Journal of Applied Horticulture, 19(3): 191-195, 2017
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*
1Division of Biotechnology, ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru- 560 089, 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
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 macro- propagation 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
Appl
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).
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.
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.
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
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).
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 Table 1. Primers used for miRNA expression analysis
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
Table 2. Target gene primers used for qRT-PCR Sl. No. Primers Primer sequence (5’-3’)
1 CSD1 Forward: GAGCTGTTGTTGTTCATGCTGA
CSD1 Reverse: ACTGCAGGCACTGTAATCTGC
2 CSD2 Forward: GTCTACAGGTTAGCTTCTGAT
CSD2 Reverse: GGCAAGTGTGTACATACAAGT
3 AP2 Forward: GCCAACATGATCTTGATCTGA
AP2 Reverse: GAATGAAGAATCCTGATGTGC
4 LAN Forward: GACAGTAGAGAAATTGGCCCTG
LAN Reverse: CACTCCTAATGTAGCTTGTTGAGC
5 CUC2 Forward: GACAGATTCATCGCCTAGCCA
CUC2 Reverse: CCTGATCTCATACAATCAC
6 NAM Forward: GCCACGTGCACTGCTTCTCCA
NAM Reverse: ACCTCTTCGTCCCGTGCCGT
7 MYB Forward: GGAGAACACCATGTTGTGAT
MYB Reverse: GATTGATTCAGATGAATCTTCC
8 CBF Forward: GGCTCGTGACTGCTTATGGATCA
CBF Reverse: CATAGCCAAGGATGAACTGCCGAT
9 SBP Forward: CCAGCAATGTAGCAGGTTCCAT
SBP Reverse: GTGCTCCACACGCTGAAGTTGT
compared statistically by one way ANOVA using MS-Excel software.
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).
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
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
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.
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.
A B
A B
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, miR159- MYB, 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.
References
Achard, P., A. Herr, D.C. Baulcombe and N.P. Harberd, 2004. Modulation of floral development by a gibberellin-regulated microRNA.
Development, 131: 3357-3365.
Aukerman, M.J. and H. Sakai, 2003. Regulation of flowering time and floral organ identity by a microRNA and its APETALA2-like target genes. Plant Cell., 15: 2730-2741.
Baker C.C., P. Sieber, F. Wellmer and E.M. Meyerowitz, 2005. The early extra petals1 mutant uncovers a role for microRNA miR164c in regulating petal number in Arabidopsis. Curr. Biol., 15: 303-315.
Busk, P.K. 2014. A tool for design of primers for microRNA-specific
quantitative RT-qPCR. BMC Bioinformatics, 15: 29.
Chang, S., J. Puryear and J. Cairney, 1993. A simple and efficient method for isolating RNA from pine trees. Plant Mol. Biol. Report, 11(2): 113-116.
Chen, X., C.Y. Zeng, C. Lu and W.Q. Wang, 2010. MiRNA Quantification methods basing on PCR technique. Chin. J. Biotechnol., 30(11):
88-93.
Chen, X., 2004. A microRNA as a translational repressor of APETALA2 in Arabidopsis flower development. Science, 303: 2022-2025.
Chuck, G., H. Candela and S. Hake, 2009. Big impacts by small RNAs in plant development. Curr. Opin. Plant Biol., 12(1): 81-86.
Cuperus, J.T., N. Fahlgren and J.C. Carrington, 2011. Evolution and functional diversification of Mirna genes. Plant Cell, 23: 431-42.
D’Hont, A., F. Denoeud, J.M. Aury, F.C. Baurens, F. Carreel and O.
Garsmeur, 2012. The banana (Musa acuminata) genome and the evolution of monocotyledonous plants. Nature, 488: 213-217.
Inal, B., M.H. Turktas, E. Eren, S. Ilhan, M. Okay, Atak and T. Unver, 2014. Genome-wide fungal stress responsive miRNA expression in wheat. Planta, 240(6): 1287-1298.
Jagadeeswaran, G., A. Saini. and R. Sunkar, 2009. Biotic and abiotic stress down-regulate miR398 expression in Arabidopsis. Planta, 229(4): 1009-1014.
Kumimoto, R.W., L. Adam, G.J. Hymus, P.P. Repetti, T.L. Reuber, C.M.
Marion and O.J. Ratcliffe, 2008. The Nuclear Factor Y subunits NF- YB2 and NF-YB3 play additive roles in the promotion of flowering by inductive long-day photoperiods in Arabidopsis. Planta, 228 (5): 709-723.
Li, W.X., Y. Oono, J. Zhu, X.J. He, J.M. Wu, K. Iida, X.Y. Lu, X. Cui, H.
Jin and J.K. Zhu, 2008. The Arabidopsis NFYA5 transcription factor is regulated transcriptionally and post transcriptionally to promote drought resistance. Plant Cell, 20: 2238-2251.
Naqvi, A.R., Q.M. Haq and S.K. Mukherjee, 2010. MicroRNA profiling of tomato leaf curl new Delhi virus (tolcndv) infected tomato leaves indicates that deregulation of mir159/319 and mir172 might be linked with leaf curl disease. Virology, 7(1): 1.
Nikovics, K., T. Blein, A. Peaucelle, T. Ishida, H. Morin, M. Aida and P. Laufs, 2006. The balance between the miR164A and CUC2 genes controls leaf margin serration in Arabidopsis. Plant Cell, 18:
2929-2945.
Palatnik, J.F., E. Allen, X. Wu, C. Schommer, R. Schwab, J.C. Carrington and D. Weigel, 2003. Control of leaf morphogenesis by microRNAs.
Nature, 425: 257-263.
Pinweha, N., T. Asvarak, U. Viboonjun and J. Narangajavana, 2015.
Involvement of miR160/miR393 and their targets in cassava responses to anthracnose disease. J. Plant Physiol., 174: 26-35.
Podevin, N., A. Krauss, I. Henry, R. Swennen and S. Remy, 2012.
Selection and validation of reference genes for quantitative RT-PCR expression studies of the non-model crop Musa. Mol. Breed., 30(3):
1237-1252.
Rao, X., X. Huang, Z. Zhou and X. Lin, 2013. An improvement of the 2ˆ (-delta delta CT) method for quantitative real-time polymerase chain reaction data analysis. Biostatistics, Bioinformatics and
Biomathematics, 3(3): 71.
Ravishankar, K.V., A. Rekha, V. Swarupa and G. Savitha, 2011. Gene expression analysis in roots of Musa acuminata spp. burmannicoides
‘Calcutta-4’, a banana genotype tolerant to Fusarium wilt. Acta Hort., 897: 363-370
Rhoades, M.W., B.J. Reinhart, L.P. Lim, C.B. Burge, B. Bartel and D.P. Bartel, 2002. Prediction of plant microRNA targets. Cell, 110:
513-520.
Schwab, R., J.F. Palatnik, M. Riester, C. Schommer, M. Schmid and D. Weigel, 2005. Specific effects of micro- RNAs on the plant transcriptome. Dev. Cell, 8: 517-527.
Silva. G.F.F.E., E.M. Silva, M.D.S. Azevedo, M.A.C. Guivin, D.A.
Ramiro, C.R. Figueiredo, H. Carrer, L.E.P. Peres and F.T.S.Nogueira, 2014. microRNA156-targeted SPL/SBP box transcription factors regulate tomato ovary and fruit development. Plant J., 78(4): 604-18.
Snyder, W.C. and H.N. Hansen, 1954. Variation and speciation in the genus Fusarium. Annals of the New York Academy of Sciences, 60(1): 16-23.
Sorin, C., M. Declerck, A. Christ, T. Blein, L. Ma and C. Lelandais- Briere, 2014. A miR169 isoform regulates specific NF-YA targets and root architecture in Arabidopsis. New Phytol., 202(4): 1197-211.
Stover, R.H. 1962. Fusarial wilt (Panama Disease) of Bananas and Other Musa species. Commonwealth Mycological Institute, Kew, England.
Stracke, R., M. Werber and B. Weisshaar, 2001. The R2R3-MYB gene family in Arabidopsis thaliana. Curr. Opin. Plant Biol., 4(5): 447-456.
Sunkar, R., A. Kapoor and J.K. Zhu, 2006. Posttranscriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by downregulation of miR398 and important for oxidative stress tolerance. Plant Cell, 18(8): 2051-2065.
Swarupa, V., K.V. Ravishankar and A. Rekha, 2013. Characterization of tolerance to Fusarium oxysporum f. sp. cubense infection in banana using suppression subtractive hybridization and gene expression analysis. Physiol. Mol. Pl. Pathol., 83: 1-7.
Wang, T., L. Chen, M. Zhao, Q. Tian and W. Zhang, 2011. Identification of drought-responsive microRNAs in Medicago truncatula by genome wide high throughput sequencing. BMC Genomics, 12: 367.
Wardlaw, C.W., C.H. Batchelder, V.L.Vivar Castro, S.Rivera de León, L.A. Montoya Armas, B. Montellano and J. Bielich Nash, 1961.
Banana diseases: including plantains and abaca (No. 634.772 W266b). IICA, Turrialba (Costa Rica).
Zeng, C.Y., W.Q. Wang, Y. Zheng, X. Chen, W.P. Bo, S. Song, W.X.
Zhang and M. Peng, 2009. Conservation and divergence of microRNAs and their functions in four agri-economically important Euphorbiaceous plants. Nucleic Acids Res., 38: 981-995.
Zhao, J.P., X.L. Jiang, B.Y. Zhang and X.H. Su, 2012. Involvement of microRNA-mediated gene expression regulation in the pathological development of stem canker disease in Populus trichocarpa. PLoS One., 7(9): e44968.
Zhu, Q.H., L. Fan, Y. Liu, H. Xu, D. Llewellyn and I. Wilson, 2013.
miR482 regulation of NBS-LRR defense genes during fungal pathogen infection in cotton. PLoS One, 8(12): e84390.
Received: August, 2017; Revised: September, 2017; Accepted: September, 2017
