Journal
Journal of Applied Horticulture, 19(3): 191-195, 2017
Appl
MicroRNA mediated regulation of gene expression in response
to soil-borne fungus Fusarium oxysporum f.sp. cubense (Foc1)
infection in two contrasting banana genotypes
K. Pavitra1, 2, A. Rekha3 and K.V. Ravishankar1*
Division of Biotechnology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru560 089, India. 2Department of Biotechnology, Centre for Post Graduate Studies, Jain University, Jayanagar,
Bengaluru- 560 011, India. 3Division of Fruit Crops, ICAR-Indian Institute of Horticultural Research, Hesaraghatta
Lake Post, Bengaluru-560 089, India. *E-mail: kvravi@iihr.res.in
1
Abstract
Fusarium wilt caused by the soil-borne fungus Fusarium oxysporum f.sp. cubense (Foc1) is one of the important diseases affecting
banana production. MicroRNAs, the short non-coding RNAs containing 22 to 24 nucleotides, function in post-transcriptional regulation
of target gene expression. MicroRNAs (miRNAs) as gene expression regulators relate to several abiotic stress responses that have
already been reported. However, the evidence for the interaction of miRNAs-mRNA in plant response to biotic stresses is very limited.
Hence, this study mainly focuses on microRNAs and their target genes in fusarium wilt infection in banana. Here, we have examined
the miRNA-mRNA expression patterns between two contrasting banana genotypes in response to fungal infection using quantitative
Real-time PCR (qPCR). A total of 6 miRNAs and 9 targets were examined for their expression at two-time points after infection (3
and 10 days post inoculation (dpi)) in both uninfected control and infected root samples. Based on expression analysis, we observed
early and continuous down regulation of miRNAs and up-regulation of the nine targets in tolerant genotype “Calcutta-4”. This negative
relation was not observed in the susceptible genotype “Kadali”. The mode of expression level of miRNAs and their putative target
genes will help in understanding the roles of miRNAs imparting tolerance to fusarium wilt in banana (Musa spp.).
Key words: Musa, microRNA, transcription factors, Fusarium wilt, Fusarium oxysporum f.sp. cubense.
Introduction
Banana is world’s most popular fruit crop produced in majority
of tropical and subtropical countries. Fusarium wilt disease
caused by Fusarium oxysporum f.sp. cubense (Foc) (Snyder and
Hansen, 1954) is a major limiting factor and highly destructive
disease, resulting in a significant reduction in yield and quality.
Foc colonizes the vascular system of the host, resulting in wilting
and death of the whole plant (Wardlaw, 1961; Stover, 1962).
As a part of a defense mechanism, plants have evolved a complex
network of cellular, physiological and molecular responses. Biotic
stresses bring about the expression of several genes in plants at
both the transcriptional and post-transcriptional levels. Over the
years, several studies have reported that microRNAs (miRNAs)
are involved in both abiotic and biotic stress responses (Sunkar et
al., 2004). Former studies have reported that miRNAs have wide
range of roles in biological and metabolic processes of plants like
regulation of plant development, signal transduction and response
to abiotic stresses and pathogen invasions (Chuck et al., 2009). A
few studies have reported that the roles of miRNAs play crucial
role in plant-microbe interaction and defense responses.
The aim of this study was to understand the concept of miRNA
mediated gene expression patterns in two contrasting genotypes
during fungal infection. The miRNA-mRNA expression during
disease progression in tolerant and susceptible genotypes for Foc
was analysed by quantitative Real-time PCR (qPCR) approach.
Here, we tried to examine two aspects: first - the role of few
selected miRNAs in fusarium wilt infection through their level
of expression in two contrasting genotypes differing in their
response to fusarium wilt disease; secondly, we also examined
the expression for putative target genes of the selected miRNAs.
Materials and methods
Plant material, fungal inoculation and RNA extraction:
Fusarium oxysporum f.sp. cubense (Foc1) was isolated from
banana corm with fusarium symptoms. Two diploid Musa
genotypes Calcutta-4 (tolerant) and Kadali (susceptible) were
used in this study (Ravishankar et al., 2011). The plants were
inoculated at four to six leaf stage under greenhouse conditions.
For inoculations, wounds were made in the newly emerged
roots of the plantlets (2 months old plantlets grown by macropropagation and placed in pots containing sterilized cocopeat)
and 50 mL conidial suspension (1x104 spores/mL) was poured
onto the injured roots and covered with sterile cocopeat. Here,
three plantlets for each treatment were inoculated with Foc1
isolate, while the remaining three uninfected control plantlets
were used to serve as controls. All inoculated and un-infected
control plantlets were maintained in the greenhouse throughout
the experiment. Root samples were harvested before inoculation
and at 0, 3 and 10 days post inoculation (dpi). These samples were
frozen immediately using liquid nitrogen and kept at -80°C until
further use (Swarupa et al., 2013).
Total RNA was extracted from the root tissue of infected and
uninfected samples (three biological replicates) using modified
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MicroRNA mediated regulation of gene expression in banana
pine tree method (Chang, 1993) followed by RNase-free DNase
treatment (Ambion, Cat#AM1907). The RNA concentrations
were quantified by a Nanodrop ND-1000 spectrophotometer. For
cDNA synthesis, miScript II RT (Qiagen: Cat no. 218160) kit was
used for miRNAs and Fermentas First-Strand cDNA Synthesis
kit was used for (Thermo Fisher Scientific; Cat no. K1622) target
genes (mRNA) (Pinweha et al., 2015).
Table 2. Target gene primers used for qRT-PCR
Selection of miRNAs and their putative target genes: Based
on previous reports, we selected a total of 6 miRNAs which are
involved in host-pathogen interaction (Naqvi et al., 2010; Zhao
et al., 2012; Zhu et al., 2013; Inal et al., 2014). The sequence of
these miRNAs was then used to identify banana miRNAs (235
conserved miRNAs) (http://bananagenome.cirad.fr/download/
musa_cds.fna.gz) through a homology search using multiple
sequence alignment tool (ClustalW) (http://www.ebi.ac.uk/
Tools/msa/clustalo/). From this, we selected six banana miRNAs
(miR159, miR164, miR169, miR172, miR156 and miR398).
These putative pathogen responsive miRNAs from banana were
used for expression analysis.
3
To perform miR-specific RT-qPCR method, primers were
designed using the software miRprimer (http://www.mirbase.org)
(Busk et al., 2014) with best possible adjustments needed and
are listed in (Table 1). As, miRNAs perceive their target mRNAs
by perfect or near-perfect base pairing, we used a web-based
software psRNATarget to predict the plant miRNA targets using
their mature miRNA sequences. For the 6 miRNAs, we selected
9 targets: R2R3-MYB gene family protein (MYB), No Apical
Meristem (NAM), Cup shaped cotyledon 2 (CUC2), Calcium
Binding Factor (CBF), Apetella 2 (AP2), Lanceolate (LAN),
Squamosa Binding Protein (SBP), Copper Sulphate Dismutase
(CSD1 and CSD2) (Jagadeeswaran, 2009; Rhoades, 2002;
Baker, 2005; Aukerman and Sakai, 2003; Sorin, 2014; Wang,
2011a). Specific primers for target genes were designed using
integrated DNA technology (IDT) software (http://eu.idtdna.
com/Primerquest/Home/Index) with default parameters and are
listed in Table 2.
8
Gene expression analysis using qRT-PCR: The expression
studies using qRT-PCR reactions were performed using DyNAmo
Flash SYBR Green qPCR (ROX) kit (Thermo Scientific) on
Statistical analysis: The gene expression data for miRNAs and
their targets were represented as mean values with standard error
(mean ± SE). The significant differences between treatments were
compared statistically by one way ANOVA
using MS-Excel software.
Table 1. Primers used for miRNA expression analysis
Sl. No. Primers
Primer sequence (5’-3’)
1
CSD1
Forward: GAGCTGTTGTTGTTCATGCTGA
CSD1
Reverse: ACTGCAGGCACTGTAATCTGC
CSD2
Forward: GTCTACAGGTTAGCTTCTGAT
CSD2
Reverse: GGCAAGTGTGTACATACAAGT
AP2
Forward: GCCAACATGATCTTGATCTGA
AP2
Reverse: GAATGAAGAATCCTGATGTGC
LAN
Forward: GACAGTAGAGAAATTGGCCCTG
LAN
Reverse: CACTCCTAATGTAGCTTGTTGAGC
CUC2
Forward: GACAGATTCATCGCCTAGCCA
CUC2
Reverse: CCTGATCTCATACAATCAC
NAM
Forward: GCCACGTGCACTGCTTCTCCA
NAM
Reverse: ACCTCTTCGTCCCGTGCCGT
MYB
Forward: GGAGAACACCATGTTGTGAT
MYB
Reverse: GATTGATTCAGATGAATCTTCC
CBF
Forward: GGCTCGTGACTGCTTATGGATCA
CBF
Reverse: CATAGCCAAGGATGAACTGCCGAT
SBP
Forward: CCAGCAATGTAGCAGGTTCCAT
SBP
Reverse: GTGCTCCACACGCTGAAGTTGT
2
4
5
6
7
9
an Applied Biosystem 7500 system. qPCR reaction mixture
contained; 2.0 μL of the diluted cDNA template added to 10 μL
of the SYBR Green with ROX dye, 1μL of each primer (5pM) and
final volume was made up to 20 μL with sterile water. Reactions
were carried out in three technical replicates and having a negative
control with no template. The 25S gene was used as an internal
control (Podevin, 2012). The expression levels were determined
by comparing the Ct values of control samples with infected
samples. Relative expression levels of miRNA and target genes
were estimated using the 2−ΔΔCt method which corresponds to fold
change in expression level (Rao, 2013).
Sl. No.Primers Primer sequence ( 5’-3’)
1
miR398 Forward: CCA AAG GTAGCCAAGGACAAACTTGC
miR398 Reverse: GGTCCAGTTTTTTTTTTTTTTTCTGCTGCTGC
2
miR164 Forward: TGTGCAGGGTGGAGAAGCAG
miR164 Reverse: GGTCCAGTTTTTTTTTTTTTTTCCATCCATCCA
3
miR172 Forward: GCAGAGAATCTTGATGATGCTGGACG
miR172 Reverse: GTCCAGTTTTTTTTTTTTTTTATGCAGATGCAGATG
4
miR169 Forward: GCCAAGGATGACTTGCCTGTGTC
miR169 Reverse: GGTCCAGTTTTTTTTTTTTTTTAGGAGAGGAGAGG
5
miR159 Forward: CGCGCGCAGTTTGGATTGAAG
miR159 Reverse: CAGGTCCAGTTTTTTTTTTTTTTTAAGAAGAAGAAGAAGAA
6
miR156a Forward: TTGACAGAAGAGAGTGAGCACACAG
miR156a Reverse: AGGTCCAGTTTTTTTTTTTTTTTACCACCACC
Results
Identification of pathogen responsive
miRNAs: The six miRNAs selected for
the study were involved in host-pathogen
interaction and the pre-miRNA sequences of
these miRNAs had to go through a homology
search with the 235 miRNAs belonging
to 37 families in banana (D’Hont et al.,
2012) using the Clustal W software. The
sequences that showed highest homology
were selected and used to design miRNA
specific primers (miR159, miR164, miR169,
miR172, miR156 and miR398) using
software miRprimer (http://www.mirbase.
org) (Table.1).
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MicroRNA mediated regulation of gene expression in banana
Pathogen responsive miRNA expression pattern during
Foc1 infection: A total of six miRNAs were validated and the
expression patterns of uninfected (control) and infected root
samples at different time intervals (3 and 10 days post inoculation
(dpi) were analysed using qPCR (Applied Biosystems 7500
USA). qRT-PCR analysis showed a down regulation of selected
miRNAs (398, 169, 159, 164, 172 and 156) in tolerant genotype
‘Calcutta-4’ (C4) at both 3 and 10 dpi (Fig.1A). However,
in susceptible genotype cv. ‘Kadali’ (K) we have observed
upregulation at 3 dpi and later the expression levels were reduced
at 10 dpi except for miR159 (Fig. 1B).
Identification of pathogen responsive miRNA targets: The
putative targets selected for the study were purely based on the
previous studies reported on miRNAs involved in host-pathogen
interaction. The same target genes were examined and confirmed
for their complementarity with the selected miRNAs through
psRNATarget database in Musa species. The selected target genes
of miRNAs belonged to various families of TFs and two genes. A
total of nine targets (MYB, CUC2, NAM, AP2, LAN, CBF, SBP
and CSD1, CSD2) (Table 2) were selected for qPCR expression
studies. Sequences of these targets were obtained from Musa
Banana Hub (http://banana-genome-hub.southgreen.fr/home1)
for primer designing using IDT software (http://eu.idtdna.com/
Primerquest/Home/Index).
Validation of pathogen responsive miRNA targets expression
upon Foc1 infection: The target genes MYB (for miR159), NAM
(for miR164), CUC2 (for miR164), CBF (for miR169), AP2 (for
193
miR172), LAN (for miR172), SBP (for miR156), CSD1 (for
miR398) and CSD2 (for miR398) were upregulated after infection
in Calcutta-4 (tolerant), both at 3 and 10 days post inoculation
(Fig. 2A). In case of Kadali (susceptible) genotype, we observed
increased expression of the target genes at 3 dpi; however, the
expression was not sustained till 10 dpi (Fig. 2B).
Discussion
With the advent of genomics, a wide range of plant miRNAs
have been identified and characterized from various plant species
(Sunkar et al., 2006; Li et al., 2008; Palatnik et al., 2003; Nikovics
et al., 2006). Plant miRNAs are found to play a wide range of
roles in diverse biological and physiological processes (Cuperus
et al., 2011; Zeng et al., 2009).
Till date, not many studies focusing on the regulatory mechanism
involving miRNA and Fusarium wilt infection in banana are
available. Except for a few published reports by D’Hont et al.
(2012) who reported 235 conserved miRNAs belonging to 37
families in ‘DH-Pahang’ (A-genome). Keeping this in view, it
is important to examine the expression and function of miRNA
including their targets.
In order to address this issue, we selected 6 miRNAs and their
targets involved in plant-microbe interaction for expression
analysis in contrasting genotypes ‘Calcutta-4’(tolerant) and
‘Kadali’ (susceptible) during disease initiation and progression
upon Fusarium oxysporum f.sp. cubense (Foc) Race 1 infection
in banana roots. qRT-PCR was used to identify miRNA and its
B
A
Fig. 1. The relative expression level of selected six miRNAs in Calcutta-4 (A) and Kadali (B) genotypes. The analyses were performed with
3 biological replicates and 3 technical triplicates and the error bars are represented on each column.
A
B
Fig. 2. The relative expression level of selected 9 target genes in Calcutta-4 (A) and Kadali (B) genotypes. The analyses were performed
with 3 biological replicates and 3 technical triplicates and the error bars are represented on each column.
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MicroRNA mediated regulation of gene expression in banana
target expression during fungal infection at two time points (3
and 10 dpi).
The expression pattern of selected miRNAs and their target genes
was altered upon fungal infection (Fig. 1 and 2). The results of
this study indicated that the level of defense response varied
between the tolerant and susceptible genotypes. Here we observed
that the miRNAs expression level decreased after infection
in ‘Calcutta-4’ at both 3 and 10 dpi. However, for ‘Kadali’
(susceptible) genotype, expression increased at 3dpi (except
miR159). In Kadali, there was not much alteration in expression
on 10 dpi for miR164; increased expression was observed for
miR398 and miR172. A decreased expression was also observed
for miR169, miR159 and miR156 (Fig. 1A and 1B). While the
targets under study showed increased expression at early (3
dpi) and later (10 dpi) stages of infection in tolerant genotype
upon Foc1 infection. However, in case of susceptible genotype
the target genes increased at 3 dpi but drastically decreased at
10 dpi (Fig. 2A and 2B). In addition to the early expression of
genes in ‘Calcutta-4’, the level of expression was also higher. A
similar trend was reported by Swarupa et al. (2013), indicating
that defense genes were constitutively expressed at higher and
further upregulated at early time points of infection in tolerant
genotype, while in case of susceptible genotype the upregulation
was delayed.
Upon fungal infection, we observed that the expression level of
six miRNAs (miR398-CSD1 and CSD2, miR169-CBF, miR159MYB, miR164-NAM and CUC2, miR172-AP2 and LAN and
miR156-SBP) decreased in tolerant genotype (Fig. 1A). Among
these miRNAs, few also respond to other pathogenic fungi in
different plants (Eg. miR156, miR159) like in galled loblolly
pine (Pinustaeda) stem infected with Cronartium quercuum f.sp.
fusiforme. Several fungi responsive-miRNAs (miR156, miR164,
miR398, miR159) have been reported to be involved in response
to multiple other stresses.
The selected genes have diverse functions and were involved in
many cellular processes including defense and signal transduction
(Fig. 1 and 2). miR398 has been recognised as a molecular
indicator by its downregulation and its modulation of CSDs
to biotic and abiotic stress (Zhao et al., 2012). Additionally,
similar patterns of expression for CSDs were observed in
Arabidopsis (Sunkar et al., 2006; Jagadeeswaran et al., 2009).
CBF, a plant-specific transcription factor plays an important role
in plant development and response to environmental stresses
(Kumimoto et al., 2008). MYB TF is involved in the signalling
network in plants and its response to changes in the environment.
Thus, suggesting that they play an important role in some basic
biological processes (Stracke et al., 2001; Achard et al., 2004)
NAC domain TFs like CUC2 & NAM which are basically
involved in transducing auxin signals downstream of F-box
protein TIR1 to promote lateral root development (Li et al., 2008)
The MYB, NAM, CUC2, AP2 and LAN are known to be involved
in signalling network (Wang et al., 2011; Aukerman and Sakai,
2003; Chen, 2004; Schwab et al., 2005). These results suggest
that fungal attack altered the gene expression of genes involved
in both resistance and physiological processes which play an
important role in providing tolerance (Fig. 1 and 2).
Moreover, the putative targets of miR156, miR159, miR172 and
miR164 were genes that encode for transcription factors (TFs)
that regulate the expression of protein-coding genes and regulate
signal transduction in plants. The Squamosa Promoter Binding
protein (SPB) gene encode plant-specific transcription factors
that play important roles in many reproductive and development
stages, including development, architecture etc., and thus helping
to fine-tune plant responses to fungal infection in banana (Silva
et al., 2014; Chen et al., 2010). All fungi-responsive miRNAs
targeted more than one gene and thus each gene alters several
physiological processes. Hence, the concept of miRNA-mRNA
gene expression in pathogen development always regulated
through a complex network indicating that there is an integrated
co-regulatory network existing during fusarium wilt disease
tolerance (Fig. 2).
Here we report an early down regulation of miRNAs during
infection in ‘Calcutta-4’ and we have also observed a concomitant
higher expression of targets in Calcutta-4 indicating that miRNAs
might have a role towards disease tolerance upon fungal infection.
However, in Kadali (susceptible) genotype, there was an increased
expression of both miRNA and their target genes at 3 dpi.
Here, we have not observed similar expected negative relation
between miRNAs and their targets after Foc Race 1 infection. In
Kadali, both on 3 and 10 dpi, we observed increased expression
of miRNAs. In susceptible genotype cv ‘Kadali’ we observed
a totally different pattern of miRNA expression. Even though
target genes up regulated upon infection on 3dpi, the extent of
expression level was low and it was not sustained at 10 dpi (Fig.
1B) as compared to ‘Calcutta-4’ (tolerant) genotype.
From this study, we hypothesize that early and sustainable
downregulation of miRNAs and upregulation of the predicted
target genes are involved in imparting tolerance against fusarium
wilt infection in banana. The results of this study indicate that the
defense responses are regulated by a combination of an induced
array of genes through miRNA in tolerant genotype. This could
help in understanding host defense responses against diverse
pathogens and other stresses. Further it may help in evolving a
new strategy for controlling Fusarium wilt in banana and also in
understanding tolerance mechanisms operating against fungus.
Acknowledgements
We thank the Indian Council of Agricultural Research, New Delhi
for financial assistance through the ICAR Network Project on
Transgenics in Crops: Functional Genomics-Fusarium wilt and
drought tolerance in Banana.
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Received: August, 2017; Revised: September, 2017; Accepted: September, 2017
Journal of Applied Horticulture (www.horticultureresearch.net)