Viger, Hancock Et Al. 2014 - More Plant Growth but Less

8/11/2019 Viger, Hancock Et Al. 2014 - More Plant Growth but Less

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More plant growth but less plant defence? First globalgene expression data for plants grown in soil amendedwith biocharM A U D V I G E R 1 , R O B E R T D . H A N C O C K 2 , F R A N C O M I G L I E T T A 3 , 4 and GA I L TA Y LO R 1

1

Centre for Biological Sciences, University of Southampton, Southampton SO17 1BJ, UK, 2

Cell &Molecular Sciences, The JamesHutton Institute, Invergowrie, Dundee DD2 5DA, UK, 3Institute of Biometeorology (IBIMET), National Research Council

(CNR), Via Caproni 8, Firenze 50145, Italy, 4FoxLab, Forest & Wood Science, San Michele AllAdige 38010, Italy

Abstract

Biochar is a carbon (C)-rich solid formed when biomass is used to produce bioenergy. This black carbon hasbeen suggested as a solution to climate change, potentially reducing global anthropogenic emissions of green-house gases by 12%, as well as promoting increased crop growth. How biochar application to soil leads to bettercrop yields remains open to speculation. Using the model plant Arabidopsis and the crop plant lettuce (LactucasativaL.), we found increased plant growth in both species following biochar application. Statistically significantincreases forArabidopsis in leaf area (130%), rosette diameter (61%) and root length (100%) were observed withsimilar findings in lettuce, where biochar application also increased leaf cell expansion. For the first time, global

gene expression arrays were used on biochar-treated plants, enabling us to identify the growth-promoting planthormones, brassinosteroid and auxin, and their signalling molecules, as key to this growth stimulation, with lim-ited impacts on genes controlling photosynthesis. In addition, genes for cell wall loosening were promoted aswere those for increased activity in membrane transporters for sugar, nutrients and aquaporins for better waterand nutrient uptake and movement of sugars for metabolism in the plant. Positive growth effects were accompa-nied by down-regulation of a large suite of plant defence genes, including the jasmonic acid biosynthetic path-way, defensins and most categories of secondary metabolites. Such genes are critical for plant protection againstinsect and pathogen attack, as well as defence against stresses including drought. We propose a conceptualmodel to explain these effects in this biochar type, hypothesizing a role for additional K+ supply in biocharamended soils, leading to Ca2+ and Reactive Oxygen Species (ROS) mediated signalling underpinning growthand defence signalling responses.

Keywords: Arabidopsis thaliana, biochar stimulated growth, carbon sequestration, geoengineering, global gene expression,

microarrays, plant immunity

Received 07 June 2013; revised version received 19 January 2014 and accepted 20 January 2014

Introduction

Biochar is formed as a byproduct when biomass, from

bioenergy crops, organic wastes or crop residues is used

to produce liquid or gaseous bioenergy with no or a

limited supply of oxygen, at temperatures between 300

and 1200 C. Biochar application to soil has been widely

suggested as an option to mitigate climate change

through carbon sequestration in long-term soil pools

(Lehmannet al., 2006). A consequential reduction in glo-

bal anthropogenic emissions of greenhouse gases by up

to 12% has been proposed, (Woolfet al., 2010), but the

wide scale use of biochar application is controversial,

since much remains unknown on the long-term impacts

in managed and natural ecosystems. For example, many

reports show that biochar application has a positive

effect in enhancing crop yields. A meta-analysis for

plant productivity after biochar application revealed a

significant mean increase of 10% (Jeffery et al., 2011),

with some studies reporting growth stimulations of

more than 50%, although the response was highly vari-

able with both negative and positive effects observed.

There remains limited understanding of how enhanced

crop growth is achieved, but improved water and nutri-

ent retention, increased soil pH, effects on soil microbes

and ethylene production have all been proposed to have

a role (Lehmann & Joseph, 2009; Sohi et al., 2010; Spokas

et al., 2010). Properties of biochar can also vary depend-

ing on different feedstocks (Sohi, 2012) and results on

crop production are influenced by experimental design,

soil and biochar properties (Jefferyet al., 2011).Correspondence: Gail Taylor, tel. +44 (0) 2380592335,

fax +44 (0) 2380594459, e-mail: [email protected]

2014 John Wiley & Sons Ltd 1

GCB Bioenergy (2014), doi: 10.1111/gcbb.12182


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Interest in biochar has increased considerably in the

past decade with research focussed on the potential for

durable carbon sequestration and increased plant pro-

ductivity. Despite this, there are relatively few studies

on modern biocharmade from pyrolysis or gasifica-

tion processes in a bioenergy system and the mecha-

nisms of action for altered soil and plant functioning

remain largely unproven. There has been no reportedinformation on the underlying plant genetic processes

following biochar application that lead to stimulated

plant growth. Global gene expression arrays are now

used routinely for gene discovery in plants, animal and

microbes and have enabled increased understanding of

how these systems work, particularly in relation to the

environment. For example, we now understand how

plants respond to drought (Street et al., 2006), to attack

by pests and pathogens (Barah et al., 2013) and variation

between difference ecotypes (Kusnierczyk et al., 2007).

Microarrays are a particularly useful technology to

discover genes expressed during a process that were

not predicted a priori (Richmond & Somerville, 2000),

revealing novel insight into a problem that may then be

followed up in hypothesis driven experimentation.

No global gene expression profiling has as yet been

reported for plants grown in soil amended with biochar

and our understanding of gene regulation following this

treatment is limited to just an handful of genes. For

example, the expression of five defence-related genes

(Meller Harel et al., 2012) were assessed in plants grow-

ing in soil mixed with biochar.

Here, we report the effects of biochar application on

the model plant Arabidopsis as well as for the crop, let-

tuce. We provide the first global gene expression datafor plants exposed to biochar and reveal important

insights into the growth-promoting effects of biochar

and unpredicted and highly novel effects on plant

defence signalling.

Material and methods

Biochar, soil and plant material and growth conditions

Biochar was obtained through gasification of poplar wood

chips (where 80% of the chips were sized 1630 mm diameter),

from a 5 year old short rotation forest grown in Northern Italy,

where carbonaceous material is partially oxidized by heating at

1200 C. The gasifier was a fixed bed, down draft, open core

design of AGT (Advanced Gasification Technology, Italy), with

biochar characterized as having a compacted bulk density of

252 g l1: pH, 10.6; ash, 15% Dry Mass (DM); total N, P, K by

DM, 1.6, 0.2, 1.8% respectively. Depending on the experiment,

biochar was applied at rates equivalent to field application: 0,

20, 30, 50 and 100 t ha1, assuming a soil bulk density of

0.4 g cm3 to a depth of 30 cm, achieved by mixing 0%, 1.6%,

2.5%, 4.2% and 8.3% (kg of biochar per kg of soil), followingthe methods in Baronti et al. (2010). Soil and biochar were pre-

cisely weighed for each condition and mixed in large boxes to

homogenize the mixture before filling the pots. We note that

soil bulk density of this soil was low, but within the observed

range, particularly for organic soils. Even in organic soils, sam-

ples derived from soil cores are likely to be more closely com-

pacted with less porosity than the soil mixture that was used in

this laboratory experiment and should be considered in inter-

preting our results more widely.

In a series of experiments, seeds of Arabidopsis thaliana (eco-

type Columbia-0) and lettuce (Lactuca sativa L.) were sown into

commercially available top soil (Table 1). The texture of the top

soil was loamy. When fertilizer was used, the rate of applica-

tion was 45 g m2, corresponding to 108, 22.5, 36 and

9 kg ha1 of nutrients applied of nitrogen, phosphorus, potas-

sium and magnesium oxide, respectively. Temperatures were

maintained at 23 C daytime and 18 C night-time, humidity at

60% and 55% (day and night, respectively) with a photoperiod

of 16 h per day at a PAR of 130 lmol m2 s1. Soil, with and

without biochar, was analysed for pH, P, K, Mg, total nitrogen

and Soil Organic Matter (Table 1).

Growth measurements and global gene expression withArabidopsis thaliana

Twenty replicates of Arabidopsis thaliana were planted for each

of five biochar conditions (0, 20, 30, 50 and 100 t ha1), 10 with

and 10 without fertilizer, in a fully replicated and randomized

design, where pots were rerandomized within treatments every

few days throughout the experiment. Images of each pot were

taken from 13 Days After Planting (DAP) every 3 days until 28

DAP and processed using ImageJ for leaf area, rosette diameter

and leaf number. Measurements of height, stem diameter and

root length were recorded at 32 DAP.

Leaves were sampled for microarrays 33 DAP and snap fro-

zen in liquid nitrogen. RNA was extracted (Chang et al., 1993)

for three replicates of control and five of biochar (50 t ha1) with

fertilizer, and were hybridized to GeneChip ArabidopsisGenome

Arrays (Affymetrix, Santa Clara, CA, USA) by the European

Arabidopsis Stock Centre (NASC, Nottingham, UK). Data were

Table 1 Soil analysis, pH, P, K, Mg, nitrogen contents and Soil Organic Matter (SOM)

Soil samples Soil pH P (kg ha1) K (kg ha1)

Mg

(kg ha1)

Total Nitrogen

(% w/w)

SOM

(%)

Soil 6.6 21 108 516 0.15 15.6

Soil + Biochar (50 t ha1) 7.2 30.6 795 513 0.21 15.9

2014 John Wiley & Sons Ltd, GCB Bioenergy, doi: 10.1111/gcbb.12182

2 M . V I G E R et al.


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analysed in GeneSpring (Agilent technologies, Santa Clara,

CA, USA). Chips were normalized by MAS5. Differentially

expressed genes were identified throught-test between samples

of control and biochar (P < 0.05, 2-fold change difference) with

a multiple testing correction (Benjamini-Hochberg). Genes were

annotated using GeneSpring (Agilent technologies, Santa

Clara, CA, USA) and the website Tair (www.arabidopsis.org).

Pathways were analysed using the software Mapman (http://

mapman.gabipd.org/web/guest/mapman). A gene ontologyanalysis was also performed on AGRIGO(Du et al., 2010) using the

tool PAGE (Parametric Analysis of Gene SetEnrichment). A hier-

archical clustering was performed focusing on five Gene Ontol-

ogy groups using MeV MultiExperiment Viewer (http://www.

tm4.org/mev/). Candidate genes were selected for real-time

PCR. Forward and Reverse primers were designed using Primer-

BLAST (www.ncbi.nlm.nih.gov/tools/primer-blast). Amplifica-

tion efficiencywas measured followingLiu & Saint (2002).

Secondary metabolites

A second Arabidopsis experiment was conducted after micro-

array analysis using 20 replicates at 0 and 50 t ha1

with fer-tilizer to confirm the role of biochar in altering the

biosynthesis of secondary metabolites. Lyophilized leaf sam-

ples were extracted and partitioned according to the method

of Foito et al. (2013) with the exception that internal standards

were omitted. Following partitioning, morin was added to the

polar fraction as internal standard to a final concentration of

0.5 mM. Glucosinolates were separated on a Synergi Hydro

RP18 column (3 lm, 150 9 2 mm, Phenomenex) using a gra-

dient consisting of 0.2% formic acid in water (A) and 0.2%

formic acid in 90% acetonitrile (B). The flow rate was a con-

stant 200 ll min1 and the flow gradient was 050% B over

30 min. Glucosinolates, anthocyanins and flavonols were iden-

tified and quantified as previously described (Tohge et al.,

2005; Rochfort et al., 2008; Yonekura-Sakakibara et al., 2008)and are presented as peak area of the identified compound

relative to peak area of the internal standard.

Growth measurements with lettuce

Following initial analysis with Arabidopsis, a model plant, we

wished to confirm our findings with a second crop species and

chose lettuce. Ten replicates for three biochar conditions were

planted for lettuce, selected from across the range used in Ara-

bidopsis experiments: 0, 50 and 100 t ha1 which all had fertil-

izer added to the soil. As with the Arabidopsis experiment,

images of each pot were taken from 15 DAP every 3 days until

25 DAP and processed using ImageJ for leaf area, rosette diam-eter and leaf number. Aboveground fresh and dry weight was

measured at the end (35 DAP). Leaf cell expansion was further

investigated following results with microarrays that identified

cell walls as key targets for gene expression change, where leaf

cell size was assessed at 0 and 50 t ha1 biochar application

rates. Cell measurements were taken on the adaxial side of a

mature leaf (number five from the newly emerged leaf) using

nail vanish (Gardner et al., 1995). Imprints were collected

with a Zeiss microscope at 9 40 magnification attached with a

camera capturing the images. Cell area (lm2) was calculated

using ImageJ from an average of 10 cells in the field of view

(40 000 lm2).

Statistical analysis

Statistical analysis was undertaken using the SPSS software

(SPSS, Chicago, IL, USA). Normality was tested (Kolmogorov

Smirnov test) and data transformed as necessary (square root

or log10). For the growth experiment using Arabidopsis plants,

biochar and fertilizer effects on leaf area, rosette diameter, leaf

number, height, stem diameter and root length were analysed

using a two-way ANOVAtest to quantify the effects of each treat-

ment and their interaction (biochar 9fertilizer):

Yij l ai bj e

where Yij is the phenotype in the ith biochar condition and in

thejth fertilizer condition, aiis the biochar effect, bjis the fertil-

izer effect, and e is the residual error. A Student Newman

Keuls post-hoc test was also performed. Secondary metabolites

measured in Arabidopsis plants were analysed using a t-test

between the two biochar rate applications (0 and 50 t ha1).

For the growth experiment and the cell measurements using

lettuce plants, only the biochar effect was tested with a one-

way ANOVAtest as fertilizer was applied on all the pots:

Yi l ai e

where Yj is the phenotype in the ith biochar condition, a i is the

biochar effect, bj is the fertilizer effect, and e is the residual

error. A Student Newman Keuls post-hoc test was also per-

formed.

Leaf area for Arabidopsis and lettuce experiments was also

analysed over time with a repeated measurement test with

time, biochar and fertilizer as effects.

Results

Plant growth is enhanced by biochar

Analysis of soil with and without biochar for pH, phos-

phorus (P), potassium (K), magnesium (Mg) and total

nitrogen content is given (Table 1). An increase in pH, P

and K contents was observed in soil mixed with bio-

char. We used the model plant Arabidopsis grown in a

soil closer to realistic soil conditions (commercial top

soil) in comparison to the typical Arabidopsis soil mix-

ture of compost and vermiculite, to study growthresponse following biochar application (Figs 1, 2;

Table 2). Leaf area of the Arabidopsis plants was

observed over time for all biochar application rates

and fertilizer treatments from images of the pots

(Fig. 1a, 2a, b). Using a repeated measurement test the

whole dataset showed significant biochar (F4,90 = 5.74,

P < 0.001), fertilizer (F1,90 = 37.71, P < 0.001) and time

effects (F1,90 = 182.77, P < 0001), but no interactions.


M E C H A N I S M F O R E N H A N C E D P L A N T G R O W T H I N B I O C H A R 3


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When studying the traits towards the end of the experi-

ment (28 DAP), leaf area, leaf number and rosette diam-

eter (Fig. 2c, d; Table 2) showed a significant increase

due to biochar application (Leaf area: F4,90 = 7.16,

P < 0.001; Rosette diameter: F4,90 = 11.25, P < 0.001;

Leaf number: F4,90 = 10.07,P < 0.001). Fertilizer also sig-

nificantly increased leaf area (F1,90 = 87.06, P < 0.001),

rosette diameter (F1,90 = 57.05, P < 0.001) and leaf num-

ber (F1,90 = 51.60, P < 0.001). Indeed plants were larger

when fertilizer was applied regardless of the biochar

application. No significant interaction of biochar x fertil-

izer was observed. A post-hoc test, revealed plants

grown with biochar at rates of application of 20, 30, 50

and 100 t ha1

were significantly bigger than thosegrown without biochar for leaf area, rosette diameter

and leaf number. At 28 DAP; leaf area was largest when

biochar was applied at 50 t ha1 in combination with

fertilizer (Table 2).

Height, stem diameter and root length were also mea-

sured (Table 2; Fig. 2e, f) at the end of the experiment

(32 DAP), all showing a significant increase in response

to biochar application (Height: F4,40 = 10.12, P < 0.001;

Stem diameter: F4,40 = 6.14, P < 0.001; Root length:

F4,40 = 4.95, P < 0.01). With the exception of root length

(F1,40 = 3.38, P = 0.074), fertilizer also had a positive

effect on height and stem diameter (F1,40 = 6.08,

P < 0.05 and F1,40 = 19.47, P < 0.001, respectively). No

interaction of biochar x fertilizer was observed for these

traits.

Growth measurements were also made on lettuce

(Figs 3, 4; Table 3), with similar results. Fertilizer was

applied to all lettuce plants. Like Arabidopsis, lettuce

produced larger leaves over time (Figs 3, 4a) and the

repeated measurement test showed a biochar

(F2,27 = 29.09, P < 0.001) and time effect (F1,27 = 2042.59,

P < 0.001). Towards the end of the experiment, leaf

area, rosette diameter and leaf number were increased

when biochar was applied (Leaf area: F2,27 = 39.91,

P < 0.001; Rosette diameter: F2,27 = 33.23, P < 0.001;

Leaf number: F2,27 = 20.87,P < 0.001). As the post-hoc

test revealed (Table 3), values were similar between the

biochar rate at 50 and 100 t ha1 (Fig. 4ac) and signifi-

cantly different to plants grown without biochar. Leaf

area increased from 3360 mm2 without biochar to

5195 mm2 on average with biochar, showing a 55%

increase with biochar application. Rosette diameter

increased by 31% from 159 mm without biochar to

209 mm with biochar. Finally, lettuce plants had on

average 6 leaves per plant without biochar compared to7.5 leaves with biochar, showing a percentage change of

25% in response to biochar application.

Fresh and dry weight were also measured for the let-

tuce plants 35 DAP (Fig. 4d) showing a significant

increase in response to biochar application (Fresh:

F2,12 = 28.86, P < 0.001; Dry: F2,12 = 42.87, P < 0.001).

Dry weight increased by 111% from 0.58 g at 0 t ha1

biochar to an average of 1.24 g at 50 and 100 t ha1.

Gene expression in response to biochar application

The microarray analysis revealed a total of 1076 genes

differently expressed when comparing control plants

with plants grown in biochar at 50 t ha1, both with

fertilizer (Table S1). Leaf area was the largest at the bio-

char application rate of 50 t ha1 with fertilizer and was

thus selected for the global gene expression analysis and

compared to plants growth without biochar but with

fertilizer to focus on the biochar effect. We identified 571

genes that were down-regulated and 505 that were

up-regulated in response to biochar application. Using

100 t

ha1

50 t

ha1

0 t

ha1

13 days 19 days 25 days 31 days Height:

+177% ***

Stem diameter:

+50% *

Rosette diameter:

+61% ***

Leaf area:

+130% ***

Leaf number:

+17% ***

Root length:

+100% **

Biocharrate

ap

plication(

tha1)

Time(a) (b)

Fig. 1 Arabidopsis rosette growth (a) at 0, 50 and 100 t ha1 equivalent biochar application with fertilizer over time and

percentage change of biomass (b) between control and 50 t ha1 biochar rate application. Asterisks indicate a significant biochar

effect (***P 0.001, ** P 0.01, * P 0.05, n.s. nonsignificant) by ANOVAtest.




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the AGRIGO software (Duet al., 2010), a complete view of

the gene ontology (GO) interaction was completed using

the gene expression data (Figure S3; Table S2). Recurrent

groups were observed, showing an effect of biochar

application, included growth (Figure S3a), cell morpho-

genesis (Figure S3a), response to stimulus or stress (Fig-

ure S3b), hormones, such as jasmonic acid, auxin and

cytokinin (Figure S3b), and secondary metabolism (Fig-

ure S3c). The three GO categories significantly repre-

sented with the highest z-score were xyloglucan:

xyloglucosyl transferase activity, intrinsic to membrane

and plant-type cell wall, whilst the groups with the low-

est z-score were secondary metabolic process, response

to wounding and response to jasmonic acid stimulus

(Table S2). Genes within those groups, except response

to wounding, were extracted and used to construct a

hierarchical clustering (Figure S1). The latter showed a

consistent up-regulation for all the biochar samples for

xyloglucan:xyloglucosyl transferase activity, intrinsic to

membrane and plant-type cell wall and a down-regulation

for secondary metabolic process and response to jasmonic

acid stimulus.

Few effects were found for genes controlling photo-

synthetic pathways (Table S1). In contrast, signalling,

transport and biosynthesis of two plant hormones central

to growth stimulationauxin and brassinosteroidwere

0

50

100

150

200

250

300

1316

1922

2528

020

3050

1000

50

100

150

200

250

300

1316

1922

2528

020

3050

100

Leafarea(mm2)

Leafarea(mm2)

Tim

e(D

aysaf

terp

lantin

g)

Tim

e(D

aysaft

erpla

ntin

g)

Biocharapplicationrate(tha1)

Biocharapplicationrate(tha1)

Height(mm)

0

20

40

60

80

100

120

140

160

180

Without fertilizer

With fertilizer

Stemd

iameter

0

20

40

60

80

100

120

Biochar application rate (t ha1)

0 20 30 50 100 0 20 30 50 100

Rosettediameter(mm)

0

20

40

60

80



0 20 30 50 100 0 20 30 50 100


Leafnumber

0

2

4

6

8

10

12

14

Without fertilizer

With fertilizer

Without fertilizer With fertilizer(a) (b)

(c) (d)

(e) (f)

Fig. 2 Growth in response to biochar application inArabidopsis thaliana: leaf area evolution over time related to biochar rate applica-

tion without (a) and with fertilizer (b), rosette diameter (c) and leaf number (d) at 28 DAP, height (e) and stem diameter (f) at 32

DAP.




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up-regulated for plants grown with biochar (Fig. 5a)

Here, auxin conjugation, for example, controlled by

IAR3, ILL5 and ILL6 was reduced by 4.13, 2.36 and

3 fold change, respectively (Table S3), leading to the

production of more free auxin (Leclere et al., 2002) and

auxin responsive proteins were stimulated (Table S3).

IAR3was also identified by Leclere et al.(2002) as a pos-

sible link between wound responses and auxin with

IAR3 proposed to control hydrolysis of amino acid

conjugates of jasmonic acid. Similarly for brassinoster-

oids, genes promoting hormone biosynthesis were

up-regulated (DWF4, CYP72C1, SMT2, SMT3: 2.19, 6.15,

2.18 and 4.01 fold change, respectively). DWF4, for exam-

ple, encodes an important steroid for a rate limiting step

in BR biosynthesis (Choeet al., 2001). Increased plant bio-

mass in biochar in this study was therefore characterized

by large stimulations in genes controlling brassinosteroid

and auxin biosynthesis and signalling, with limited

impacts on genes controlling the photosynthetic machin-

ery (Fig. 5a). In addition, genes controlling cell wallloosening, including numerous xyloglucan endotrans-

glucosylases and expansins (Fig. 5a; Table S3) were

up-regulated in biochar suggesting enhanced growth was

underpinned by increased cell expansion. For example,

XTH9, XTH33, XTR3, XTR4, XTR6, XTR7, XTH17, TCH4,

EXGT-A3and EXGT-A1 were xyloglucan endotransglu-

cosylases and xyloglucan:xyloglucosyl transferases that

were up-regulated in response to biochar with a fold

change between 2.3 to 16.57. ATEXLA1, ATEXLA2 and

ATEXPA11 were expansins that were up-regulated in

plants growing with biochar by 15.20, 4.42 and 2.44 fold

change respectively while only two expansinsATEXPA4

andATEXLB1were down regulated with a fold change of

2.44 and 2.66, respectively (Table S3). Cell wall pro-

teins were also promoted, such asAGP24, AGP7, AGP20,

AGP17, AGP22, FLA13 and FLA9, with a fold change

varying from 2.22 to 11.76.

For lettuce, cell expansion was assessed on a mature

leaf growing with and without biochar (50 and 0

t ha1), with larger cells observed for plants grown with

added biochar, although this was only apparent as a

Table 2 Average values and standard errors of growth inArabidopsis at different rates of biochar, with and without fertilizer, and

statistical results presenting the p-value for each trait using a GLM test for the biochar and fertilizer effects and the interaction biochar

x fertilizer effect. Bold values are significant (P < 0.05). The letters correspond to the post-hocresults

Biochar

application

(t ha1) Fertilizer

Leaf area 28

DAP (mm2)

Rosette

diameter 28

DAP (mm)

Leaf number

28 DAP

Height 32 DAP

(mm)

Stem diameter

32 DAP (mm)

Root length

32 DAP (mm)

0 No 7.7 0 .6a 9.3 0.4a 5.5 0.2 a 3.7 1.1a 0 0 a 20.8 1.1a

20 No 118.0 37.4a,b 36.9 4.9b,c 8.7 0.3b,c,d 73.5 18.5b,c 0.5 0.09a,b 75.1 12.3a,b

30 No 109.2 33.6a,b 39.5 6.4b,c 8.3 0.3b,c 114.3 18.3b,c 0.5 0.11a,b 68.6 21.9a,b

50 No 81.8 39.4a,b 31.3 8.9b 7.9 0.8b 53.3 17.8a,b,c 0.2 0.08a,b 34.0 8.6a,b

100 No 96.7 21.3a,b 39.4 4.9b,c 8.9 0.5b,c,d 113.1 10.2b,c 0.4 0.05a,b 90.0 13.9b

0 Yes 122.0 22.7a,b 42.2 3.6b,c 8.8 0.6b,c,d 39.1 10.1a,b 0.5 0.09a,b 41.8 8.4a,b

20 Yes 190.1 31.4b,c 57.6 5.8c,d 9.9 1.4 c,d 92.1 26.8b,c 0.7 0.08b,c 71.9 21.5a,b

30 Yes 265.9 53.8b,c 68.1 8.8d 10.0 1.6 c,d 132.0 26.7c 0.6 0.15b,c 80.2 23.9a,b

50 Yes 280.6 34.8b,c 67.8 5.0d 10.3 1.5 c,d 108.4 25.1b,c 0.7 0.12b,c 83.4 8.4a,b

100 Yes 255.1 41.1b,c 64.8 6.7d 10.5 1.2 d 129.7 10.9c 0.9 0.06c 96.3 8.2b

Statistics

P-value

Biochar 0.003


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values from the microarrays were confirmed by real-time

PCR on a selection of genes (Figure S2), including an eth-

ylene responsive binding element (ATERF15), a sugar

transporter (STP14), a phosphate responsive (EXO) and

a raffinose metabolism related gene (DIN10). STP14,

EXO and DIN10 were all up regulated in plants grown

in biochar.

However, these positive effects on growth were

linked to large and consistent down-regulation of genes

controlling plant defence mechanisms, including the jas-

monic and salicylic acid biosynthetic pathways, defen-

sins and most categories of secondary metabolites

(Fig. 5b; Table S3), which all have roles in plant defence

against pathogens and pest attacks (Abe et al., 2008).

Genes linked to the JA biosynthesis pathway included

LOX2, AOS, AOC4 andAOC1, were all down-regulated

in biochar grown plants (Fold change 5.11, 4.55,

2.81 and 4.01, respectively). LOX2 was a candidate

gene used for microarray confirmation by real-time PCR

and showed a down regulation in response to biochar

both in the microarray and real-time PCR analysis (Fig-

ure S2). Numerous genes related to jasmonic acid and

jasmonate signalling were also down-regulated in plants

grown with biochar (Fig. 5b; Table S3) such as JAL31,

JR1, JAZ2, JAZ5, JAZ9and JAZ10with fold change from

3.07 to 10.42. The largest decreases in gene expres-

sion in biochar were observed for ethylene- and jasmo-

nate-responsive plant defensins, for example CHIB,

THI2.1,PDF1.2band PDF1.2with observed fold changes

from 16.96 to 49.47 (Table S3). Decreased expression

in genes related to secondary metabolites in biochar

was detected including the largest negative fold change

of the microarray analysis for TPS04 of155.33 (Table

S3). This observation was confirmed with the analysis of

glucosinolates and flavonoids in leaf samples collected

19 DAP from a separate replicated experiment using

Arabidopsis. A significant reduction of anthocyanins,

flavonols and glucosinolates was observed for the plants

growing in biochar (50 t ha1) compared with the con-

trol (Table 4).

Plant growth smulated Plant defence reduced

DefensinsPDF1.2, ATHCHIB, THI2.1

Glutathione-S-

transferasesGSTU7, GSTU5, GSTU6,

GSTF5, GSTF12

Brassinosteroid

biosynthesis and signallingEXL5, DWF4, SMT2, CYP72C1, BIM1

Cell wall modificaonXTH9, XTH33, ATEXLA1,

ATEXLA2, XTR4, XTR7, TCH4

Cell wall proteinsAGP7, AGP20, AGP22,

FLA9

Sugar and water transportSPT1, ERD6, STP4, PIP1D, PIP1C, TIP2

BIOCHAR APPLICATION

Jasmonic acid biosynthesisLOX2, AOS, AOC4, AOC1

Ethylene signallingERF2, ERF6, ERF15, MES9

JA reduced

Decreased signal

transducon and

gene acvaon for

defence (Wasternack &Hause, 2013

Plant defences

against ins ects, fungi

and pathogens

reduced (Farmer et al,2003)

> 3

2 to 3

1 to 2

0

1 to 2

2 to 3

> 3

Log2 Response to abiocstress reduced(Farmer et al., 2003)

Jasmonic acid and

Jasmonates signallingJAS1, JAZ2, JAZ5, JAZ9, JR1, JAL31, MYC2

Redox Ascorbate

and glutathioneVTC2, VTC5, DHAR2

Signalling in sugar and

nutrient physiologyEXO, PHI-1

Signalling G-proteinsARAC4, RAB7, RAB7A, RAB8C

BR increasedPlant growth,

cell elongaon

and division

promoted (Choeet al., 199 8; Shrder

et al., 2011)

Auxin biosynthesis

IAR3, ILL6

Auxin transport and signallingCYP83B1, CYP711A1, GRH1, SAUR-like proteins,

IAA19, IAA6, SHY2, MYB proteins

Salicylic acid

biosynthesisFAMT

Cell elongaon promoted(McQueen-Mason, 1995)

Smulated ssue

morphogenesis,

cell growth and

division (Du et al.,1996)

Improved

transmembrane

sugar transport in

sink ssues (Szenthe

et al., 2007)

Aquaporins

improved water

transport (Postaire

et al., 2010)

Involved in signalling

process coordinaon

BR responses and

growth promoted(Shrder et al., 2011)

Regulated si gnal

transducon, cell

proliferaon, cytoskeletal

organisaon and

intracellular membrane

trafficking (Vernoud et al, 2003)

Secondary metabolismGlucosinolates, Anthocyanins,

Dihydroflanols, Phenylpropanoids

Root elongaon

increased(Waste rnack& Hause,

2013

Seed germinaon

increased (Wasternack&Hause, 2013)

Flower and

pollen

development

reduced(Wasternack&

Hause, 2013)

Leaf

senescence

decreased(Wasternack &

Hause, 2013)

SA reduced

Auxin freely released(LeClere et al., 2002)

(a) (b)

Fig. 5 A summary of gene expression analysis in response to biochar application (50 t ha1), 33 days after planting, focusing on

gene expression related to (a) plant growth response and (b) plant defence. Each square represents a single gene probe, with green

up-regulated and red down-regulated in biochar treated soil (biochar) compared to soil without addition (control).




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Discussion

We report the first global gene expression study, to our

knowledge, following plant growth in soil amended

with biochar made from poplar wood chips, providing a

clear insight into how this type of biochar results in

growth promotion. These data give the first glimpse of

an important mechanistic understanding and may help

to elucidate why some but not all biochars are effective

in promoting crop yield. We now have a model system

where many biochars could be tested since it has been

observed that plants react differently to different biochar

types, but the reasons for different responses remain

unclear (Jefferyet al., 2011). Our data show overwhelm-

ing evidence that auxin is central to biochar stimulatedgrowth, occurring largely through enhanced plant cell

expansion. Leaf expansion was stimulated in both the

model plantArabidopsisand the crop plant lettuce (130%

and 49% respectively), and when investigated in lettuce,

we observed that increased leaf size was attributed to

increased cell expansion rather than production (12%),

but only significant at the 10% level of probability. Com-

bined with these observations, a high number of cell

wall related genes such as xyloglucan endotransglucosy-

lases, expansins and arabinogalactan-proteins were up-

regulated in plants grown in biochar (Fig. 6). Those

have a role in cell wall loosening and growth (Mcqueen-

Mason, 1995; Du et al., 1996) and our data suggest that

this is an important part of the mechanism explaining

enhanced growth in biochar, with several GO categories

in the functional analysis showing an up-regulation fol-

lowing exposure to biochar (Table S2; Figure S3a). Sev-

eral strands of evidence point to auxin as the hormone

controlling this response. Firstly, the auxin receptor

GRH1, identified as an F-box protein belonging to the

TIR1 subfamily which mediates transcriptional res-

ponses to auxin (Kepinski & Leyser, 2005), was up-regu-

lated in plants grown with biochar. This suggests that

more down-stream effects of auxin action are likely.

Similarly several auxin response factors coding for

ARF proteins - were up-regulated in plants grown with

biochar, includingARF7, which has a known role in pro-

moting leaf expansion (Wilmoth et al., 2005), as well as

inducing lateral root formation. Several components ofthe auxin biosynthesis pathway were also stimulated in

biochar (IAR3, ILL5, ILL6), providing further evidence

that biochar results in an increase in auxin biosynthesis

perhaps in both young leaves and roots. Auxin is known

to be important in promoting a variety of plant growth

processes including increased shoot elongation, leaf

growth, meristematic activity and root and shoot

branching, with the expression of many genes regulated

by auxin including those identified here for cell growth.

Why auxin biosynthesis is stimulated remains open to

speculation but both altered pH and soluble sugar con-

tent are thought to impact on auxin biosynthesis and

action (Lageret al., 2010), and it is possible that biochar

exposure had a primary effect on ion uptake, (through

altered soil pH and increased nutrient availability,

Table 1), leading to improved transport of water and

nutrients and altered cell signalling. Soil analysis

revealed an increase in pH, phosphate, potassium and

total nitrogen when biochar was applied to soil

(Table 1). Soil pH increased from slightly acidic (6.6) to

neutral (7.2). In Jeffery et al. (2011), the meta-analysis

showed that increase of soil pH had a positive effect on

crop growth. Other factors also influenced biochar

effects including soil structure, crop species or biochar

feedstock (Jeffery et al., 2011). A second meta-analysisconfirmed this with significant biochar effects on soil

pH, soil P, K content, total N and C, crop yield and

aboveground biomass (Biederman & Harpole, 2012). K

concentration in plant tissue was also significantly

increased after biochar application in their study. Our

findings add significantly to these meta-analyses and

also revealed no significant interaction between biochar

addition and nutrient status of the plant (Table 2). For

plants grown on biochar, there was an up-regulation of

genes related to water transport such as TIP and PIP

and to sugar transport and signalling (Szenthe et al.,

2007) (Fig. 5a).PIP genes are known to enable improved

root hydraulic conductivity (Postaire et al., 2010). EXO

(a phosphate-responsive protein) and PHI-1 (a phos-

phate-induced protein) showed the highest gene expres-

sion change in response to biochar and are considered

essential for leaf cell expansion and growth promotion

(Schroderet al., 2011), achieved by mediating brassinos-

teroid (BR)- induced growth promotion. BR is also

known to be primarily involved in growth-promotion

through its action on plant cell expansion, and several

0 50

Ce

llarea(m2)

0

200

400

600

800

1000

Biochar applicaon rate (t ha1)

Fig. 6 Leaf epidermal cell area (lm2) at 0 and 50 t ha1 bio-

char application rate. in lettuce, with fertilizer addition.




10/15

Table 4 Quantification of secondary metabolites (glucosinolates and flavonoids) by LC/MS in control (0 t ha1) and biochar (50

t ha1) with fertilizer in Arabidopsis thaliana. Metabolite concentrations are presented as values relative to internal standards as

described in materials and methods. Bold values are significant (P < 0.05).n = 20

Class Name

Control

(0 t ha1)

Biochar

(50 t ha1) t-test

Glucosinolates

Methionine

derived

Glucoerucin 2.536 3.475 0.067

Glucoberteroin 0.290 0.270 0.656

Glucolesquerellin 0.102 0.096 0.656

Heptyl GLS 0.101 0.077 0.035

Glucoarabishin 2.552 2.240 0.385

Glucoibarin 0.442 0.423 0.722

Glucoraphanin 1 2.515 1.913 0.030

Glucoraphanin 2 2.426 1.794 0.005

Glucohesperin 0.050 0.035 0.005

Glucoibarin 0.373 0.261 0.006

Glucoalyssin 0.225 0.127


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genes involved in BR biosynthesis, signalling and action

were also up-regulated in plants grown with biochar,

including STM2 and STM3 and CYP72C1, while BIM1

was down-regulated (Vert et al., 2005). BR has previ-

ously been shown to be closely involved in auxin signal-

ling (Nakamoto et al., 2006). It is also linked to delayed

leaf senescence and to promoted plant growth, cell elon-

gation and cell division. For example, DWF4was signifi-

cantly up-regulated in biochar grown plants. The study

of its mutant revealed a dwarfed phenotype due to the

reduction of cell elongation and that it had a defective

step which was rate-limiting in BR biosynthesis path-

way (Choe et al., 1998). The magnitude of the growth

effect found here was similar to that observed previ-

ously for a range of crop plants (Jeffery et al., 2011), with

height growth increased by 177%, root length by 100%

and leaf area (size) by 130% when comparing control

with 50 t ha1 biochar application with fertilizer

(Fig. 1b). Similar observations on lettuce revealed a sig-

nificant increase in leaf area, leaf number, rosette diame-

ter and fresh and dry weight following biocharapplication with fertilizer (Table 3; Fig. 4). It was also

observed in the Arabidopsis experiment that leaf area,

rosette diameter, leaf number, height and stem diameter

were larger when biochar and fertilizer were combined,

compared with plants where fertilizer was applied with-

out biochar. Similarly, Steiner et al.(2007) grain produc-

tion was doubled when charcoal and biochar were

combined than fertilizer without biochar.

Although no obvious toxicity was observed even at

high rates of biochar (100 t ha1) in plants ofArabidopsis

and lettuce, a novel and unpredicted finding, revealed

by the microarray, was the consistent and large down-

regulation of a suite of genes known to control plant

defence and response to both biotic and abiotic stress.

There was a clear down-regulation in genes related to

jasmonates (defined to include biologically active inter-

mediates in the pathway for jasmonic acid biosynthesis),

as well as the biologically active derivatives of jasmonic

acid, JA (Turner et al., 2002) but also defence and sec-

ondary metabolism (Fig. 5b). Response to jasmonic acid

was a GO category that was significantly and highly

down-regulated in plants grown in biochar treatment

(Table S2). This phytohormone is involved in plant

immunity and resistance to abiotic stresses (Farmer

et al., 2003) and influences the expression of defence

genes. It is also more generally involved in the hyper-

sensitive response, including plant exposure to acute

concentrations of ozone (Rao et al., 2000). A number of

genes involved in JA biosynthesis and action were

down-regulated following biochar application, but more

importantly, the JAZ proteins, that are known to be tar-

gets of the SCFCOI1complex, the JA receptor, were also

down-regulated. This complex and its interaction with

theJAZ proteins, is central to JA biosynthesis perception

and signalling (Wasternack & Hause, 2013), enabling JA

induced gene expression to be initiated. JAZ acts as a

negative regulator of JA action, whilst MYC2 is a tran-

scription factor that promotes JA-responsive gene

expression, but both were down-regulated here. Other

examples of highly reduced gene expression after bio-

char application included the defensin genes such as

CHIB, THI2.1, PDF1.2, which when promoted enhanceresistance to different biotic stress (Penninckx et al.,

2003; Chan et al., 2005). Coupled to decreased JA bio-

synthesis and action, there was also evidence for bio-

char impacts on associated ethylene and salicylic acid

perception and signalling. For example, JA and ethylene

are known to act together to signal the expression of

PDF1.2(Pre et al., 2008), through the action of the AP2/

ERF domain transcription factor. We provide evidence

that this type of cross-talk exists for response to biochar

since several ERFs from the superfamily were affected,

although both up- and down-regulation were observed

(Table S2), confirming earlier findings that ERFs can

both negatively and positively regulate the expression

of PDF1.2 (Pre et al., 2008). Evidence for reduced sali-

cylic acid (SA) biosynthesis was also apparent with

FAMT reduced following biochar application, although

no regulatory genes involved in SA-JA cross-talk

responded to biochar application. Taken together, these

data provide powerful evidence that gene expression

related to plant immunity and defence was reduced fol-

lowing biochar application to soil. Very few data on

Table 4 (continued)

Class Name

Control

(0 t ha1)

Biochar

(50 t ha1) t-test

Kaempferol 3-O-arabinoside 7-O-rhamnoside 0.040 0.024


12/15

gene expression in plants following exposure to biochar

have been published to date and none on global gene

expression, to our knowledge, but the few data that are

available are for defence genes. In contrast with the data

provided here, a previous report suggests a positive role

for biochar in the Systemic Acquired Resistance (SAR)

of strawberry following fungal pathogen attacks (Eladet al., 2011; Meller Harel et al., 2012). The expression of

five defence genes including LOX was followed and

showed an up-regulation in genes related to defence in

response to biochar, conflicting with our results. How-

ever, the growth medium for the strawberries in this

prior work was coconut fibre and peat and the biochar

made from different feedstock to that reported here,

highlighting a need for future research to unravel these

different responses. In particular, Arabidopsis grown in

soil amended with biochar should be challenged with

pests and pathogens to test the validity of the idea that

their defense responses are impaired, including the

development of a dose-response relationship for the

efficacy of this effect.

A pressing question from this current study is how

application of biochar to the soil, results in the altered

expression of approximately 1000 genes in our model

system, leads to stimulated plant growth and possibly,

reduced plant immunity and defence. What are the key

signalling mechanisms? We can propose some potential

mechanisms given the extensive literature of the

impacts of altered gene expression and links to function

in the modelArabidopsis. It seems likely that the primary

effects of biochar on soil pH, potassium (K +), phospho-

rous (P) and nitrogen (N, Table 1), result in conditions

that enable the plant to take up more nutrients, perhaps

K+ in particular, but also P and N (Fig. 7). The conse-

quences of this would be an increased osmoticum inplant cells with reduced water potential triggering for

alter gene expression. When plants are exposed to K +

starvation, Armengaud et al. (2004) intriguingly, have

revealed that the most prominent response found was

for genes linked to jasmonic acid biosynthesis and

action, including many of those reported here and was

proposed as a novel signalling molecule to regulate

plant response to this stress. Following K+ resupply,

analogous to our high K+ biochar, gene expression cat-

egories found to be most sensitive and up-regulated

were the aquaporins including PIP1, and a TIP which

were also up-regulated here following biochar applica-

tion. Alongside this category, cell wall proteins and cal-

cium signalling molecules were most sensitive to K+

supply, again categories also highly sensitive to biochar.

It seems likely that these categories represent some of

the earliest responses to biochar. Similarly the most

prominent categories of genes down-regulated on

resupply of K+ were those related to JA biosynthesis.

There is therefore a striking similarity between our

results in biochar and those related to gene expression

Increased pH and availabilityof K+, P, N andpossibly C

Increased plant growthDecreased plant

immunity and defence

Jasmonicacid

Salicylicacid

Ethyleneinteraction

with JA

Secondarymetabolites

ROS Ca2+

Biochar application to soil

Early signalling events initiated

Water potentialdecreased

Possible increasedmicrobiological diversity

Defensins

K+, P uptake

Auxinsignallingand action

Brassino-steroids

Cell wallloosening

Cell wallproteins

Plant cellexpansion

Model of molecular processes underpinning plant response to biocharfollowing application to soil

PIP1, TIP2

JAZ/SCFCOI1, MYC2CIPK5, AKT2, RD20,ATPT2, CML38, EXO

GGT4, RBOH

PDF1.2

THI2.1, ATHCHIB,ASA1

ERF/AP2, ATHCHIB

AOS, LOX, APR3, AOC1, AOC4

TPS04, 4CL2, CYP83B1,OBP2, MBP1, LDOX, F3H

XTH9, ATEXLA1XTHs and ATEXLAs

AGP24, AGP7,AGP1, AGP20

IAA19, IAA6, SHY2Saur-like, CYP38B1BIM1, DWF4, EXL5

Fig. 7 A conceptual model to explain the early responses, signalling and altered gene expression following exposure ofArabidopssis

thaliana to biochar, derived from pyrolysis and proposed consequences for plant growth, and immunity and defence. Text in italics

represents changes likely from the literature on biochar but not measured here, whilst genes are those identified from analysis that

were significantly differentially expressed and are key to the proposed mechanisms.




13/15

following changes in K+ supply (Armengaud et al.,

2004), suggesting that similar signalling and response

pathways occur that explain our findings (Fig. 7). Fur-

ther evidence for this comes from a proposed role for

redox status and calcium signalling, with redox homeo-

stasis a highly up-regulated functional category in

response to biochar (Fig. 5) and several calmodulin

related proteins and Ca2+

sensors including CIPK5 andCIPK15, both down-regulated in biochar. Interaction

between protein kinases and calcium sensing proteins

(CBLs) has previously been shown to be central for reg-

ulating K+ uptake may be increased when plants are

exposed to K+ stress (Li et al., 2006; Liu et al., 2013).

Here, the K+ transporterAKT2, known to have a role in

K+ transport for source to sink (Lacombe et al., 2000)

was also down-regulated. Similar to our finding for K+

sensing and signalling, we also found a large suite of

genes previously associated with P starvation to be

down-regulated in our experiment. This suggests that

as with potassium, the plant is sensing available phos-

phate and moderating gene expression accordingly and

that this regulation involving transporters (atPT2), tran-

scription factors (PAP1), and a suite of other genes

(MGD2, SEN1,) may represent the up-stream sensing

and initiation of signalling that leads to the down-

stream impacts on growth and defence. The availability

of extensive mutant collections in Arabidopsis should

enable these ideas to be tested as single gene knock-

outs, for example for gene related to auxin biosynthesis

and Ca2+ signalling can be grown in biochar and their

response tested.

Taken together, our study showed that biochar, at an

application rate equivalent to 50

100 t ha1

, resulted inincreased plant growth for both the model plant Arabid-

opsis (leaf area, plant height and root growth) and for a

leafy crop, lettuce (leaf area, fresh and dry weight). For

the first time, we have quantified global gene expression

for biochar treated plants, with 507 genes up- and 571

genes down-regulated in response to biochar applica-

tion. From these gene expression data, we identified

auxin and brassinosteriod signalling as central for the

control of enhanced growth following biochar applica-

tion. Our data are limited in that they cannot conclu-

sively unravel the mechanistic understanding that links

increased soil pH, availability of soil K+ and P to bio-

char impacts but nevertheless, the literature provides

strong evidence that increased pH and K+ in particular,

could trigger a series of signalling and functional

changes in the plant that lead to enhanced cell expan-

sion regulated through auxin and brassinosteroid

action. Many of the genes that were down regulated

were related to plant immunity and defence and this

is a novel finding, contrary to a previous study

(Meller Harel et al., 2012). This highlights the complex

interaction between different plant, soil and biochar

types and suggests that future investigations are

required, at a range of biochar application rates and in

both model and crop plants, to determine if these

changes in gene expression related to defence, result in

reduced plant immunity and defence when plants are

subjected to pathogen and pest attack. Our measure-

ments of secondary metabolites, particularly glucosino-lates, flavonoids and flavonols, provide further support

for the idea that defence mechanisms may be impaired.

Future research should consider a much lower concentra-

tion of biochar, below 10 t ha1, as likely to be commer-

cially relevant. They should consider gene expression

studies that target signalling and metabolic pathways

involved in auxin, brassinosteriod and jasmonic acid

action, where cell expansion and cell wall biophysical

properties are used as indicator traits for impact of

biochar on growth and where metabolites linked to

plant defence are quantified in a wide range of tissues

when plants are subjected to abiotic and biotic stresses.

Acknowledgements

This research was supported by the Seventh Framework ForResearch of the European Commission within the projectEuroChar (Contract No 265179). We thank E. Miranda, C.Vidal, C. Zavalloni for assistance and A. Pozzi (AdvancedGasification Technology, AGT, Cremona, Italy) for providingthe biochar. Research in the laboratory of GT on bioenergyis also supported by NERC as part of the Carbo-BioCropproject (Grant reference number: NE/H010742/1).

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Supporting Information

Additional Supporting Information may be found in the online version of this article:

Figure S1.Hierarchical clustering of genes within the categories most responsive to biochar application, including Plant-type cellwall, Xyloglucan:xyloglucosyl transferase activity, Intrinsic to membrane, Response to jasmonic acid and Secondary metabolic pro-

cess.Figure S2.Comparison of log2expression values between microarray and real-time PCR for five candidate genes: ATERF15(ethyl-ene responsive element binding factor 15), LOX2(jasmonic acid biosynthesis),STP14(sugar transporter), EXO (phosphate respon-sive) andDIN10(raffinose metabolism).Figure S3. Complete view of the gene ontology (GO) interaction using the AgriGo analysis in representation of gene ontology forresponse to biochar application, identifying biological processes and cellular components most responsive to biochar applicationin a hierarchical image: (a) cell and growth response, (b) response to stimulus and (c) metabolic processes. In each box the GeneOntology term, adjusted p-value in brackets and GO description are given. Green boxes signify positive response to biochar andred boxes a negative response.Table S1. Significant genes differentially expressed between soil (control) and in soil plus 50 t ha1 biochar (biochar) (p < 0.05, 2-fold change difference) with Arabidopsis GeneChip ID, (Affymetrix, Santa Clara, USA), Log 2 fold change, Gene ontologies, andfunctional description.Table S2. PAGE analysis with significant Gene Ontology (GO) groups, describing for each a GO term name, a description of theGO term, the number of significant genes from the microarray within the GO term, the z-score (which is a positive or negativevalue from a two-tailed z-test, corresponding to either an up-regulation or a down-regulation of the genes present in the GO term)

and the False Discovery Rate (http://bioinfo.cau.edu.cn/agriGO).Table S3. List of genes represented in Fig. 6 with the ID number from the ArabidopsisGeneChip (Affymetrix, Santa Clara, USA),fold change between control and biochar, Log2, At number and a brief functional description.



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Viger, Hancock Et Al. 2014 - More Plant Growth but Less