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Malays. Appl. Biol. (2018) 47(5): 135–148
DE NOVO TRANSCRIPTOME SEQUENCING AND
IDENTIFICATION OF UPREGULATED GENES INVOLVED
IN PHENYLPROPANOID PATHWAY OF Acacia mangium
IN RESPONSE TO Ceratocystis INFECTION
NUR NABILAH ALIAS1*, NORLIA BASHERUDIN1, MOHD FAIZAL ABU BAKAR2,
SAMSUDDIN AHMAD SYAZWAN1, NORWATI MUHAMMAD1, MOHD FARID AHMAD
and MOHD ZAKI ABDULLAH
1Forest Research Institute Malaysia (FRIM), 52109 Kepong, Selangor
2Malaysia Genome Institute, Jalan Bangi, 43000 Kajang, Selangor
*E-mail: nabilah@frim.gov.my
Accepted 4 October 2018, Published online 30 November 2018
ABSTRACT
Vascular wilt disease, caused by Ceratocystis fungi is a major threat to Acacia mangium plantations in Southeast Asia.
Previous studies reported that the activation of key enzymes in phenylpropanoid pathway indicates plant defense response
towards pathogenic infection. Due to limited information on the defense mechanism of Acacia mangium against Ceratocystis,
transcriptome sequencing was performed to study A. mangium’s early defense mechanism upon infection. We sampled control
(non-inoculated) and infected (inoculated) A. mangium at four-time points (1, 5, 10 and 15 days post-inoculation (dpi)).
About 7,463 differentially expressed genes (DEGs) of which 164 unique transcripts with potential relevance to defense
mechanism were identified based on Gene Ontology (GO). From Kyoto Encyclopaedia of Genes and Genomes (KEGG)
analysis, ten key enzymes associated with phenylpropanoid pathway were upregulated after infection such as phenylalanine
ammonia-lyase (PAL), peroxidase (POD), cinnamyl alcohol dehydrogenase (CAD), caffeoyl-CoA O-methyltransferase
(CCoAOMT), cinnamoyl-CoA reductase (CCR), cinnamate 4-hydroxylase (C4H), phenylalanine/tyrosine ammonia-lyase
(PTAL), caffeic acid O-methyltransferase (COMT), O-hydroxycinnamoyl transferase (HCT) and 4-Coumarate-CoA ligase
(4CL). Eight of them were upregulated upon 15 dpi excluding HCT and 4CL. PAL, CAD, and POD transcripts were identified
to express higher in infected samples compared to control, showing their important defensive role of A. mangium against
Ceratocystis.
Key words: Acacia mangium, vascular wilt disease, Ceratocystis infection, differentially expressed genes,
transcriptomic defense mechanism
INTRODUCTION
Acacia mangium is known as one of the important
sources for pulp and paper industry in Southeast
Asia. Recently, A. mangium plantations in Malaysia,
Indonesia, and Vietnam have been infected by
Ceratocystis, fungi which causes vascular wilt
disease, the most devastating disease for A. mangium
(Brawner et al., 2015). Ceratocystis attack A.
mangium trees by entering the host through small
openings or wounds caused by animals like
elephant, wood-boring insects and unsound
silviculture practice (Mohd-Farid et al., 2015).
Ceratocystis would then kill the host cells and
tissue to derive nutrition from dead cells, proliferate
within the vascular tissue, disrupt water trans-
location and cause the typical wilt symptoms (Van
Wyk et al., 2007). Other symptoms of this disease
include canker, gummosis, blister lesions and
vascular discoloration of the woody tissues which
would lead to tree death within six months after
infection (Tarigan et al., 2011). Additionally,
studies by Mohd-Farid et al. (2017) reported that
Ceratocystis killed A. mangium seedlings within five
weeks after inoculation.
There are various defence approaches used
by plants to protect against pathogens, such as
through complicated perceiving, transducing and
exchanging signals (Verhage et al., 2010). Plants
respond to pathogen infection by activating certain
136 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
responses that have been implicated as mechanisms
of disease resistance (Loon et al., 2006). These
responses include the hypersensitive reaction,
synthesis of phytoalexins, proteinase inhibitors,
hydrolytic enzymes as well as increased production
and deposition of lignin into plant cell wall (León
& Montesano, 2013).
Secondary metabolites like phenylpropanoid,
play a fundamental role in the plant to fight against
invading pathogens (Hao et al., 2016). Several
studies of genes in phenylpropanoid pathway have
been conducted in Arabidopsis (Scheideler et al.,
2002), tomato (Kandan et al., 2002), rice (Duan et
al., 2013) and legume plants, including pea and
soybean (Zabala et al., 2006). These studies
demonstrated that phenylpropanoid pathway was
involved in plant defense response (Naoumkina et
al., 2010). However, such studies have never been
reported for A. mangium.
To date, there are numerous studies on plant
defense mechanisms using transcriptome approach
as it provides enhanced detection compared to
conventional approach like microarray and northern
blot analysis (Birch & Kamoun, 2000). In the past
few years, transcriptome sequencing has been
successfully used for plant-pathogen interaction
investigations in black pepper (Hao et al., 2016),
palm oil (Goh et al., 2014; Ho et al., 2016), oak
(Maboreke et al., 2016), banana (Bai et al., 2013),
soybean (Jain et al., 2016), and rice (Kawahara et
al., 2012). This technology is often used as more
genes can be sequenced in a shorter time with less
cost, provides a better estimation of absolute
expression levels and increases understanding of
plant stress response (Nibedita & Jolly, 2017).
Through these studies, numerous novel stress-
responsive genes have been successfully discovered
(Collinge & Boller, 2001; Bezier et al., 2002).
Presently, researchers were still unsuccessful in
developing an efficient controlling method for A.
mangium’s wilt disease as it is a soil-borne vascular
disease. Attempts to improve A. mangium resistance
to Ceratocystis through conventional breeding have
been unsuccessful too. It was found that the response
of A. mangium towards Ceratocystis infection is
complex because it involves biological and
physiological processes. Apart from that, there is
limited genetic information on anti-Ceratocystis in
A. mangium and only a few studies have addressed
the molecular mechanisms of A. mangium’s wilt
disease caused by Ceratocystis (Roux & Wingfield,
2009; Tarigan et al., 2011; Mandy & Wickneswari,
2014). In fact, deeper investigations and ample time
are required to understand the defense mechanism
of A. mangium against this infection.
In this study, transcriptome sequencing was
conducted on infected A. mangium at 1, 5, 10 and
15 days post-inoculation (dpi) as well as on non-
infected A. mangium (control) to understand the
early mechanism of Ceratocystis resistance in
this plant through molecular and bioinformatics
approaches. The role of induced defense responses
in A. mangium against Ceratocystis and identified
the expression patterns of genes encoding key
enzymes of phenylpropanoid pathway was also
investigated. The results generated in this study
were expected to provide fundamental information
for future plant development control and disease
resistance in A. mangium.
MATERIALS AND METHODS
Preparation of plant materials, RNA extraction
and transcriptome sequencing
Five Acacia mangium seedlings with heights
of one meter each, kindly provided by FRIM
Pathology Nursery were used as study materials.
Four seedlings were inoculated with artificial
Ceratocystis manginecans on their stems and were
left over a period of 1, 5, 10 and 15 days respectively
while one non-inoculated seedling was used as a
control. Stem samples from five seedlings were
collected at each sampling time point, frozen in
liquid nitrogen and stored in -80°C freezer. Total
RNA from inoculated and non-inoculated stems
were extracted using combination method of RNeasy
Plant Mini Kit (Qiagen, USA) and Fruit-mateTM
(Takara, Shiga, Japan). The RNA integrity and
quantification were verified using Agilent 2100
BioAnalyzer (Agilent Technologies, Santa Clara,
CA, USA) with the minimum RNA integrated
number (RIN) value of 8 (Bharudin et al., 2014). The
cDNA libraries were constructed using Illumina
TruSeq RNA Sample Preparation Kit Protocol and
sequencing was done on Illumina HiSeq 4000
platform at Beijing Genomics Institute (BGI).
Pre-processing analysis and de novo
transcriptome assembly
The quality of the raw transcriptome reads of
inoculated and non-inoculated A. mangium was
checked using FastQC (Andrews, 2010). The
sequences had undergone pre-processing analysis
using SolexaQA++ (Cox et al., 2010) to filter
sequences with a low quality value of less than
QV20 and discard sequences with less than 50 bp
in length. The reads were then screened for
contamination by aligning onto phiX library using
Bowtie2 tool (Langmead & Salzberg, 2012). De
novo transcriptome assembly of the cleaned paired-
end reads was performed using Trinity RNA-Seq
v2.4.0 with default parameters (Grabherr et al.,
2011).
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 137
Identification of differentially expressed genes
(DEGs)
In order to identify the differentially expressed
genes (DEGs), each individual libraries of
inoculated and non-inoculated A. mangium were
mapped back to the assembled transcript using
Bowtie2 (Langmead & Salzberg, 2012). Transcript
abundance was estimated using RNA-seq by
Expectation Maximization (RSEM) software
(Li & Dewey, 2011). RSEM will generate two
files which are ‘RSEM.isoforms.results’ and
‘RSEM.genes.results’. Subsequently, the DEGs were
identified using edgeR with default parameters
(Robinson et al., 2010). Transcripts with the FDR
value of < 0.01 were considered as significant.
Additionally, significant transcripts with the log
fold-change value logFC > 2 were marked as up-
regulated transcripts and logFC < -2 as down-
regulated transcripts. The Fragments per Kilobase
of transcript per Million fragments mapped
(FPKM) values across samples were normalized
with Trimmed Mean of M-values (TMM) method
and the distribution of DEGs was visualized in MA
and volcano plot.
Functional annotation of transcripts
The annotation of DEGs was carried out using
Blast2GO version 4.19 (Gotz et al., 2008) to obtain
the Gene Ontology (GO) term for the transcripts, thus
describing the biological process and molecular
function of cellular components. BLASTX against
NCBI non-redundant (nr) sequence database was
conducted with cut-off E-value < 1E-05. The Kyoto
Encyclopaedia of Genes and Genomes (KEGG), a
pathway-based analysis, was performed to acquire
pathway information for all the annotated
sequences, enabling further understanding on the
biological functions of genes.
Discovery and evaluation of phenylpropanoid
pathway genes
From KEGG analysis, a collection of genes
encoding enzymes involved in phenylpropanoid
pathway were identified. The expression analysis, as
well as the transcriptional level of phenylpropanoid
pathway genes, were studied based on their FPKM
values. Transcripts with FPKM <1 were considered
as not being expressed in a particular condition.
Sequence validation was performed by searching the
protein sequences of selected genes from different
plant species; Arabidopsis thaliana, Zea mays and
Oryza sativa, obtained from NCBI protein database.
The transcripts were also undergone validation of
open reading frame using NCBI ORFinder tool.
Validation of RNA-seq data by RT-qPCR
Three candidate genes that involved in
phenylpropanoid pathway were selected to validate
the RNA-seq data by performing quantitative real-
time PCR (RT-qPCR). Glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) was selected as the
reference gene to normalize the expression of target
genes in the infected seedlings relative to the
control. Gene-specific primers with amplicon length
ranging from 150 to 250 bp (Table 1) were designed
using Primer-BLAST (Ye et al., 2012). All the
designed primers were tested for their efficiency
using standard curve real-time PCR.
The same RNA extracts as for RNA-seq
experiments were used in this analysis. The
concentration and quality of RNA extracts was
determined by NanoDrop 2000 Spectrophotometer
(Thermo Fisher Scientific, USA) and Agilent 2100
BioAnalyzer (Agilent Technologies, Santa Clara,
CA, USA). The cDNA strand was first synthesized
using High Capacity RNA-to-cDNA Master Mix
(Applied Biosystems, USA). Then, the qPCR assays
were performed on Fast Real-Time PCR System
(Applied Biosystems, USA) by using the SYBR
Select Master Mix (Applied Biosystems, USA),
following the manufacturer protocol. The qPCR
parameters were set as following: 1 cycle at 50°C
for 2 min and 95°C for 10 min, followed by another
40 cycles of 95°C for 15 s and 60°C for 1 min.
The relative quantification of each gene was
determined using the comparative ΔΔCT method
(Livak & Schmittgen, 2001). The ΔΔCT values
(ΔCT of test sample – ΔCT of calibrator sample)
Table 1. Description of primers used in quantitative reverse transcription PCR (RT-qPCR) analysis
Gene identity Primer sequence (5' to 3') Amplicon length
GAPDH (Forward) 5’-GGCCTTCCCTATTCCTTCTATG-3’ 161
GAPDH (Reverse) 5’-AGTCAGTGGACTTCACATCTTC-3’ 161
PAL (Forward) 5’-CGCACTAGAGAATGGCGATAA-3’ 207
PAL (Reverse) 5’-CCCAGATCCTCTCTCACAAAC-3’ 207
POD (Forward) 5’-ATACGTTTGGGAGAGCAAGG-3’ 174
POD (Reverse) 5’-TATCGGGAGTTGTGGGATCTA-3’ 174
CAD (Forward) 5’-GTTTATTGCACGAAGGGATCAG-3’ 192
CAD (Reverse) 5’-GCGCATCATCGGAGAATAGA-3’ 192
138 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
Table 2. Summary of the results obtained of each cDNA library sequenced. Results show
the number of paired reads (raw reads) of each condition, the number of cleaned reads
left after trimming with SolexaQA++ and the percentage left after trimming. Dpi = days post
infection
Condition Number of paired reads Number of cleaned reads Cleaned
(raw reads) (Pre-processed reads) (%)
Control 29,733,282 26,592,141 89.44
1 dpi 29,557,612 26,360,628 89.18
5 dpi 39,243,516 35,512,484 90.49
10 dpi 28,820,256 25,785,879 89.47
15 dpi 30,325,270 27,304,208 90.04
Total 157,679,936 141,555,340 89.77
Table 4. Pairwise comparison of differentially expressed genes
Number of differentially expressed transcripts
Ctrl-1 dpi Ctrl-5 dpi Ctrl-10 dpi Ctrl-15 dpi
Upregulated 697 1,185 920 1,507
Downregulated 405 924 734 1,092
Total 1,102 2,109 1,654 2,599
Table shows the numbers of differentially expressed transcripts in
Acacia mangium
at different days
post-inoculation (dpi) following pairwise comparisons. Control versus 1-day post-inoculation (Ctrl-1
dpi), Control versus 5 days post-inoculation (Ctrl-5 dpi), Control versus 10 days post-inoculation
(Ctrl-10 dpi) and Control versus 15 days post-inoculation (Ctrl-15 dpi). FDR cut-off < 0.01.
Table 3. Basic statistics of
de novo
assembly using Trinity
Number of transcripts 587,654
Percentage of GC (%) 42.58
N50 transcript 1,530
Mean length of transcripts (bp) 905
Longest transcript (bp) 15,603
Smallest transcript (bp) 201
represent the difference in the expression after being
normalized to internal control and relative to a
calibrator. The calibrator is normally an untreated
sample or the sample with the lowest CT value. The
relative expression (RQ) of the target genes was
calculated using the equation of 2–ΔΔCT while the
fold changes were expressed as log of RQ values.
Venn diagram was constructed to represent
overlapping and non-overlapping expression of
significantly differentially expressed genes
according to Oliveros (2007).
RESULTS AND DISCUSSION
Transcriptome sequencing and de novo assembly
To generate the transcriptome of A. mangium,
five cDNA libraries were prepared from a non-
inoculated sample and four inoculated samples at
four different time points (1, 5, 10 and 15 days post-
inoculation (dpi)) which were then subjected to
paired-end sequencing using the Illumina HiSeq
4000 platform. After filtering adapter sequences and
discarding low-quality reads using SolexaQA++, a
total of 141,555,340 high-quality paired-end reads
from 157,679,936 raw reads with a mean length of
100 bp were obtained (Table 2). Using the Trinity
program, the de novo transcriptome assembly of the
remaining high-quality reads yielded 587,654
transcripts with an N50 length of 1530 bp. Trinity
was found to be effective in reconstructing the
transcriptome, inclusive of the splicing and
duplication events. The basic statistics of the
libraries were summarized in Table 3.
Identification of differentially expressed genes
(DEGs)
A total of 7,464 differentially expressed genes
(DEGs) were identified, of which 1,102 were
between Ctrl-1 dpi (697 up-regulated and 405 down-
regulated), 2,109 between Ctrl-5 dpi (1,185 up-
regulated and 924 down-regulated), 1,654 between
Ctrl-10 dpi (920 up-regulated and 734 down-
regulated) and 2,599 between Ctrl-15 dpi (1,507 up-
regulated and 1,092 down-regulated). This showed
that the total number of DEGs was the highest in
Ctrl-15 dpi compared to the other groups. The
numbers of the DEGs obtained were tabulated in
Table 4.
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 139
The distribution of upregulated and down-
regulated DEGs of each group were presented in MA
and Volcano plot (Figure 1). The highest proportion
of upregulated and downregulated genes can be
observed in Ctrl-15 dpi whereas the lowest was in
Ctrl-1 dpi. For MA-plot, log fold change (logFC) was
plotted on the y-axis while the average of the counts
normalized by size factor (logCounts) was shown on
the x-axis. Each gene was denoted with a dot. The
dots that were highlighted in red indicate DEGs with
FDR < 0.01. For volcano plot, the x-axis specifies
the logFC between two conditions while y-axis
specifies negative logarithm to the base 10 of false
discovery rate (-log10FDR). LogFC > 2 indicates
Fig. 1. The MA and Volcano plots, showing the proportion of upregulated and
downregulated DEGs. Comparisons across samples. (a) Control versus 1-day post-
inoculation (b) Control versus 5-days post-inoculation (c) Control versus 10-days post-
inoculation and (d) Control versus 15-days post-inoculation.
140 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
transcript level increased by >100% (upregulated)
whereas logFC < -2 indicates transcript levels
reduced by >50% (downregulated). The black dots
represent transcripts in which their expression levels
did not reach statistical significance.
Functional annotation and gene ontology (GO)
analysis
Gene ontology (GO) analysis was conducted to
further explore potential functions and metabolic
pathways of selected DEGs in response to
Ceratocystis infection. About 164 unique transcripts
out of 4,309 upregulated DEGs were discovered to
have potential relevance to defense mechanism.
According to Figure 2 and Figure 3, group Ctrl-15
dpi has the highest number of transcripts with that
function, representing 65 transcripts (36%) followed
by Ctrl-10 dpi (51 transcripts, 28%), Ctrl-5 dpi
(44 transcripts, 25%) and Ctrl-1 dpi (19 transcripts,
11%). The 19 unique transcripts that were expressed
as early as 1 dpi were found to be crucial as an early
defense mechanism of A. mangium against
Ceratocystis. Majority of the transcripts upregulated
during this stage were involved in glucosinolate
biosynthesis and tryptophan metabolism. The
accumulation of glucosinolates was induced in
response to a variety of biological stresses, for
instance, pathogen infection (Tierens et al., 2001).
This secondary metabolite has been proven to act
as a defensive barrier in plants (Seo et al., 2017).
Interestingly, 15 transcripts were expressed in
common between these four groups of comparison.
The other 22, 8, 14 and three transcripts were
exclusively found in Ctrl-15 dpi, Ctrl-10 dpi, Ctrl-
5 dpi and Ctrl-1 dpi, respectively. These 22 unique
transcripts discovered from Ctrl-15 dpi plays
important defensive role of A. mangium against
Ceratocystis as the majority of them were
involved in glycerolipid metabolism, ADP binding,
isocitrate dehydrogenase (NADP+) activity and
phenylpropanoid biosynthetic (Table 5) which
modulates the expression of defense gene and resists
pathogen infection (Kachroo et al., 2004; DeYoung
& Innes, 2007; Mhamdi et al., 2010; Mutuku &
Nose, 2012). In addition, the number of transcripts
involved to fight the infection was noticeably
increased as the strength of infection increased.
Analysis of phenylpropanoid pathway genes
during Ceratocystis infection
In the transcriptome data, 143 upregulated DEGs
were mapped to phenylpropanoid pathway with nine
transcripts during 1 dpi, 47 transcripts during 5 dpi,
38 transcripts during 10 dpi and 49 transcripts
Fig. 2. Venn diagram of unique transcripts with potential
relevance to defense mechanism at four different post-
inoculation periods.
Fig. 3. Number of unique transcripts with potential relevance to defense mechanism at four
different post-inoculation periods.
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 141
Table 5. Summary of 22 unique transcripts with potential relevance to defense mechanism discovered from Ctrl-15 dpi
Transcript_ID Transcript Description GO
TRINITY_DN59861_c0_g2_i1 Isocitrate dehydrogenase [NADP] Isocitrate dehydrogenase
(NADP+) activity
TRINITY_DN60659_c0_g5_i3 Stress-induced SAM22-like Defense response
TRINITY_DN60454_c0_g3_i2 Glycerol kinase Glycerolipid metabolism
TRINITY_DN59566_c0_g1_i4 Cysteine-rich receptor kinase 25 Defense response
TRINITY_DN60040_c0_g1_i12 Accelerated cell death 6-like Defense response
TRINITY_DN65513_c1_g4_i3 Thaumatin 1 Defense response
TRINITY_DN66396_c0_g1_i12 Homolog of mammalian lyst-interacting protein 5 Defense response
TRINITY_DN71161_c3_g1_i8 Probable disease resistance At5g66900 Defense response
TRINITY_DN59776_c1_g1_i3 Cysteine-rich receptor kinase 25 Defense response
TRINITY_DN65513_c1_g4_i2 Thaumatin 1 Defense response
TRINITY_DN59861_c0_g2_i4 Isocitrate dehydrogenase [NADP] Isocitrate dehydrogenase
(NADP+) activity
TRINITY_DN66684_c2_g3_i5 Allene oxide synthase Defense response
TRINITY_DN57017_c0_g1_i8 Oxalate-ligase Defense response
TRINITY_DN70955_c3_g5_i3 NBS-LRR type disease resistance ADP binding
TRINITY_DN65988_c0_g4_i9 Disease resistance response 206-like Phenylpropanoid biosynthetic
TRINITY_DN61910_c0_g5_i2 NBS-LRR type disease resistance ADP binding
TRINITY_DN55992_c5_g1_i1 Disease resistance response 206-like Phenylpropanoid biosynthetic
TRINITY_DN65862_c1_g1_i3 Disease resistance response 206-like Phenylpropanoid biosynthetic
TRINITY_DN66343_c0_g1_i1 Disease resistance At1g50180 ADP binding
TRINITY_DN52218_c0_g1_i3 Pathogenesis-related genes transcriptional DNA binding
activator PTI6-like
TRINITY_DN53602_c1_g1_i1 Pathogenesis-related genes transcriptional DNA binding
activator PTI5-like
TRINITY_DN56706_c0_g1_i14 Pathogenesis-related 1-like Extracellular region
during 15 dpi. It was observed that majority of the
upregulated phenylpropanoid transcripts were
regulated at 15 dpi. The induction of enzymes in
phenylpropanoid pathway is often linked to the
high production of phenols and lignin which are the
factors contributing to the resistance of the plant
cell (Zhang et al., 1997).
Based on KEGG analysis, ten genes were
identified to be involved in phenylpropanoid
pathway (Figure 4) which were EC:1.11.1.7 -
peroxidase (POD), EC:1.1.1.195 - Cinnamyl-alcohol
dehydrogenase (CAD), EC:2.3.1.133 - O-
hydroxycinnamoyl transferase (HCT), EC:6.2.1.12 -
4-coumarate-CoA ligase (4CL), EC:1.14.13.11 -
Cinnamate 4-hydroxylase (C4H), EC:4.3.1.24 -
Phenylalanine ammonia-lyase (PAL), EC:4.3.1.25 -
Phenylalanine/tyrosine ammonia-lyase (PTAL),
EC:2.1.1.68 - Caffeic acid O-methyltransferase
(COMT), EC:2.1.1.104 - Caffeoyl-CoA O-
methyltransferase (CCoAOMT) and EC:1.2.1.44 -
Cinnamoyl-CoA reductase (CCR). Each of them was
upregulated at different dpi. According to Govender
et al. (2017), the phenylpropanoid pathway begins
with the deamination of L-phenylalanine into
cinnamic acid by phenylalanine ammonia lyase
(PAL) enzyme. The putative cinnamic acid
undergoes a series of reduction processes catalyzed
by the cinnamyl alcohol dehydrogenase (CAD) and
cinnamoyl-CoA reductase (CCR) enzymes in order
to produce hydroxyphenyl alcohols, known as
monolignols (Eynck et al., 2012). The biosynthesis
of monolignols is also associated with O-
hydroxycinnamoyl transferase (HCT) enzyme
(Ralph, 2010). Lastly, the polymerization of
monolignols catalyzed by peroxidase (POD) enzyme
will produce lignin (Higuchi, 1990; Boudet, 2000;
Donaldson, 2001; Boerjan et al., 2003; Vanholme
et al., 2008; Tu et al., 2010).
Xu et al. (2011) reported that the key enzymes
that make up the entry for phenylpropanoid pathway
were PAL, C4H and, 4CL. Subsequently, the
pathway will be divided into three specific branch
142 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
Fig. 4. KEGG map: Phenylpropanoid pathway (Map00940). Ten genes were identified in this pathway; EC:1.11.1.7 - peroxidase (POD), EC:1.1.1.195 - Cinnamyl-alcohol
dehydrogenase (CAD), EC:2.3.1.133 - O-hydroxycinnamoyl transferase (HCT), EC:6.2.1.12 - 4-coumarate-CoA ligase (4CL), EC:1.14.13.11 - Cinnamate 4-hydroxylase
(C4H), EC:4.3.1.24 - Phenylalanine ammonia-lyase (PAL), EC:4.3.1.25 - Phenylalanine/tyrosine ammonia-lyase (PTAL), EC:2.1.1.68 - Caffeic acid O-methyltransferase
(COMT), EC:2.1.1.104 - Caffeoyl-CoA O-methyltransferase (CCoAOMT) and EC:1.2.1.44 - Cinnamoyl-CoA reductase (CCR).
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 143
pathways for the formation of lignin, anthocyanins
and, flavonoids (Govender et al., 2017). From the
obtained results tabulated in Table 6, it was
discovered that majority of the phenylpropanoid
pathway genes (excluding 4CL and HCT) were
upregulated after 15 days of inoculation whereas
only three genes were upregulated upon one dpi,
namely POD, CAD, and HCT. Interestingly, the 4CL
gene appeared to accumulate significantly by five
days after inoculation and started to downregulate
upon 10 days dpi. In contrast, the upregulation of
POD gene can be observed at every stage of dpi.
Additionally, the inoculation with Ceratocystis at
10 and 15 dpi had induced PAL, PTAL, COMT and
CCoAOMT gene in A. mangium. It can be concluded
that some of the 10 identified genes in this pathway
exhibited both up and downregulated expression
pattern across different dpi.
Comparison expression levels of phenylpropanoid
pathway transcripts between Ceratocystis infected
A. mangium and control
The expression levels of phenylpropanoid
pathway transcripts in Ceratocystis infected A.
mangium and control sample were determined using
FPKM method (Table 7). In non-infected A. mangium
(control), the POD, PAL, and CCR transcripts were
not expressed (FPKM = 0). However, upon 1 dpi, the
POD and PAL transcript started to increase by 0.53
and 0.25 FPKM, respectively while CCR remains 0
(not expressed at all). At 5 dpi, the expression of
PAL and POD transcripts increased to 3.32 and 3.19
FPKM respectively. Both transcripts increased
further after 10 and 15 dpi. The results showed that
the level of POD and PAL were significantly higher
in infected A. mangium (inoculated samples)
compared to control. However, the CCR gene
Table 7. The expression patterns of phenylpropanoid pathway genes based on FPKM value before and after
Ceratocystis
infection
Genes Selected transcripts FPKM value
Control 1 dpi 5 dpi 10 dpi 15 dpi
POD TRINITY_DN57960_c0_g2_i3 0 0.53 3.19 5.23 8.34
CAD TRINITY_DN60218_c0_g2_i3 3.02 6.96 7.19 7.53 8.13
HCT TRINITY_DN60390_c0_g1_i1 82.46 84.34 41.51 59.43 86.36
4CL TRINITY_DN68236_c0_g1_i13 142.16 107.75 79.97 63.89 61.94
C4H TRINITY_DN65240_c4_g2_i11 859.59 500.66 359.31 308.47 284.73
PAL TRINITY_DN65788_c1_g1_i5 0 0.25 3.32 3.97 24.54
PTAL TRINITY_DN65788_c1_g1_i9 165.82 123.75 109.62 79.77 91.04
COMT TRINITY_DN60523_c0_g1_i1 593.96 291.04 332.66 417.74 428.81
CCoAOMT TRINITY_DN61067_c3_g1_i11 14.47 0.09 0.78 14.33 23.37
CCR TRINITY_DN70778_c7_g2_i1 0 0 0.06 0.33 1.37
Results show the expression of phenylpropanoid pathway genes before and after
Ceratocystis
infection. Genes with FPKM <1 were considered
as not expressed in a particular condition.
Table 6. Upregulation and downregulation of phenylpropanoid pathway genes during
Ceratocystis
infection
Genes Enzyme code 1 dpi 5 dpi 10 dpi 15 dpi
POD EC:1.11.1.7 / / / /
CAD EC:1.1.1.195 / / X /
HCT EC:2.3.1.133 / / X X
4CL EC:6.2.1.12 X / X X
C4H EC:1.14.13.11 X / / /
PAL EC:4.3.1.24 X X / /
PTAL EC:4.3.1.25 X X / /
COMT EC:2.1.1.68 X X / /
CCoAOMT EC:2.1.1.104 X X / /
CCR EC:1.2.1.44 X / X /
Results show the upregulation and downregulation of phenylpropanoid genes at different days post
inoculation (dpi). / = upregulated; X = downregulated.
144 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
remained relatively lowest in both control and
infected samples.
Additionally, transcripts of POD, CAD and PAL
were highly expressed in infected A. mangium
compared to the control. In contrast, the 4CL, C4H,
PTAL, and COMT expressed higher in control than
in infected samples. The results were comparable to
the previous study by Mackay et al. (1997) which
demonstrated that the total lignin content of mutant
Pinus taeda increased as the expression of CAD
increased.
According to Zang et al. (2015), phenylalanine
is the precursor in complex phenylpropanoid
pathway. In this present study, Figure 5 presented
that both PAL and POD genes were collectively
expressed at early stages of Ceratocystis infection
(1 and 5 dpi). Between these two genes, the
transcript level of POD was higher at 1 dpi, however,
at 5 dpi, PAL showed higher expression. The
transcript of POD consistently showed higher
expression than PAL at 10 and 15 dpi. Fagerstedt et
al. (2010) reported that POD gene polymerized
individual monolignols to form complex lignin. In
this study, the transcript of POD increased greatly
after inoculation of Ceratocystis which showed
that this gene played a significant role in the
biosynthesis of lignin in A. mangium seedlings
during defense response against Ceratocystis.
Previous studies had proved that the inoculation of
the pathogen in resistant cucumber, potato and,
tobacco plants had induced a greater increase of
POD gene level (Alcazar et al., 1995). Additionally,
Hiraga et al. (2000) reported that the POD was
upregulated in rice upon environmental stimuli or
prior attack by pathogens which render the crop with
self-defense mechanism against physical, chemical
and biological stresses.
Validation of gene expression pattern by RT-qPCR
To experimentally validate the expression
pattern of phenylpropanoid pathway genes, three
genes (PAL, POD and CAD) were selected for RT-
qPCR analysis. The RT- qPCR results (Figure 6)
clearly demonstrated that the expression level of
PAL, POD and CAD increased gradually throughout
the sampling points (1, 5, 10 and 15 dpi).
Additionally, the PAL gene showed the highest
relative expression, followed by POD and CAD
genes at 15 dpi. Overall, the RT- qPCR results of
these three genes showed general agreement with
RNA-seq results in term of their transcript
abundance changes, thus proving the reliability of
the transcriptome profiling data.
CONCLUSION
Identification of phenylpropanoid pathway genes
in susceptible Acacia mangium in response to
Ceratocystis infection was one of the first known
study. This study reported the comprehensive
identification of ten phenylpropanoid pathway
genes upon Ceratocystis infection through de
novo transcriptome assembly, differential gene
expression, and functional annotation analysis. It
was discovered that most of the phenylpropanoid
pathway genes were upregulated upon 15 days post-
inoculation, indicating highest defence response of
A. mangium towards Ceratocystis infection during
this stage. This study also identified that PAL, CAD
Fig. 5. Expression patterns of PAL, POD and CAD transcripts in Ceratocystis infected Acacia
mangium seedlings at 1, 5, 10 and 15 days post-inoculation (dpi) and control sample based on FPKM
values. Bars represent the mean ± standard error.
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 145
and POD genes involved greatly in the biosynthesis
of lignin, thus played the important defensive role
of A. mangium against Ceratocystis.
ACKNOWLEDGEMENTS
We thank Ministry of Natural Resources and
Environment (NRE) and Forest Research Institute of
Malaysia (FRIM) for the fund and support. We also
thank Malaysia Genome Institute (MGI) for the
assistance in bioinformatics analysis as well as FRIM
Genetic Laboratory members and Pathology
Laboratory members for their technical assistance.
REFERENCES
Alcazar, M.D., Egea, C. & Espin, A. 1995.
Peroxidase isoenzymes in the defence response
of Capsicum annuum to Phytophthora capsici.
Plant Physiology, 94: 736-742.
Andrews, S. 2010. FastQC: a quality control tool for
high throughput sequence data. Available online
at http://www.bioinformatics.babraham.ac.uk/
projects/fastqc.
Bai, T., Xie, W., Zhou, P., Wu, Z., Xiao, W., Zhou,
L. & Li, H. 2013. Transcriptome and expression
profile analysis of highly resistant and
susceptible banana roots challenged with
Fusarium oxysporum f. sp. cubense. Tropical
Race 4. PLoS ONE, 8(9): e73945.
Bezier, A., Lambert, B. & Baillieul, F. 2002. Study
of defence-related gene expression in grapevine
leaves and berries infected with Botrytis cinerea.
European Journal of Plant Pathology, 108:
111-120.
Bharudin, I., Zaki, N.Z., Abu Bakar, F.D., Mahadi,
N.M., Najimudin, N., Illias, R.M. & Murad,
A.M.A. 2014. Comparison of RNA extraction
methods for transcript analysis from the
psychrophilic yeast, Glaciozyma antarctica.
Malaysian Applied Biology, 43(2): 71-79.
Birch, P.R.J. & Kamoun, S. 2000. Studying
interaction transcriptomes: analyses of gene
expression during plant-microbe interactions.
Trends in Plant Science. Supplement: Life
Science Research in the 21st Century: A Trends
Guide. pp. 77-82.
Boerjan, W., Ralph, J. & Baucher, M. 2003. Lignin
biosynthesis. Annual Review of Plant Biology,
54: 519-546.
Fig. 6. Relative expression of PAL, POD and CAD genes based on GAPDH as the reference housekeeping
gene. The relative expression for RT-qPCR was calculated by using comparative ΔΔCT method.
146 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
Boudet, A. 2000. Lignins and lignification: selected
issues. Plant Physiol. Biochem, 38: 81-96.
Brawner, J., Japarudin, Y., Lapammu, M., Rauf, R.
Boden D. & Wingfield, M.J. 2015. Evaluating
the inheritance of Ceratocystis acaciivora
symptom expression in a diverse Acacia
mangium breeding population. Southern
Forests, 77 (1): 83-90.
Collinge, M. & Boller, T. 2001. Differential
induction of two potato genes, Stprx2 and
StNAC in response to infection by Phytophthora
infestans and to wounding. Plant Molecular
Biology, 46: 521-526.
Cox, M.P., Peterson, D.A. & Biggs, P.J. 2010.
SolexaQA: At-a-glance quality assessment of
Illumina second-generation sequencing data.
BMC Bioinformatics, 11: 485.
DeYoung, B.J. & Innes, R.W. 2007. Plant NBS-LRR
proteins in pathogen sensing and host defense.
Nature Immunology, 7(12): 1243-1249.
Donaldson, L.A. 2001. Lignification and lignin
topochemistry – an ultrastructural view.
Phytochemistry, 57: 859-873.
Duan, C., Yu, J., Bai, J., Zhu, Z. & Wang, X. 2013.
ScienceDirect Induced defense responses in
rice plants against small brown planthopper
infestation. The Crop Journal, 2(1): 55-62.
Eynck, C., Seguin-swartz, G., Clarke, W.E. & Parkin,
I.A.P. 2012. Monolignol biosynthesis is
associated with resistance to Sclerotinia
sclerotiorum in Camelina sativa. Molecular
Plant Pathology, 52: 186-194.
Fagerstedt, K.V., Kukkola, E.M., Koinstinen, V.V.,
Takahashi, J. & Marjamaa, K. 2010. Cell wall
lignin is polymerized by class III secretable
plant peroxidase in Norway spruce. Journal of
Intergrative Plant Biology, 52: 186-194.
Goh, Y.K., Ng, F.W., Kok, S.M., Goh, Y.K. & Goh,
K.J. 2014. Aggressiveness of Ganoderma
boninense isolates on the vegetative growth of
oil palm (Elaeis guineensis) seedlings at
different ages. Malaysian Applied Biology,
43(2): 11-16.
Gotz, S., Garcia-Gomez, J.M., Terol, J., Williams,
T.D., Nagaraj, S.H., Nueda, M.J. & Conesa, A.
2008. High-throughput functional annotation
and data mining with the Blast2GO suite.
Nucleic Acids Research, 36(10): 3420-3435.
Govender, N.T., Mahmood, M., Seman, I.A. & Wong,
M.Y. 2017. The phenylpropanoid pathway and
lignin in defense against Ganoderma boninense
colonized root tissues in oil palm (Elaeis
guineensis Jacq.). Frontier Plant Science, 8:
1395.
Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z.,
Thompson, D.A., Amit, I. & Regev, A. 2011.
Trinity: reconstructing a full-length transcriptome
without a genome from RNA-Seq data. Nature
Biotechnology, 29(7): 644-652.
Hao, C., Xia, Z., Fan, R., Tan, L., Hu, L., Wu, B. &
Wu, H. 2016. De novo transcriptome sequencing
of black pepper (Piper nigrum L.) and analysis
of genes involved in phenylpropanoid meta-
bolism in response to Phytophthora capsici.
BMC Genomics, 17: 822.
Higuchi, T. 1990. Lignin biochemistry: biosynthesis
and biodegradation. Wood Science Technology,
24: 23-63.
Hiraga, S., Yamamoto, K., Ito, H., Sasaki, K., Matsui,
H., Honma, M., Nagamura, Y., Sasaki, T. &
Ohashi, Y. 2000. Diverse expression profiles of
21 rice peroxidase genes. FEBB Letters, 471(2):
245-250.
Ho, C.L., Tan, Y.C., Yeoh, K.A., Ghazali, A.K., Yee,
W.Y. & Hoh, C.C. 2016. De novo transcriptome
analyses of host-fungal interactions in oil palm
(Elaeis guineensis Jacq.). BMC Genomics, 17:
66.
Jain, S., Chittem, K., Brueggeman, R. & Osorno, J.M.
2016. Comparative transcriptome analysis
of resistant and susceptible common bean
genotypes in response to soybean cyst nematode
infection. PLoS ONE, Volume: 1-21.
Kachroo, A., Venugopal, S.C., Lapchyk, L., Falcone,
D., Hildebrand, D. & Kachroo, P. 2004. Oleic
acid levels regulated by glycerolipid meta-
bolism modulate defense gene expression in
Arabidopsis. Proceedings of the National
Academy of Sciences, 101(14): 5152-5157.
Kandan, A., Commare, R.R., Nandakumar, R.,
Ramiah, M., Raguchander, T. & Samiyappan, R.
2002. Induction of phenylpropanoid meta-
bolism by Pseudomonas fluorescens against
tomato spotted wilt virus in tomato. Folia
Microbiologica, 47(2): 121-129.
Kawahara, Y., Oono, Y., Kanamori, H., Matsumoto,
T. & Itoh, T. 2012. Simultaneous RNA-seq
analysis of a mixed transcriptome of rice and
blast fungus interaction. PLoS ONE, 7(11): 1-
15.
Langmead, B. & Salzberg, S.L. 2012. Fast gapped-
read alignment with Bowtie 2. Nature Methods,
9(4): 357-359.
León, I.P. & Montesano, M. 2013. Activation of
defense mechanisms against pathogens in
mosses and flowering plants. International
Journal of Molecular Sciences, 14: 3178-3200.
PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION 147
Li, B. & Dewey, C.N. 2011. RSEM/: accurate
transcript quantification from RNA-Seq data
with or without a reference genome. BMC
Bioinformatics, 12: 323.
Livak, K.J. & Schmittgen, T.D. 2001. Analysis of
relative gene expression data using real-time
quantitative PCR and the 2–ΔΔCT Method.
METHODS, 25: 402-408.
Loon, L.C., Rep, M. & Pieterse, C.M.J. 2006.
Significance of inducible defense-related
proteins in infected plants. Annual Review of
Phytopathology, 44: 135-162.
Maboreke, H.R., Feldhahn, L., Bönn, M., Tarkka,
M.T., Buscot, F., Herrmann, S. & Ruess, L. 2016.
Transcriptome analysis in oak uncovers a strong
impact of endogenous rhythmic growth on the
interaction with plant-parasitic nematodes.
BMC Genomics, Volume: 1-16.
Mackay, J.J., O’Malley, D.M., Presnell, T., Booker,
F.L., Campbell, M.M. & Whetten, R.W. 1997.
Inheritance, gene expression and lignin
characterization in a mutant pine deficient in
cinnamyl alcohol dehydrogenase. Plant
Biology, 94: 8255-8260.
Mandy, M. & Wickneswari, R. 2014. Incidences and
severity of vascular wilt in Acacia mangium
plantations in Sabah, Malaysia. AIP Conference
Proceedings, 1614: 784-789.
Mhamdi, A., Mauve, C., Gouia, H., Saindren, P.,
Hodges, M. & Noctor, G. 2010. Cytosolic
NADP-dependent isocitrate dehydrogenase
contributes to redox homeostasis and the
regulation of pathogen responses in Arabidopsis
leaves. Plant Cell Environment, 33(7): 1112-
1123.
Mohd-Farid, A., Patahayah, M., Japaruddin, Y. &
Ahmad-Zuhaidi, Y. 2015. Wilt disease, a threat
to Acacia plantation. FRIM in Focus December
2015. pp. 4-5.
Mohd-Farid, A., Syazwan, S.A., Wan Muhammad
Azrul, W.A., Patahayah, M., Mohd-Salleh, S. &
Abriza, M.Z. 2017. Penyakit layu disebabkan
kulat Ceratocystis di ladang Acacia mangium di
Malaysia dan ancamannya kepada pokok hutan
dan pokok pertanian terpilih. Prosiding FRIM,
12: 21-24.
Mutuku, J.M. & Nose, A. 2012. Changes in the
contents of metabolites and enzyme activities
in rice plants responding to Rhizoctonia solani
Kuhn infection: activation of glycolysis and
connection to phenylpropanoid pathway. Plant
and Cell Physiology, 53(6): 1017-1032.
Naoumkina, M.A., Zhao, Q., Gallego-Giraldo, L.,
Dai, X., Zhao, P.X. & Dixon, R.A. 2010.
Genome-wide analysis of phenylpropanoid
defence pathways. Molecular Plant Pathology,
11(6): 829-846.
Nibedita, C. & Jolly, B. 2017. Transcriptomics: A
successful approach to unravel the molecular
mechanism of plant-pathogen interaction in
post-genomic era. Research Journal of Bio-
technology, 12(8): 78-88.
Oliveros, J.C. 2007. VENNY. An interactive tool for
comparing lists with Venn Diagrams. Available
online at http://bioinfogp.cnb.csic.es/tools/
venny/index.html.
Ralph, J. 2010. Hydrocinnamates in lignification.
Phytochemistry Reviews, 9: 65-83.
Robinson, M.D., McCarthy, D.J. & Smyth, G.K.
2010. edgeR: a Bioconductor package for
differential expression analysis of digital gene
expression data. Bioinformatics, 26(1): 139-140.
Roux, J. & Wingfield, M.J. 2009. Ceratocystis
species: emerging pathogens of non-native
plantation Eucalyptus and Acacia species.
Southern Forests: a Journal of Forest Science,
71(2): 115-120.
Scheideler, M., Schlaich, N.L., Fellenberg, K.,
Beissbarth, T., Hauser, N.C., Vingron, M.,
Slusarenko, A.J. & Hoheisel, D. 2002.
Monitoring the switch from housekeeping to
pathogen defense metabolism in Arabidopsis
thaliana using cDNA arrays. Journal of
Biological Chemistry, 277(12): 10555-10561.
Seo, M., Jin, M., Sohn, S. & Kim, J.S. 2017.
Expression profiles of BrMYB transcription
factors related to glucosinolate biosynthesis and
stress response in eight subspecies of Brassica
rapa. FEBS Open Bio, 7: 1646-1659.
Tarigan, M, Roux, J., Van Wyk, M., Tjahjono, B. &
Wingfield, M.J. 2011. A new wilt and die-back
disease of Acacia mangium associated with
Ceratocystis manginecans and C. acaciivora sp.
in Indonesia. South Africa Journal Botany, 77:
292-304.
Tierens, K., Thomma, B.P.H., Brouwer, M., Schmidt,
J., Kistner, K., Porzel, A., Mauch-Mani, B.,
Cammue, B.P.A. & Broekaert, W.F. 2001. Study
of the role of antimicrobial glucosinolate-
derived isothiocyanates in resistance of
Arabidopsis to microbial pathogens. Plant
Physiology, 125: 1688-1699.
Tu, Y., Rochfort, S., Liu, Z., Ran, Y., Griffith, M.
& Badenhorst, P. 2010. Functional analysis
of Caffeic acid O-methyltransferase and
cinnamoyl- CoA-reductase genes from perennial
ryegrass (Lolium perenne). Plant Cell, 22: 3357-
3373.
Van Wyk, M., Al-Adawi, A.O., Khan, I.A., Deadman,
M.L., Al-Jahwari, A., Wingfield, B.D., Ploetz,
R. & Wingfield, M.J. 2007. Ceratocystis
manginecans sp. nov., causal agent of a
destructive mango wilt disease in Oman and
Pakistan. Fungal Diversity, 27: 213-230.
148 PHENYLPROPANOID PATHWAY OF Acacia mangium IN RESPONSE TO Ceratocystis INFECTION
Vanholme, R., Morreel, K., Ralph, J. & Boerjan, W.
2008. Lignin engineering. Plant Biology, 11:
278-285.
Verhage, A., Van Wees, S.C.M. & Pieterse, C.M.J.
2010. Plant immunity: it’s the hormones talking,
but what do they say? Plant Physiology, 154(2):
536-540.
Xu, L., Zhu, L., Tu, L., Liu, L., Yuan, D., Jin, L.,
Long, L. & Zhang, Xi. 2011. Lignin metabolism
has a central role in the resistance of cotton to
the wilt fungus Verticillium dahliae as revealed
by RNA-Seq-dependent transcriptional analysis
and Histochemistry. Journal of experimental
botany, 62: 5607-5621.
Ye, J., Coulouris, G., Zaretskaya, I., Cutcutache, I.,
Rozen, S. & Madden, T.L. 2012. Primer-BLAST:
a tool to design target-specific primers for
polymerase chain reaction. BMC Bioinformatics,
13: 134.
Zabala, G., Zou, J., Tuteja, J., Gonzalez, D.O.,
Clough, S.J. & Vodkin, L.O. 2006. Transcrip-
tome changes in the phenylpropanoid pathway
of Glycine max in response to Pseudomonas
syringe infection. BMC Plant Biology, 6(2): 26-
44.
Zang, Y., Jiang, T., Cong, Y., Zheng, Z. & Ouyang,
J. 2015. Molecular characterization of a
recombinant Zea mays phenylalanine ammonia-
lyase (ZmPAL2) and its application in trans-
cinnamic acid production from L-phenylalanine.
Applied Biochemistry & Biotechnology, 176:
924-937.
Zhang, I., Robbines, M.P., Carver, I.I.W. & Zeyen,
R.J. 1997. Induction of phenylpropanoid gene
transcript in oat attached by Erysiphe graminis
at 20! and 10!. Physiological and Molecular
Plant Pathology, 51: 15-33.
