
 vector
 lines)
 in
 terms
 of
 the
 average
 number
 of
 seeds
 per
 silique,
 average
 silique
length,
or
average
germination
rate
when
compared
to
empty
vector
control
 lines
(Fig.
11;
A,
B
and
D).

Average
seed
weights
for
all
lines
fell
into
a
range
of
18‐ 25µg
 per
 seed.
 The
 results
 for
 average
 weight
 per
 seed
 showed
 significant
 differences
(Fig.
11;
C)
as
represented
by
the
lack
of
overlap
in
the
error
bars,
but
 significant
variation
was
also
seen
for
both
control
lines
as
well.


A
one‐way
ANOVA
 test
 of
 the
 overall
 model
 was
 done
 to
 determine
 if
 there
 was
 a
 statistically
 significant
difference
in
means
(with
respect
to
seed
weight)
between
genotypes.

In
 this
 case,
 the
 p‐value
 was
 small
 P
 <
 0.001
 (Appendix
 E),
 therefore
 there
 was
 a
 statistically
significant
difference
in
seed
weight
among
genotypes.
 
 
  
  63
  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
 
 Figure
 11.
 Seed­related
 phenotypes
 of
 T3
 generation
 seeds
 from
 transgenic
 and
 empty
 vector
 constructs.
 
 Average
 number
 of
 seeds
 per
 silique
 (A),
 average
 silique
 length
 (B),
 average
 weight
 per
 seed
 (C)
 and
 average
 germination
 rate
 (D).

 Error
bars
represent
the
95%
confidence
interval
of
an
average
of
30
samples
per
 genotype
 for
 (A)
 and
 (B),
 6
 samples
 per
 genotype
 for
 (C)
 and
 3
 samples
 per
 genotype
 for
 (D).
 
 GSTU19pro­SND1
 lines
 were
 treated
 for
 24
 hours
 with
 100µM
 benoxacor
in
water,
at
4‐weeks.
 
 3.6.2
 Root
growth
and
lateral
root
density
 
 Another
 facet
 of
 plant
 development
 in
 Arabidopsis
 is
 the
 production
 of
 a
 highly
 branched
root
system.

Plant
roots
are
important
tissues
involved
in
many
processes
 such
 as
 uptake
 of
 water,
 interactions
 with
 soil‐microbes,
 the
 secretion
 of
 compounds
required
for
defense
against
pathogens
and
absorption
of
soil
nutrients.

 Furthermore,
 they
 protect
 the
 aboveground
 tissues
 against
 the
 effects
 of
 acidic
  
  64
  conditions
or
heavy
metals
in
the
soil,
and
against
desiccation
(Koyama
et
al.
2005).

 Since
I
was
overexpressing
a
transcription
factor
in
the
roots,
which
is
not
a
tissue
in
 which
it
is
usually
highly
expressed,
I
asked
whether
the
overexpression
of
SND1
in
 the
roots
of
my
transgenic
plants
had
altered
their
root
development.

To
assess
this,
 I
 examined
 root
 growth
 and
 architecture
 by
 measuring:
 1)
 the
 primary
 root
 extention
 among
 14‐day‐old
 seedlings
 at
 a
 similar
 stage
 of
 developmental
 (i.e.
 similar
primary
root
length)
(Fig.
12A)
and
2)
the
number
of
lateral
roots
forming
 on
 these
 primary
 extentions
 (Fig.
 12B).
 
 Lateral
 root
 density
 (LRD)
 was
 then
 determined
by
dividing
the
average
number
of
lateral
roots
counted,
by
the
average
 length
of
the
primary
root
(Fig.
12C).


 
 Both
of
the
GSTU19pro­SND1
transgenic
lines
(A‐7
and
B‐5)
showed
an
increase
in
 LRD
compared
to
the
empty
vector
control.


In
comparison,
one
of
the
two
4CL1pro­ SND1
transgenic
lines
analyzed,
(G‐8),
showed
higher
lateral
root
density,
whereas
 the
 other
 line
 (F‐7)
 did
 not
 show
 any
 difference
 compared
 to
 the
 empty
 vector
 control
line.

A
one‐way
ANOVA
test
of
the
overall
model
was
done
to
determine
if
 there
 was
 a
 statistically
 significant
 difference
 in
 means
 (with
 respect
 to
 LRD)
 between
 genotypes.
 
 In
 this
 case,
 the
 p‐value
 was
 small
 P
 =
 0.000
 (Appendix
 E),
 therefore
 there
 was
 a
 statistically
 significant
 difference
 in
 lateral
 root
 density
 among
genotypes.
 
  
  65
  B  34&'$5&"'((%"#&05%6"(7"8" 9$2"(#9")&&9#105)":+,;"  '" &#("  <'1,$'2".((%"=>%&0)1(0"  34&'$5&"0?,@&'"(7"#$%&'$#" '((%)"(7"ABC9$2C(#9" )&&9#105)"  A  &"  -$%&'$#".((%"D(',$E(0"  %#("  &" %#("  -.*"4'5"  %"  /.+"4'5"  $#("  0.*"4(5"  $"  1.("4)5"  !#("  C  $"  !"#$%&'$#"'((%)*+,""  !#,"  -.*"4'5"  $#("  /.+"4'5"  $"  0.*"4(5" 1.("4)5"  !#("  2#3#"6'!"  !"  %"  2#3#"6'!"  !"  -$%&'$#".((%"/&0)1%2"  !#+"  -.*" /.+" 0.*" 1.(" 23"'!"  !#*" !#)" !#(" !#'" !#&" !#%" !#$" !"  
 Figure
 12.
 
 Primary
 root
 extention,
 lateral
 root
 formation
 and
 number
 of
 lateral
roots
per
cm
(lateral
root
density)
of
14­day­old
seedlings.

Left
to
right,
 4CL1pro­SND1
(red);
GSTU19pro­SND1
(grey);
empty
vector
(neutral).

Lateral
root
 density
 was
 calculated
 by
 dividing
 the
 number
 of
 lateral
 roots
 by
 the
 length
 of
 primary
 root
 (cm).
 Lateral
 roots
 that
 had
 emerged
 at
 least
 1.0
 mm
 from
 the
 root
 surface
 were
 counted.
 Error
 bars
 represent
 the
 95%
 confidence
 interval
 of
 an
 average
of
20
samples
per
genotype.
 
 3.6.3
 Plant
growth
and
height

 
 Plant
 growth
 and
 development
 are
 controlled
 by
 the
 combined
 action
 of
 many
 different
 signaling
 pathways,
 which
 integrate
 information
 from
 the
 environment
 with
 metabolic
 and
 developmental
 signals.
 
 If
 these
 normal
 developmental
 pathways,
 such
 as
 the
 phenylpropanoid
 pathway,
 are
 disrupted
 or
 altered,
 severe
 consequences
to
overall
plant
growth
and
function
could
ensue.

To
investigate
the
 effects
of
SND1
overexpression
in
roots
on
general
plant
growth
and
development,
I
  
  66
  examined
 transgenic
 lines
 over
 a
 six‐week
 period
 to
 look
 for
 any
 obvious
 phenotypic
differences
in
normal
plant
growth
and
development,
such
as
flowering
 time,
overall
plant
height
and
shape,
and
leaf
morphology.

Transgenic
plants
did
not
 show
any
visible
phenotypic
differences
as
compared
to
empty
vector
control
lines
 as
shown
in
Figure
13.


 


  D  A  !"#$%&#  '()*+,-./0(12+#  %34+-./0(12+#  !"#$%&#  '()*+,-./0(12+#  %34+-./0(12+#  B  C  !"#$%&#  '()*+,-./0(12+#  %34+-./0(12+#  !"#$%&#  '()*+,-./0(12+#  %34+-./0(12+#  
  
 Figure
 13.
 
 Plant
 growth
 and
 height
 time­course
 experiment
 for
 transgenic
 plants
overexpressing
SND1
and
empty
vector
lines.

Photographs
are
detailing
 plant
growth
at
(A)
3
weeks,
(B)
4
weeks,
(C)
5
weeks
and
(D)
6
weeks.

GSTU19pro­ SND1
lines
were
treated
at
4
weeks
for
24
hours
with
100µm
benoxacor.
 
 
  
  67
  3.6.4
 Microscopy
 
 In
SND1
overexpression
plants
where
the
gene
was
under
the
control
of
the
CaM35S
 promoter,
 ectopic
 secondary
 wall
 thickening
 was
 not
 always
 observed
 in
 root
 cell
 types
 but
 was
 occasionally
 seen
 in
 the
 epidermal
 cells
 of
 hypocotyls
 and
 cortical
 cells
(Zhong
et
al.
2006).

To
investigate
lignin
deposition
patterns
in
my
transgenic
 lines
 overexpressing
 SND1
 under
 the
 control
 of
 more
 root‐specific
 promoters,
 I
 conducted
 a
 histochemical
 analysis
 of
 the
 root‐hypocotyl
 in
 the
 various
 different
 transgenic
plant
genotypes
I
had
developed.

Root‐hypocotyls
were
fixed,
embedded
 in
 paraffin
 wax
 and
 sectioned.
 
 For
 visualization
 of
 lignified
 secondary
 walls,
 the
 sections
 were
 stained
 with
 phloroglucinol‐HCl
 reagent
 (Pomar
 et
 al.
 2002).

 Phloroglucinol–HCl
staining
should
identify
cell
walls
that
have
lignin
deposition,
by
 staining
 them
 red.
 
 However,
 my
 transgenic
 plants
 did
 not
 show
 any
 visible
 differences
 in
 lignin
 deposition
 when
 compared
 with
 empty
 vector
 controls
 (Fig.
 14).
 
 
 There
 was
 notable
 variation
 in
 lignin
 content
 along
 the
 5mm
 sections
 of
 hypocotyl
 analyzed,
 however,
 which
 made
 it
 difficult
 to
 establish
 developmental
 equivalencies.
 Nevertheless,
 the
 histochemical
 results
 suggest
 that
 SND1
 overexpression
 in
 root
 tissue
 had
 produced
 no
 observable
 difference
 in
 lignin
 deposition
patterns
in
the
tissues
analyzed.
  
  68
  A  B  X  C  P  NV  GSTU19pro-SND1 D  Empty Vector  E  F  4CL1pro-SND1  Empty Vector  
 
 Figure
 14.
 Wax­embedded
 root­hypocotyl
 cross­sections
 of
 SND1
 overexpressors
and
empty
vector
control
lines.
The
10
µm
sections
were
stained
 with
 phloroglucinol‐HCl
 to
 show
 lignified
 walls.
 X=xylem,
 P=phloem
 and
 NV=non‐ vascular.
 Scale
 bars
 represent
 200µm
 at
 5x
 magnification.
 
 
 A=A‐7;
 B=D‐6;
 C=EV
 (safener
 treated);
 D=F‐7;
 E=G‐8;
 F=EV.
 
 A,
 B
 and
 C
 were
 treated
 with
 100µM
 benoxacor
for
24
hours.

 
 To
 further
 analyze
 lignin
 deposition
 patterns,
 lignin
 autofluorescence
 was
 monitored
 in
 tissues
 irradiated
 with
 UV
 light
 at
 360±40nm
 (Fig.
 15).

 Autofluorescence
at
this
irradiation
wavelength
allows
an
assessment
of
the
overall
 localization
 of
 lignin
 in
 tissues
 that
 are
 lignified
 (Tao
 et
 al.
 2009).
 
 
 Observations
 from
 low
 (5x)
 to
 high
 (40x)
 magnification
 (data
 not
 shown)
 revealed
 no
 apparent
 differences
in
lignin
location
or
architecture.

Again,
there
was
some
variation
in
the
 observed
fluorescence
along
the
5mm
developmental
gradient.

However,
as
seen
at
 20x
magnification
(Fig.
15)
there
was
no
substantial
difference
in
cell
wall
thickness
 or
organization
among
sections
and
tissues
analyzed.
  
  69
  A  B  C  GSTU19pro-SND1 D  Empty Vector  E  F  4CL1pro-SND1  Empty Vector  
 
 Figure
 15.
 Auto­fluorescence
 of
 lignin
 in
 root­hypocotyl
 cross­sections.
 UV
 fluorescence
 microscopy
 (UV
 360±40nm)
 of
 10µm
 wax‐embedded
 root
 cross‐ sections
visualized
at
20x
magnification.
Bars=50µm.

A=A‐7;
B=D‐6;
C=EV
(safener
 treated);
D=F‐7;
E=G‐8;
F=EV.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  70
  4.
 
  Discussion
  Soils
 represent
 the
 main
 carbon
 pool
 of
 the
 global
 carbon
 cycle.
 
 Photosynthesis
 enables
 plants
 to
 convert
 atmospheric
 CO2
 into
 carbohydrates
 (such
 as
 starch
 and
 cellulose)
or
into
other
more
stable
organic
carbon
forms
such
as
lignin
(Zibilske
&
 Bradford
 2007).
 
 Next
 to
 cellulose,
 lignin
 is
 the
 second
 most
 abundant
 carbon
 biopolymer
on
earth,
accounting
for
an
estimated
30%
of
the
organic
carbon
(C)
in
 the
 biosphere
 (Dungait
 et
 al.
 2008).
 
 It
 is
 known
 that
 the
 abundance,
 tissue
 distribution
and
composition
of
this
important
plant
cell
wall
polymer
can
have
an
 important
 effect
 on
 plant
 health,
 as
 well
 as
 agro‐industrial
 processing
 and
 carbon
 sequestration
potential
(Saballos
et
al.
2009).


In
fact,
the
decomposition
of
lignin
in
 roots
and
plant
residues
in
soils
used
for
agriculture,
forestry
and
land
reclamation
 has
 been
 recognized
 as
 a
 potential
 option
 to
 sequester
 carbon
 and
 mitigate
 global
 change
 by
 trapping
 carbon
 into
 longer‐lived
 pools
 (Kumar
 et
 al.
 2006).


 Furthermore,
 a
 high
 content
 of
 polyphenolic
 compounds,
 such
 as
 lignin,
 in
 plant
 residues
 can
 prolong
 the
 retention
 of
 C
 in
 soils
 (Zibilske
 &
 Bradford
 2007).
 
 
 Soil
 organic
carbon
is
an
essential
component
of
healthy
soils
and
has
been
reported
to
 increase
 the
 water‐holding
 capability
 of
 sandy
 soil
 and
 to
 improve
 the
 structural
 stability
 of
 clay
 loam
 soils
 by
 helping
 to
 form
 particle
 aggregates
 (Zibilske
 &
 Bradford
 2007).
 
 
 Soil
 organic
 carbon
 is
 an
 effective
 medium
 for
 sequestration
 of
 inorganic
nutrients;
it
can
bind
both
cations
and
trace
elements
that
can
affect
crop
 growth
 and
 yield.
 
 This
 yield
 enhancement
 can
 involve
 either
 the
 direct
 supply
 of
 nutrients
to
plant
root
systems,
or
indirectly
alter
the
physical
properties
of
the
soil,
  
  71
  thus
 improving
 the
 root
 environment
 and
 stimulating
 plant
 growth
 (Hati
 et
 al.
 2007).
 
 
 The
 sequestration
 capacity
 of
 organic
 carbon
 in
 soils
 is
 advantageous
 to
 plants
 when
 it
 comes
 to
 plant
 stress
 because
 roots
 serve
 as
 the
 proverbial
 foot
 soldiers
in
the
plant’s
battle
to
survive
in
an
often
hostile
environment.

Roots
are
 the
 first
 and
 most
 critical
 plant
 organ
 to
 experience
 nutrient
 deficiency,
 drought,
 osmotic
 and
ionic
 stress,
soil
 salinization,
 heavy
 metal
accumulation
 and
 pathogen
 interactions.
 
 In
 response
 to
 these
 various
 stresses,
 plants
 undergo
 physiological
 and
metabolic
changes
underpinned
by
alterations
in
gene
expression
that
produce,
 among
other
things,
complex
mixtures
of
biologically
active
secondary
metabolites
 involved
 in
 important
 processes
 such
 as
 cellular
 protection
 and
 ion
 homeostasis
 (Jones
 et
 al.
 2008).
 
 For
 example,
 the
 production
 of
 secondary
 metabolites
 via
 the
 phenylpropanoid
 pathway
 provides
 intermediates
 for
 the
 synthesis
 of
 UV
 protectants
  (flavonols),
  defense
  compounds
  (isoflavonoids),
  pigments
  (anthocyanins/flavonols),
nodulation
inducers
(flavones)
and
lignins
(monolignols)
 (Kumar
et
al.
2006;
Nessler
1994).


 
 As
 a
 model
 for
 engineering
 increases
 in
 soil
 carbon
 stocks
 (if
 implemented
 in
 a
 widely
planted
crop
system),
I
proposed
to
create
transgenic
Arabidopsis
plants
with
 the
 ability
 to
 produce
 enhanced
 levels
 of
 lignin
 in
 their
 roots.
 
 To
 engineer
 transgenic
plants
with
a
desired
phenotype,
such
as
enhanced
root
lignin,
the
choice
 of
promoter
is
a
crucial
factor.

Strong
promoters
are
needed
for
effective
transgene
 expression
in
plant
cells,
but
regrettably,
most
of
the
widely
used
constitutive
gene
 expression
 systems,
 like
 the
 35S
 promoter
 from
 the
 Cauliflower
 Mosaic
 Virus
  
  72
  (CaMV35S),
 can
 produce
 undesirable
 pleiotropic
 effects
 due
 to
 spatially
 and/or
 temporally
 inappropriate
 ectopic
 gene
 expression
 patterns
 (Yoshida
 &
 Shinmyo
 2000).


For
my
project,
it
was
desirable
to
restrict
transgene
expression
exclusively
 to
 root
 tissues.
 
 So
 far,
 only
 a
 handful
 of
 root‐specific
 gene
 promoters
 have
 been
 identified
in
plant
species
such
as
Arabidopsis,
rice,
tomato
and
tobacco.

However,
 these
promoters
are
often
limited
in
their
applicability
due
to:
a)
restricted
activity
 in
specific
developmental
stages,
regions
or
tissues
within
the
root
structure,
b)
to
 undesirable
 effects
 of
 biotic
 and
 abiotic
 factors
 on
 their
 regulation,
 or
 c)
 to
 a
 requirement
 for
 specific
 growth
 conditions
 (Jones
 et
 al.
 2008).
 
 Genes
 controlling
 cell
 fate
 in
 Arabidopsis
 in
 15
 different
 root
 zones
 (endodermis,
 endodermis
 and
 cortex,
 epidermal
 atrichoblasts
 and
 lateral
 root
 cap)
 that
 relate
 to
 cell
 types
 and
 tissues
at
progressive
developmental
stages
(stage
1,
2
and
3)
have
been
previously
 described
 (Birnbaum
 &
 Benfey,
 2004).
 
 
 Data
 mining
 of
 the
 complete
 microarray
 gene
expression
data
set
from
these
studies
enabled
me
to
develop
my
own
list
of
 candidate
 genes
 whose
 promoters
 could
 be
 used
 to
 drive
 SND1
 gene
 expression.

 These
 candidate
 genes
 were
 then
 examined
 within
 the
 Genevestigator
 microarray
 database
 (Hruz
 et
 al.
 2008,
 https://www.genevestigator.com)
 for
 relative
 expression
 in
 roots
 compared
 to
 other
 plant
 organs
 and
 tissues.
 
 Based
 on
 these
 results,
one
candidate
gene,
GSTU19,
was
selected
for
further
analysis.


 
 The
 second
 candidate
 gene,
 4CL1,
 was
 selected
 based
 on
 previous
 studies
 that
 reported
 high
 levels
 of
 4CL1
 gene
 expression
 in
 seedling
 roots.
 Specifically,
 transgenic
 Arabidopsis
 plants
 containing
 the
 4CL1
 or
 4CL2
 promoter
 fused
 to
 the
  
  73
  beta‐glucuronidase
 (GUS)
 reporter
 gene
 showed
 developmentally
 regulated
 GUS
 expression
 in
 the
 xylem
 tissues
 of
 both
 the
 root
 and
 shoot,
 with
 At4CL1::GUS
 lines
 showing
its
highest
levels
of
gene
expression
in
seedling
roots
(Soltani
et
al.
2006).

 In
order
to
confirm
these
4CL1
results
and
validate
the
potential
of
these
candidate
 promoters
 to
 drive
 transgene
 expression
 in
 the
 roots,
 the
 expression
 of
 both
 candidate
 genes
 was
 checked
 using
 semi‐quantitative
 reverse
 transcription
 (RT)‐ PCR
 in
 flower,
 leaf,
 stem
 and
 roots
 of
 four‐week‐oldplants.
 4CL1
 showed
 only
 a
 negligible
 increase
 in
 gene
 expression
 in
 the
 roots
 compared
 to
 other
 tissues
 but
 was
retained
as
a
candidate
based
on
earlier
studies
of
the
organ‐specific
expression
 pattern
of
4CL1,
which
detected
the
highest
4CL1
mRNA
levels
in
3‐day‐old
seedling
 roots
and
in
bolting
stems
of
mature
plants
(Soltani
et
al.
2006;
Ehlting
et
al.
2002).


 This
 difference
 in
 gene
 expression
 patterns
 among
 plant
 organs,
 and
 among
 these
 organs
 at
 different
 stages
 of
 development,
 suggests
 that
 4CL1
 may
 exhibit
 some
 root‐specificity
but
only
at
a
given
point
in
the
plant’s
growth
cycle.

As
a
side
note,

 the
 4CL1
 promoter
 was
 an
 attractive
 candidate
 due
 to
 its
 active
 involvement
 in
 channeling
carbon
flow
into
branch
pathways
of
phenylpropanoid
metabolism.

 
 This
 RT‐PCR
 analysis
 also
 demonstrated
 that
 GSTU19
 is
 in
 fact
 expressed
 at
 a
 noticeably
 higher
 level
 in
 roots
 compared
 to
 other
 organs.
 
 These
 results
 were
 consistent
with
the
Genevestigator
heat
map
profile
as
well
as
with
previous
studies
 showing
that,
under
control
conditions,
expression
of
GSTU19
mRNA
was
higher
in
 roots
than
in
shoots
(DeRidder
&
Goldsbrough
2006).


In
summary,
the
data
shown
 for
the
expression
of
4CL1
and
GSTU19
in
different
plant
organs
along
with
evidence
  
  74
  from
the
previous
studies
mentioned,
suggests
that
the
promoters
from
these
genes
 could
both
be
good
candidates
to
drive
SND1
transgene
expression
in
roots,
but
for
 different
 reasons.
 
 Based
 on
 my
 results
 from
 the
 RT‐PCR
 analysis,
 the
 4CL1
 promoter
does
not
seem
to
be
a
good
candidate
for
driving
root‐specific
expression
 but
 conversely,
 GSTU19
 does
 seem
 to
 have
 the
 potential
 to
 drive
 root‐specific
 expression,
which
is
further
supported
by
this
promoters
ability
to
be
induced
in
a
 root
specific
manner
when
treated
with
the
herbicide
safener
benoxacor.
 
 
 The
 ability
 to
 turn
 on
 gene
 expression
 both
 spatially
 and
 temporally
 offers
 the
 opportunity
 to
 fine‐tune
 ectopic
 gene
 expression
 without
 compromising
 the
 viability
of
the
organism
or
the
function
of
the
organ
being
altered,
in
this
case
the
 roots.
 
 
 Plant
 promoters
 that
 impart
 root‐specific
 expression
 are
 of
 interest
 for
 improving
tolerance
to
abiotic
stresses
such
as
drought
and
salinity,
for
engineering
 pathogen
 resistance
 and
 for
 improving
 nutrient
 uptake
 (Vijaybhaskar
 et
 al.
 2008),
 due
to
their
potential
to
express
recombinant
proteins,
such
as
the
Cry
toxins,
in
the
 root
 (Nitz
 et
 al.
 2001;
 Vijaybhaskar
 et
 al.
 2008;
 Maizel
 &
 Weigel
 2004).

 Interestingly,
 a
 considerable
 number
 of
 root‐specific
 promoters
 have
 been
 characterized,
 including:
 
 Pyk10
 from
 Arabidopsis
 thaliana
 (Nitz
 et
 al.
 2001),
 a
 glycosyltransferase
gene
(At1g73160)
from
Arabidopsis
thaliana
(Vijaybhaskar
et
al.
 2008),
 the
 PHT1
 gene
 from
 Arabidopsis
 thaliana
 (Koyama
 et
 al.
 2005),
 the
 mannopine
synthase
2'
(mas2')
promoter
from
Agrobacterium
tumefacians
(Ni
et
al.
 1996),
 the
 iron
 deficiency
 specific
 clone
 no.
 2
 (IDS2)
 promoter
 from
 barley
 (Kobayashi
et
al.
2003),
putrescine
N‐methyltransferase
(PMT)
gene
(Mizusaki
et
al.
  
  75
  1971)
and
TobRB7
promoter
from
tobacco
(Yamamoto
et
al.
1991)
and
SlREO
gene
 from
Solanum
lycopersicum.

Despite
these
examples,
strong
root‐specific
promoters
 (i.e.
promoters
that
provide
for
a
high
level
of
gene
expression)
that
can
be
used
for
 various
crop
improvements
are
still
thought
to
be
limited
(Cai
et
al.
2007).

Indeed,
 when
 I
 examined
 the
 expression
 level
 of
 the
 so‐called
 “root‐specific”
 Arabidopsis
 promoters
 (mentioned
 above)
 within
 the
 Birnbaum
 et
 al.
 (2003)
 data
 set
 used
 to
 identify
 GSTU19,
 I
 found
 that
 their
 relative
 probe
 intensity
 values
 within
 the
 stele
 and
 endo‐cortex,
 fell
 below
 my
 chosen
 cutoff
 of
 1500‐5000.
 
 They
 were
 therefore
 excluded
 from
 this
 project,
 but
 that
 does
 not
 mean
 they
 should
 be
 rejected
 as
 candidate
 promoters
 to
 drive
 root‐specific
 transgenes
 in
 general.
 
 Further
 studies
 could
 test
 the
 strength
 of
 these
 promoters
 experimentally
 by
 quantifying
 the
 GUS
 activity
expressed
in
promoter::GUS
transgenic
lines.


Moreover,
when
considering
 the
 use
 of
 these
 promoters
 for
 genetic
 engineering,
 it
 may
 be
 important
 to
 determine
 (via
 the
 data
 set
 in
 Birnbaum
 et
 al.
 (2003)
 or
 by
 promoter::GUS
 expression
 patterns)
 in
 which
 tissues
 these
 promoters
 are
 predominantly
 expressed,
so
that
their
usefulness
to
drive
transgene
expression
can
be
assessed
in
 the
context
of
particular
biological
questions
and
objectives.


 
 The
identification
of
the
afore‐mentioned
root‐specific
promoters
from
the
primary
 literature,
 along
 with
 the
 various
 other
 candidates
 that
 I
 screened,
 raises
 an
 interesting
 question:
 What
 makes
 a
 promoter
 root‐specific?
 
 The
 answer
 to
 this
 question
 remains
 somewhat
 inconclusive,
 but
 there
 is
 some
 evidence
 suggesting
 that
gene
expression
is
determined,
at
least
in
part,
by
motifs
or
cis‐elements,
within
  
  76
  the
 promoter
 sequence
 of
 regulated
 genes
 (Cai
 et
 al.
 2007).
 In
 plants,
 distinct
 cis‐ regulatory
 elements
 have
 been
 linked
 to
 specific
 responses
 to
 various
 treatments,
 and
analysis
of
the
associated
DNA
sequence
motifs
has
resulted
in
the
elucidation
 of
 a
 number
 of
 promoter
 sequence
 motifs
 related
 to
 stress
 responses,
 developmental
 and
 organ‐specific
 regulation
 (Ma
 &
 Bohnert
 2007).
 
 The
 characteristics
of
some
of
these
root‐specific
cis‐acting
regulatory
DNA
elements
are
 summarized
 in
 Table
 5.
 
 
 In
 my
 in
 silico
 analysis
 of
 the
 4CL1
 promoter
 using
 the
 PLACE
 (Plant
 Cis‐acting
 Regulatory
 DNA
 Elements)
 database,
 almost
 all
 of
 the
 cis‐ regulatory
 motifs
 mentioned
 in
 Table
 5
 were
 present,
 with
 the
 exception
 of
 the
 ACGTROOT1,
TELO
and
SORLIP1AT
elements.

Similarly,
my
analysis
of
the
GSTU19
 promoter
 showed
 that
 it
 contained
 almost
 all
 the
 motifs
 with
 the
 exception
 of
 the
 ACGTROOT1
and
TELO
elements.

These
findings
suggest
that
these
elements
could
 play
 a
 role
 in
 conferring
 the
 root‐specificity
 previously
 described
 for
 these
 genes,
 albeit
at
different
stages
of
plant
growth
and
development.

For
this
reason,
I
chose
 the
largest
possible
promoter
region
sequences
for
my
constructs
that
excluded
any
 upstream
 genes,
 yet
 included
 as
 many
 of
 the
 putative
 root‐specific
 regulatory
 elements
as
possible.
 
 
 
 
 
 
 
 
 
 
 
 
 
  77
  Table
5.
Summary
of
cis­acting
regulatory
DNA
elements
associated
with
root­ specific
gene
expression.
 
 Putative
root­specific
 element
 ARFAT
  ASF1MOTIFCAMV
  OSE1ROOTNODULE
  OSE2ROOTNODULE
  RAV1AAT
  ROOTMOTIFTAPOX1
  SORLIP1AT
  SP8BFIBSP8BIB
  SURECOREATSULTR11
  TELO
  WUSATAg
  
  Sequence
 TGTCTC
  TGACG
  AAAGAT
  CTCTT
  CAACA
  ATATT
  GCCAC
  TACTATT
  GAGAC
  AAACCCTAA
  TTAATAG
  Description
  Reference
  ARF
binding
site
found
in
the
 promoters
of
primary/early
auxin
 response
genes
of
Arabidopsis
thaliana.
 A
xenobiotic
stress‐activated
 transcription
factor
that
binds
to
the
 TGACG
motif
and
is
expressed
 preferentially
in
root
apical
meristems.
 A
consensus
sequence
motif
of
organ‐ specific
elements
characteristic
of
 activated
promoters
found
in
the
 infected
cells
of
root
nodules.
 A
consensus
sequence
motif
of
organ‐ specific
elements
characteristic
of
 activated
promoters
found
in
the
 infected
cells
of
root
nodules.
 Binds
specifically
to
DNA
with
bipartite
 motifs
of
RAV1‐A
(CAACA)
and
 RAV1‐B
(CACCTG).
Expression
levels
of
 RAV1
were
reported
to
be
high
in
 rosette
leaves
and
roots.
 Motif
found
in
rolD
promoters.
The
rol
 A,
B,
C
and
D
genes
have
been
 identified
as
the
main
determinants
of
 the
hairy
root
disease
caused
on
dicots
 by
Agrobacterium
rhizogenes
(Bettini
et
 al.
2003).

 Sequences
Over‐Represented
in
Light‐ Induced
Promoters
(SORLIPs)
in
 Arabidopsis.
Over‐represented
in
light‐ induced
cotyledon
and
root
common
 genes
and
root‐specific
genes.

 A
nuclear
factor
that
binds
to
the
5′
 upstream
regions
of
three
different
 genes
coding
for
major
proteins
of
 sweet
potato
tuberous
roots.
 Core
of
sulfur‐responsive
element
 (SURE)
found
in
the
promoter
of
 SULTR1;1
high‐affinity
sulfate
 transporter
gene
in
Arabidopsis.

 SURE
contains
auxin
response
factor
 (ARF)
binding
sequence
(GAGACA)
 Found
in
the
Arabidopsis
eEF1A
 A1gene
promoter
as
well
as
in
the
5′
 region
of
genes
encoding
components
 of
the
translational
apparatus.
 Implicated
in
the
activation
of
gene
 expression
in
root
primordia
and
root
 meristems.
 Target
sequence
of
WUS
in
the
intron
 of
AGAMOUS
gene
in
Arabidopsis.
 WUSCHEL‐type
homoebox
gene
that
is
 specifically
expressed
in
the
central
 cells
of
a
quiescent
center
in
the
root
 apical
meristem.
  (Inukai
et
al.
2005)
  78
  (Klinedinst
et
al.
 2000),

 (Vieweg
et
al.
 2004)
 (Vieweg
et
al.
 2004)
 (Kagaya
et
al.
 1999)
  (Elmayan
&
Tepfer
 1995)

  (Jiao
et
al.
2005)

  (Ishiguro
&
 Nakamura
1992)
 (Maruyama‐ Nakashita
et
al.
 2005)
  (Tremousaygue
et
 al.
1999)

  (Kamiya
et
al.
 2003)
  I
chose
to
use
a
chemical‐inducible
system
to
turn
on
gene
expression
of
SND1
at
a
 specific
 time
 point
 in
 order
 to
 avoid
 the
 possible
 negative
 effects
 of
 constitutive
 gene
expression.

The
benoxacor‐inducible
system
used
to
induce
SND1
expression
 from
 the
 GSTU19pro­SND1
 construct,
 offers
 an
 advantage
 over
 other
 available
 chemical‐inducible
 gene
 expression
 systems.
 
 My
 results
 showed
 that
 the
 GSTU19
 promoter
was
already
root‐specific
in
its
expression
and
that
this
expression
could
 be
further
induced
by
the
herbicide
safener
causing
an
additional
increase
in
gene
 expression
within
that
organ.


These
results
were
confirmed
by
the
transcriptional
 analysis
 of
 SND1
 and
 its
 downstream
 targets
 in
 T3
 generation
 transgenic
 plants,
 which
caused
a
marked
increase
in
gene
expression
preferentially
in
roots.


 
 These
 results
 show
 that
 when
 driven
 by
 the
 GSTU19
 promoter,
 benoxacor
 may
 in
 fact
be
an
excellent
inducer
of
transgene
expression
but
there
are
some
important
 points
to
consider
(such
as
induction
time,
concentration
and
application
methods)
 when
 examining
 the
 potential
 of
 this
 safener‐induction
 system
 to
 be
 used
 in
 root‐ specific
crop
biotechnology
applications.

The
use
of
herbicidal
safeners
as
chemical‐ inducible
 gene
 expression
 systems
 in
 Arabidopsis,
 was
 previously
 examined
 by
 De
 Veylder
et
al.
(1997)
who
expressed
the
In2­2
promoter
from
maize
in
Arabidopsis
 and
 induced
 its
 expression
 by
 treatment
 with
 benzenesulfonamide
 herbicide
 safeners.


Similar
to
later
studies
done
on
the
induction
of
GSTs
in
Arabidopsis
by
 herbicide
 safeners
 (DeRidder
 &
 Goldsbrough
 2006;
 DeRidder
 et
 al.
 2002),
 GUS
 staining
of
the
In2­2
transgenic
lines
was
visible
exclusively
in
the
root
as
soon
as
24
 hours
after
induction.

In
addition,
the
authors
conducted
a
time‐course
experiment
  
  79
  on
 two‐week‐old
 In2­2
 transgenic
 plants
 containing
 the
 GUS
 reporter
 gene
 by
 transferring
 seedlings
 from
 safener‐free
 media
 to
 media
 containing
 safener
 (50mg/L).

After
transfer
of
the
plants
back
to
safener‐free
medium,
they
found
that
 GUS
staining
disappeared
within
three
days,
indicating
a
strong
correlation
between
 the
 presence
 of
 the
 safener
 and
 In2‐2
 expression.
 They
 also
 found
 that
 prolonged
 induction
by
safeners
(at
a
concentration
of
50mg/L)
resulted
in
inhibition
of
root
 growth,
indicating
that
the
amount
of
time
the
plant
was
exposed
to
the
chemical
at
 that
 concentration
 was
 critical.
 
 Therefore,
 the
 majority
 of
 studies
 involving
 herbicide
safeners
use
an
induction
time
of
24
hours.


It
was
not
immediately
clear
 in
 the
 literature
 why
 the
 standard
 induction
 concentration
 now
 used
 among
 most
 research
 groups
 for
 herbicide
 safeners
 is
 100µM
 but
 it
 appears
 that
 this
 concentration
is
thought
to
serve
as
an
“antidotally
effective
amount”
(Mccutchen
et
 al.
 2008)
 that
 is
 the
 amount
 that
 should
 be
 added
 to
 an
 herbicide
 formulation
 in
 order
to
eliminate
or
reduce
the
phytotoxic
effects
of
the
herbicide
to
certain
crops.



 
 Although
studies
have
suggested
that
herbicide
safeners
could
be
potentially
useful
 as
a
tissue‐specific
transient
expression
system
where
inducible
transcription
in
the
 root
 is
 required,
 there
 have
 been
 no
 studies
 reported
 where
 this
 system
 had
 been
 optimized
 with
 respect
 to
 safener
 concentration
 and
 time
 of
 induction
 within
 the
 context
 of
 driving
 transgene
 expression.
 
 In
 addition
 to
 the
 time
 of
 induction
 and
 concentration
 of
 reagent,
 the
 type
 of
 application
 method
 may
 be
 an
 important
 component
 of
 a
 safener‐inducible
 gene
 expression
 system.
 
 For
 example,
 previous
 studies
 have
 shown
 that
 adding
 the
 safeners
 to
 hydroponically
 grown
 plants
  
  80
  resulted
in
consistent
induction
patterns
among
all
safeners
tested,
whereas,
foliar
 application
did
not
induce
any
GUS
activity
(De
Veylder
et
al.
1997).

Later
studies
 using
 three‐week‐old
 Arabidopsis
 plants
 treated
 with
 safeners
 (100µM)
 by
 foliar
 application
required
treatment
once
per
day
for
four
consecutive
days
to
achieve
the
 desired
 level
 of
 gene
 induction
 (DeRidder
 &
 Goldsbrough
 2006).
 
 These
 results
 provide
 some
 insight
 into
 the
 efficacy
 of
 a
 particular
 application
 method
 with
 respect
 to
 the
 time
 of
 induction
 of
 the
 inducible
 promoter.
 
 Absorption
 of
 the
 safener
 via
 the
 roots
 seems
 to
 result
 in
 a
 much
 faster
 and
 more
 direct
 induction
 whereas
 to
 achieve
 similar
 results
 via
 foliar
 application
 longer
 exposure
 to
 the
 inducer
 at
 similar
 concentrations
 is
 required.
 
 Further
 studies
 are
 needed
 to
 optimize
this
system
if
safeners
are
to
be
more
widely
used
as
root‐specific
chemical
 induction
systems.


 
 The
reverse
transcription
PCR
analysis
in
flower,
leaf,
stem
and
roots
also
detected
 AtSND1
 expression
 exclusively
 in
 stems
 of
 four‐week‐oldplants.
 
 Given
 that
 the
 lignin
 biosynthetic
 pathway
 seems
 to
 be
 regulated
 by
 a
 network
 of
 TFs,
 such
 as
 SND1,
it
is
important
to
consider
the
implications
of
introducing
a
regulatory
gene
 into
 an
 environment
 in
 which
 it
 is
 usually
 not
 expressed.
 
 
 Previous
 studies
 have
 shown
 that,
 in
 roots,
 the
 expression
 level
 of
 a
 cohort
 of
 TF
 genes
 working
 downstream
 of
 SND1,
 as
 well
 as
 of
 SND1
 itself,
 was
 largely
 restricted
 to
 the
 developing
secondary
xylem
but
this
expression
was
at
very
low
levels
compared
to
 their
 expression
 in
 stems
 (Zhong
 
 2008).
 
 At
 the
 outset
 of
 this
 project,
 it
 was
 not
 known
 how
 root‐specific
 overexpression
 of
 SND1
 might
 affect
 secondary
 cell
 wall
  
  81
  thickening
in
roots,
or
if
the
regulatory
network
activated
by
SND1
would
function
 the
 same
 way
 in
 this
 organ
 as
 it
 does
 in
 stems.
 
 
 It
 is
 possible
 that
 transcriptional
 activators,
 such
 as
 SND1
 and
 its
 downstream
 targets,
 might
 be
 able
 to
 regulate
 secondary
cell
wall
formation
in
non‐sclerenchymatous
tissues
of
the
growing
plant
 by
 acting
 as
 repressors
 of
 gene
 expression
 in
 order
 to
 prevent
 any
 pleiotropic
 effects
 associated
 with
 the
 ectopic
 expression
 of
 genes
 controlling
 and
 involved
 in
 lignin
biosynthesis.

However,
only
a
limited
number
of
expression
repressors
have
 been
identified
in
plants
thus
far.



 
 
 

 Secondary
 wall
 formation
 is
 a
 highly
 coordinated
 process
 that
 results
 from
 the
 subsequent
deposition
of
cellulose,
hemicelluloses
and
lignin
as
soon
as
primary
cell
 growth
 has
 ceased.
 The
 proportion
 of
 each
 of
 these
 major
 components
 is
 highly
 variable
depending
on
the
climate,
geographic
location,
species,
age
and
part
of
the
 plant.


Knowledge
of
how
the
coordinated
regulation
of
genes
leading
to
secondary
 cell
wall
formation
and
how
this
regulation
leads
to
the
relative
composition
of
the
 main
 constituents,
 is
 still
 growing
 (Ko
 et
 al.
 2009).
 
 However,
 there
 are
 still
 some
 gaps
 in
 our
 understanding
 and
 as
 a
 result,
 it
 was
 difficult
 to
 predict
 how
 SND1
 overexpression
would
influence
lignin
deposition
in
roots,
a
tissue
in
which
only
low
 levels
 of
 the
 TFs
 involved
 in
 regulating
 secondary
 cell
 wall
 formation
 have
 been
 previously
 described
 (Zhong
 et
 al.
 2008).
 
 I
 created
 two
 different
 root‐specific
 overexpression
constructs
(4CL1pro­SND1
and
GSTU19pro­SND1)
in
Arabidopsis
and
 results
from
the
transcriptional
analysis
of
SND1
gene
expression
in
T2
generation
 plants
confirmed
that
SND1
was
indeed
overexpressed
in
the
roots
in
almost
all
of
  
  82
  the
lines
analyzed
within
each
overexpression
construct.

Transcriptional
analysis
of
 SND1
 in
 T3
 generation
 transgenic
 plant
 lines,
 however,
 showed
 overexpression
 in
 both
roots
and
shoots
compared
to
empty
vector
control
lines,
indicating
transgene
 expression
was
observed
in
both
tissues
and
that
expression
in
the
roots
was
only
 slightly
 higher
 in
 shoots.
 
 The
 promoters
 selected
 to
 drive
 transgene
 expression
 (4CL1pro
and
GSTU19pro)
are
not
necessarily
“root‐specific”
in
the
sense
that
their
 native
 expression
 pattern
 indicate
 that
 they
 are
 expressed
 elsewhere
 in
 the
 plant,
 which
may
be
why
SND1
was
seen
to
be
overexpressed
in
shoots
as
well
as
roots
in
 transgenic
 plants.
 
 On
 the
 other
 hand,
 given
 that
 the
 native
 expression
 analysis
 in
 different
plant
organs
in
addition
to
the
data
obtained
from
Genevestigator,
showed
 that
 SND1
 was
 expressed
 somewhat
 exclusively
 in
 stems,
 the
 fact
 that
 overexpression
 of
 SND1
 was
 seen
 in
 roots
 of
 transgenic
 lines
 indicates
 that
 the
 promoters
 are
 functioning
 in
 their
 ability
 to
 drive
 expression
 of
 the
 transgene
 in
 roots,
albeit
not
in
a
comparatively
restricted
manner.
 
 SND1
 has
 been
 previously
 shown
 to
 upregulate
 the
 expression
 of
 several
 transcription
 factors
 that
 are
 highly
expressed
 in
fibres
during
 secondary
cell
 wall
 biosynthesis
 (Zhong
 et
 al.
 2006).
 
 Therefore,
 it
 was
 not
 surprising
 that
 my
 results
 indicated
an
increase
in
gene
expression
(specifically
in
roots)
of
the
transcription
 factors
 acting
 downstream
 of
 SND1
 (MYB46,
 SND3,
 MYB103
 and
 KNAT7).
 
 Given
 that
these
transcription
factors
have
been
previously
shown
to
be
expressed
at
very
 low
levels
in
roots
(Zhong
et
al.
2006;
Zhong
et
al.
2008),
my
data
further
confirms
 that
 the
 4CL1pro­SND1
 and
 GSTU19pro­SND1
 constructs
 are
 behaving
 in
 a
 root‐  
  83
  specific
 manner.
 
 These
 results
 correlate
 with
 the
 previously
 characterized
 hierarchical
 organization
 of
 these
 transcription
 factors
 acting
 as
 direct
 targets
 of
 SND1,
 therefore
 it
 seems
 as
 though
 the
 interactions
 previously
 described
 in
 aerial
 tissues,
behave
in
a
similar
fashion
in
root
tissues
(Ko
et
al.
2009;
Zhong
et
al.
2008).


 
 However,
 there
 is
 still
 much
 that
 we
 do
 not
 know
 about
 the
 organization,
 association
 and
 interrelation
 of
 the
 entire
 regulatory
 cascade
 involved
 in
 the
 activation
 and
 regulation
 of
 lignin
 biosynthetic
 genes
 during
 secondary
 cell
 wall
 formation
in
stems,
let
alone
in
the
roots.
This
could
be
problematic
when
trying
to
 determine
 and
 interpret
 what
 is
 happening
 downstream
 of
 these
 master
 transcriptional
switches,
such
as
SND1
and
MYB46,
and
how
the
lignin
biosynthetic
 pathway
 is
 being
 specifically
 altered
 in
 roots
 of
 transgenic
 plants,
 an
 environment
 within
which
these
TFs
do
not
normally
operate.


The
growing
amount
of
data
(and
 many
 different
 interpretations
 of
 this
 data)
 being
 generated
 and
 subsequently
 presented
in
the
literature
is
usually
studied
within
stems
and
leaf
protoplast
and
is
 often
 confusing
 and
 sometimes
 conflicting.
 
 Further
 studies
 are
 needed
 to
 characterize
 all
 the
 putative
 TFs
 involved
 in
 regulating
 secondary
 cell
 wall
 formation,
 in
 addition
 to
 studies
 aimed
 at
 determining
 associations
 between
 these
 factors
 and
 with
 biosynthetic
 genes.
 
 These
 studies
 should
 clarify
 some
 of
 the
 missing
links
in
our
current
knowledge,
at
least
within
aerial
tissues.

Significantly
 more
work
would
be
required
in
Arabidopsis
root
systems
in
order
to
determine
the
 effects
 of
 overexpressing
 regulatory
 factors
 involved
 in
 secondary
 cell
 wall
 formation
 in
 tissues
 not
 normally
 heavily
 lignified.
 
 This
 is
 an
 important
  
  84
  consideration
for
future
attempts
at
inducing
hyper‐lignification
in
Arabidopsis
root
 systems,
 before
 attempts
 can
 be
 made
 at
 increasing
 soil
 carbon
 stocks
 in
 a
 large‐ scale
crop
system
through
similar
approaches
and
methods.


 
 The
genes
involved
in
cellulose,
xylan,
and
lignin
biosynthesis
need
to
be
turned
on
 in
order
to
make
lignified
secondary
cell
walls
in
Arabidopsis.

The
RT‐PCR
analysis
 of
 three
 phenylpropanoid
 pathway
 enzymes
 leading
 to
 the
 production
 of
 monolignols
 (4CL1,
 CCR
 and
 COMT)
 showed
 no
 observable
 difference
 in
 gene
 expression
among
these
lignin
biosynthetic
genes
or
among
tissue
types
(root
and
 shoot).


Several
possibilities
could
explain
this
finding,
despite
the
overexpression
 of
SND1
and
its
direct
targets:
(i)
they
are
not
involved
in
the
transcriptional
control
 of
 these
 particular
 lignin
 biosynthetic
 genes,
 (ii)
 they
 require
 the
 involvement
 of
 other
 transcription
 factor(s)
 to
 function,
 or
 (iii)
 they
 are
 not
 directly
 involved
 in
 secondary
wall
formation
(Ko
et
al.
2009).


The
first
explanation
could
certainly
be
 true
 where
 SND3
 and
 MYB103
 are
 concerned,
 since
 they
 were
 recently
 shown
 to
 induce
 the
 GUS
 reporter
 gene
 expression
 driven
 by
 the
 CesA8
 promoter,
 from
 a
 cellulose
synthase
gene
required
for
cellulose
synthesis
during
secondary
cell
wall
 formation
 (Zhong
 et
 al.
 2008).
 This
 proves
 that
 SND1
 is
 involved
 in
 regulating
 certain
 genes
 involved
 in
 other
 aspects
 of
 the
 secondary
 cell
 wall
 biosynthetic
 program,
in
addition
to
that
of
lignin.

On
the
other
hand,
the
MYB46
transcription
 factor
was
shown
to
be
a
direct
target
of
SND1
and
both
TFs
were
previously
shown
 to
be
capable
of
turning
on
a
whole
set
of
genes
involved
in
secondary
wall
synthesis
 in
 general
 (Zhong
 et
 al.
 2007b;
 Ko
 et
 al.
 2009).
 
 Therefore,
 it
 is
 puzzling
 that
 overexpression
 of
 this
 gene
 did
 not
 activate
 key
 lignin
 biosynthetic
 enzymes
 in
 
  85
  either
 the
 root
 or
 shoot,
 where
 previous
 studies
 have
 shown
 this
 to
 occur.
 
 For
 example,
 MYB85
 gene
 expression
 was
 previously
 shown
 to
 be
 upregulated
 by
 MYB46
 overexpression,
 and
 MYB85
 was
 shown
 to
 be
 able
 to
 induce
 expression
 of
 the
 GUS
 reporter
 gene,
 when
 driven
 by
 the
 4CL1
 promoter
 in
 leaf
 protoplasts.


 Studies
have
shown
that
overexpression
of
MYB85
led
to
ectopic
deposition
of
lignin
 in
epidermal
and
cortical
cells
in
stems
(Zhong
et
al
2007a;
Zhong
et
al.
2006;
Zhong
 et
al.
2008).

Therefore,
since
MYB46
has
been
shown
to
be
a
direct
target
of
SND1,
I
 am
 unable
 to
 explain
 (within
 the
 current
 model
 of
 this
 SND1‐mediated
 regulatory
 network)
why
the
overexpression
of
SND1
and
MYB46
did
not
specifically
cause
the
 4CL1
gene
to
be
turned
on
through
induction
of
the
4CL1
promoter
by
MYB85.

The
 gene
 expression
 level
 of
 MYB85
 was
 not
 examined
 in
 the
 roots
 of
 my
 transgenic
 lines,
 therefore
 transcriptional
 analysis
 of
 this
 gene
 by
 RT‐PCR,
 could
 provide
 further
 information
 into
 determining
 why
 the
 4CL1
 gene
 was
 not
 turned
 on
 in
 response
 to
 SND1
 overexpression.
 
 Nevertheless,
 there
 are
 several
 other
 transcription
factors
that
have
been
previously
reported
to
regulate
secondary
wall
 biosynthesis
 including,
 KNAT7,
 MYB52,
 MYB54,
 MYB58
 and
 MYB63.
 
 
 KNAT7,
 for
 example,
was
overexpressed
in
the
roots
of
my
transgenic
plants
but
did
not
seem
to
 influence
the
secondary
lignin
biosynthetic
genes
tested
here.

This
could
be
because
 KNAT7
is
not
involved
in
activating
lignin
biosynthetic
genes
directly.

To
test
this
 theory,
the
characterization
of
KNAT7
using
reverse
genetics
approaches
along
with
 the
 yeast
 two‐hybrid
 system
 for
 determining
 protein
 interactions,
 may
 provide
 some
 insight
 into
 its
 specific
 function
 and
 interacting
 partners.
 
 In
 short,
 TFs
 in
 general
have
diverse
roles
in
regulating
gene
transcription.

For
instance,
they
may
  
  86
  act
as
part
of
a
complex
with
other
TFs
or
regulatory
proteins,
which
together
might
 be
 involved
 in
 directly
 regulating
 gene
 expression
 in
 a
 particular
 biosynthetic
 pathway.

Others,
however,
might
be
involved
in
enhancing
or
fine‐tuning
the
level
 of
expression
of
different
metabolic
pathway
genes
(Zhong
et
al.
2008).


 
 Interest
 in
 lignin
 biosynthesis
 and
 lignin
 deposition
 is
 mainly
 due
 to
 the
 extensive
 involvement
 of
 lignin
 in
 plant
 biology
 (Boudet
 et
 al.
 2003;
 Humphreys
 &
 Chapple
 2002).

Lignin
can
be
defined
two
ways:
1)
from
a
chemical
point
of
 view
(chemical
 composition
and
structure)
or
2)
from
 a
functional
point
of
view
(what
lignin
does
 within
the
 plant)
(Hatfield
&
Fukushima
2005).

Regardless
of
these
definitions,
it
is
 important
 to
 be
 able
 to
 determine
 the
 concentration
 of
 lignin
 within
 a
 broad
 assortment
 of
 cell
 wall
 varieties.
 
 One
 would
 think
 that
 lignin
 would
 be
 relatively
 easy
to
measure,
given
that
it
is
somewhat
resistant
to
 both
chemical
and
biological
 degradation.

However,
there
have
been
several
methods
and
techniques
that
have
 been
developed
and
adapted
throughout
 the
years
to
quantitatively
determine
total
 lignin
 content
 and
 composition
 in
 different
 types
 of
 plant
 samples,
 yet
 not
 one
 of
 them
 has
 been
 deemed
 as
 a
 standard
 clear‐cut
 method
 for
 all
 samples
 (Hatfield
 &
 Fukushima
 2005).
 Worth
 mentioning,
 however,
 for
 the
 determination
 of
 lignin
 content
 in
 plant
 samples,
 are
 non‐invasive
 approaches
 such
 as:
 near
 infrared
 spectroscopy
 (NIRS)
 and
 nuclear
 magnetic
 resonance
 spectroscopy
 (NMR).
 These
 methods
 of
 lignin
 content
 determination
 offer
 an
 advantage
 over
 more
 invasive
 methods
in
that
they
ultimately
leave
the
lignin
in
the
sample
chemically
unaltered
 (Hatfield
 &
 Fukushima
 2005).
 
 Alternatively,
 two
 procedures
 (thioglycolate
 and
  
  87
  acetyl
 bromide)
 rely
 on
 the
 solubilization
 of
 lignin
 in
 an
 appropriate
 solvent
 whereby
 the
 lignin
 in
 solution
 can
 be
 measured
 (Hatfield
 &
 Fukushima
 2005).

 Lastly,
 various
 methods
 have
 been
 proposed
 using
 mineral
 acids
 to
 solubilize
 and
 hydrolyze
carbohydrates
leaving
the
lignin
residue
to
be
measured
and
determined
 gravimetrically,
such
as
the
Klason
lignin
method
(Hatfield
&
Fukushima
2005).

Is
 seems
 that
 the
 most
 commonly
 used
 method
 for
 determining
 lignin
 is
 the
 Klason
 lignin
or
72%
(v/v)
H2SO4
acid
procedure.

 
 Given
the
relatively
low
amount
of
lignin
present
in
roots
to
begin
with,
as
well
as
 the
limited
amount
of
root
material
available
working
in
the
Arabidopsis
system,
it
 was
 important
 to
 be
 prudent
 and
 judicial
 with
 the
 choice
 of
 lignin
 content
 determination
method.


Results
from
the
acetyl
bromide
analysis
of
soluble
lignin
 content,
 showed
 a
 marked
 decrease
 in
 total
 lignin
 content
 (~40‐50%)
 in
 both
 GSTU19pro­SND1
lines
but
only
one
of
the
4CL1pro­SND1
lines.


The
Klason
lignin
 analysis
 supported
 the
 data
 obtained
 from
 the
 acetyl
 bromide‐based
 method
 by
 confirming
 a
 decrease
 in
 insoluble
 lignin
 content
 in
 the
 GSTU19pro­SND1
 overexpression
line.

On
the
other
hand,
one
4CL1pro­SND1
line
in
each
of
the
lignin
 content
 analyses
 showed
 negligible
 changes
 in
 lignin
 content.
 
 
 Nevertheless,
 I
 reasoned
that
the
decreases
seen
in
lignin
content
in
the
majority
of
lines
analyzed
 (and
 also
 lack
 of
 change
 in
 gene
 expression
 of
 indicative
 lignin
 biosynthetic
 enzymes),
 could
 be
 a
 result
 of
 carbon
 reallocation
 to
 a
 different
 area
 of
 carbon
 metabolism
(such
as
production
of
cellulose
and
starch).


Results
from
the
cellulose
 and
starch
content
analyses,
disproved
this
theory
by
showing
a
similar
decrease
in
  
  88
  cellulose
and
hemicellulose
content
in
the
GSTU19pro­SND1
line
analyzed.


I
should
 note,
that
results
from
the
cellulose,
starch
and
Klason
lignin
analyses
were
absolute
 values
 from
 a
 single
 biological
 replicate
 making
 the
 data
 somewhat
 unreliable,
 however,
 given
 that
 they
 correlate
 to
 certain
 degree
 with
 results
 seen
 using
 the
 acetyl
bromide‐based
method,
I
have
included
them
in
this
thesis.


 
 An
 overall
 trend
 of
 decreased
 cell
 wall
 composition
 (lignin,
 cellulose
 and
 hemicellulose)
 was
 seen
 in
 both
 SND1
 overexpression
 constructs
 analyzed.


 Previous
 studies
 have
 shown
 that
 although
 SND1
 overexpression
 induces
 ectopic
 secondary
 wall
 deposition
 in
 cells
 that
 are
 normally
 not
 lignified,
 excess
 SND1
 apparently
inhibits
normal
secondary
wall
thickening
in
fibres
(Zhong
et
al.
2006).

 In
 these
 studies,
 SND1
 overexpression
 was
 seen
 to
 induce
 secondary
 cell
 wall
 production
 in
 many
 parenchyma
 cells
 in
 leaves
 and
 floral
 organs
 as
 well
 as
 epidermal
 cells
 in
 stems;
 however,
 ectopic
 secondary
 wall
 deposition
 was
 seldom
 seen
 in
 the
 parenchyma
 cells
 of
 other
 organs.
 
 Moreover,
 SND1
 overexpressors
 showed
 that
 ectopic
 secondary
 wall
 thickening
 was
 rarely
 observed
 in
 the
 epidermal
 cells
 of
 hypocotyls
 and
 cortical
 cells
 of
 roots
 but
 was
 not
 seen
 in
 other
 root
cell
types
(Zhong
et
al.
2006).

This
finding
suggests
that
different
cell
types
in
 different
 organs
 might
 exhibit
 differential
 competence
 to
 induction
 of
 secondary
 wall
 thickening
 by
 SND1.
 
 Equally,
 this
 differential
 induction
 could
 be
 a
 case
 of
 substrate
 availability,
 meaning
 that
 the
 required
 precursors
 for
 monolignol
 biosynthesis
 may
 be
 in
 short
 supply
 in
 the
 root,
 given
 that
 Arabidopsis
 root
 tissue
 does
 not
 normally
 contain
 high
 levels
 of
 lignin.
 
 Either
 way,
 any
 of
 these
 reasons
  
  89
  could
account
for
the
fact
that
overexpression
of
SND1
in
the
root‐specific
(4CL1pro­ SND1)
 and
 inducible
 (GSTU19pro­SND1)
 constructs
 did
 not
 result
 in
 the
 direct
 activation
of
lignin
biosynthetic
genes
as
demonstrated
using
the
RT‐PCR
analysis,
 which
 should
 have
 resulted
 in
 an
 increase
 in
 root
 lignin
 content
 instead
 of
 the
 observed
decrease
in
lignin
content.



 
 As
 for
 the
 other
 cell
 wall
 constituents
 analyzed,
 Ko
 et
 al.
 (2007)
 reported
 that
 cellulose
compositions
of
the
cell
wall
were
decreased
in
the
inflorescent
stems
and
 roots
of
plants
overexpressing
SND1
driven
by
the
CaMV35S
promoter,
most
likely
 resulting
 from
 defects
 in
 xylary
 fibre
 formation.
 
 However,
 my
 results
 showed
 an
 increase
 in
 the
 relative
 gene
 expression
 of
 SND3
 and
 MYB103
 as
 seen
 in
 the
 transcriptional
 analysis
 of
 T3
 generation
 transgenic
 plants,
 which
 should
 have
 resulted
in
an
increase
in
cellulose
content
given
that
these
downstream
targets
of
 SND1
 were
 recently
 shown
 to
 induce
 the
 GUS
 reporter
 gene
 expression
 driven
 by
 the
CesA8
promoter
(Zhong
et
al.
2008).
Instead,
I
generally
observed
a
decrease
in
 cellulose
and
hemicellulose
content,
similar
to
that
observed
for
lignin.


 
 Overexpression
 of
 mRNA
 can
 sometimes
 lead
 to
 a
 drastic
 reduction
 in
 the
 level
 of
 expression
of
the
endogenous
genes
concerned,
i.e.
host
genes
can
be
silenced
as
a
 consequence
of
the
presence
of
a
homologous
transgene,
thus
limiting
the
potential
 application
 of
 genetic
 transformation;
 a
 phenomenon
 called
 co‐suppression
 (Vaucheret
et
al.
2001).

One
way
of
understanding
this
phenomenon
is
that
when
 RNA
 transcripts
 accumulate
 beyond
 a
 critical
 threshold,
 they
 are
 selectively
  
  90
  degraded
 by
 ribonucleases
 (RNases),
 a
 type
 of
 nuclease
 that
 catalyzes
 the
 degradation
of
RNA.

An
accumulation
of
elevated
levels
of
mRNAs
might
lead
to
the
 production
 of
 abnormal
 sense
 RNA
 transcripts
 of
 the
 transgene
 (Vaucheret
 et
 al.
 2001)
and
accumulation
of
these
anomalous
RNA
transcripts
is
proposed
to
activate
 the
 RNA‐dependent
 RNA
 polymerase,
 which
 transcribes
 the
 RNA
 transcripts
 to
 produce
 antisense
 RNA.
 The
 antisense
 RNA
 transcripts
 then
 bind
 to
 the
 accumulated
normal
and
abnormal
RNA
transcripts
of
the
transgene
as
well
as
the
 endogenous
 gene,
 producing
 RNA
 duplexes
 that
 are
 then
 targeted
 by
 double‐ stranded
RNA
specific
RNases.

This
often
leads
to
a
radical
reduction
in
the
level
of
 transgene
 expression
 as
 well
 as
 the
 expression
 of
 the
 endogenous
 gene
 and
 sometimes
homologous
genes
as
well.

This
series
of
events
are
collectively
referred
 to
 as
 gene
 silencing
 and
 are
 defined
 by
 predominantly
 taking
 place
 at
 the
 post‐ transcriptional
 level,
 where
 RNA
 does
 not
 accumulate
 even
 though
 transcription
 occurs
(Vaucheret
et
al.
2001).

The
degradation
of
RNA
via
gene
silencing
may
be
 why
I
observed
a
decrease
in
total
lignin
content
in
my
transgenic
plants
but
it
does
 not
explain
why
I
observed
an
increase
in
mRNA
transcripts
in
my
transgenic
lines.

 One
reason
for
this
could
be
because
the
transcriptional
analysis
was
performed
on
 three‐week‐old
plants
and
the
lignin
analysis
was
performed
on
mature
plants
that
 were
roughly
eight‐weeks
old.

It
is
possible
that
gene
silencing
is
occurring
during
 secondary
cell
wall
formation
in
plants
that
are
older
then
three‐weeks.
Using
RT‐ PCR
to
analyze
SND1
and
its
targeted
TFs
in
the
root
tissue
from
transgenic
lines
at
 different
developmental
stages
could
test
this
hypothesis.


 
  
  91
  An
 alternative
 possibility
 for
 this
 observed
 difference
 in
 increased
 mRNA
 versus
 decreased
lignin
could
be
some
kind
of
regulation
at
the
translational
level,
but
the
 mechanisms
for
this
type
of
control
are
poorly
understood.

It
is
clear
that
there
are
 many
mechanisms
in
place
to
control
and
maintain
normal
levels
of
plant
cell
wall
 constituent
 biosynthesis
 and
 deposition.
 
 This
 presents
 a
 significant
 challenge
 to
 overcome
 when
 designing
 and
 engineering
 genetic
 constructs
 for
 crop
 improvement.
 
 As
 more
 knowledge
 is
 gained
 regarding
 the
 mechanisms
 that
 regulate
transcription
of
secondary
cell
wall
components
as
a
whole
(as
well
as
the
 coordinated
 expression
 of
 the
 cohort
 of
 transcription
 factors
 and
 proteins
 regulating
 the
 lignin
 biosynthetic
 pathway),
 we
 will
 undoubtedly
 be
 able
 to
 gain
 new
 insight
 that
 will
 help
 us
 to
 develop
 more
 complex
 and
 fine‐tuned
 gene
 expression
 systems
 that
 could
 complement
 or
 counteract
 any
 other
 regulatory
 mechanisms
present
that
may
prevent
us
from
achieving
the
desired
end‐product
or
 phenotype.

 
 It
 is
 imperative
 to
 the
 process
 of
 genetic
 engineering
 for
 agricultural
 purposes
 to
 drive
transgene
expression
in
a
manner
that
evades
health
costs
to
the
plant
caused
 by
the
constitutive
expression
of
target
genes.

It
was
therefore
important
to
survey
 a
variety
of
different
key
plant
physiological
traits
that
could
have
a
dire
impact
on
 the
 efficacy
 of
 crop
 production.
 
 Overexpression
 of
 key
 genes
 involved
 in
 normal
 plant
 growth
 and
 development,
 such
 as
 secondary
 cell
 wall
 pathways,
 could
 be
 implicated
in
normal
agricultural
activities
such
as
seed
production
and
crop
yield,
 thus
 resulting
 in
 major
 economic
 consequences
 if
 altered
 inappropriately.
 
 The
 phenotypic
analysis
of
seed‐related
traits
revealed
that
overexpression
of
SND1
did
 
  92
  not
 cause
 any
 undesirable
 pleiotropic
 effects
 in
 seed
 production
 and/or
 viability
 among
 my
 transgenic
 plants.
 
 Given
 that
 GSTU19pro­SND1
 lines
 were
 induced
 by
 herbicide
 safener
 at
 four‐weeks
 post‐flowering,
 it
 was
 expected
 that
 these
 lines
 would
 not
 result
 in
 a
 phenotype
 involving
 seed‐related
 traits.
 
 This
 data
 supports
 my
 previous
 analyses
 showing
 that
 both
 construct
 promoters
 were
 shown
 to
 be
 root‐specific,
 which
 means
 that
 SND1
 overexpression
 in
 the
 roots
 should
 not
 activate
gene
expression
of
secondary
cell
wall
biosynthetic
genes
in
seeds.
 
 To
determine
whether
overexpression
of
SND1
in
roots
caused
any
variation
in
root
 architecture,
 lateral
 root
 density
 (LRD)
 was
 analyzed
 for
 two
 lines
 in
 each
 constructs
and
showed
an
increase
in
LRD
in
three
out
of
the
four
lines
analyzed.

It
 was
interesting
that
the
transgenic
lines
showing
an
increase
in
LRD
were
the
same
 transgenic
 lines
 corresponding
 to
 a
 decrease
 in
 total
 lignin
 content,
 as
 seen
 in
 the
 chemical
lignin
analysis.

It has been previously shown, that SND1
is
a
member
of
the
 NAC
 domain
 protein
 family,
 which
 comprises
 approximately
 100
 genes
 in
 the
 Arabidopsis
genome
and
function
as
plant‐specific
transcriptional
factors.

To
date,
 only
a
small
number
of
NAC
domain
genes
have
been
characterized
and
NAC
domain
 proteins
 have
 been
 implicated
 in
 a
 wide
 variety
 of
 processes,
 including
 the
 establishment
 of
 the
 shoot
 apical
 meristem,
 the
 signaling
 pathway
 involved
 in
 abiotic
 stress,
 defense
 responses
 and
 lateral
 root
 formation.
 
 Specifically,
 AtNAC1

 (At1g56010)
 has
 been
 shown
 to
 mediate
 auxin
 signaling
 and
 promote
 lateral
 root
 formation
(Xie
et
al.
2000).

A
multiple
sequence
alignment
of
various
NAC
domain
 genes,
from
a
previous
study,
has
shown
that
AtNAC1
is
a
distant
relative
of
SND1
 (Zhong
et
al.
2006).

Plant
roots
have
a
distinct
organization
that
is
fundamental
to
 
  93
  the
 formation
 of
 lateral
 roots.
 
 The
 outer
 tissues
 of
 dicot
 plant
 roots
 (epidermis,
 cortex,
and
endodermis)
are
organized
into
separate
concentric
 layers
whereas
the
 vascular
 tissues
 of
 the
 central
 stele
 have
 a
 more
 bilateral
 symmetry
 (Parizot
 et
 al.
 2008).


The
outermost
layer
of
the
stele,
known
as
the
pericycle,
is
composed
of
two
 different
 cell
 types:
 one
 subset
 is
 associated
 with
 the
 xylem,
 whereas
 the
 other
 is
 associated
 with
 the
 phloem.
 
 The
 former
 has
 the
 strong
 capability
 to
 initiate
 cell
 division
 but
 the
 latter
 appears
 to
 remain
 inactive
 (Parizot
 et
 al.
 2008).
 
 
 The
 formation
of
lateral
roots
is
a
result
of
a
subset
of
pericycle
cells
(called
the
pericycle
 founder
 cells)
 that
 are
 positioned
 at
 the
 xylem
 poles
 within
 parent
 root
 tissues.
 Subsequently,
 the
 mature
 pericycle
 cells
 form
 lateral
 root
 primordium
 (LRP)
 via
 dedifferentiation,
which
then
undergoes
consistent
cell
divisions
to
generate
a
well‐ organized
LRP.

Cell
expansion
causes
the
LRP
to
emerge
from
the
parent
root,
and
 the
 lateral
 root
 meristem
 becomes
 activated
 resulting
 in
 continued
 growth
 of
 the
 lateral
 root
 (Lee
 et
 al.
 2009).
 
 The
 positioning
 of
 the
 pericycle
 founder
 cells
 to
 the
 xylem
poles
may
provide
a
testable
hypothesis
regarding
the
decrease
in
lignin
and
 increase
in
LRD
in
transgenic
lines
overexpressing
SND1
and
its
downstream
target
 MYB46.

Previously,
ectopic
secondary
wall
thickening
in
the
parenchymatous
cells
 of
leaves,
floral
organs
and
inflorescence
stems
was
seen
in
MYB46
overexpressors
 (Ko
et
al.
2009).

In
addition,
SND1
overexpression
showed
a
small
increase
in
the
 wall
 thickness
 of
 vessels
 (Zhong
 
 2006).
 
 Although
 I
 did
 not
 specifically
 look
 at
 ectopic
secondary
wall
thickening
in
my
transgenic
lines,
a
possible
increase
in
wall
 thickening
due
to
SND1
and
MYB46
overexpression
in
root
xylem
vessels
may
have
 caused
 a
 movement
 in
 auxin
 pools
 near
 the
 xylem
 poles,
 causing
 lateral
 roots
 to
  
  94
  form.

One
way
to
test
this
hypothesis
would
be
to:
i)
to
confirm
that
secondary
wall
 thickness
 was
 in
 fact
 perturbed
 and
 ii)
 to
 transform
 the
 SND1
 root‐specific
 overexpression
 constructs
 (GSTU19pro­SND1
 and
 4CL1pro­SND1)
 with
 the
 promoter‐marker
 gene
 fusion
 DR5::GUS
 activated
 by
 auxins
 to
 visualize
 auxin
 response
patterns
in
the
root.


 
 Another
 possible
 explanation
 for
 this
 increase
 in
 lateral
 root
 density
 found
 in
 the
 GSTU19pro­SND1
 transgenic
 lines
 in
 particular,
 could
 be
 due
 to
 the
 fact
 that,
 in
 addition
to
high
levels
of
expression
in
the
stele
and
endo‐cortex,
GSTU19
was
found
 to
have
an
even
higher
level
of
expression
in
lateral
root
cap
tissues
as
seen
by
the
 Genevestigator
heat
map
that
I
generated
and
the
relative
probe
intensities
from
the
 Birnbaum
and
Benfey
dataset
(2004).

The
root
cap
has
been
shown
to
be
a
complex
 and
 dynamic
 plant
 organ.
 
 Root
 caps
 are
 responsible
 for
 sensing
 and
 transmitting
 environmental
 signals,
 synthesizing
 and
 secreting
 small
 molecules
 and
 macromolecules,
and
in
some
species
shedding
metabolically
active
cells
(Tsugeki
&
 Federoff
1999).

One
study
reported
the
identification
and
use
of
a
root
cap‐specific
 promoter
to
genetically
destroy
root
caps
by
directing
root
cap‐specific
expression
 of
 a
 diphtheria
 toxin
 A‐chain
 gene.
 
 The
 roots
 of
 these
 transgenic
 plants
had
 more
 highly
 branched
 lateral
 roots
 than
 those
 of
 wild‐type
 control
 plants.
 
 
 Root
 cap
 ablation
 (where
 individual
 cells
 are
 destroyed
 for
 experimental
 purposes)
 in
 this
 study
 was
 shown
 to
 alter
 root
 architecture
 both
 by
 inhibiting
 root
 meristematic
 activity
 and
 by
 stimulating
 lateral
 root
 initiation.
 
 These
 observations
 implied
 that
  
  95
  root
caps
contain
essential
components
of
the
signaling
system
that
determines
root
 architecture
(Tsugeki
&
Federoff
1999).


 If
 SND1
 overexpression
 in
 GSTU19pro­SND1
 lines
 caused
 a
 similar
 ablation
 or
 alteration
in
lateral
root
caps
this
could
certainly
explain
the
observed
increases
in
 LRD
seen
among
the
two
transgenic
lines
analyzed
for
this
particular
construct.

One
 way
 to
 test
 this
 hypothesis
 would
 be
 to
 visualize
 longitudinal
 sections
 of
 primary
 root
 tips
 using
 electon
 or
 confocal
 microscopy
 in
 order
 to
 determine
 the
 differentiation
 of
 root
 cells
 in
 my
 transgenic
 and
 empty
 vector
 control
 plants.


 Another
 interesting
 observation
 from
 Tsugeki
 &
 Federoff
 (1999)
 was
 that
 despite
 the
 abnormal
 root
 structure
 of
 their
 transgenic
 lines,
 the
 appearance
 of
 the
 aerial
 parts
of
the
transgenic
plants
was
normal
on
both
MS
agar
medium
and
in
soil.


The
 normal
aerial
phenotype
was
also
observed
in
my
transgenic
lines,
including
those
 showing
 increased
 lateral
 root
 formation
 and
 a
 decrease
 in
 total
 lignin
 content.

 According
 to
 Tsugeki
 &
 Federoff
 (1999),
 these
 results
 could
 indicate
 that
 the
 formation
 of
 more
 lateral
 roots
 might
 compensate
 for
 the
 effect
 of
 the
 short‐root
 phenotype
seen
in
previous
studies
involving
the
SHORT­ROOT
(SHR)
gene,
which
is
 typified
by
the
absence
of
gravitropic
response
in
shoots
and
exhibits
a
determinate
 root
growth
pattern
(Benfey
et
al.
1993).

 
 Multiple
 signaling
 pathways
 are
 responsible
 for
 controlling
 normal
 plant
 growth
 and
 development.
 
 These
 pathways
 are
 able
 to
 integrate
 information
 from
 the
 environment
 using
 metabolic
 and
 developmental
 signals.
 
 If
 these
 normal
 developmental
 and
 signaling
 pathways,
 such
 as
 the
phenylpropanoid
 pathway,
 are
  
  96
  disrupted
 or
 altered,
 consequences
 to
 overall
 plant
 growth
 and
 function
 could
 result.
 
 In
 order
 to
 determine
 any
 phenotypes
 involving
 flowering
 time,
 overall
 height
 and
 shape
 (leaf
 and
 plant),
 plant
 growth
 was
 examined
 over
 a
 six‐week
 period.
 
 My
 transgenic
 plants
 overexpressing
 SND1
 did
 not
 show
 any
 observable
 phenotype
 among
 aerial
 plant
 tissues,
 which
 could
 mean
 that:
 a)
 my
 transgenic
 constructs
 were
 sufficiently
 root‐specific
 that
 overexpression
 of
 SND1
 in
 roots
 did
 not
seem
to
interefere
with
normal
plant
growth
and
development
or
b)
there
is
no
 alteration
 in
 secondary
 cell
 wall
 composition
 that
 could
 cause
 an
 observable
 phenotype
 in
 aerial
 tissues.
 
 Either
 of
 these
 reasons
 could
 explain
 why
 the
 pendulous
 phenotype
 (as
 well
 as
 other
 severe
 phenotypes
 in
 flowers
 and
 leaves),
 previously
 seen
 in
 SND1
 overexpressors
 under
 the
 control
 of
 the
 constitutive
 CaMV35S
promoter,
was
not
observed
in
my
transgenic
plants
(Zhong
et
al.
2006).


 
 Histochemical
staining
and
UV
autofluorescence
of
lignin
in
root‐hypocotyls
did
not
 show
 significant
 visible
 phenotypic
 changes
 even
 though
 considerable
 variation
 in
 lignin
content
was
seen
along
the
5mm
sections
of
hypocotyl
analyzed,
which
could
 be
due
to
differences
in
developmental
equivalencies.

It
is
possible
that
visualizing
 wall
thickness
and
lignin
content
at
this
magnification
using
this
particular
type
of
 microscopy,
was
not
sufficient
to
observe
any
changes
in
cell
wall
thickness
or
lignin
 deposition
 patterns
 in
 the
 roots.
 
 A
 more
 sensitive
 method
 might
 be
 needed
 to
 distinguish
 more
 subtle
 differences
 in
 cell
 wall
 thickness
 among
 transgenic
 lines,
 such
as
transmission
electron
microscopy.


 
 
  
  97
  5.
  Conclusions
and
Future
Directions
  
 
 To
 my
 knowledge,
 this
 is
 the
 first
 investigation
 into
 the
 manipulation
 of
 lignin
 deposition
 in
 Arabidopsis
 roots
 for
 the
 end‐use
 of
 increasing
 carbon
 stocks
 in
 agricultural
root
systems,
such
as
canola
or
soybean.

Using
a
metabolic
engineering
 approach,
 SND1,
 a
 key
 transcriptional
 activator
 controlling
 secondary
 cell
 wall
 biosynthesis
 and
 deposition
 in
 Arabidopsis,
 was
 identified
 as
 a
 suitable
 candidate
 gene
to
alter
the
expression
of
several
endogenous
genes
and
transcription
factors
 involved
 in
 lignin
 biosynthesis,
 through
 overexpression
 in
 root
 tissues.
 
 In
 my
 transgenic
 plant
 lines
 overexpressing
 SND1
 in
 roots
 (driven
 by
 two
 different
 root‐ specific
 candidate
 gene
 promoters,
 4CL1
 and
 SND1),
 I
 found
 that
 SND1
 overexpression
upregulated
previously
known
downstream
targets
of
SND1,
did
not
 result
 in
 a
 modification
 of
 lignin
 biosynthetic
 pathway
 genes,
 generally
 showed
 a
 decrease
in
total
lignin
and
carbohydrate
content,
showed
an
increase
in
lateral
root
 density
and
did
not
exhibited
any
visible
phenotypes
regarding
seed‐related
traits,
 plant
growth
and
development,
plant
height
or
lignin
deposition
patterns
in
roots.

 
 SND1
 did
 not
 behave
 in
 a
 predictable
 manner
 when
 overexpressed
 in
 an
 environment
 that
 it
 does
 not
 normally
 operate
 in.
 
 There
 is
 still
 much
 to
 discover
 about
 the
 organization,
 association
 and
 interrelation
 of
 the
 entire
 regulatory
 cascade
 of
 TFs
 (along
 with
 regulatory
 proteins
 and
 cofactors)
 involved
 in
 the
 activation
 or
 supression
 of
 lignin
 biosynthetic
 genes
 during
 secondary
 wall
 formation
 in
 shoots,
 let
 alone
 in
 the
 roots.
 
 
 Further
 studies
 are
 underway,
 in
  
  98
  Arabidopsis,
 to
 characterize
 the
 TFs
 involved
 in
 the
 SND1‐mediated
 regulation
 of
 secondary
cell
wall
formation
(probably
through
reverse
genetics
approaches).

The
 mechanisms
 in
 place
 to
 control
 and
 maintain
 normal
 levels
 of
 plant
 cell
 wall
 biosynthesis
 and
 deposition
 present
 a
 significant
 challenge
 to
 overcome
 when
 designing
 and
 engineering
 genetic
 constructs
 to
 ectopically
 express
 transcription
 factors
that
regulate
secondary
cell
wall
metabolic
pathways,
in
plant
organs
where
 these
 factors
 do
 not
 normally
 regulate
 this
 process.
 
 TFs
 in
 general
 have
 very
 diverse
roles
in
regulating
gene
transcription
and
may
act
as
part
of
a
complex
with
 other
 TFs
 or
 regulatory
 proteins,
 which
 together
 might
 be
 involved
 in
 directly
 regulating
 gene
 expression
 in
 a
 particular
 biosynthetic
 pathway.
 
 Others
 might
 be
 involved
 in
 enhancing
 or
 fine‐tuning
 the
 level
 of
 expression
 of
 different
 metabolic
 pathway
genes.

Therefore,
studies
are
needed
to
determine
the
specific
associations
 between
these
factors
and
with
cell
wall
biosynthetic
genes
(in
vivo,
in
vitro
and
in
 planta)
 could
 also
 provide
 more
 insight
 into
 how
 this
 particular
 lignin
 metabolic
 pathway
 is
 controlled
 as
 well
 as
 possibly
 present
 new
 candidate
 genes
 whose
 overexpression
 might
 induce
 ectopic
 lignification
 in
 root
 tissues.
 
 All
 these
 studies
 combined
 should
 clarify
 some
 of
 the
 missing
 links
 in
 our
 current
 knowledge
 of
 secondary
cell
wall
formation,
within
above
ground
tissues.

Significantly
more
work
 is
 required
 in
 Arabidopsis
 root
 systems
 to
 determine
 how
 (and
 even
 which)
 secondary
 cell
 wall
 regulatory
 factors
operate
 in
 these
 tissues.
 
These
 studies
 may
 even
 elucidate
 new
 candidate
 genes
 controlling
 lignin
 deposition
 specifically
 in
 roots.



 
  
  99
  Suitable
promoters
and
a
safener‐inducible
gene
expression
system
were
identified
 in
 this
 project
 and
 used
 to
 induce
 root‐specific
 expression
 in
 transgenic
 plants.

 Experimentally
 testing
 the
 strength
 and
 tissue‐specificity
 of
 all
 the
 other
 putative
 root‐specific
 promoters
 that
 have
 been
 previously
 identified
 in
 Arabidopsis
 can
 be
 used
to
assess
their
ability
to
drive
transgene
expression
in
the
context
of
particular
 biological
questions
and
objectives.


Since
in
silico
analysis
of
regulatory
motifs
or
 cis‐elements
in
promoter
regions
indicates
that
these
binding
sequences
could
play
 an
important
role
in
conferring
root‐specificity,
as
previously
described
for
these
so‐ called
“root‐specific”
genes,
it
may
be
valuable
to
determine
which
of
these
putative
 motifs
 are
 in
 fact
 directly
 linked
 to
 root‐specific
 gene
 expression
 by
 more
 direct
 experimental
 approaches.
 
 For
 example,
 recapitulation
 studies
 using
 intact
 and
 mutated
 versions
 of
 the
 predicted
 cis­element
 driving
 a
 reporter
 gene
 (such
 as
 luciferase)
in
transgenic
plants
could
be
used
to
validate
the
hypothesized
function
 of
 the
 cis­acting
 regulatory
 element
 in
 vivo.
 
 
 The
 additional
 information
 gathered
 from
 these
 future
 studies,
 could
 provide
 us
 with
 more
 ways
 to
 fully
 explore
 the
 various
 gene
 expression
 resources
 available
 for
 manipulating
 lignin
 deposition
 in
 roots,
thereby
enabling
us
to
develop
new
highly
specific
gene
expression
constructs
 for
 enhancing
 lignin
 deposition
 in
 roots.
 
 Furthermore,
 the
 root‐specific
 gene
 induction
 system
 in
 dicots
 using
 benoxacor
 and
 fenclorim
 as
 chemical
 inducers
 of
 the
 GSTU19
 promoter
 used
 to
 drive
 root‐specific
 transgene
 expression,
 showed
 some
promise
in
conferring
spatial
and
temporal
control
of
transgene
expression
in
 the
 roots
 of
 transgenic
 plants
 analyzed
 in
 this
 project
 but
 this
 system
 needs
 to
 be
 optimized
 with
 respect
 to
 safener
 concentration,
 induction
 time
 and
 application
  
  100
  method
 if
 it
 is
 to
 be
 used
 widely
 as
 an
 acceptable
 chemical‐inducible
 root‐specific
 gene
expression
for
various
root‐related
biotechnology
applications.


For
example,
 direct
induction
of
transgene
expression
in
hydroponically
grown
plants
is
the
most
 effective
 way
 to
 induce
 transgene
 expression
 in
 roots
 by
 allowing
 direct
 access
 to
 the
 safener
 by
 root
 systems,
 a
 method
 that
 may
 not
 be
 well‐suited
 to
 large‐scale
 crop
systems.
 
 Studies
with
the
overall
aim
of
modifying
lignin
content
and
composition
in
plants
 have
many
potential
economic
and
environmental
benefits
to
humans.

As
a
result
of
 this
importance,
in
just
over
a
decade,
a
number
of
studies
have
been
conducted
to
 manipulate
 gene
 expression
 in
 the
 monolignol
 pathway
 within
 phenylpropanoid
 metabolism.
 
 For
 instance,
 cheaper
 and
 more
 easily
 processed
 trees
 for
 pulp
 and
 paper
manufacture
that
could
decrease
pollution,
more
readily
digestible
forage
for
 livestock
 and
 improved
 feedstock
 for
 fuel/chemical
 production
 (Anterola
 &
 Lewis
 2002).
 
 These
 research
 endeavors,
 along
 with
 high
 throughput
 transcriptional
 and
 metabolic
profiling
studies,
have
produced
an
immense
collection
of
scientific
data.

 These
 studies
 are
 important
 in
 gaining
 significant
 insight
 into:
 1)
 the
 overall
 dynamics
 of
 phenylpropanoid
 metabolism
 (i.e.
 how
 carbon
 flux
 through
 various
 pathways
 is
 differentially
 controlled)
 and
 2)
 how
 genetic
 manipulations
 can
 alter
 and
disrupt
programmed
lignin
assembly
in
a
predictable
manner
without
affecting
 overall
 plant
 viability
 (Anterola
 &
 Lewis
 2002).
 
 In
 fact,
 metabolic
 engineering
 in
 general
is
now
beginning
to
take
over
from
single‐gene
engineering
as
the
best
way
 to
 manipulate
 metabolic
 flux
 in
 transgenic
 plants.
 
 
 The
 ability
 to
 control
 several
  
  101
  points
 in
 a
 given
 metabolic
 pathway
 at
 the
 same
 time
 either
 by
 overexpressing
 and/or
 suppressing
 several
 enzymes
 through
 the
 use
 of
 transcriptional
 regulators
 controlling
endogenous
genes
is
a
powerful
tool
in
developing
complex
phenotypes
 resulting
 from
 modifications
 of
 entire
 pathways.
 Our
 knowledge
 of
 metabolic
 pathways
 continues
 to
 expand
 via
 the
 use
 of
 applied
 genomics,
 proteomics
 and
 metabolomics,
 while
 advances
 in
 systems
 biology
 help
 us
 to
 model
 the
 impact
 of
 different
modifications.

In
conclusion,
these
more
recent
biotechnological
advances
 are
 greatly
 increasing
 our
 understanding
 of
 the
 regulatory
 processes
 involved
 in
 controlling
secondary
cell
wall
biosynthesis
and
deposition.


 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
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  111
  Appendices

 
 Appendix
A.
 Primary
sequences
of
gene
expression
constructs
  
  4CL1pro­SND1
(2381
bp)
 -1280 -1260 -1197 -1134 -1071 -1008 -945 -882 -819 -756 -693 -630 -567 -504 -441 -378 -315 -252 -189 -126 -63  EcoR IForward primer 5’-GAATTCTTTTCGGTCTCTAA TACCTCCGGTTTTAAAAAAAAACATATCAGTTGAAGGATGAGTTTGGTGAAGGCTATATTGTC CATTGATTTTGGAGATATATGTATTATGGTCATGATTATTACGATTTTTATATAAAAGAATAT TAAAAATGGTGGGGTTGGTGAAGAAATGAAGATTTATCGTCAAATATTTCAATTTTTACTTGG ACTATTGCTTCGGTTATATCGTCAACATGGGCCCACTCTTCCACCAAAGCCCAATCAATATAT CTCTCGCTATCTTCACCAACCCACTCTTCTTCTCTTACCAAACCCATTTCCTTTATTTCCAAC CCTACCCCTTTATTTCTCAAGCTTTACACTTTTAGCCCATAACTTTCTTTTTATCCAAATGGA TTTGACTGGTCTCCAAAGTTGAATTAAATGGTTGTAGAAATAAAATAAAATTATACGGGTTCA ATTGTTCAATTGTTCATATACCGTTGACGTTCAATTGTTCATATACGGGTTCCGTGGTCGTTG GTAATATATATGTCTTTTATGGAACCAAAATAGACCAAATCAACAACAAATGAAGAAATTGTT AGAGTATGATACACTCATATATACCCAAATATAGCATATATTTATAATATAACTTTTGGCTAT GTCATTTTACATGATTTTTTTGGCTTATCTATTAAAAGTATCATACAAACTGTTTTTACTTCT TTTTTTTCTTAGAATATATATGCCCAAAATGGAAAAGAACATATGCCAAGGTTGATTTTATCG CTTATATGGTAAAAATTGGAAAAACATACAAATCATTACTTTATTTAATTAAATCATGTGAAG AAACATATTCAATTACGGTAATACGTTATCAAAACATTTTTTTTTACATTAATTGTTACATTT TTTTTTTTTGCAAATATTCTTAAATAACCATTCTTTTTTTATTTACTATAATTAACATAAAAA TAAATAAAATATAACATTTCAACAAAGAAATTTGCTTATGAAAAATACAAAATCCAGTTAATT TTTCAGAAAAATACAAATTTGCTTATAAATATATTACCACTAGTTTATGTGATTTTAAAAGAA AGAAATGCAGCTTACCAAACGCAACGTGAAAATTTGAGAAACCCATACTCAAAAAAGATTAAA TGACAAAATCACCCTCAGCAAAATCATGAAACAACAACACTAACATTTTCACCAACCCCACCG TCTACTCCGGTGAATTGTCTATATGAACTCCTCCGATACAACTCCTGTTTCCTTCAGCCGCGG Reverse primer Sac II  +1 MetAlaAspAsnLysValAsnLeuSerIleAsnGlyGlnSerLysValProProGlyPheArg ATGGCTGATAATAAGGTCAATCTTTCGATTAATGGACAATCAAAAGTGCCTCCAGGTTTCAGA 63 Forward Primer PheHisProThrGluGluGluLeuLeuHisTyrTyrLeuArgLysLysValAsnSerGlnLys TTCCATCCCACCGAAGAAGAACTTCTCCATTACTATCTCCGTAAGAAAGTTAACTCTCAAAAG 126 IleAspLeuAspValIleArgGluValAspLeuAsnLysLeuGluProTrpAspIleGlnGlu ATCGATCTTGATGTCATTCGTGAAGTTGATCTAAACAAGCTTGAGCCTTGGGATATTCAAGAG 189 GluCysArgIleGlySerThrProGlnAsnAspTrpTyrPhePheSerHisLysAspLysLys GAATGTAGAATCGGTTCAACGCCACAAAACGACTGGTACTTCTTCAGCCACAAGGACAAGAAG 252 TyrProThrGlyThrArgThrAsnArgAlaThrValAlaGlyPheTrpLysAlaThrGlyArg TATCCAACCGGGACCAGGACGAACCGGGCAACAGTCGCTGGATTCTGGAAAGCTACCGGACGT 315 AspLysIleIleCysSerCysValArgArgIleGlyLeuArgLysThrLeuValPheTyrLys GACAAAATCATCTGCAGTTGTGTCCGGAGAATTGGACTGAGGAAGACACTCGTGTTCTACAAA 378 GlyArgAlaProHisGlyGlnLysSerAspTrpIleMetHisGluTyrArgLeuAspAspThr GGAAGAGCTCCTCACGGTCAGAAATCCGACTGGATCATGCATGAGTATCGCCTCGACGATACT 441 ProMetSerAsnGlyTyrAlaAspValValThrGluAspProMetSerTyrAsnGluGluGly CCAATGTCTAATGGCTATGCTGATGTTGTTACAGAAGATCCAATGAGCTATAACGAAGAAGGT 504  
  112
  TrpValValCysArgValPheArgLysLysAsnTyrGlnLysIleAspAspCysProLysIle TGGGTGGTATGTCGAGTGTTCAGGAAGAAGAACTATCAAAAGATTGACGATTGTCCTAAAATC 567 ThrLeuSerSerLeuProAspAspThrGluGluGluLysGlyProThrPheHisAsnThrGln ACTCTATCTTCTTTACCTGATGACACGGAGGAAGAGAAGGGGCCCACCTTTCACAACACTCAA 630 AsnValThrGlyLeuAspHisValLeuLeuTyrMetAspArgThrGlySerAsnIleCysMet AACGTTACCGGTTTAGACCATGTTCTTCTCTACATGGACCGTACCGGTTCTAACATTTGCATG 693 ProGluSerGlnThrThrThrGlnHisGlnAspAspValLeuPheMetGlnLeuProSerLeu CCCGAGAGCCAAACAACGACTCAACATCAAGATGATGTCTTATTCATGCAACTCCCAAGTCTT 756 GluThrProLysSerGluSerProValAspGlnSerPheLeuThrProSerLysLeuAspPhe GAGACACCTAAATCCGAGAGCCCGGTCGACCAAAGTTTCCTGACTCCAAGCAAACTCGATTTC 819 SerProValGlnGluLysIleThrGluArgProValCysSerAsnTrpAlaSerLeuAspArg TCTCCCGTTCAAGAGAAGATAACCGAAAGACCGGTTTGCAGCAACTGGGCTAGTCTTGACCGG 882 LeuValAlaTrpGlnLeuAsnAsnGlyHisHisAsnProCysHisArgLysSerPheAspGlu CTCGTAGCTTGGCAATTGAACAATGGTCATCATAATCCGTGTCATCGTAAGAGTTTTGATGAA 945 GluGluGluAsnGlyAspThrMetMetGlnArgTrpAspLeuHisTrpAsnAsnAspAspAsn GAAGAAGAAAATGGTGATACTATGATGCAGCGATGGGATCTTCATTGGAATAATGATGATAAT 1008 ValAspLeuTrpSerSerPheThrGluSerSerSerSerLeuAspProLeuLeuHisLeuSer GTTGATCTTTGGAGTAGTTTCACTGAGTCTTCTTCGTCTTTAGACCCACTTCTTCATTTATCT 1071 Reverse Primer Val HisHisHisHisHisHis 
 GTATGACATCATCATCATCATCATGGATCC-3’ 1101 6xHis tag BamH I  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  113
  
 
 GSTU19pro­SND1
(2558
bp)
 -1457 -1449 -1386 -1323 -1260 -1197 -1134 -1071 -1008 -945 -882 -819 -756 -693 -630 -567 -504 -441 -378 -315 -252 -189 -126 -63  EcoR I Forward primer 5’GAATTCGC TACGTGTCGTGAGATATCGAACCCAACGCAGATATGAGTATGTTGAGCTAGTTTCTTCTTATG AAACAATCATATATGTCTATAATGAATAGATCACATTATCTGCCTGAAAAAAATCCCGTATAT TACTCGACGAAATATAAATACCCAATGTAGCTGATTTTGCTTTCTCTGGTGACATATCCAATT TGGCTAAATTTGTTAACTAGTCTATTATAGGTTTATAATAGATCTAGCTATGTTAAAGATACT AAAGCATCAGTTACATAAATTTTTGGCGCGAGTTTATATCTTTTGGAATTAAAAATAAGAGAA TTTAAAAATAAGAAGATCATTTTGTTTGGCCACAGGAGTTCTGAAAGGTCAGGTATGATTTTT TTCTTGCTCGCTCTTATGATTTTGTTTTTATTAATGGGTTTTCAAATAAGAAAAACTGTTTTT CGAAGCCCGGTTCAGATCCATTGTTTTTTGTAAAATATAGGCCCAATTCACCATAAGTCCATG ACCAAAACAAAAATAAGATAGAACCAATACTGAACCAGGATCTTCTCTCGCTTTCGTGATCAA TGTCGCCAAGCTTCTCGAGATCATGTGGTCACGTCAATTGTATAAATACAATTATTGACGTAA CACAATCTCTACAGTTCCATCGAAATATCTCGAAAATTTCCAGTTAATTCTGGTAACGTGAAC GTATCTTCCACCTCTTCAACCTACACAGCTTTCTAGAAATTTGGCTCGCTTTTCTAAGTCCTC TGTATTTTTTTGCACGTTTTTCAACTAAGTTTCAATATGAATCATTTCTTCTATAAATAAATG ATATTTTCATCAGGTAATGATACATTGTGCCGAAATAAAACGTCAATACTCATTAGTCAAATT AATTGTTCACATAATTTAAAACTGTGTTAATCCATCCAGTTATTTTCTTACAACAAAATAATC TTTTCCATCAACTTTTAAAATAATTAAACGCAGTGCTAAGAAATCTAAAATCTTGATTTAGAA ATCCATTATGGTTTCTGGTCAACTGAAATCCATAATTTCCTTTAACATCCAAAATCCAAATTT GCTACTATGATAATAGATTTCAGACGATTTTTTTTCTTTTTTCAATCATAGAGTCCACACGAA TATTTGCAAGTTACTATATAAAACACTATAATGGTCAACAGATAAAAAAAAGGCGAATGAAGA TATGTTACGTAAAAAGAAAATACTGTAATTATAAATTATTACTTTAAAAAGCTTTAAAATCTG GCCACATGTTTTTAAAGAGTGGTGTGACGTAACGACTAGAGTCAGCACAATCCATTATTGTAT CATAAATATTCTCATCTATAAATTACCTAAACCCTTACAGGTAGTGTCCCAACCAAACAAATC GAGAAAGACGAACACTTACAAAAAAAAATCTCTTTGTGAGCTTTAGCGATCGTAACACCGCGG Reverse primer SacII  +1 MetAlaAspAsnLysValAsnLeuSerIleAsnGlyGlnSerLysValProProGlyPheArg ATGGCTGATAATAAGGTCAATCTTTCGATTAATGGACAATCAAAAGTGCCTCCAGGTTTCAGA 63 Forward Primer PheHisProThrGluGluGluLeuLeuHisTyrTyrLeuArgLysLysValAsnSerGlnLys TTCCATCCCACCGAAGAAGAACTTCTCCATTACTATCTCCGTAAGAAAGTTAACTCTCAAAAG 126 IleAspLeuAspValIleArgGluValAspLeuAsnLysLeuGluProTrpAspIleGlnGlu ATCGATCTTGATGTCATTCGTGAAGTTGATCTAAACAAGCTTGAGCCTTGGGATATTCAAGAG 189 GluCysArgIleGlySerThrProGlnAsnAspTrpTyrPhePheSerHisLysAspLysLys GAATGTAGAATCGGTTCAACGCCACAAAACGACTGGTACTTCTTCAGCCACAAGGACAAGAAG 252 TyrProThrGlyThrArgThrAsnArgAlaThrValAlaGlyPheTrpLysAlaThrGlyArg TATCCAACCGGGACCAGGACGAACCGGGCAACAGTCGCTGGATTCTGGAAAGCTACCGGACGT 315 AspLysIleIleCysSerCysValArgArgIleGlyLeuArgLysThrLeuValPheTyrLys GACAAAATCATCTGCAGTTGTGTCCGGAGAATTGGACTGAGGAAGACACTCGTGTTCTACAAA 378 GlyArgAlaProHisGlyGlnLysSerAspTrpIleMetHisGluTyrArgLeuAspAspThr GGAAGAGCTCCTCACGGTCAGAAATCCGACTGGATCATGCATGAGTATCGCCTCGACGATACT 441 ProMetSerAsnGlyTyrAlaAspValValThrGluAspProMetSerTyrAsnGluGluGly CCAATGTCTAATGGCTATGCTGATGTTGTTACAGAAGATCCAATGAGCTATAACGAAGAAGGT 504 TrpValValCysArgValPheArgLysLysAsnTyrGlnLysIleAspAspCysProLysIle TGGGTGGTATGTCGAGTGTTCAGGAAGAAGAACTATCAAAAGATTGACGATTGTCCTAAAATC 567  
  114
  ThrLeuSerSerLeuProAspAspThrGluGluGluLysGlyProThrPheHisAsnThrGln ACTCTATCTTCTTTACCTGATGACACGGAGGAAGAGAAGGGGCCCACCTTTCACAACACTCAA 630 AsnValThrGlyLeuAspHisValLeuLeuTyrMetAspArgThrGlySerAsnIleCysMet AACGTTACCGGTTTAGACCATGTTCTTCTCTACATGGACCGTACCGGTTCTAACATTTGCATG 693 ProGluSerGlnThrThrThrGlnHisGlnAspAspValLeuPheMetGlnLeuProSerLeu CCCGAGAGCCAAACAACGACTCAACATCAAGATGATGTCTTATTCATGCAACTCCCAAGTCTT 756 GluThrProLysSerGluSerProValAspGlnSerPheLeuThrProSerLysLeuAspPhe GAGACACCTAAATCCGAGAGCCCGGTCGACCAAAGTTTCCTGACTCCAAGCAAACTCGATTTC 819 SerProValGlnGluLysIleThrGluArgProValCysSerAsnTrpAlaSerLeuAspArg TCTCCCGTTCAAGAGAAGATAACCGAAAGACCGGTTTGCAGCAACTGGGCTAGTCTTGACCGG 882 LeuValAlaTrpGlnLeuAsnAsnGlyHisHisAsnProCysHisArgLysSerPheAspGlu CTCGTAGCTTGGCAATTGAACAATGGTCATCATAATCCGTGTCATCGTAAGAGTTTTGATGAA 945 GluGluGluAsnGlyAspThrMetMetGlnArgTrpAspLeuHisTrpAsnAsnAspAspAsn GAAGAAGAAAATGGTGATACTATGATGCAGCGATGGGATCTTCATTGGAATAATGATGATAAT 1008 ValAspLeuTrpSerSerPheThrGluSerSerSerSerLeuAspProLeuLeuHisLeuSer GTTGATCTTTGGAGTAGTTTCACTGAGTCTTCTTCGTCTTTAGACCCACTTCTTCATTTATCT 1071 Reverse Primer Val HisHisHisHisHisHis
 GTATGACATCATCATCATCATCATGGATCC-3’ 1101 6XHis tag BamH I  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  115
  Appendix
B.
 Cis‐acting
DNA
regulatory
element
analysis
of
At4CL1
and
 AtGSTU19
promoters
  
 Table
 6.
 Cis­acting
 DNA
 regulatory
 element
 analysis
 of
 At4CL1,
 2000bp
 upstream
of
the
transcription
start
site.
 
 Putative
root
motifs
 (Vijaybhaskar
et
al.
2008)
 ARFAT
  ‐424
  (+)
  Signal
 sequence
 TGTCTC

  ‐341
  (+)
  TGACG

  ASF1MOTIFCAMV
 ASF1MOTIFCAMV
 ASF1MOTIFCAMV
 OSE1ROOTNODULE
  ‐1214
 ‐912
 ‐957
 ‐2873
  (+)
 (–)
 (–)
 (+)
  TGACG

 TGACG

 TGACG

 AAAGAT
  OSE1ROOTNODULE
 OSE1ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 RAV1AAT
  ‐1873
 ‐494
 ‐427
 ‐973
 ‐1024
 ‐1032
 ‐960
  (+)
 (–)
 (+)
 (+)
 (+)
 (+)
 (+)
  AAAGAT
 AAAGAT
 CTCTT
 CTCTT
 CTCTT
 CTCTT
 CAACA

  RAV1AAT
  ‐1293
  (+)
  CAACA

  RAV1AAT
  ‐1296
  (+)
  CAACA

  RAV1AAT
  ‐1713
  (+)
  CAACA

  RAV1AAT
  ‐1914
  (+)
  CAACA

  RAV1AAT
  ‐1917
  (+)
  CAACA

  RAV1AAT
  ‐198
  (–)
  CAACA

  ROOTMOTIFTAPOX1

  ‐64
  (+)
  ATATT
  ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

  ‐92
 ‐307
 ‐337
 ‐366
 ‐687
 ‐804
 ‐871
 ‐918
 ‐1353
 ‐1572
 ‐1644
 ‐1787
 ‐91
 ‐115
 ‐159
 ‐169
 ‐469
 ‐686
 ‐870
 ‐917
 ‐994
 ‐1255
  (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (+)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
  ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
  ASF1MOTIFCAMV
  
  Location
  Strand
  116
  Description
(Higo
et
al.
1999;
Prestridge
1991)
 
 ARF
 binding
 site
 found
 in
 the
 promoters
 of
 primary/early
 auxin
 response
 genes
 of
 Arabidopsis
thaliana
 
 ASF‐1
binding
site
involved
in
transcriptional
 activation
of
several
genes
 by
auxin
and/or
salicylic
acid
 ASF‐1
binding
site

 ASF‐1
binding
site
 ASF‐1
binding
site
 A
 consensus
 sequence
 motif
 of
 organ‐specific
 elements
 characteristic
 of
 activated
 promoters
 found
in
the
infected
cells
of
root
nodules
 organ‐specific
elements

 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 RAV1
 transcription
 factor
 binding
 consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 Motif
found
in
rolD
promoters;
organ
specificity
 and
strength
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
  ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 SP8BFIBSP8BIB
 SP8BFIBSP8BIB
 SURECOREATSULTR11
  ‐1343
 ‐1361
 ‐1454
 ‐1643
 ‐1701
 ‐1784
 ‐275
 ‐510
 ‐425
  (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
 (–)
  ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 TACTATT
 TACTATT
 GAGAC
  SURECOREATSULTR11
  ‐741
  (–)
  GAGAC
  SURECOREATSULTR11
  ‐1135
  (–)
  GAGAC
  ‐416
  (+)
  TTAATGG
  WUSATAg

  Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 SPBF
binding
site
 SPBF
binding
site
 Core
of
SURE
found
in
the
promoter
of
 SULTR1;
sulfate
uptake
and
transport
 Core
of
SURE
found
in
the
promoter
of
 SULTR1;
sulfate
uptake
and
transport
 Core
of
SURE
found
in
the
promoter
of
 SULTR1;
sulfate
uptake
and
transport
 Target
 sequence
 of
 WUS
 in
 the
 intron
 of
 AGAMOUS
gene
in
Arabidopsis
  
 
 Table
 7.
 Cis­acting
 DNA
 regulatory
 element
 analysis
 of
 AtGSTU19,
 2000bp
 upstream
of
the
transcription
start
site.
 
 Putative
root
motifs
 (Vijaybhaskar
et
al.
2008)
 ARFAT
  ‐359
  (+)
  Signal
 sequence
 TGTCTC

  ‐371
  (+)
  TGACG

  ASF1MOTIFCAMV
 ASF1MOTIFCAMV
 ASF1MOTIFCAMV
 ASF1MOTIFCAMV
 OSE1ROOTNODULE
  ‐1267
 ‐1929
 ‐1243
 ‐1504
 ‐888
  (+)
 (+)
 (–)
 (–)
 (+)
  TGACG

 TGACG

 TGACG

 TGACG

 AAAGAT
  OSE1ROOTNODULE
 OSE1ROOTNODULE
 OSE1ROOTNODULE
 OSE1ROOTNODULE
 OSE1ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 OSE2ROOTNODULE
 RAV1AAT
  ‐34
 ‐127
 ‐177
 ‐934
 ‐1587
 ‐47
 ‐158
 ‐1033
 ‐1349
 ‐953
 ‐1919
 ‐1577
  (–)
 (–)
 (–)
 (–)
 (–)
 (+)
 (+)
 (+)
 (+)
 (–)
 (–)
 (+)
  AAAGAT
 AAAGAT
 AAAGAT
 AAAGAT
 AAAGAT
 CTCTT
 CTCTT
 CTCTT
 CTCTT
 CTCTT
 CTCTT
 CAACA

  RAV1AAT
  ‐1814
  (+)
  CAACA

  RAV1AAT
  ‐639
  (–)
  CAACA

  RAV1AAT
  ‐685
  (–)
  CAACA

  ROOTMOTIFTAPOX1

  ‐336
  (+)
  ATATT
  ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

  ‐605
 ‐767
 ‐1464
 ‐1778
 ‐1973
 ‐267
 ‐391
 ‐781
  (+)
 (+)
 (+)
 (+)
 (+)
 (–)
 (–)
 (–)
  ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 ATATT
  ASF1MOTIFCAMV
  
  Location
  Strand
  117
  Description
(Higo
et
al.
1999;
Prestridge
1991)
 
 ARF
 binding
 site
 found
 in
 the
 promoters
 of
 primary/early
 auxin
 response
 genes
 of
 Arabidopsis
thaliana
 
 ASF‐1
binding
site
involved
in
transcriptional
 activation
of
several
genes
 by
auxin
and/or
salicylic
acid
 ASF‐1
binding
site

 ASF‐1
binding
site
 ASF‐1
binding
site
 ASF‐1
binding
site
 A
 consensus
 sequence
 motif
 of
 organ‐specific
 elements
 characteristic
 of
 activated
 promoters
 found
in
the
infected
cells
of
root
nodules
 organ‐specific
elements

 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 organ‐specific
elements
 RAV1
 transcription
 factor
 binding
 consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 RAV1
transcription
factor
binding
consensus
 sequence
 Motif
found
in
rolD
promoters;
organ
specificity
 and
strength
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
  ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 ROOTMOTIFTAPOX1

 SORLIP1AT
  ‐1119
 ‐1298
 ‐1434
 ‐1777
 ‐1972
 154
  (–)
 (–)
 (–)
 (–)
 (–)
 (+)
  ATATT
 ATATT
 ATATT
 ATATT
 ATATT
 GCCAC
  SORLIP1AT
  435
  (+)
  GCCAC
  SORLIP1AT
  988
  (+)
  GCCAC
  SORLIP1AT
  1905
  (+)
  GCCAC
  SP8BFIBSP8BIB
 SURECOREATSULTR11
  ‐330
 ‐496
  (–)
 (+)
  TACTATT
 GAGAC
  SURECOREATSULTR11
  ‐360
  (–)
  GAGAC
  ‐1053
  (+)
  TTAATGG
  WUSATAg

  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  118
  Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 Motif
found
in
rolD
promoters
 One
 of
 "Sequences
 Over‐Represented
 in
 Light‐ Induced
 Promoters
 (SORLIPs)
 in
 Arabidopsis;
 Computationally
 identified
 phyA‐induced
 motifs;
SORLIP
1
is
most
over‐represented,
and
 most
statistically
significant
 One
of
"Sequences
Over‐Represented
in
Light‐ Induced
Promoters
(SORLIPs)
 One
of
"Sequences
Over‐Represented
in
Light‐ Induced
Promoters
(SORLIPs)
 One
of
"Sequences
Over‐Represented
in
Light‐ Induced
Promoters
(SORLIPs)
 SPBF
binding
site
 Core
of
SURE
found
in
the
promoter
of
 SULTR1;
sulfate
uptake
and
transport
 Core
of
SURE
found
in
the
promoter
of
 SULTR1;
sulfate
uptake
and
transport
 Target
 sequence
 of
 WUS
 in
 the
 intron
 of
 AGAMOUS
gene
in
Arabidopsis
  Appendix
C.
 Primer
sequences
 
 
 Table
8.
List
of
all
primer
sequences
used
for
PCR,
reverse
transcription­PCR
 and
sequencing.
 
 No.
 1
  5
  Name
 4CL1
Forward

 
 4CL1
Reverse
 
 GSTU19
Forward
 
 GSTU19
Reverse
 
 4CL1pro
Forward

  6
  4CL1pro
Reverse
  7
  GSTU19pro
Forward

  8
  GSTU19pro
Reverse
  9
  SND1
Forward
 
 
 SND1
Reverse
 
 
 4CL1pro­SND1
Rev
 (mid‐insert)
 GSTU19pro­SND1
Rev
 (mid‐insert)
 MYB46
Forward
 
 MYB46
Reverse
 
 SND3
Forward
 
 SND3
Reverse
 
 MYB103
Forward
 
 MYB103
Reverse
 
 KNAT7
Forward
 
 KNAT7
Reverse
 
 SND1
Forward
 
 SND1
Reverse
 
  2
 3
 4
  10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
  
  Primer
Sequence
 5’-TCCAGAGGTGTAAAGTGACGGTGGC-3’  Comments
 Native
gene
expression
  5’-CCGTCATTCCGTATCCCTGACCGAG-3’  Native
gene
expression
  5’-AGGTGTGGGCGACAAAGGGTG-3’  Native
gene
expression
  5’-CCACGCTCTCCCTCTGCAAACAC-3’  Native
gene
expression
  5'-GGGCACGˇAATTCTTTTCGGTCTCTAATACCTCC3’ 5’CACGAGGˇGATCCGˇGTNACCCCGCˇGGCTGAAGGA AACAGGAGTTGTATC-3’ 5’-GGGTCTGˇAATTCGCTACGTGTCGTGAGATATCG3’ 5’CACGAGGˇGATCCGˇGTNACCCCGCˇGGTGTTACGAT CGCTAAAGCTCAC-3’ 5’GAGCTCCCGCˇGGATGGCTGATAATAAGGTCAATCT TTCG-3’  EcoRI
RE
site
  5’GGGTGTGˇGATCCATGATGATGATGATGATGTCATA CAGATAAATGAAGAAGTGGGTC-3’  BamHI
RE
site
and
HIS
x6
 tag
  5’-GTCACGTCCGGTAGCTTTCC-3’  5’-CTGGTCGGACCGATAACGAG-3’  For
sequencing
from
the
 middle
of
the
insert
 For
sequencing
from
the
 middle
of
the
insert
 300bp
fragment
  5’-GGTGGCTGATCATGTTTCCC-3’  300bp
fragment
  5’-ACGCTTGAAGGAGAGAATGG-3’  300bp
fragment
  5’-CTGATGCATCACCCAATTCG-3’  300bp
fragment
  5’-AGGTGGGCTCATATAGCTAG-3’  400bp
fragment
  5’-CTCTTCCTCCTCTTTGCGTG-3’  400bp
fragment
  5’-CAGCACGTGAGGGTTCATGC-3’  300bp
fragment
  5’-CCCAGCCCTTCTCTTCCTCA-3’  300bp
fragment
  5’-GATCATGCATGAGTATCGCC-3’  200bp
fragment
  5’-CGGGCTCTCGGATTTAGGTG-3’  200bp
fragment
  5’-TCTCCGGACACAACTGCAGATG-3’  119
  BamHI,
BstEII
and
SacII
RE
 sites
 EcoRI
RE
site
 BamHI,
BstEII
and
SacII
RE
 sites
 SacII
RE
site
  23
  4CL1
L1
  5’-TCAACCCGGTGAGATTTGTA-3’  24
  4CL1
R1
  5’-TCGTCATCGATCAATCCAAT-3’  25
  CCR1
L1
  5’-GTGCAAAGCAGATCTTCAGG-3’  26
  CCR1
R1
  5’-GCCGCAGCATTAATTACAAA-3’  27
  COMT1
L1
  5’-GTGCAAAGCAGATCTTCAGG-3’  28
  COMT1
R1
  5’-CATGGTGATTGTGGAATGGT-3’  29
  ACT8F(QRT)
  5’-TCTAAGGAGGAGCAGGTTTGA-3’  30
  ACT8R(QRT)
  5’-TTATCCGAGTTTGAAGAGGCTAC-3’
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  120
  From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
 From
Apurva
Bhargava
 (Ellis
Lab)
  Appendix
D.
 Media,
Buffers
and
Reagent
Stocks
 
 
 • Tryptone
 
 
 • Yeast
Extract
 
 • NaCl
 
 
 *For
plates
add
15g
agar
 
 
  LB
broth
(1L)
 
 
 
  10
g
 5
g
 10
g
  ½
MS
media
(1L)
 
 2.2
g
 0.5
g
 10
g
(phenotyping)
 20
g
(growth)
  • MS
salt
plus
vitamin
 
 • MES
hydrate
 
 
 • Sucrose
 
 
 
 
 
 
 
 
 *For
plates
add
7g
agar
 *Adjust
pH
to
5.7
using
1M
KOH
 
 
 1/10
Johnson
solution
(20L)
 
 • 20mM
Fe‐EDTA
(use
3mL/20L
solution)
 • 10mM
CaSO4
(use
800mL/20L
solution)
 • Macro
stock
(mix:
20mL/L
of
1M
MgSO4,
40mL/L
of
1M
KH2PO4,
80mL/L
of
0.5M
 K2SO4)
(use
100mL/20L
solution)
 • Micro
stock
(mix:
25mM
H3BO3,
2mM
MnSO4
x
H20,
2mM
ZnSO4
x
H20,
0.5mM
 CuSO4
x
5H2O,
0.5mM
NaMoO4)
(use
3mL/20mL
solution)
 • 2
spoons
of
CaCO3
powder
 • Add
NH2NO3
directly
to
a
final
concentration
of
1mM


 
 
 
 Benoxacor
100mM
Stock
Solution
(1000x)
 
 • Benoxacor
 125
mg

 • Acetone
 
 4.81
mL
 
 
 Fenclorim
100mM
Stock
Solution
(1000x)
 
 • Fenclorim

 125
mg
 • Acetone
 
 5.55
mL
 
 
  
  121
  72%
H2SO4
  Klason
lignin
procedure
solutions
 
  665
mL
conc.
H2SO4
 300
mL
DI
H2O
 cool,
bring
to
1L
 
 4%
H2SO4
 37
mL
conc.
H2SO4
 950
mL
DI
H2O
 cool,
bring
to
1L
 
 Sugar
Control
(in
50
mL
DI
H2O)
 arabinose
 10
mg
 galactose
 10
mg
 glucose
 200
mg
 xylose

 60
mg
 mannose
 60
mg
 rhamnose
 50
mg
 
 High
standard:
 sugar
stock
 30
mL
 
 
 
 DI
H2O
82
mL
 
 
 
 72%
H2SO4
 3
mL
 Medium
Standard:
 sugar
stock
 10
mL
 
 
 
 DI
H2O
102
mL
 
 
 
 72%
H2SO4
 3
mL
 Low
Standard:
 sugar
stock
 5
mL
 
 
 
 DI
H2O
107
mL
 
 
 
 72%
H2SO4

 3
mL
 
 Internal
Standard
 
 fucose

 10
mg/mL
 
 
 
 
 
 
 
 
 
  
  122
  Appendix
E.
 One‐way
analysis
of
variance
(ANOVA)
for
average
seed
weight

 
 
 and
lateral
root
density
 
  2.0 1.6  1.8  Lateral Root Density (# roots/cm)  2.2  2.4  Seed Weight (ug) ANOVA Report  !  40  41  A!7_5  B!5_6  D!2_6  F!5_10  F!7_4  G!8_4  Genotype list(Df = c(7, 40), ‘Sum Sq‘ = c(1.53145833333333, 2.13166666666667), ‘Mean Sq‘ = c(0.218779761904761, 0.0532916666666668), ‘F value‘ = c(4.10532782307604, NA), ‘Pr(>F)‘ = c(0.00175643763379917, NA))  !"#  $%&#$'#  ()*+#$'#  ,#-*.%)#  /012,3# -*.%)#  $))4#5)6789#  :#  ;<=>;?@#  A<B;C:C#  ?<;A=>#  A<AA;:=@#  D)E64%*.E#  ?A#  B<;>;@:#  A<A=>BF#  Figure
16.
 
 
  
  
 One­way
ANOVA
statistical
analysis
to
determine
differences
in

 
 average
seed
weight
between
genotypes
 
  123
  
 
 
 
  1.0  1.2  1.4  Lateral Root Density (LRD) ANOVA Report  0.8 0.6 0.0  0.2  0.4  Lateral Root Density (# roots/cm)  !  A-7  B-5  roots_cmA!75  !"#  F-7  roots_cmF!74  $%&#$'#Genotype ()*+#$'#  G-8  EV40  roots_cmEV40  ,#-*.%)#  /012,3#  list(Df = c(4, 95), ‘Sum Sq‘ = c(3.70348645871960, 10.2922317372679), ‘Mean Sq‘ = c(0.925871614679899, 0.108339281444925), ‘F value‘ = c(8.54603798669804, NA), ‘Pr(>F)‘ = c(6.19424094405413e!06, NA))  45!#  6#  789:7;#  :8<=;<#  5)BCD%*.B#  <;#  @:8=<==#  :8@:>7#  >8;6?#  ?8@<6)A:?#  
 
 Figure
17.

 One­way
ANOVA
statistical
analysis
to
determine
differences
in

 
 
 
 average
number
of
lateral
roots
between
genotypes
  
  124
  

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