Journal of Life Sciences Volume 7 Number (3)
J LS
Journal of Life Sciences
Volume 7, Number 3, March 2013 (Serial Number 59)
Contents
Molecular Biology and Bioinformatics
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
Guang-Sheng Yuan, Jian Gao, Zhi-Ming Zhang, Juan Du, Gui-Qing Mu and Guang-Tang Pan
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction of Candidate Genes Infected by SCMV in Zea mays Genome
Li Liu, Xiu-Jing He, Zhi-Ming Zhang, Mao-Jun Zhao and Guang-Tang Pan 236
BRCA1 Mutation Detection Using Fluorescent Hybridization Probes and Melting Curves
Safa R. Fitouri, Nouri B. Ermeli, Salah M. Bensaber, Mousa I. Jaeda, Ibrahim A. Mrema, Anton Hermann and Abdul M. Gbaj
Clustering and Expression Analysis of Chitinases in Maize and Rice
Kui Xiang, Wei-Tao Li, Xue-Wei Chen, Guang-Sheng Yuan, Wei-Lan Chen, Zhi-Ming Zhang, Ya-Ou Shen, Hai-Jian Lin and Guang-Tang Pan
Simulation of Spread of Infectious Diseases and Population Mobility in a Deterministic Epidemic Patch Model
Ariel Félix Gualtieri and Juan Pedro Hecht
Microbiology
Tests of Antibiotic Properties of Algerian Desert Truffle against Bacteria and Fungi
Samir Neggaz and Zohra Fortas
267 Detection of Delayed Hypersensitivity to Fonsecaea pedrosoi Metabolic Antigen (Chromomycin) in
Healthy People in an Endemic Area
Conceição de Maria Pedrozo e Silva de Azevedo, Antônio Augusto Moura da Silva, Sirlei Garcia Marques, Oscar Bruña-Romero, Gilnara Fontinelle Silva, Cecília Silva de Lima, Flávia Raquel Fernandes do Nascimento and Maria Aparecida de Resende Stoianoff
276 Inhibitory Effect of the Essential Oil from Hyptis suaveolens (L.) Poit on the Growth and Aflatoxins Synthesis of Aspergillus flavus
Ana Carolina Pessoa Moreira, Egberto Santos Carmo, Paulo Alves Wanderley, Evandro Leite de Souza and Edeltrudes de Oliveira Lima
Botany and Zoology
Effect of Some Bioproducts on Winter Mortality of Grafted Buds and the Number of Maiden Fruit Trees Produced in an Organic Nursery
Zygmunt Stanis ław Grzyb, Wojciech Piotrowski, Paweł Bielicki and Lidia Sas Paszt
289 Comparative Evaluation of NPK Fertilizer and Tithonia diversifolia Biomass in Sweet Pepper (Capsicum annum) Production in Ado Ekiti, Nigeria
Ademiluyi Benson Oluwafemi 293
Sprinkler Irrigation and Soil Tillage Practices in Sugarcane Plantations as Influenced by Soil Texture and Water Storage in Northern Ivory Coast
Crépin B. Péné, Souleymane N’Diaye and Chantal N’Guessan-Konan 302
Effects of a Brine Discharge over Bottom Polychaeta Community Structure in Chabahar Bay
Seyyed Mohammad Bagher Nabavi, Mohadese Miri, Babak Doustshenas, Ali Reza Safahieh and Mehran Loghmani
Interdisciplinary Researches
308 Real and Legal Nutritional Alternative (e.g. Application of Free Amino Acids) to Replace Forbidden Doping Substances to Produce Excellent Sport Performance
Andras S. Szabo 313
The Bioclimate in the Steppe of Tlemcen (Oran, Western Algeria)
Assia Bekkouche, Fouzia Ayache and Mohammed Bouazza
322 Biology and Culture
Joseph Neumann
Mar. 2013, Vol. 7, No. 3, pp. 219-226 Journal of Life Sciences, ISSN 1934-7391, USA
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
Guang-Sheng Yuan, Jian Gao, Zhi-Ming Zhang, Juan Du, Gui-Qing Mu and Guang-Tang Pan Maize Research Institute, Sichuan Agricultural University, Ya’An 625014, China
Received: November 29, 2012 / Accepted: January 24, 2013 / Published: March 30, 2013.
Abstract: To better know FM (Fusarium moniliforme) induced genes in maize ear rot, GO (gene ontology) method was performed to analyze detail physiological functions in the defensive response after pathogen infection. This gene annotation system was widely used to investigate large numbers of genes involving in real active role or regulator in cell response. First of all, differentially expressed genes were isolated by using genechip platform at 96 h post-inoculation with FM in maize inbred Bt-1. In total, 482 differentially expressed unique genes were screened out in inbred Bt-1 when compared to mock-inoculated bract tissues. Then, each gene was annotated to define functional class by GO method. Finally, these large FM-responsive genes with significant differentially change were sorted into cellular component, molecular function and biological process with complicated network by molecular annotation system. The demonstrated information in the GO analysis could provide another view for understanding the molecular mechanism and indicate a deeply complicated network with gene function underlying disease development in the host tissue. The findings in this study provide important bases to probe the molecular processes, the alteration of metabolism and the immune mechanism upon the FM infection in maize.
Key words: Ear rot, genechip, Fusarium moniliforme, gene ontology, Zea mays.
1. Introduction
ingestion of FM infected grain can cause severe adverse effects in both humans and animals due to the
Fusarium ear rot, predominantly caused by FM production of diverse and potent mycotoxins [8]. A (Fusarium moniliforme), F. proliferatum, and F.
variety of active defense mechanisms are known in subglutinans , is among the most destructive diseases plants to protect them from microbial pathogen for its decrease of grain yield in maize [1-3]. Especially, infection [9]. After specific recognition of a pathogen,
a high incidence of ear rot occurs in the moist and the HR (hypersensitive responses) are induced in plants humid regions of southwest China, as well as other to resist microbial pathogens. It has been proven that regions with similar longitude in other countries [4, 5]. the most efficient way to control plant diseases is to The symptom for Fusarium ear rot usually consists of a build up the most resistance in new cultivars. To this white or light pink mold on bracts or kernels [6]. end, it is great important to breed efficient, Biochemical treatments and planting resistant maize broad-spectrum and stable-resistant cultivars with inbred lines are the most common methods for resistant potential function in maize ear rot. controlling this disease. However, current resistant Within the past several years, considerable progress inbred lines are only partially resistant, and severe has been made in investigation of the resistant system outbreaks of ear rot can occur when climatic conditions involved in maize ear rots infected by FM, including are favorable for the pathogen [7]. In addition, the isolation of disease resistance genes, characterization
Corresponding author: Guang-Tang Pan, Ph.D., professor, of defense responses, and elucidation of signal research fields: plant genetics and breeding. E-mail:
transduction leading to activation of defense pangt1956@yahoo.com.cn.
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
responses [10-12]. In response to FM infection, the PR-like proteins, chitinases, -1,3-glucanases and calcium-dependent protein kinase were overproduced in maize [13]. Moreover, the disease resistance genes Hm1 and guanylyl cyclase-like protein (ZmGC1) were isolated closely involving in maize ear rot [14, 15]. Despite several resistant genes on FM infection described in maize, their possible molecular mechanisms underlying activation of plant defense responses are still unknown. It is widely accepted that plant disease resistances, such as to maize ear rot, are controlled by a multigene trait linking with QTL (quantitative trait loci). In our previous works, we have isolated and mapped several QTLs on chromosome using maize cultivars R15 (resistant) and Ye478 (susceptible) for resistance to FM ear rot [16]. Although QTLs mapping have advanced our knowledge regarding the genetic mechanisms of disease resistance, the molecular processes and gene regulation of the defense system relevant to maize ear rot remains poorly understood.
In this study, one objective was to use Gene ontology method analyzing host gene expression changes in maize inbred lines: Bt-1, which is completely resistant to FM. The inbred line has been investigated for many years for response to FM infection in southwest China. To better understand the host genes involved in the maize defense response to ear rot, the authors examined gene expression changes in bract tissue of resistant maize inbred line Bt-1 at the
4 day after inoculation with FM, using a whole-genome genechip. Results showed that 482 genes were specifically found in resistant line Bt-1. Finally, these large number genes were annotated to different functional categories by Gene ontology. We found that the host genes can be involved in cellular component, molecular function, biological process with complicated network to FM infection. Overall, the present study might help promote further understanding of mechanisms underlying in maize defense against this pathogen.
2. Materials and Methods
2.1 Plant Materials and Inoculation Procedures
A resistant maize inbred line Bt-1 with high level resistance to FM (Fusarium moniliforme), preliminary evaluated through many years for field trial, was used in this study. The line Bt-1 is derived from the tropical germplasm with high resistance to Fussrium ear rot and excellent agronomic characters in maize. The spores of FM were cultured on PDA (potato dextrose agar) media for 15 days prior to collection for inoculations. Inoculum was prepared by washing conidia from the cultures and diluting to
a final concentration of approximately 1.0 × 10 6 spores/mL in water. Milky stage maize plants were inoculated with 3 mL on each bract by injection. The inoculated plants were grown under controlled conditions at the Maize Research Institute of Sichuan Agricultural University.
2.2 Sampling and Affymetrix Chip Hybridization To identify specifically expressed genes in response
to FM inoculation at the fourth day, genechip hybridization were performed using RNAs from the independent FM-infected bract tissues and their controls. After HR (hypersensitive responses) occurring, the 96 h post-inoculation and mock-inoculation bract tissues were sampled by collecting two independent biological replicates, each consisting of independent maize bract tissue. Samples were frozen immediately in liquid nitrogen and sent to the Bioassay Laboratory of Capital Bio Corporation (Beijing, China) for cDNA synthesis, labeling, hybridization to the maize Affymetrix GeneChip Maize Genome Array (Affymetrix, Santa Clara, CA, USA), washing, and scanning. The genechip tool contains 17,555 probe sets representing 14,850 maize gene transcripts, and can provide a powerful resource for characterizing the host response at the gene expression level in maize ear rot disease. Details of the maize Affymetrix GeneChip Maize Genome Array can
be found at http://www.affymetrix.com/
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
products/arrays/specific/maize.affx. Both treated and in maize bract tissue in resistant line Bt-1 at 96 h after control bract tissues were performed for two replicates.
inoculation with FM. In total, 482 unique genes were found as be up-regulated more than 1.5-fold in
2.3 Affymetrix Chip Data Analysis resistant line Bt-1 (ANOVA, P < 0.05) when
Resulting Affymetrix data files are publically compared to mock-inoculated bract tissues (Fig. 1). available from Gene Expression Omnibus Further analysis of the 482 FM-induced genes (http://www.ncbi.nlm.nih.gov/geo/) under the identified in Bt-1 line indicated that 372 are already accession number GSE19501. Data analysis was
annotated, since the remaining 110 unknown, based performed using Affymetrix GeneChip Operating
on the UniGene assignment (published data in SoftwareVersion 1.4 (GCOS) as described Ref. [18]). Bioinformatic analysis was undertaken to (Affymetrix Statistical Algorithms Reference Guide)
assign a description and functional categorization to [17]. Raw data was normalized by dividing each probe
the FM-induced genes.
set value by the median of that probe set from all
3.2 Molecular Function Annotation of FM-induced samples, effectively centering the data around 1 and
Genes in Bt-1
enabling simple identification of differentially expressed genes. Statistical analysis was performed to
GO (Gene ontology) method was used for identify genes that were differentially expressed in
functional classification to the 482 FM-induced genes FM-inoculated samples compared to mock-inoculated
by the Web Gene Ontology Annotation Plot and the samples using analysis of variance (ANOVA, P <
results were plotted in Fig. 2. Using all genes in the
0.05) across all replicates. Induction or repression of plant genome as background for significance testing, significantly differentially expressed genes was we found that these genes were involved in three determined by dividing the raw signal value for each
functional categories including cellular component, replicate from FM-inoculated bract tissues by the
molecular function and biological process. Further average of the raw signal values from classification of these differentially expressed genes mock-inoculated controls. Genes were then described
were significantly enriched in seven cellular as “up-regulated” or “down-regulated” if their change
component categories, five molecular function in expression was > 1.5-fold.
categories, and nine biological process categories.
2.4 Annotation and Sequence Alignment
3.3 GO Annotation Involved in Cellular Component The further research was to examine the function of
Annotation of gene sequences was performed by the differentially expressed genes involved in cellular
searching the NCBI database component. It was found that quite there are a few
(http://www.ncbi.nih.gov/) for homology sequences genes associated with organelle in plant cellular
using the BLASTx (Basic Local Alignment Search component, such as membrane, cytoplasm or
Tool X) algorithm. The putative physiological nucleolus. As showed in Fig. 3, many genes were
functions of sequences were classified according to observed particularly involving in cellular plasma
the gene ontology analysis. membrane part. The result indicates that the
3. Results and Discussion
interaction between host tissues and pathogen occurred at cellular membrane surface first. The
3.1 FM-induced Genes Expression Changes in Bt-1 previous document showed that the host defense genes
Using the GeneChip Maize Genome Array platform, in cellular membrane could be stimulated firstly after large-scale gene expression analysis was investigated
pathogen infection. Upon recognition of the pathogen
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
CK1 CK2 T1 T2
Fig. 1 Cluster analysis on Affymetrix GeneChip maize genome array.
Cellular Component
Molecular Function Biological Process
Fig. 2 Molecular annotation on differentially expressed genes from genechip data.
infection in plant, it is usually interacted with associating with signal transduction, dehydrogenation membrane in cell, which has been proposed to
oxidate, phosphorylation, protein kinase, orchestrate the establishment of different defensive
transcriptional regulation, and ROS (reactive oxygen barriers against pathogen [19].
scavenging). The functional genes could provide deeply information on physiological responses during
3.4 GO Annotation Involved in Molecular Function FM inoculation (Fig. 4). Early literature illustrated In the GO analysis, many differentially expressed
that genes involving in signal transduction pathways genes showed important physiological functions may play different important roles in the host defense
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
GO:0016029 membrane
GO:0044425
GO:0005886 plasma
membrane part
membrane
GO:0044459 plasma
GO:0031224 intrinsic to
membrane part
membrane
GO:0031226 intrinsic to
GO:0016021 intergral to membrane
GO:0031225 anchored to
membrane
membrane
GO:0005887 intergral to plasma
membrane
Fig. 3 Pathway graph of GO function analysis on cellular component. Pathway of the gene in the crosstalk was indicated in the cellular part.
GO:0016722 transferase activity
GO:0016779
GO:0016301 kinase
GO:0016773
nucleotidetransferase activity
activity
phosphotransferase activity
GO:0004672 protein ethanolamine-phosphate cytidyly
GO:0004306
GO:0008905 mannose-phosphate
guanylyltansferase
kinase activity
GO:0004712 protein mannose1-phosphate
serine/threonine kinase guanylyltansferase
protein
tau-protein kinase
serine/threonine
activity
GO:0004708 MAP kinase kinase activity
Fig. 4 Pathway graph of GO function analysis on molecular function. Pathway of the gene participating in molecular function was indicated in the network.
against pathogen infection, such as MAPKs involved in catabolic process, which can be found (mitogen-activated protein kinases). These differential
widely in plant against pathogens. Of course, these genes are important in the development, growth, and
GST genes may play some other roles in physiological response to endogenous and environmental cues [20].
responses [21]. The present analysis could enhance The group genes of molecular function were our hypothesis that the accumulation of GST caused
associated with roles in plant defense activities in by pathogens has been linked to reduce symptoms response to pathogen infection. Further analysis on the
and higher levels of resistance after FM affection. molecular function class by GO, a GST This information provided that GST genes may (glutathione-S-transferase) family with high contribute to improve host tissues resistance to FM. homology was specifically elicited during molecular
3.5 GO Annotation Involved in Biological Process annotation process (Fig. 5). As is known, the GST
family is belonged to important antioxidant and Differentially expressed genes in this class were
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
Fig. 5 Homology analysis on GST family genes. The high area of homology was marked with different color.
GO:0032501 multicellular organismal process
GO:0050794 regulation of cellular process
GO:0007568 aging
GO:0007165 signal
GO:0051239 regulation of organismal
transduction
physiology
GO:0051128 regulation of cell organization GO:0007242 intracellular signaling cascade
GO:0007243 protein kinase GO:0007264 small GTPase medicated signal
cascade
transduction
GO:0000165 MAPKKK cascade
Fig. 6 Pathway graph of GO function analysis on biological process. Pathway of the gene participating in biological process was indicated in the network.
associated with various biological process and here, suggesting that this class genes associated with complicated network in cell, including protein complicated biological process could regulate plant synthesis and destination, transcriptional regulation,
defense responses to FM infection. Everyone knows metabolism and energy, growth and development,
that a pathogen-induced disease could induce multiple signal transduction pathway or defensive reaction. As
cellular activities, including various physiological showed in our analysis result, MAPK and CDPK
changes, membrane integrity, DNA-protein interaction, (calcium-dependent protein kinase) pathways were
and gene expression [22]. The striking finding in our identified by GO elucidation (Fig. 6). The two signal
analysis could provide important information that the transduction pathways were particularly presented
signal transduction pathways may play an important
Gene-Ontology Analysis on the Differentially Expressed Genes in Maize (Zea mays L.) Ear Rot
role in the host defense against FM. Moreover, genes involved in other biological process also could play complicated roles in defense system.
4. Conclusion
Ear rot disease in maize has a direct effect on maize kernels and bract tissues; thus, investigation of the defense responses that occur in bract tissues following inoculation with FM will improve our understanding of the host–pathogen interaction. It widely known that massive information could be generated basing on genechip application in the plant resistant genes screening. In our previous works, we have isolated and identified large number induced genes association with resistance to Fusarium ear rot. Based on microarray platform, 482 genes were significantly induced in Bt-1 after FM infection. The role of the FM-induced genes in the genechip data in conferring disease resistance requires further investigation, and altering the levels of such genes might play critical roles in modulating or enhancing resistance to FM affection. This GO analysis is a continuation of the previous report.
Bioinformatics analysis based on molecular function annotation is an important research method in predicting gene function and has been applied in many species for deeply digging further information [23]. In this study, it was attempted to analyze the detail physiological function of large number genes in the process of defense system in maize ear rot by GO annotation. GO analysis performed here indicates that the interaction between maize and FM results in a range of differentially expressed genes encoding related important proteins in plant defense, signal transduction, and regulation of transcription, particularly in resistant inbred line Bt-1. All the FM-induced genes were classified into cellular component, molecular function and biological process with complicated network by molecular annotation system, which could provide information on physiological responses during FM inoculation. The FM-induced genes associating with the three
classifications in Bt-1 might play important roles in modulating the response to FM infection or enhancing plant protection system.
In conclusion, the GO analysis is the further step for large number of genes toward better understanding of the molecular responses in maize ear rot. The presented results are a valuable guide for further functional genomics studies addressing resistant mechanisms in maize ear rot. Further functional analysis of these FM-induced genes to FM may provide new insights into the molecular mechanisms of the host defense response. In future studies, the involvement of each gene in FM inducement should
be investigated and will help us clarify the process of defense mechanisms acquisition combating invasion in maize ear rot.
Acknowledgments
This research was supported by the Natural National Science Foundation of China (No. 30571173, No. 31201274), National High Technology Research and Development Program of China (863 Program) (No. 2012AA10A307).
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Mar. 2013, Vol. 7, No. 3, pp. 227-235 Journal of Life Sciences, ISSN 1934-7391, USA
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction of Candidate Genes Infected by SCMV in Zea mays Genome
Li Liu , Xiu-Jing He 1, 2 2 , Zhi-Ming Zhang 2 , Mao-Jun Zhao 3 and Guang-Tang Pan 2
1 Personnel Department, Sichuan Agricultural University, Ya’an 625014, China 2 Maize Research Institute, Sichuan Agricultural University/Key Laboratory of Crop Genetic Resources and Improvement of Chinese
Ministry of Education, Chengdu 611130, China 3 Department of Life Sciences, Sichuan Agricultural University, Ya’an 625014, China
Received: January 28, 2013 / Accepted: March 11, 2013 / Published: March 30, 2013.
Abstract: DNA methylation is an important component of the epigenetic network, and it plays important roles in gene expression regulation and epigenetic change response to various stresses. In this study, the authors assessed the methylation patterns stressed by SCMV (sugarcane mosaic virus) in maize by methylation-sensitive amplified polymorphism (MSAP), and identified important candidate genes related to SCMV resistance through combining microarray analysis with CpG islands prediction. The results of MSAP indicated DNA methylation levels appeared dynamic changes inoculated for 0 d, 1 d, 4 d, 5 d and 10 d. 118 candidate genes were identified infected by SCMV, which may participate in DNA methylation modification. Among them, eight candidate genes were mapped on Scmv1 and Scmv2 QTL regions, which are crucial for SCMV resistance. In conclusion, DNA methylation is closely related with maize resistance to SCMV and plays an important role in regulating gene expression responded to maize resistance.
Key words: Maize, SCMV, DNA methylation, MSAP, CpG islands.
1. Introduction methylation, to maintain this genomic plasticity, allowing relatively rapid adaptation to new conditions
Biotic and abiotic stresses are important limiting and regulating genome functions to a large extent
factors for crop growth and improvements in yields. Moreover, they are huge evolutionary forces causing
without changing the DNA sequence. Significant differences in DNA methylation levels, especially
genetics mutation and epigenetic changes. In methylation of cytosine, have been observed among
eukaryotic genomes, epigenetics provide stability and various tissue types and different growth stage in
diversity to the phenotype through epigenetic higher plants, which contribute to the control of gene
modifications that affect local transcriptional potential
expression to response to stress.
and that are preserved or regenerated during Plants contain relatively high levels of
organisms growth and development. Epigenetic 5-methylcytosine, and promoter regions of silent genes
modifications consist mainly of DNA methylation, have been found to be more methylated than actively
histone modifications, nucleosome location and transcribed sequences [4]. In higher plants, methylated
expression of non-coding RNA [1-3]. Plants employ cytosines are distributed both asymmetric
epigenetic regulatory strategies, such as DNA (mCpNpN)-methylation and symmetric (mCpG and
Corresponding author: Guang-Tang Pan, Ph.D., professor, mCpNpG)-methylation. CpG dinucleotide context is an research fields: crop genetics and breeding. E-mail:
pangt1956@yahoo.com.cn. evolutionarily conserved DNA modification pattern that
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
is found in vertebrates, plants and fungi [5]. CpGs are mechanisms underlying the development and enriched in short stretches of CpG-dense DNA known
progression of SCMV infection.
as CpG islands. CpG islands often appear to be frequent
2. Materials and Methods
targets of hypermethylation events [6, 7], so they are treated as the focus in DNA methylation research.
2.1 Plant Material and Treatments
A series of developments in the methods were used In the present study, inbred lines Huangzao 4 to detect DNA methylation. Recently developed (highly resistant to SCMV) and Mo17 (highly methods can be classified into three main approaches susceptible to SCMV) were grown and maintained according to the principles used in detection: under controlled greenhouse conditions. The sap for endonuclease digestion, affinity enrichment and the inoculation was produced by homogenizing the bisulphite conversion [3]. Methylation-sensitive
infected leaves in 0.05 M potassium phosphate amplified polymorphism (MSAP) analysis is based on
buffer, pH 7.2 (1:10, w/v). Plants at the 3- to 4-leaf endonuclease digestion, and use one pair
stage were used for virus inoculations using isoschizomers for detection of DNA methylation. It is
mechanical rub inoculation [15]. Non-infected plants
a modification of amplified fragment length and infected plants were kept in separate growth polymorphism (AFLP) technique, in which the chambers after inoculation. Infected leaves were
isoschizomers HpaII and MspI are employed as collected at five time points (0 d, 1 d, 4 d, 5 d and 10 “frequent-cutter” enzymes, to assess the extents and
d) after inoculation and immediately frozen in liquid patterns of cytosine methylation [8]. Moreover, MSAP
nitrogen and total genomic DNA extracted following have become an important tool for characterization of
the CTAB method [16].
DNA methylation in heterosis analysis, developmental regulation and stress responses [9-12].
2.2 Methylation-Sensitive Amplification Polymorphism The SCMV (sugarcane mosaic virus) is major
Analysis
pathogens of maize worldwide. It is one of the most To detect MSAP, restriction and ligation were done important virus diseases of maize, resulting in
concurrently and two consecutive PCRs, including significant yield losses and economic losses in maize.
pre-selective amplification and selective amplification, Scmv1 and Scmv2 were mapped to chromosome arms
were used to selectively amplify the EcoRI–HpaII and 6S and 3L, have been shown to confer complete
EcoR I–MspI DNA fragments. The adapters and resistance to SCMV [13, 14]. However, the molecular
primers for enzyme “rare- cutter” EcoRI was the same mechanisms underlying resistance to SCMV in maize
as that used in standard AFLP analysis, while enzyme have not been extensively characterized. Nowadays, a
“frequent-cutter” HpaII/MspI adapter was designed large number of maize microarray experiments are
according to Xiong et al. [17]. MSAP analysis was accessible via different public resources such as
carried out according an established protocol [17]. The arrayexpress or GEO, and offer the chance to identify
second PCR products were separated by and characterize important gene relate to resistance
electrophoresis on 6% sequencing gels and stained and get a deep insight into DNA methylation
with silver as described by Bassam et al. [18]. mechanism of biotic stress in maize. In this study, the
2.3 CpG Island Predition and Candidate Gene authors assess the extents and patterns of DNA
Identification
methylation by MSAP in maize, identify candidate genes associated with DNA methylation changes
To identify candidate gene associated with DNA using microarray and propose the molecular methylation under SCMV stress, microarray data of
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
gene expression atlas (E-MEXP-253 [19],
3.2 Methylation Profiles in Inoculated Plants E-TABM-586 [15]) of the maize under SCMV stress
Comparison of the fragments obtained after were downloaded from the publicly available digestions with EcoRI/HpaII and EcoRI/MspI of DNA databases arrayexpress (http://www.ebi.ac.uk/ from maize at five time points after inoculation, arrayexpress/). Microarray data were analysed using revealed four main kinds of patterns: (1) The the TIGR Microarray Data Analysis System as
5 ′-CCGG-3′ is unmethylated or hemi-methylated described by Shi et al. [19] and Anna U żarowska et al. (single strand) at the internal cytosine; both HpaII and [15]. Differentially expressed ESTs were used to
I recognize the site and cut the DNA, product the query B73 genome sequences (http:// same fragments in HpaII and MspI electrophoresis www.maizesequence.org/index.html) using blast tool. lanes. (2) The 5 ′-CCGG-3′ is hemi-methylated at the Parameters were as followings: maximum identity >
Msp
external cytosine or at both cytosines lead to the 95%, length > 200 bp and E value < 10 . appearance of a fragment generated from the To investigate DNA methylation in promoter EcoR I/HpaII digest, but not in that obtained from the regions, 3 kb of genomic DNA sequences upstream of EcoR I/MspI digest. (3) The HpaII/MspI recognition initiation codon ATG were retrieved from the B73 site is fully methylated (both strands) at the internal maize sequencing database and searched against the cytosine; MspI cuts, whereas HpaII does not. (4) PLACE database (http:// Furthermore, make two isoschizomers are insensitive www.dna.affrc.go.jp/PLACE/). Subsequently, to fully methylation occur at external or both external differentially expressed genes sequences and promoter and internal cytosines, no fragments are produced with regions were used to predict CpG islands by CpGPAP
either HpaII or MspI [22].
[20]. Parameters were as followings: CpG minimum 144 pairs of primers were detected in pre-selective length exceeds 200 bp, the observed/expected (O/E) amplification, in order to determine conditions that ratio surpasses 0.65 and minimum GC content is would yield distinct amplified fragments on the greater than 55%, other parameters took default sequencing gel. Among them, 20 pairs of primers values. were screened and used to detect cytosine methylation GO annotation of the candidate genes were at the 5 ′-CCGG-3′ sequence in Huangzao4. A total of analysed by Goanna tools in AgBase 3,712 fragments in 688 fragment sites resolved by 20 (http://www.agbase.msstate.edu), and plotted by primer pair combinations were detected by MSAP in WEGO [21]. Candidate genes genetic map positions DNA extracted from various time-points (Table 1). were determined using the MaizeGDB For each primer combination, each individual (http://www.maizegdb.org/). time-point displayed approximately 35 fragment sites,
3. Results
each of the fragment sites represented a recognition site cleaved by one or both of the isoschizomers. Of
3.1 Plants Phenotype Analysis after Inoculation with the 3,712 fragments, 788 were differentially amplified
SCMV from the two digests for at least one of five time
With the increase stress time, the mosaic symptoms points, due to differentially sensitivity of HpaII and became more and more serious in susceptible Mo17.
Msp
I to cytosine methylation.
Typical mosaic symptoms, mosaic and chlorosis, were Based on our results, Huangzao4 showed a observed in leaves of susceptible Mo17 10 d after
significant genome-wide hypermethylation in the inoculation with SCMV, whereas Huangzao4 5 ′-CCGG-3′ sequences. The fragments of 0 d time- displayed no SCMV symptoms.
point represented DNA methylation levels in normal
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
Table 1 Methylation levels of 5 time-point after inoculation in maize.
Pattern
Time-point Total sites Ⅰ
Hemi-methylation Fully methylation Ⅱ Methylation ratio
ratio (%) a Ⅲ IV Ⅲ+IV
ratio (%) b (%) c
a: Hemi-methylation ratio = II/(I + II + III + IV), b: Fully methylation ratio = (III+IV)/(I+II+III+IV), c: Methylation ratio = (II + III + IV)/(I + II + III + IV).
maize plants, unmethylation sites, hemi-methylation methylation increased after an obvious decline. In sites, and fully methylation sites equal to 41.13%,
combination, these results suggested that maize 11.19% and 47.67% of 688 fragments sites. In detail,
regulate gene expression to resist SCMV by changing hemi-methylation sites accounted for 19.01% of the
DNA methylation patterns.
total methylation ratio (approximately 58%), the In detail, changes in methylation patterns among remaining percentages were ascribed to fully four time-points (0 d, 1 d, 4 d and 5 d) were analysed methylation sites (Table 1). Huangzao4 showed a
by comparing patterns of amplified fragments in significant hypermethylation in the 5 ′-CCGG-3′
single sites. Three major classes of changes patterns sequence similar to genome-wide methylation of B73
were identified among the differentially amplified inbred lines [23]. This high level of DNA methylation
fragments (Table 2). In the first class, the same in 5 ′-CCGG-3′ sequence was consistent with methylation sites were detected in all time-points; hypermethylation of cytosine [24, 25].
these are referred to as monomorphic with respect to cytosine methylation. There were 278 sites detected
3.3 Changes in Patterns of Cytosine Methylation by 20 primer pairs presented monomorphic, 131 sites between Five Time-points Revealed by MSAP reflected unmethylation in cytosine, and 147
To seek to clarify the relative levels of DNA fragments were the results of hemi-methylation and methylation variation among different time-points in
fully methylation.
maize under SCMV stress, the authors assessed Methylation polymorphism was detected among changes in patterns of cytosine methylation between
four time-points at 410 sites resolved by MSAP. five time-points, as detected by MSAP. These results
These sites were grouped into two major classes: showed that the general trend of the methylation ratio
demethylation and methylation (Table 2). descreased with time-course had only risen slightly at
Demethylation class consisted of five changes of
10 d after inoculation. Hemi-methylation ratio and patterns, 214 sites showed differential cytosine fully methylation ratio presented similar trends (Table
methylation among five time-points. The sites in this 1). The situation showed a reverse trend to class indicated that occurred demethylation at the accumulation of HC-Pro, which is a helper component
cytosine, resulted in expression of resistant gene. The proteinase produced from SCMV (Table 1) [26]. In
same as demethylation, methylation included five the early stages of infection, expression levels of
changes of patterns. These sites indicated that the new HC-Pro increased and reached the maximum 9 d after
methylation had occurred at these sites in maize under inoculation, subsequently showed gradually trending
SCMV stress (Table 2). Interestingly, fully down. On the contrary, the levels of cytosine
methylations were inclined to change in two classes of
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
Table 2 Changes of cytosine methylation between 0 d time-point and 5 d time-point in the Huangzao4.
changes in patterns
0d 5d Number of sites
Ratio
Not polymorphic Ⅰ Ⅰ 131 19.04%
23 3.34% IV IV 74 10.76%
methylation polymorphism with 23.11% and 20.79%
islands prediction. These important candidate genes
sites, respectively. On the whole, the demethylation
had higher probability of DNA methylation changes in
sites were higher methylation sites, resulted in decline
comparison with the others, and may be regulated by
of methylation in cytosine.
DNA methylation changes in expression levels.
It is worth noting that 26% (data unshown) sites
Microarray-based expression analysis has revealed
recovered to previous metylation patterns at 10 d after
that 118 differential expression candidate genes may
in inoculation with SCMV. These sites may be not
participate in responses to SCMV stress, among which
involved in the Huang4 response to SCMV stress, but
77 genes were up-regulated and 41 genes were
resulted from the secondary effects produced by
down-regulated under SCMV stress (data unshown).
changes of the methylation status. In addition, these
Furthermore, CpG Islands characteristics of candidate
sites partly reflected high resistance of Huangzao4.
genes were analysed using CpGPAP [20]. In addition,
The specific functions of these sites need further
promoter regions of candidate genes, obtained from
investigation.
B73 maize sequencing database, were predicted through the same method.
3.4 Candidate Genes Identification and CpG Island
Analysis of CpG islands in promoter regions
Predition
showed that CpG islands length range 201-2334 bp,
CpG islands are DNA regions that contain a high
total 106 CpG islands were identified (data unshown).
frequency of CpG dinucleotides relative to their
Morever, 137 CpG islands were detected in 97
occurrence in the bulk genome, often appear to be
candidate genes exon regions, length range 204-1514
frequent targets of hypermethylation events [6, 7]. So,
bp. By following the steps above, 109 candidate
the authors extracted differential expression candidate
genes were selected as important candidate genes
genes under SCMV stress from microarray data, and
related to DNA methylation, which has at least one
then identified important candidate genes by CpG
CpG islands in promoter or exon regions. Among
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
them, eight important candidate genes were located
4. Discussion
in Scmv1 and Scmv2 regions (Fig. 2a). As shown in
4. 1 Biotic Stress-Induced Methylation Alteration Fig. 2b, the results of cis-acting regulatory elements
in promoter showed that CGCG-BOX was major Several environmental and genetic stimuli are elements, which involved in signal transduction
known to induce DNA methylation alteration in plants. pathway and regulation of plant hormone. W-BOX,
C has been described as an obligatory component of EBOX, MYC recognition site also were found in
transcriptionally silent chromatin, and was considered promoter regions of candidate genes, which were
widely to be a mechanism that protected the genome transcription factor binding site. They are involved in
against transposable elements and retro-viruses, and many biological processes, such as plant suppressed the activity of repetitive sequences and development, metabolism, and responses to biotic
pseudogenes [6, 27]. In the present study, MSAP and abiotic stresses.
approach was used to confirm whether SCMV stress caused DNA methylation changes and assess the
3.5 GO Classification of Candidate Genes Affected by extents and patterns of cytosine methylation in maize. DNA Methylaiton Modification The results showed the dynamic changes of
Go annotation of differentially expressed genes methylation in five time-points after inoculation with association with SCMV stress found that the SCMV. The opposite trends between DNA differentially expressed genes involved in biological
methylation and HC-Pro revealed DNA methylation process such as response to stimulus, signal played an important role in stress responses. Changes transmission and molecular function such as cabalistic
in DNA methylation can be considered either passive and transcription regulation (Fig. 3). Diverse reactive of SCMV stress or active defensive categories were observed, it is interesting that the
mechanism for regulating the gene expression. In this numbers of genes in molecular function are study, some sites, recovered to previous metylation significantly different between up- and patterns, may be involved in passive reactive of down-regulation (Fig. 3). This result reveals that
SCMV stress. Another site maybe regulate the gene maize predominantly depend on up- regulated expression to resist SCMV through active defensive transcription regulator for response to SCMV stress.
mechanism.
(A) (B)
Fig. 2 A: Cis-acting regulatory elements in promoter of candidate genes; B: Mapping of the candidte genes affected by DNA methylation modification on Scmv1 and Scmv2 regions.
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome
Fig. 3 Gene ontology annotation of candidate genes. Red bars indicated up-regulated genes and green bars represented down-regulated genes.
Establishing, maintaining and modifying DNA under SCMV stress. The results showed that this methylation patterns are critical for diverse biological
technique is highly efficient for large-scale detection processes. In plants, de novo methylation is catalyzed
of cytosine methylation in the maize genome. by Domains rearranged methyltransferase 2 (DRM2)
However, it should be pointed out, this method can and maintained by DNA methyltransferase 1 (MET1),
only investigate a part of the cytosines in the genome, Chromomethylase (CMT3) and DRM2 in CpG,
leading to cannot fully reflect levels of DNA CpNpG and CpNpN methylation, respectively [28]. A
methylation. Another constraint ascribed to number of studies have revealed the involvement of
isoschizomers, the isoschizomers did not allow us to small interfering RNAs (siRNAs) in RNA-directed
distinguish unmethylation from hemi-methylated at DNA methylation (RdDM), and small RNAs seem to
the internal cytosine.
be important factors to determine the distribution of
4.2 Important Candidate Genes Affected by DNA chromatin modifications [29, 30]. Although in most
Methylation
cases DNA methylation is a stable, reduced levels of methylation are observed in plants under stress.
Two major quantitative trait locus (QTL) regions, Demethylations were processed by enzyme reaction
Scmv1 and Scmv2, which are crucial for complete and DNA replication [31]. However, DNA is scarcely
SCMV resistance were mapped to chromosome arms replicated in stressed tissues, so demethylation must
6S and 3L. The Scmv1 region contains a minimum of
be processed by enzyme reaction mechanism. It is two QTL (Scmv1a and Scmv1b [12, 13, 32]). worth noting that demethylations were higher than
Together with three additional minor QTL identified methylation during SCMV infection, which leaded to
on chromosomes 1, 5 and 10 [12], a minimum of six up-regulated expression of gene related to resistance.
QTL regions have now been implicated in inherited From the mentioned above, the analysis of MSAP
resistance to SCMV. With regard to the Scmv1 and suggested that SCMV stress induce DNA methylation
Scmv2 regions, eight candidate genes affected by changes, which may be a key defence mechanism in
DNA methylation are mapped in these chromosome response to SCMV stress in maize.
segments (Fig. 2a). The mapped genes on Scm1 were The authors have adapted MSAP technique for
lesser than Scmv2 may ascribe sampling time in detection of cytosine methylation in the maize genome
microarray experiments. Scmv1 is sufficient for
Analysis of Methylation-Sensitive Amplified Polymorphism and Prediction
of Candidate Genes Infected by SCMV in Zea mays Genome