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BarleyBase/PLEXdb A Unified Expression Profiling Database for Plants and Plant Pathogens
Abstract
BarleyBase (http://barleybase.org/) and its successor, PLEXdb (http://plexdb.org/), are public resources for large-scale gene expression analysis for plants and plant pathogens. BarleyBase/PLEXdb provides a unified web interface to support the functional interpretation of highly parallel microarray experiments integrated with traditional structural genomics and phenotypic data. Users can perform hypothesis building queries from multiple interlinked resources, e.g., a particular gene, a protein class, EST entries, and physical or genetic map position-all coupled to highly parallel gene expression, for a variety of crop and model plant species, from a large array of experimental or field conditions. Array data are interlinked to analytical and biological functions (e.g., Gene and Plant Ontologies, BLAST, spliced alignment, multiple alignment, regulatory motif identification, and expression analysis), allowing members of the community to access and analyze comparative expression experiments in conjunction with their own data.
... OmicsViz uses data files in formats ranging from comma separated value files to Excel spreadsheets to take advantage of data from PLEXdb [32,33], GEO, and other microarray databases. OmicsViz can map multiple datasets to networks at the same time. ...
... This heterogeneity of binding modes between SM and SNARE proteins introduces uncertainties and complexity into the interaction network of regulation in vesicular fusion, and thus greatly complicates the understanding of key functional roles of the SM protein family in exocytosis. SM proteins have been proposed to be both positive and negative regulators in yeast and neuron [33,[85][86][87][88][89][90]. Rothman and Melia's study for SM regulation in SNARE system provided predictive insights at the system level: the dynamics of the dual roles of SM may determine which outcome dominates in observed overall exocytosis [33]. ...
... SM proteins have been proposed to be both positive and negative regulators in yeast and neuron [33,[85][86][87][88][89][90]. Rothman and Melia's study for SM regulation in SNARE system provided predictive insights at the system level: the dynamics of the dual roles of SM may determine which outcome dominates in observed overall exocytosis [33]. For this complex system, a single mathematical or computational representation of the network does not sufficiently capture the whole range of system behaviors. ...
A key aim of current systems biology research is to understand biology at the system level, to systematically catalogue all molecules and their interactions within a living cell, rather than the characteristics of isolated parts of a cell or organism. Network modeling is characterized by viewing cells in terms of their underlying network structure at many different levels of detail is a cornerstone of systems biology. Two emerging methodologies
in network modeling provide invaluable insights into biological systems: static large-scale biological network modeling and dynamic quantitative modeling. Static large-scale biological network modeling focuses on integrating, visualizing and topologically modeling
To facilitate application of these methods in biological research and improve existing network modeling software, this work presents: i) OmicsViz and OmicsAnalyzer, software tools, dedicated to integrating and analyzing omics data sets in network context. ii)
CytoModeler, software tool, dedicated to providing a bridge between static large-scale biological network modeling and dynamic quantitative modeling methods. It not only facilitates network design, model creation, and computational simulation but provides
advanced visualization for simulation results. iii) Comparative network modeling application in the systems biology of the SM-SNARE protein regulation in exocytotic membrane fusion.
This work presents applications of biological network modeling methods to understand regulation mechanisms in complex biological systems. all kinds of omics data sets which are produced by innovative high throughput screening biotechnologies. Dynamic quantitative modeling focuses on exploring dynamics of biological
systems by applying computational simulation and mathematical modeling.
... The microarray data for the genes screened above with DDD were searched against PLEXdb (http://www.plexdb. org)[19]. A total of 322 probesets corresponding to 256 (63%) unigenes were analyzed here. ...
... The searching tool was " Profile Neighbors " in PLEXdb (http://www.plexdb.org//modules/glSuite/ gl_main.php)[19]. One hundred and seventy-four additional probsets were retrieved by removing the redundant information and probsets with expression profiles that were not seed-specific. ...
... The expression data for the genes studied in different developmental contexts in wheat were obtained from PLEXdb (http://www.plexdb.org)[19]experiment TA3[18]. ...
Wheat is one of the most important cereal crops for human beings, with seeds being the tissue of highly economic value. Various morphogenetic and metabolic processes are exclusively associated with seed maturation. The goal of this study was to screen and identify genes specifically expressed in the developing seed of wheat with an integrative utilization of digital differential display (DDD) and available online microarray databases.
A total of 201 unigenes were identified as the results of DDD screening and microarray database searching. The expressions of 6 of these were shown to be seed-specific by qRT-PCR analysis. Further GO enrichment analysis indicated that seed-specific genes were mainly associated with defense response, response to stress, multi-organism process, pathogenesis, extracellular region, nutrient reservoir activity, enzyme inhibitor activity, antioxidant activity and oxidoreductase activity. A comparison of this set of genes with the rice (Oryza sativa) genome was also performed and approximately three-fifths of them have rice counterparts. Between the counterparts, around 63% showed similar expression patterns according to the microarray data.
In conclusion, the DDD screening combined with microarray data analysis is an effective strategy for the identification of seed-specific expressed genes in wheat. These seed-specific genes screened during this study will provide valuable information for further studies about the functions of these genes in wheat.
... Leaf samples were collected at 12, 24, 72, 144, 216 and 288 hai. The abundance of soybean mRNA transcripts was assayed using the Gene ChipSoybean Genome Array (Affymetrix) and these results were deposited in the Plant Expression Database (Accession number GM37;Wise et al. 2007). Significantly differentially expressed probe sets were identified from the six different time points using a 0.01% FDR (q 0.0001, Nettleton 2006). ...
... RNA samples were hybridised to the Gene Chip Soybean Genome Array (Affymetrix) and analysed for differential gene expression. Results were deposited in the Plant Expression Database (accession number GM51; Wise et al. 2007). ...
Rpp4 (Resistance to Phakopsora pachyrhizi 4) confers resistance to Phakopsora pachyrhizi Sydow, the causal agent of Asian soybean rust (ASR). By combining expression profiling and virus induced gene silencing (VIGS), we are developing a genetic framework for Rpp4-mediated resistance. We measured gene expression in mock-inoculated and P. pachyrhizi-infected leaves of resistant soybean accession PI459025B (Rpp4) and the susceptible cultivar (Williams 82) across a 12-day time course. Unexpectedly, two biphasic responses were identified. In the incompatible reaction, genes induced at 12 h after infection (hai) were not differentially expressed at 24 hai, but were induced at 72 hai. In contrast, genes repressed at 12 hai were not differentially expressed from 24 to 144 hai, but were repressed 216 hai and later. To differentiate between basal and resistance-gene (R-gene) mediated defence responses, we compared gene expression in Rpp4-silenced and empty vector-treated PI459025B plants 14 days after infection (dai) with P. pachyrhizi. This identified genes, including transcription factors, whose differential expression is dependent upon Rpp4. To identify differentially expressed genes conserved across multiple P. pachyrhizi resistance pathways, Rpp4 expression datasets were compared with microarray data previously generated for Rpp2 and Rpp3-mediated defence responses. Fourteen transcription factors common to all resistant and susceptible responses were identified, as well as fourteen transcription factors unique to R-gene-mediated resistance responses. These genes are targets for future P. pachyrhizi resistance research.
... Since the whole genome transcript analysis revealed that eibi1 activated some signaling pathways in response to stress factors, we performed a comparative analysis of differentially expressed genes from eibi1 to other barleys' transcriptome change under various stress treatments on PlexDB database [41][42][43]. The available Affymetrix Barley1 GeneChip data included barley transcriptome change in response to four abiotic factors including chilling and freezing temperature (BB81, BB95), drought (BB84, BB89), and three biotic factors from powdery mildew resistance genes mlo-5 (BB7), mla-13 (BB4) and rar1 (BB5). ...
... The differentially expressed (at least two-fold up or down-regulated) probe sets from our experiment were compared with the expression of the same probe sets in public barley GeneChip experiments from the PlexDB database [43]. Seven transcriptome changes representing barley in response to abiotic and biotic factors were chosen. ...
Wild barley eibi1 mutant with HvABCG31 gene mutation has low capacity to retain leaf water, a phenotype associated with reduced cutin deposition and a thin cuticle. To better understand how such a mutant plant survives, we performed a genome-wide gene expression analysis. The leaf transcriptomes between the near-isogenic lines eibi1 and the wild type were compared using the 22-k Barley1 Affymetrix microarray. We found that the pleiotropic effect of the single gene HvABCG31 mutation was linked to the co-regulation of metabolic processes and stress-related system. The cuticle development involved cytochrome P450 family members and fatty acid metabolism pathways were significantly up-regulated by the HvABCG31 mutation, which might be anticipated to reduce the levels of cutin monomers or wax and display conspicuous cuticle defects. The candidate genes for responses to stress were induced by eibi1 mutant through activating the jasmonate pathway. The down-regulation of co-expressed enzyme genes responsible for DNA methylation and histone deacetylation also suggested that HvABCG31 mutation may affect the epigenetic regulation for barley development. Comparison of transcriptomic profiling of barley under biotic and abiotic stresses revealed that the functions of HvABCG31 gene to high-water loss rate might be different from other osmotic stresses of gene mutations in barley. The transcriptional profiling of the HvABCG31 mutation provided candidate genes for further investigation of the physiological and developmental changes caused by the mutant.
... We compared differentially expressed (at least two-fold up-or down-regulated) probe sets from our experiment with the expression of the same probe sets in a following set of publicly available barley GeneChip experiments from the PlexDB database (Shen et al. 2005; Wise et al. 2008) representing barley transcriptome change in response to abiotic and biotic factors: rar1-BB5 (Mitra et al. 2004), Rpg1_24hpi-BB49 (Zhang et al. 2008), Pseudom.-BB79 (Ueda, Wood 2008), senesc.-BB50 ...
... We performed a comparative analysis of differentially expressed genes from nec3 and publicly available Affymetrix Barley1 GeneChip data on barley transcriptome change under various stress treatments. We chose a set of barley GeneChip experiments from the PlexDB database (Wise et al. 2008) representing barley transcriptome change in response to four abiotic factors (chilling, freezing temperature, drought, mercury toxicity) and five biotic factors (powdery mildew resistance of specific Mla alleles, effect of mlo-5 and rar1 mutations, stem rust resistance of transgenic Golden Promise containing Rpg1 gene and response to Pseudomonas aeruginosa). We compared a set of differentially expressed genes from nec3 with the differentially expressed gene sets from the selected microarray experiments. ...
The transcriptome of two fast neutron induced allelic barley mutants, FN362 and FN363, was analyzed with the Affymetrix Barley1 GeneChip microarray in order to characterize the necrotic leaf spot 3 (nec3) gene and its function. Twenty one genes, at least two-fold down-regulated in the mutants compared to the wild-type, were detected, but PCR analyses failed to identify a candidate Nec3 gene. It is possible that the probe set for the Nec3 gene is not on the Barley1 GeneChip, or that it is expressed at very low levels or the expression is confined to specific developmental stage or tissue type. Comparison of the genes differentially expressed in FN362 and FN363 mutants with publicly available Affymetrix Barley1 GeneChip expression data sets revealed significant overlap with barley abiotic stress transcriptome. The highest similarity was observed with the transcriptome of barley under drought and freezing stress. These results imply a possible involvement of the wild-type Nec3 in signaling pathways regulating abiotic stress response in barley.
... Probesets identified as regulated specifically by dormancy (from the two-way ANOVA analysis), and those differentially expressed between dry D and dry AR seeds (twofold change and P £ 0.05 cut-off value) are shown in black and blue, respectively, and their names are indicated at right. 143 and 183 probesets were identified to be up-regulated by after-ripening in the coleorhiza of barley at 8 and 18 HAI, respectively, and translation of these barley probesets into their wheat equivalents by microarray platform translator (Wise et al., 2007) produced 131 and 151 unique wheat probesets, respectively. Comparison of the 131 probesets with those up-regulated in our 12 HAI AR (738 probesets; Figure 3a) and the 151 probesets with those up-regulated in the 24 HAI AR (1125 probesets; Figure 3c) wheat seeds identified 10 and 47 putative wheat-barley orthologues as up-regulated specifically by AR, respectively (Table S7). ...
... Microarray platform translator (http://www.plexdb.org/modules/MPT; Wise et al., 2007) software was used to translate barley probesets into their wheat equivalents. ...
Seed dormancy is an important agronomic trait in wheat (Trticum aestivum). Seeds can be released from a physiologically dormant state by after-ripening. To understand the molecular mechanisms underlying the role of after-ripening in conferring developmental switches from dormancy to germination in wheat seeds, we performed comparative transcriptomic analyses between dormant (D) and after-ripened (AR) seeds in both dry and imbibed states. Transcriptional activation of genes represented by a core of 22 and 435 probesets was evident in the dry and imbibed states of D seeds, respectively. Furthermore, two-way ANOVA analysis identified 36 probesets as specifically regulated by dormancy. These data suggest that biological functions associated with these genes are involved in the maintenance of seed dormancy. Expression of genes encoding protein synthesis/activity inhibitors was significantly repressed during after-ripening, leading to dormancy decay. Imbibing AR seeds led to transcriptional activation of distinct biological processes, including those related to DNA replication, nitrogen metabolism, cytoplasmic membrane-bound vesicle, jasmonate biosynthesis and cell wall modification. These after-ripening-mediated transcriptional programs appear to be regulated by epigenetic mechanisms. Clustering of our microarray data produced 16 gene clusters; dormancy-specific probesets and abscisic acid (ABA)-responsive elements were significantly overrepresented in two clusters, indicating the linkage of dormancy in wheat with that of seed sensitivity to ABA. The role of ABA signalling in regulating wheat seed dormancy was further supported by the down-regulation of ABA response-related probesets in AR seeds and absence of differential expression of ABA metabolic genes between D and AR seeds.
... PLEXdb (Plant Expression Database) is a gene expression-based resource to bridge between genotype to phenotype through transcript profiling. PLEXdb integrates multiple data sets from a wide variety of plant and plant pathogen microarrays and provides a single site to access, analyze and disseminate expression data for comprehensive comparative functional genomics studies (1,2). The goal of PLEXdb is to make this data easily accessible to help users answer biological questions and begin to leverage existing results from related large-scale expression studies. ...
... The Model Genome Interrogator (MGI), Version 3 provides structural genomic support for integrated and comparative exploration of gene expression data (2). Based on user input of single or batch queries of microarray probe set identifiers from most of the microarray platforms supported by PLEXdb, MGI uses the sequenced genomes, the annotate protein-coding genes, cDNA and locus coordinate data of either rice or Arabidopsis to identify putative orthologs for the source gene that correspond to the probesets. ...
PLEXdb (http://www.plexdb.org), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species,
promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These
analyses facilitate the interpretation of structure, function and regulation of genes in economically important plants. A
list of Gene Atlas experiments highlights data sets that give responses across different developmental stages, conditions
and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI)
tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs.
The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene
lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level
analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across
many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation
under diverse conditions or checking any gene’s suitability as a steady-state control.
... Three biological replicates of each sample (untreated control, control + ABA, 35S::VvABF2, and 35S::VvABF2 + ABA) were hybridized on NimbleGen microarray 090818 Vitis exp HX12 (Roche, NimbleGen), bearing a set of probes for 29,582 unigenes based on the 12X grapevine V1 gene model pre- diction (http://genomes.cribi.unipd.it/). The chip probe design is available at http://ddlab.sci.univr.it/FunctionalGenomics/. Robust multiarray average- processed data are available at PLEXdb ( Wise et al., 2007) with accession number VV30:VvABFOx. Data analyses were performed using R/Bioconductor (Gentleman et al., 2004). ...
In grape (Vitis vinifera), abscisic acid (ABA) accumulates during fruit ripening and is thought to play a pivotal role in this process, but the molecular basis of this control is poorly understood. This work characterizes ABSCISIC ACID RESPONSE ELEMENT-BINDING FACTOR2 (VvABF2), a grape basic leucine zipper transcription factor belonging to a phylogenetic subgroup previously shown to be involved in ABA and abiotic stress signaling in other plant species. VvABF2 transcripts mainly accumulated in the berry, from the onset of ripening to the harvesting stage, and were up-regulated by ABA. Microarray analysis of transgenic grape cells overexpressing VvABF2 showed that this transcription factor up-regulates and/or modifies existing networks related to ABA responses. In addition, grape cells overexpressing VvABF2 exhibited enhanced responses to ABA treatment compared with control cells. Among the VvABF2-mediated responses highlighted in this study, the synthesis of phenolic compounds and cell wall softening were the most strongly affected. VvABF2 overexpression strongly increased the accumulation of stilbenes that play a role in plant defense and human health (resveratrol and piceid). In addition, the firmness of fruits from tomato (Solanum lycopersicum) plants overexpressing VvABF2 was strongly reduced. These data indicate that VvABF2 is an important transcriptional regulator of ABA-dependent grape berry ripening.
... In the last years versatile tools for the meta-analysis of gene expression have been developed. PLEXdb (http://plexdb.org/) is a public resource for large-scale gene expression analysis of plants and provides a unified web interface to support the functional interpretation of microarray experiments by integrating structural-genomic and phenotypic data (Wise et al. 2006(Wise et al. , 2007. BarleyBase (Shen et al. 2005), which is now integrated into PLEXdb, contains expression data from 54 publicly available experiments corresponding to 1,724 hybridizations using the Affymetrix 22K Barley1 GeneChip. ...
Current high-throughput plant phenotyping pipelines are mainly focused on quantitative assessment of macroscopic parameters. Such morphological or physiological parameters measured on entire plants or major plant parts are not well adapted to the accurate description of plant-pathogen interactions because plant pathogens are microorganisms causing only microscale changes in their hosts or non-hosts during the initial stages on infection, which often decide about susceptibility or resistance. This makes the use of microscopic phenomics techniques unavoidable. However, the high-throughput requirements of modern phenomics screens represent a considerable challenge to the available microscopic approaches and underlying instruments used to characterize plant-pathogen interactions. To meet this challenge we have developed a platform that combines high-throughput DNA cloning, single cell transformation protocols, and automated microscopy and phenotyping that we called microphenomics. It was used to address the function of genes in nonhost- and race-nonspecific host resistance of barley interacting with the powdery mildew fungus Blumeria graminis. More than 1,300 genes derived from plant or fungal genomes were tested by silencing and approximately 100 of them had a significant effect on the resistance or susceptibility to the pathogen. The chapter gives an overview on the current status of this microphenomics platform for very early and early stages of plant-pathogen interactions. © 2014 Springer Science+Business Media Dordrecht. All rights are reserved.
... In contrast to Z. tritici, the extremely large and repeat-rich genome sequence of hexaploid wheat is still being finalized (Eversole et al., 2014). However, large numbers of ESTs, in addition to various individually sequenced chromosomes, are available to support molecular analyses (Wise et al., 2007;Eversole et al., 2014). In addition, a limited number of studies have begun to address the metabolomic responses of wheat toward pathogens and/or pathogen effectors (Du Fall and Solomon, 2013). ...
The “hemibiotrophic” fungus Zymoseptoria tritici causes Septoria tritici blotch disease of wheat (Triticum aestivum). Pathogen reproduction on wheat occurs without cell penetration, suggesting dynamic and intimate intercellular communication occurs between fungus and plant throughout the disease cycle. We used deep RNA sequencing and metabolomics to investigate the physiology of plant and pathogen throughout an asexual reproductive cycle of Z. tritici on wheat leaves. Over 3,000 pathogen genes, >7,000 wheat genes and >300 metabolites were differentially regulated. Intriguingly, individual fungal chromosomes contributed unequally to the overall gene expression changes. Early transcriptional down regulation of putative host defense genes was detected in inoculated leaves. There was little evidence for fungal nutrient acquisition from the plant throughout symptomless colonization by Z. tritici, which may instead be utilizing lipid and fatty acid stores for growth. However the fungus then subsequently manipulated specific plant carbohydrates, including fructan metabolites, during the switch to necrotrophic growth and reproduction. This switch coincided with increased expression of jasmonic acid (JA) biosynthesis genes and large scale activation of other plant “defense” responses. Fungal genes encoding putative secondary metabolite clusters and secreted effector proteins were identified with distinct infection phase-specific expression patterns, although functional analysis suggested many have overlapping / redundant functions in virulence. The pathogenic lifestyle of Z. tritici on wheat revealed through this study, involving initial defense suppression by a slow growing extracellular and nutritionally limited pathogen, followed by defense (hyper-) activation during reproduction, reveals a subtle modification on the conceptual definition of hemibiotrophic plant infection.
http://www.plantphysiol.org/content/early/2015/01/16/pp.114.255927.full.pdf+html
... In the last years versatile tools for the meta-analysis of gene expression have been developed. PLEXdb (http://plexdb.org/) is a public resource for large-scale gene expression analysis of plants and provides a unified web interface to support the functional interpretation of microarray experiments by integrating structural-genomic and phenotypic data (Wise et al. 2006(Wise et al. , 2007. BarleyBase (Shen et al. 2005), which is now integrated into PLEXdb, contains expression data from 54 publicly available experiments corresponding to 1,724 hybridizations using the Affymetrix 22K Barley1 GeneChip. ...
The plant immune system shows similarities with the innate immunity system of insects and mammals, yet keeping many plant-specific characteristics. Nonhost- and race-nonspecific host (basal-) resistance are two types of plant durable resistance hence of high importance to plant breeders. However, they are usually controlled by multiple quantitative trait loci (QTL) and therefore, difficult to approach by conventional or marker-assisted breeding. Understanding the genes underlying durable disease resistance will allow us to utilize it in a more targeted manner. Transient-induced gene silencing (TIGS) is one way to discover candidate genes underlying resistance QTL. We have developed and exploited a TIGS-based phenomics platform, which takes advantage of the well established model pathosystem of barley and the powdery mildew fungus together with efficient cloning and transformation protocols, and automated microscopic systems. The screening pipeline can be fed with candidates genes selected by different approaches such as transcript profiling, gene functional catalogs, co-localization with QTLs, etc. Until present we have tested approximately 1500 genes, which revealed 70 candidate genes significantly increasing resistance or susceptibility upon TIGS, as reflected by increased or decreased number of fungal haustoria inside transformed epidermal cells. We are working on further development of the phenomics platform towards quantification of hyphal growth rates, higher level of automation, and expanding the host and pathogen range.
... The IDs of probe sets present on the array corresponding to the VvARF genes were extracted using the VMatch tool at PLEXdb (http://www.plantgdb.org) (Wise et al. 2007). ...
Key message:
Our study has identified and analyzed the VvARF gene family that may be associated with the development of grape berry and other tissues. Auxin response factors (ARFs) are transcription factors that regulate the expression of auxin responsive genes through specific binding to auxin response elements (AuxREs). The ARF genes are represented by a large multigene family in plants. Until now, many ARF families have been characterized based on genome resources. However, there is no specialized research about ARF genes in grapevine (Vitis vinifera). In this study, a comprehensive bioinformatics analysis of the grapevine ARF gene family is presented, including chromosomal locations, phylogenetic relationships, gene structures, conserved domains and expression profiles. Nineteen VvARF genes were identified and categorized into four groups (Classes 1, 2, 3 and 4). Most of VvARF proteins contain B3, AUX_RESP and AUX_IAA domains. The VvARF genes were widely expressed in a range of grape tissues, and fruit had higher transcript levels for most VvARFs detected in the EST sources. Furthermore, analysis of expression profiles indicated some VvARF genes may play important roles in the regulation of grape berry maturation processes. This study which provided basic genomic information for the grapevine ARF gene family will be useful in selecting candidate genes related to tissue development in grapevine and pave the way for further functional verification of these VvARF genes.
... In the last years versatile tools for the meta-analysis of gene expression have been developed. PLEXdb (http://plexdb.org/) is a public resource for large-scale gene expression analysis of plants and provides a unified web interface to support the functional interpretation of microarray experiments by integrating structural-genomic and phenotypic data (Wise et al. 2006(Wise et al. , 2007. BarleyBase (Shen et al. 2005), which is now integrated into PLEXdb, contains expression data from 54 publicly available experiments corresponding to 1,724 hybridizations using the Affymetrix 22K Barley1 GeneChip. ...
Current high-throughput plant phenotyping pipelines are mainly
focused on quantitative assessment of macroscopic parameters.
Such morphological or physiological parameters measured on entire
plants or major plant parts are not well adapted to the accurate
description of plant-pathogen interactions because plant pathogens
are microorganisms causing only microscale changes in their hosts
or non-hosts during the initial stages on infection, which often decide
about susceptibility or resistance. This makes the use of microscopic
phenomics techniques unavoidable. However, the high throughput
requirements of modern phenomics screens represent a
considerable challenge to the available microscopic approaches and
underlying instruments used to characterize plant-pathogen
interactions. To meet this challenge we have developed a platform
that combines high-throughput DNA cloning, single cell
transformation protocols, and automated microscopy and
phenotyping that we called “microphenomics”. It was used to address
the function of genes in nonhost- and race-nonspecific host
resistance of barley interacting with the powdery mildew fungus
Blumeria graminis.More than 1,300 genes derived from plant or
fungal genomes were tested by silencing and approximately 100 of
them had a significant effect on the resistance or susceptibility to the
pathogen. The chapter gives an overview on the current status of this
microphenomics platform for very early and early stages of plantpathogen interactions.
... Three biological replicates of each sample (untreated control, control + ABA, 35S::VvABF2, and 35S::VvABF2 + ABA) were hybridized on NimbleGen microarray 090818 Vitis exp HX12 (Roche, NimbleGen), bearing a set of probes for 29,582 unigenes based on the 12X grapevine V1 gene model prediction (http://genomes.cribi.unipd.it/). The chip probe design is available at http://ddlab.sci.univr.it/FunctionalGenomics/. Robust multiarray averageprocessed data are available at PLEXdb (Wise et al., 2007) with accession number VV30:VvABFOx. Data analyses were performed using R/Bioconductor (Gentleman et al., 2004). ...
In grape (Vitis vinifera L.), abscisic acid (ABA) accumulates during fruit ripening and is thought to play a pivotal role in this process, but the molecular basis of this control is poorly understood. The present work characterizes VvABF2, a grape bZIP transcription factor belonging to a phylogenetic sub-group previously shown to be involved in ABA and abiotic stress signaling in other plant species. VvABF2 transcripts mainly accumulated in the berry, from the onset of ripening to the harvesting stage, and were up-regulated by ABA. Microarray analysis on transgenic grape cells overexpressing VvABF2 showed that this transcription factor upregulates and/or modifies existing networks related to ABA responses. In addition, grape cells overexpressing VvABF2 exhibited enhanced responses to ABA treatment compared to control cells. Among the VvABF2-mediated responses highlighted in this study, the synthesis of phenolic compounds and cell wall softening were the most strongly affected. VvABF2 overexpression strongly increased the accumulation of stilbenes that play a role in plant defense and human health (resveratrol and piceid). In addition, the firmness of fruits from tomato plants overexpressing VvABF2 was strongly reduced. These data indicate that VvABF2 is an important transcriptional regulator of ABA-dependent grape berry ripening.
... The comparison of the “RNA degradation plots” graphs obtained in this experiment (Additional file 1) with those of 18 experiments stored in the PlexDB database from 2005 to 2013 (http://www.plexdb.org) [21] supports the high quality of the hybridizations reported in this work. The observed average background ranged from 37.4 to 46.0 units of expression, well within the parameters defined by Affymetrix, and comparable with the values obtained in other experiments that have used the GeneChip® Wheat Genome Array [7, 22]. ...
Durum wheat often faces water scarcity and high temperatures, two events that usually occur simultaneously in the fields. Here we report on the stress responsive strategy of two durum wheat cultivars, characterized by different water use efficiency, subjected to drought, heat and a combination of both stresses.
The cv Ofanto (lower water use efficiency) activated a large set of well-known drought-related genes after drought treatment, while Cappelli (higher water use efficiency) showed the constitutive expression of several genes induced by drought in Ofanto and a modulation of a limited number of genes in response to stress. At molecular level the two cvs differed for the activation of molecular messengers, genes involved in the regulation of chromatin condensation, nuclear speckles and stomatal closure. Noteworthy, the heat response in Cappelli involved also the up-regulation of genes belonging to fatty acid beta-oxidation pathway, glyoxylate cycle and senescence, suggesting an early activation of senescence in this cv. A gene of unknown function having the greatest expression difference between the two cultivars was selected and used for expression QTL analysis, the corresponding QTL was mapped on chromosome 6B.
Ofanto and Cappelli are characterized by two opposite stress-responsive strategies. In Ofanto the combination of drought and heat stress led to an increased number of modulated genes, exceeding the simple cumulative effects of the two single stresses, whereas in Cappelli the same treatment triggered a number of differentially expressed genes lower than those altered in response to heat stress alone. This work provides clear evidences that the genetic system based on Cappelli and Ofanto represents an ideal tool for the genetic dissection of the molecular response to drought and other abiotic stresses.
... Raw expression data (CEL files) from selected Affymetrix Fusariuma520094 GeneChip studies (FG1, FG2 [58], FG5 [59], FG6 [60]) were retrieved from PLEXdb [61]. These experiments were selected to represent a large part of the Fusarium life cycle. ...
Genes for the production of a broad range of fungal secondary metabolites are frequently colinear. The prevalence of such gene clusters was systematically examined across the genome of the cereal pathogen Fusarium graminearum. The topological structure of transcriptional networks was also examined to investigate control mechanisms for mycotoxin biosynthesis and other processes.
The genes associated with transcriptional processes were identified, and the genomic location of transcription-associated proteins (TAPs) analyzed in conjunction with the locations of genes exhibiting similar expression patterns. Highly conserved TAPs reside in regions of chromosomes with very low or no recombination, contrasting with putative regulator genes. Co-expression group profiles were used to define positionally clustered genes and a number of members of these clusters encode proteins participating in secondary metabolism. Gene expression profiles suggest there is an abundance of condition-specific transcriptional regulation. Analysis of the promoter regions of co-expressed genes showed enrichment for conserved DNA-sequence motifs. Potential global transcription factors recognising these motifs contain distinct sets of DNA-binding domains (DBDs) from those present in local regulators.
Proteins associated with basal transcriptional functions are encoded by genes enriched in regions of the genome with low recombination. Systematic searches revealed dispersed and compact clusters of co-expressed genes, often containing a transcription factor, and typically containing genes involved in biosynthetic pathways. Transcriptional networks exhibit a layered structure in which the position in the hierarchy of a regulator is closely linked to the DBD structural class.
... For example, our recently predicted protein–protein interactions deposited in FPPI database (9) give a global interactome map of F. graminearum proteins; gene expression data from PLEXdb database (http://www.plexdb.org/) (10) describes the transcriptional activity under distinct conditions; pathway information available in KEGG database (11) characterizes the context in which genes function. ...
Fusarium graminearum is a plant pathogen, which causes crop diseases and further leads to huge economic damage worldwide in past decades. Recently, the accumulation of different types of molecular data provides insights into the pathogenic mechanism of F. graminearum, and might help develop efficient strategies to combat this destructive fungus. Unfortunately, most available molecular data related to F. graminearum are distributed in various media, where each single source only provides limited information on the complex biological systems of the fungus. In this work, we present a comprehensive database, namely eFG (Electronic resource for Fusarium graminearum), to the community for further understanding this destructive pathogen. In particular, a large amount of functional genomics data generated by our group is deposited in eFG, including protein subcellular localizations, protein–protein interactions and orthologous genes in other model organisms. This valuable knowledge can not only help to disclose the molecular underpinnings of pathogenesis of the destructive fungus F. graminearum but also help the community to develop efficient strategies to combat this pathogen. To our best knowledge, eFG is the most comprehensive functional genomics database for F. graminearum until now. The eFG database is freely accessible at http://csb.shu.edu.cn/efg/ with a user-friendly and interactive interface, and all data can be downloaded freely.Database URL:
http://csb.shu.edu.cn/efg/
... Affymetrix grape microarray data were downloaded from ArrayExpress [82] and PLEXdb [83] databases. A total of 16 experiments were used for our gene expression analyses (Table S6). ...
Background
The SBP-box gene family is specific to plants and encodes a class of zinc finger-containing transcription factors with a broad range of functions. Although SBP-box genes have been identified in numerous plants including green algae, moss, silver birch, snapdragon, Arabidopsis, rice and maize, there is little information concerning SBP-box genes, or the corresponding miR156/157, function in grapevine.
Methodology/Principal Findings
Eighteen SBP-box gene family members were identified in Vitis vinifera, twelve of which bore sequences that were complementary to miRNA156/157. Phylogenetic reconstruction demonstrated that plant SBP-domain proteins could be classified into seven subgroups, with the V. vinifera SBP-domain proteins being more closely related to SBP-domain proteins from dicotyledonous angiosperms than those from monocotyledonous angiosperms. In addition, synteny analysis between grape and Arabidopsis demonstrated that homologs of several grape SBP genes were found in corresponding syntenic blocks of Arabidopsis. Expression analysis of the grape SBP-box genes in various organs and at different stages of fruit development in V. quinquangularis ‘Shang-24’ revealed distinct spatiotemporal patterns. While the majority of the grape SBP-box genes lacking a miR156/157 target site were expressed ubiquitously and constitutively, most genes bearing a miR156/157 target site exhibited distinct expression patterns, possibly due to the inhibitory role of the microRNA. Furthermore, microarray data mining and quantitative real-time RT-PCR analysis identified several grape SBP-box genes that are potentially involved in the defense against biotic and abiotic stresses.
Conclusion
The results presented here provide a further understanding of SBP-box gene function in plants, and yields additional insights into the mechanism of stress management in grape, which may have important implications for the future success of this crop.
... Barley transcript data were acquired from the PLEXdb database Affymetrix Chip experiment BB3 entitled (http://www.plexdb.org/modules/tools/plexdb_blast.php) [30,59]. The database was searched using available cDNAs from barley endo-(1,4)-β-glucanase ESTs and contigs. ...
Background
Endo-(1,4)-β-glucanase (cellulase) glycosyl hydrolase GH9 enzymes have been implicated in several aspects of cell wall metabolism in higher plants, including cellulose biosynthesis and degradation, modification of other wall polysaccharides that contain contiguous (1,4)-β-glucosyl residues, and wall loosening during cell elongation.
Results
The endo-(1,4)-β-glucanase gene families from barley (Hordeum vulgare), maize (Zea mays), sorghum (Sorghum bicolor), rice (Oryza sativa) and Brachypodium (Brachypodium distachyon) range in size from 23 to 29 members. Phylogenetic analyses show variations in clade structure between the grasses and Arabidopsis, and indicate differential gene loss and gain during evolution. Map positions and comparative studies of gene structures allow orthologous genes in the five species to be identified and synteny between the grasses is found to be high. It is also possible to differentiate between homoeologues resulting from ancient polyploidizations of the maize genome. Transcript analyses using microarray, massively parallel signature sequencing and quantitative PCR data for barley, rice and maize indicate that certain members of the endo-(1,4)-β-glucanase gene family are transcribed across a wide range of tissues, while others are specifically transcribed in particular tissues. There are strong correlations between transcript levels of several members of the endo-(1,4)-β-glucanase family and the data suggest that evolutionary conservation of transcription exists between orthologues across the grass family. There are also strong correlations between certain members of the endo-(1,4)-β-glucanase family and other genes known to be involved in cell wall loosening and cell expansion, such as expansins and xyloglucan endotransglycosylases.
Conclusions
The identification of these groups of genes will now allow us to test hypotheses regarding their functions and joint participation in wall synthesis, re-modelling and degradation, together with their potential role in lignocellulose conversion during biofuel production from grasses and cereal crop residues.
... Affymetrix grape microarray data were downloaded from ArrayExpress [58] and PLEXdb [59] databases. A total of 12 experiments were used for our gene expression analyses (Table S1). ...
The TIFY gene family constitutes a plant-specific group of genes with a broad range of functions. This family encodes four subfamilies of proteins, including ZML, TIFY, PPD and JASMONATE ZIM-Domain (JAZ) proteins. JAZ proteins are targets of the SCF(COI1) complex, and function as negative regulators in the JA signaling pathway. Recently, it has been reported in both Arabidopsis and rice that TIFY genes, and especially JAZ genes, may be involved in plant defense against insect feeding, wounding, pathogens and abiotic stresses. Nonetheless, knowledge concerning the specific expression patterns and evolutionary history of plant TIFY family members is limited, especially in a woody species such as grape.
A total of two TIFY, four ZML, two PPD and 11 JAZ genes were identified in the Vitis vinifera genome. Phylogenetic analysis of TIFY protein sequences from grape, Arabidopsis and rice indicated that the grape TIFY proteins are more closely related to those of Arabidopsis than those of rice. Both segmental and tandem duplication events have been major contributors to the expansion of the grape TIFY family. In addition, synteny analysis between grape and Arabidopsis demonstrated that homologues of several grape TIFY genes were found in the corresponding syntenic blocks of Arabidopsis, suggesting that these genes arose before the divergence of lineages that led to grape and Arabidopsis. Analyses of microarray and quantitative real-time RT-PCR expression data revealed that grape TIFY genes are not a major player in the defense against biotrophic pathogens or viruses. However, many of these genes were responsive to JA and ABA, but not SA or ET.
The genome-wide identification, evolutionary and expression analyses of grape TIFY genes should facilitate further research of this gene family and provide new insights regarding their evolutionary history and regulatory control.
... To publish research involving microarrays, most journals require authors to follow these guidelines and deposit their data into a public repository that follows these guidelines. These include the Gene Expression Omnibus (GEO) [23], ArrayExpress [24] and PLEXdb [25], which is of particular importance as it specializes in plant and plant–pathogen microarrays. ...
Wheat (Triticum aestivum L.) is one of the most important food crops in the world, and transcriptomics studies of this crop promise to reveal the expression dynamics of genes that control many agriculturally important traits. In this review of wheat transcriptomics research, the current status of transcriptome surveying technology is presented, with particular emphasis on breakthrough techniques that will promote rapid progress in understanding the wheat genome. Microarrays have now become routine in wheat research, and the 55K Affymetrix Wheat GeneChip has enabled the generation of numerous high-quality datasets. In fact, the broad range of gene expression datasets provides future opportunities for integrating these data in a systematic approach that may reveal gene coexpression networks that underlie important traits. Wheat microarrays have also recently been used in other valuable approaches, including simultaneous transcriptome and genome profiling through single-feature polymorphism markers, the mapping of translocation breakpoints, and surveying of antisense transcription. The future use of wheat microarrays for gene expression measurement may be challenged by new sequencing-based transcriptomics techniques. These new techniques are presented, and the application of sequencing-by-synthesis as a future area of wheat transcriptomics research is highlighted. How-ever, the yet to be fully sequenced polyploid wheat genome poses problems for some of these technologies when attempting to annotate and assign short-sequence tags. For this reason, the Roche 454 technology is considered the best option for future progress because of its longer sequence reads that can be more easily annotated, as well as its unbiased potential for covering the entire wheat transcriptome.
... There are numerous other databases on transcriptome analysis. As additional examples,Table 4 lists a number of databases that accumulate data on several [80, 81] or individual82838485868788 plant species. In a transcriptome database, the user can find a list of genes expressed in a particular organ, tissue, or cell type, at a particular developmental stage, in the wild type or an altered genotype, or in response to stressors (biotic or abiotic). ...
Plant developmental genetics as a scientific discipline integrates data from such different fields of biology as embryology,
plant anatomy, molecular biology and genetics, and studies their interactions in the course of plant development. To date,
traditional publication of scientific studies in articles is supplemented by presenting in databases the data generated by
high-throughoutput methods in genomics, transcriptomics, proteomics, and phenomics. The information burst, caused both by
genome-scale research projects and growth in the number of articles, requires the development of general standards of annotating
data from different sources for their integration and comparison. In this review, we present classification and analysis of
existing databases, in which the user can find various data on plant developmental genetics, and discuss problems of these
data integration both within informational resources and among them.
... The Affymetrix probe set identifiers were imported and mapped with Populus trichocarpa/Ptrich_AFFY_09:1.0 and the pathway overview 1.0 (http://mapman.gabipd.org/web/guest). Annotation of Affymetrix probe set identifiers was done by using BarleyBase/PLEXdb (Wise et al., 2007). ...
Many plant species grow extrafloral nectaries and produce nectar to attract carnivore arthropods as defenders against herbivores. Two nectary types that evolved with Populus trichocarpa (Ptr) and Populus tremula × Populus tremuloides (Ptt) were studied from their ecology down to the genes and molecules. Both nectary types strongly differ in morphology, nectar composition and mode of secretion, and defense strategy. In Ptt, nectaries represent constitutive organs with continuous merocrine nectar flow, nectary appearance, nectar production, and flow. In contrast, Ptr nectaries were found to be holocrine and inducible. Neither mechanical wounding nor the application of jasmonic acid, but infestation by sucking insects, induced Ptr nectar secretion. Thus, nectaries of Ptr and Ptt seem to answer the same threat by the use of different mechanisms.
... Other sites, such as the Arabidopsis Information Resource Center (TAIR) [3] and plexDB.org [4], provide standard analytical tools such as gene expression graphs across samples for genes of interest, hierarchical and partitional clustering analysis, and the display of heat maps for genes across samples. ...
Recent advances in microarray technologies have resulted in a flood of genomics data. This large body of accumulated data could be used as a knowledge base to help researchers interpret new experimental data. ArraySearch finds statistical correlations between newly observed gene expression profiles and the huge source of well-characterized expression signatures deposited in the public domain. A search query of a list of genes will return experiments on which the genes are significantly up- or downregulated collectively. Searches can also be conducted using gene expression signatures from new experiments. This resource will empower biological researchers with a statistical method to explore expression data from their own research by comparing it with expression signatures from a large public archive.
... Affymetrix grape microarray data were downloaded from ArrayExpress [59] and PLEXdb [60] databases. A total of 19 experiments were used for our gene expression analyses (Table S1). ...
Background:
The completion of the grape genome sequencing project has paved the way for novel gene discovery and functional analysis. Aldehyde dehydrogenases (ALDHs) comprise a gene superfamily encoding NAD(P)(+)-dependent enzymes that catalyze the irreversible oxidation of a wide range of endogenous and exogenous aromatic and aliphatic aldehydes. Although ALDHs have been systematically investigated in several plant species including Arabidopsis and rice, our knowledge concerning the ALDH genes, their evolutionary relationship and expression patterns in grape has been limited.
Methodology/principal findings:
A total of 23 ALDH genes were identified in the grape genome and grouped into ten families according to the unified nomenclature system developed by the ALDH Gene Nomenclature Committee (AGNC). Members within the same grape ALDH families possess nearly identical exon-intron structures. Evolutionary analysis indicates that both segmental and tandem duplication events have contributed significantly to the expansion of grape ALDH genes. Phylogenetic analysis of ALDH protein sequences from seven plant species indicates that grape ALDHs are more closely related to those of Arabidopsis. In addition, synteny analysis between grape and Arabidopsis shows that homologs of a number of grape ALDHs are found in the corresponding syntenic blocks of Arabidopsis, suggesting that these genes arose before the speciation of the grape and Arabidopsis. Microarray gene expression analysis revealed large number of grape ALDH genes responsive to drought or salt stress. Furthermore, we found a number of ALDH genes showed significantly changed expressions in responses to infection with different pathogens and during grape berry development, suggesting novel roles of ALDH genes in plant-pathogen interactions and berry development.
Conclusion:
The genome-wide identification, evolutionary and expression analysis of grape ALDH genes should facilitate research in this gene family and provide new insights regarding their evolution history and functional roles in plant stress tolerance.
... We were able to make use of MaizeGDB and NCBI [16] warehoused data to search and retrieve information from many projects and to access additional databases: GRASSIUS [17], Gramene [18], MaizeSequence.org (http://www.maizesequence.org/), DFCI [19], Plant Genomics MAGIs [20], PLEXdb [21], PlantGDB [10], the Photosynthesis Mutant Library (PML) [22], and Phytozome (http://www.phytozome.net/search.php). Personnel working at these databases allowed access to their data and, in some instances, installed or permitted us to install Web services on their servers (GRASSIUS, DFCI, PLEXdb) or developed tools (PlantGDB) to enable our access. ...
The purpose of the online resource presented here, POPcorn (Project Portal for corn), is to enhance accessibility of maize genetic and genomic resources for plant biologists. Currently, many online locations are difficult to find, some are best searched independently, and individual project websites often degrade over time-sometimes disappearing entirely. The POPcorn site makes available (1) a centralized, web-accessible resource to search and browse descriptions of ongoing maize genomics projects, (2) a single, stand-alone tool that uses web Services and minimal data warehousing to search for sequence matches in online resources of diverse offsite projects, and (3) a set of tools that enables researchers to migrate their data to the long-term model organism database for maize genetic and genomic information: MaizeGDB. Examples demonstrating POPcorn's utility are provided herein.
... and the Fungal Genomic Program at the Joint Genome Institute (JGI; http://genome.jgi-psf.org/programs/fungi/index.jsf) that house fungal genomes, as well as the Integrated Microbial Genomes (IMG) (31), which supports a wide range of microbial genomes. Other databases are available that specialize in particular types of data, such as pathogen–host interactions (PHI-base) (32), pathogenic fungal ESTs (COGEME) (33), fungal secretome (FSD) (34) and a plant pathogen expression profile database (PLEXdb) (35). These specialized databases tend to store only particular types of data dedicated to specific phytopathogens. ...
The Comprehensive Phytopathogen Genomics Resource (CPGR) provides a web-based portal for plant pathologists and diagnosticians to view the genome and trancriptome sequence status of 806 bacterial, fungal, oomycete, nematode, viral and viroid plant pathogens. Tools are available to search and analyze annotated genome sequences of 74 bacterial, fungal and oomycete pathogens. Oomycete and fungal genomes are obtained directly from GenBank, whereas bacterial genome sequences are downloaded from the A Systematic Annotation Package (ASAP) database that provides curation of genomes using comparative approaches. Curated lists of bacterial genes relevant to pathogenicity and avirulence are also provided. The Plant Pathogen Transcript Assemblies Database provides annotated assemblies of the transcribed regions of 82 eukaryotic genomes from publicly available single pass Expressed Sequence Tags. Data-mining tools are provided along with tools to create candidate diagnostic markers, an emerging use for genomic sequence data in plant pathology. The Plant Pathogen Ribosomal DNA (rDNA) database is a resource for pathogens that lack genome or transcriptome data sets and contains 131 755 rDNA sequences from GenBank for 17 613 species identified as plant pathogens and related genera.
Database URL: http://cpgr.plantbiology.msu.edu.
... 24-96 hours post inoculation) were preferentially distributed to the sub-telomeric regions in areas of high recombination (Figure 3c). Since this initial dataset was published a further twelve microarray experiments have been published and these data are available from the Barleybase (PLEXdb) website [33]. These have been displayed using this software to explore their genomic distribution patterns and to link this with other data types, datasets and bespoke sequence annotation analyses (data not shown). ...
•
Acquiring and exploring whole genome sequence information for a species under investigation is now a routine experimental approach. On most genome browsers, typically, only the DNA sequence, EST support, motif search results, and GO annotations are displayed. However, for many species, a growing volume of additional experimental information is available but this is rarely searchable within the landscape of the entire genome. •
We have developed a generic software which permits users to view a single genome in entirety either within its chromosome or supercontig context within a single window. This software permits the genome to be displayed at any scales and with any features. Different data types and data sets are displayed onto the genome, which have been acquired from other types of studies including classical genetics, forward and reverse genetics, transcriptomics, proteomics and improved annotation from alternative sources. In each display, different types of information can be overlapped, then retrieved in the desired combinations and scales and used in follow up analyses. The displays generated are of publication quality. •
OmniMapFree provides a unified, versatile and easy-to-use software tool for studying a single genome in association with all the other datasets and data types available for the organism.
Bioinformatics being a multidisciplinary data-driven field has revolutionized several aspects of life sciences research, and area of drug development through medicinal plants is no exception. Medicinal plants have been known to play a major role in the primary healthcare system of several communities across the globe since ancient times. They continue to provide a multitude of pharmacologically active compounds. Now, to increase the utility of medicinal plants for drug discovery, bioinformatics plays a major role in replacing the conventional expensive, time-consuming and sluggish methods of drug development through high-throughput computational approaches. In this chapter, we attempt to present the comprehensive and updated summary on the role of bioinformatics in the area of medicinal plant research through the development of plant-based drugs. We need to understand the role of different bioinformatics approaches in medicinal plant research as it could serve as harbinger for the discovery of new therapeutic potential leads against various pharmacological targets. Owing to the increasing demand of herbal drugs in the market due to a wide continuum of beneficial effects they can offer to humankind over their non-plant counterparts, it becomes mandatory to pay attention to the medicinal plant-based research area in which there has been limited application of bioinformatics approaches. The chapter therefore aims to provide an overview on the current scenario of bioinformatics in analysing the data pertaining to medicinal plants, which ultimately could lead to quicker and economical drug designing with improved pharmacokinetics.
Reduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple ‘omics methodologies on cell suspensions of hybrid poplar (Populus tremula x Populus alba). Acclimation and growth of the cell suspensions in four nutrient regimes ranging from abundant to deficient supplies of carbon and nitrogen revealed that cell growth under low-nitrogen levels was associated with substantially higher NUE. To investigate the underlying metabolic and molecular mechanisms, we concurrently performed steady-state 13C metabolic flux analysis with multiple isotope labels and transcriptomic profiling with cDNA microarrays. The 13C flux analysis revealed that the absolute flux through the oxidative pentose phosphate pathway (oxPPP) was substantially lower (~3-fold) under low-nitrogen conditions. Additionally, the flux partitioning ratio between the tricarboxylic acid (TCA) cycle and anaplerotic pathways varied from 84%:16% under abundant carbon and nitrogen to 55%:45% under deficient carbon and nitrogen. Gene expression data, together with the flux results, suggested a plastidic localization of the oxPPP as well as transcriptional regulation of certain metabolic branchpoints including those between glycolysis and the oxPPP. The transcriptome data also indicated that NUE-improving mechanisms may involve a redirection of excess carbon to aromatic metabolic pathways and extensive downregulation of potentially redundant genes (in these heterotrophic cells) that encode photosynthetic and light-harvesting proteins, suggesting the recruitment of these proteins as nitrogen sinks in nitrogen-abundant conditions. This article is protected by copyright. All rights reserved.
Background
A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates.
Results
We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays.
Conclusions
The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.
Electronic supplementary material
The online version of this article (10.1186/s12859-017-1810-x) contains supplementary material, which is available to authorized users.
Progress in sequencing the barley genome has lagged behind that made in small genome plant species as well as in so-called cash crops that have much higher levels of investment in research and development. However, by exploiting a range of different sequencing technologies and adopting a diverse spectrum of approaches, over the past 10 years, comprehensive sequence resources for barley have been developed. These include sequence tags derived from commonly used RFLP markers, systematically sequenced expressed sequence tags (ESTs), BAC sequences that emerged from map-based cloning of specific target genes and more recently from tiled BAC clones positioned on a physical map, survey sequences from flow-sorted chromosomes and latterly deep whole-genome shotgun sequences. Here I provide a summary of currently available genomic sequence resources, outline planned future developments and highlight areas of application for these resources in barley research and ultimately in crop improvement.
Pattern recognition receptors represent a first line of plant defense against pathogens. Comparing the flag leaf transcriptomes of barley (Hordeum vulgare L.) near-isogenic lines varying in the allelic state of a locus controlling senescence, we have previously identified a leucine-rich repeat receptor-like protein kinase gene (LRR-RLK; GenBank accession: AK249842), which was strongly upregulated in leaves of early-as compared to late-senescing germplasm. Bioinformatic analysis indicated that this gene codes for a subfamily XII, non-arginine-aspartate (non-RD) LRR-RLK. Virus-induced gene silencing resulted in a two-fold reduction of transcript levels as compared to controls. Transcriptomic comparison of leaves from untreated plants, from plants treated with virus only without any plant sequences (referred to as 'empty virus' control), and from plants in which AK249842 expression was knocked down identified numerous genes involved in pathogen defense. These genes were strongly induced in 'empty virus' as compared to untreated controls, but their expression was significantly reduced (again compared to 'empty virus' controls) when AK249842 was knocked down, indicating that their expression partially depends on the LRR-RLK investigated here. Expression analysis, using datasets from BarleyBase/PLEXdb, demonstrated that AK249842 transcript levels are heavily influenced by the allelic state of the well-characterized mildew resistance a (Mla) locus, and that the gene is induced after powdery mildew and stem rust infection. Together, our data suggest that AK249842 is a barley pattern recognition receptor with a tentative role in defense against fungal pathogens, setting the stage for its full functional characterization.
The primary goal of this chapter is to provide practical information for utilizing the array of Saccharinae bioinformatics resources that are presently available. The chapter begins with the description of a survey of Saccharinae bioinformatics resources that was undertaken early in 2010. Resources are categorized by life science area(s), available data types, and modes of data access. Navigating resources and searching for Saccharinae data is then described through a broad collection of search examples that cover categories ranging from maps, markers, and genomic sequence through transcriptome-, proteome-, and biochemistry-related data. Data integration, as means for providing answers to more complex biological questions, is discussed in terms of existing applications of reference genome sequence and possible future applications of co-expression network data.
Abiotic stresses such as frost, drought, salinity, hypoxia, and mineral deficiency or toxicity frequently limit growth and productivity of temperate cereal crops, for which barley (Hordeum vulgare L. ssp. vulgare) could represent a model. Improving barley resistance to such constraints is thus fundamental in view of the expected climate change for minimizing the gap between potential and actual yield (the so-called “yield gap”), increasing the yield stability, and guaranteeing the sustainability of the crop. As different omics technologies have been developed during the past few decades, they enabled systematic analysis of changes that occur in plants in response to abiotic stresses. In this chapter, we focus on the “omics” contribution to the improvement of abiotic stress tolerance in barley. After a brief summary of the most relevant abiotic stresses that limit the crop yields worldwide, successful genomics approaches have been described, starting from the exploitation of germplasm resources. Structural and functional approaches that helped in understanding the mechanisms and the genetic bases of abiotic stress tolerance, when applied to barley and model species (mainly Arabidopsis, rice, and Brachypodium), have been reviewed as an important step toward crop tolerance improvement. Quantitative genetics and genetical genomics of abiotic stress tolerance have been discussed, as they represent both a huge source of information and a challenge for future holistic approaches. Then, we present an overview of the contribution of other omics sciences (e.g., proteomics, epigenomics, metabolomics, ionomics, and phenomics). In the last section, integrative (systems) biology, together with a series of strategies for the future, is proposed and discussed.
We investigated the growth behavior and amylolytic enzymes of Fusarium graminearum cultivated on different types of native starch granules including barley (A-type crystalline polymorph), potato and Curcuma zedoaria (B-type crystalline polymorph), cassava (C-type crystalline polymorph), and high AM maize (A + Vh-type crystalline polymorphs). F. graminearum grew poorly on B-type starches and the accumulation of biomass was similar to that obtained for fungi cultivated under carbohydrate starvation conditions. In comparison, three- to fivefold higher accumulation of fungal biomass was observed for growth on the A-, C- and A + Vh-type starches. Fungal glucoamylase and α-amylase activity increased over time in the presence of native starch granules. Interestingly, resistant B-type starches induced the highest amylolytic activity indicating that F. graminearum interacts with B-type granules although only limited degradation occur. Starch degradation products maltose and malto-oligosacharides was found to increase glucoamylase and α-amylase activity, whereas glucose acted as a catabolite repressor.
Leguminosae is a large and economically important family of plants that, because of their capacity to fix atmospheric nitrogen in symbiosis with rhizobia, are essential components of agricultural ecosystems and an important source in the production of food, feed, forage and other compounds with strong industrial and commercial relevance. During the last decade, the 'omics' technologies of legumes especially the model legumes have provided and still provide unprecedented amount of molecular information that has to be understood in a physiological, developmental and organismal context. New technologies, for example high-throughput sequencing, high multiplexed mapping techniques and rapid development of new bioinformatics tools have provided new information about current model systems and emerging new models as well. The latest information on the status of development of genomic resources and of related information in model legumes and some other economically important legume crops are summarized in this review. The infection of the plant root by rhizobia triggers several important events in the root cell, resulting in the formation of a nodule - a nitrogen-fixing compartment. Some of the signal molecules involved in the communication between the symbiotic partners have been studied but little is known about the genes and proteins involved in membrane and protein trafficking and targeting towards the symbiosome-the cellular compartment containing the nitrogen-fixing bacteria in the nodule, which is one of the most important processes in nodule formation and development. The central point of this review is to summarize the recent developments in functional genome, transcriptome and proteome of model legume plants specially Medicago truncatula, Lotus japonicus and Glycine max. A multidisciplinary approach, including plant and bacterial genetics, molecular biology, live cell imaging, biophysics and bioinformatics has been taken to understand the plant-microbe interaction and the biogenesis of root nodules and the genes and proteins involved in nodule formation and efficient nitrogen fixation. Vesicular trafficking plays an important role in rhizobia- root interaction, infection thread formation and the development of root nodules. I have described the role of several small GTP binding proteins in symbiosome formation and root nodule development. Furthermore, there is an increasing need to efficiently convert scientific results into practical applications or products. The economic and environmental costs of the heavy use of chemical N fertilizers in agriculture are a global concern. For this reason legumes could be used as an alternative source for N fertilizers and this would help for cleaning up the environmental pollution caused by chemical fertilizers. Additionally nitrogen-fixing biological systems represent an economically attractive and ecologically sound means of reducing external inputs and improving internal resources. I hope the scientific information given in this review paper could not only be useful to the molecular geneticists and plant breeders but will also assist the agronomists to carry out their research efficiently. © 2012 Springer Science+Business Media B.V. All rights reserved.
Obligate fungal biotrophs have co-evolved with their plant hosts, a direct result of an intimate interaction that protects the integrity of the plant during pathogenesis, allowing it to obtain essential nutrients. To restrict the establishment of pathogen colonization, plants have evolved complex regulatory mechanisms to control the defense response, the most extreme of which involves Resistance (R) gene-mediated programmed cell death. While it is known that de novo gene expression and subsequent protein synthesis are required for several cell death programs, the primary transcriptional targets of R gene-mediated responses are unknown. Two alternative approaches were used to identify these transcriptional targets. The first approach uses a time-course microarray experiment that contrasts wild-type and loss-of-function mutant alleles of the Mla (powdery mildew) R gene to identify transcripts that distinguish incompatibility from compatibility. Earlier expression and stronger transcriptional responses were observed in compatible plants at 20 hours after inoculation, though this reaction diminished at later time points. In contrast, incompatible interactions exhibited a time-dependent strengthening of the transcriptional response, with increases in both fold change and total number of genes differentially expressed. These results implicate MLA as a repressor of early gene expression response and provides further evidence for a link between basal and R gene-mediated resistance. The second approach uses natural variation present in a doubled-haploid population to identify the regulatory hierarchy of gene expression during the interaction of barley and stem rust. A trans-eQTL hotspot is not associated with the R gene Rpg-TTKSK, but instead an inoculation-dependent expression polymorphism in Adf3 implicates it as a candidate susceptibility gene. In contrast, co-localization of a trans-eQTL hotspot with an enhancer of R gene-mediated resistance to stem rust associates the suppression of gene expression with enhanced resistance. Lastly, Blufensin1 (Bln1) is used as a case study for functional analysis using gene expression, structural features, and phenotype. Although greater expression of Bln1 was previously associated with incompatibility, virus-induced gene silencing and transient overexpression implicates that Bln1 negatively impacts defense. Collectively, these studies suggest that our understanding of gene expression and its phenotypic consequences is more complex than previously thought.
The identification of virulence genes in plant pathogenic fungi is important for understanding the infection process, host range and for developing control strategies. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a 'guilt by association' approach. Here we study 133 genes in the globally important Ascomycete fungus Fusarium graminearum that have been experimentally tested for their involvement in virulence. An integrated network that combines information from gene co-expression, predicted protein-protein interactions and sequence similarity was employed and, using 100 genes known to be required for virulence, we found a total of 215 new proteins potentially associated with virulence of which 29 are annotated as hypothetical proteins. The majority of these potential virulence genes are located in chromosomal regions known to have a low recombination frequency. We have also explored the taxonomic diversity of these candidates and found 25 sequences, which are likely to be fungal specific. We discuss the biological relevance of a few of the potentially novel virulence associated genes in detail. The analysis of already verified virulence genes in phytopathogenic fungi in the context of integrated functional networks can give clues about the underlying mechanisms and pathways directly or indirectly linked to fungal pathogenicity and can suggest new candidates for further experimental investigation, using a 'guilt by association' approach.
The use of DNA markers in public sector plant breeding is now the norm. Such markers are common across breeding programs and this commonality enables and enhances collaboration. Therefore, large collaborative research projects that measure several phenotypes across multiple environments coupled wiThthe expanding amount of genotype data attainable wiThcurrent marker technologies are on the rise and these projects demand effi cient data delivery. However, development of computational tools for advanced data integration, visualization, and analysis is still a bottleneck, even though these resources have the greatest potential impact for users who are extracting and developing hypothesis-based solutions. The Hordeum Toolbox (THT) was developed as a data resource for the Barley Coordinated Agricultural Project (CAP) wiThthe novel capability of constructing user-defi ned downloadable sets of phenotype and/or genotype data for downstream analysis. Internal tools in THT enable users to create clusters of a selected group of lines based on genotype data, parse pedigrees, and select germplasm based on haplotype, phenotype, and agronomic properties. The Hordeum Toolbox can be adapted to breeding programs or collaborations to assist researchers in germplasm selection, genotype data visualization, and the integration of complex data sets for statistical analysis.
Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean.
We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses.
This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization.
The SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SBP) proteins form a family of transcriptional regulators, which are present exclusively
in plants. Members of this family control processes such as flower development, sporogenesis, toxin resistance, control of
GA levels, and response to copper. A genome-wide characterization of this family has not been conducted in a berry species,
such as grapevine. Recent publication of the complete grapevine genome opens the possibility for an in depth analysis of the
SBP-box gene family in grapevine. By screening the available databases, we identified 19 SBP-box genes with high sequence
identity within the conserved SBP domain. An analysis of a complete set of SBP-box proteins in grapevine is presented, including
their classification, gene structures, conserved motifs, and phylogenetic relationships. The grapevine SBP-box proteins can
be classified into three groups (A, B, and C) based on their phylogenetic relationships with Arabidopsis SBP-box proteins. The expression patterns of the SBP-box genes were further investigated by searching against EST and microarray
data. We found that the grapevine SBP-box genes were expressed primarily in flowers and fruit. The comparison of the SBP-box
proteins of grapevine and tomato suggested that grapevine SBP-box genes might play an important role in fruit development.
Key wordsVitis vinifera-SBP-box-grapevine-phylogenetic analysis-EST-expression profiling
Plant pathogens elicit dramatic changes in the expression of host genes during both compatible and incompatible interactions. Gene expression profiling studies of plant-pathogen interactions have only considered messenger RNAs (mRNAs) present in total RNA, which contains subpopulations of actively translated mRNAs associated with polyribosomes (polysomes) and non-translated mRNAs that are not associated with polysomes. The goal of this study was to enhance previous gene expression analyses by identifying host mRNAs that become differentially associated with polysomes following pathogen inoculation. Total and polysomal RNA were extracted from barley (Hordeum vulgare) plants at 32 h after inoculation with Blumeria graminis f. sp. hordei, and Arabidopsis thaliana plants at 10 days after inoculation with Turnip mosaic virus. Gene expression profiles were obtained for each pathosystem, which represent diverse plant host-obligate pathogen interactions. Using this approach, host mRNAs were identified that were differentially associated with polysomes in response to pathogen treatment. Approximately 18% and 26% of mRNAs represented by probe sets on the Affymetrix Barley1 and Arabidopsis ATH1 GeneChips, respectively, differentially accumulated in the two populations in one or more combinations of treatment and genotype. Gene ontology analysis of mRNAs sharing the same pattern of accumulation in total and polysomal RNA identified gene sets that contained a significant number of functionally related annotations, suggesting both transcript accumulation and recruitment to polyribosomes are coordinately regulated in these systems.
Plants have been used as a source of medicine since historic times and several commercially important drugs are of plant-based
origin. The traditional approach towards discovery of plant-based drugs often times involves significant amount of time and
expenditure. These labor-intensive approaches have struggled to keep pace with the rapid development of high-throughput technologies.
In the era of high volume, high-throughput data generation across the biosciences, bioinformatics plays a crucial role. This
has generally been the case in the context of drug designing and discovery. However, there has been limited attention to date
to the potential application of bioinformatics approaches that can leverage plant-based knowledge. Here, we review bioinformatics
studies that have contributed to medicinal plants research. In particular, we highlight areas in medicinal plant research
where the application of bioinformatics methodologies may result in quicker and potentially cost-effective leads toward finding
plant-based remedies.
The analysis of gene expression data generated by high-throughput microarray transcript profiling experiments has shown that transcriptionally coordinated genes are often functionally related. Based on large-scale expression compendia grouping multiple experiments, this guilt-by-association principle has been applied to study modular gene programmes, identify cis-regulatory elements or predict functions for unknown genes in different model plants. Recently, several studies have demonstrated how, through the integration of gene homology and expression information, correlated gene expression patterns can be compared between species. The incorporation of detailed functional annotations as well as experimental data describing protein-protein interactions, phenotypes or tissue specific expression, provides an invaluable source of information to identify conserved gene modules and translate biological knowledge from model organisms to crops. In this review, we describe the different steps required to systematically compare expression data across species. Apart from the technical challenges to compute and display expression networks from multiple species, some future applications of plant comparative transcriptomics are highlighted.
Certain plant receptor-like cytoplasmic kinases were reported to interact with small monomeric G-proteins of the RHO of plant (ROP; also called RAC) family in planta and to be activated by this interaction in vitro. We identified a barley (Hordeum vulgare) partial cDNA of a ROP binding protein kinase (HvRBK1) in yeast (Saccharomyces cerevisiae) two-hybrid screenings with barley HvROP bait proteins. Protein interaction of the constitutively activated (CA) barley HvROPs CA HvRACB and CA HvRAC1 with full-length HvRBK1 was verified in yeast and in planta. Green fluorescent protein-tagged HvRBK1 appears in the cytoplasm and nucleoplasm, but CA HvRACB or CA HvRAC1 can recruit green fluorescent protein-HvRBK1 to the cell periphery. Barley HvRBK1 is an active kinase in vitro, and activity is enhanced by CA HvRACB or GTP-loaded HvRAC1. Hence, HvRBK1 might act downstream of active HvROPs. Transient-induced gene silencing of barley HvRBK1 supported penetration by the parasitic fungus Blumeria graminis f. sp. hordei, suggesting a function of the protein in basal disease resistance. Transient knockdown of HvRBK1 also influenced the stability of cortical microtubules in barley epidermal cells. Hence, HvRBK1 might function in basal resistance to powdery mildew by influencing microtubule organization.
Metabolome refers to the complete set of metabolites synthesized through a series of multiple enzymatic steps from various biochemical pathways processing the information encrypted in the plant genome. Knowledge about synthesis and regulation of various plant metabolic substances has improved substantially with availability of Omics data originating from sequencing of plant genomes. Metabolic profiling of crops is increasingly becoming popular in assessing plant phenotypes and genetic diversity. Metabolic compositional changes vividly reflect the changes occurring during plant growth, development, and in response to stress. Hence, study of plant metabolic pathways, the interconnections between them in context of systems biology is increasingly becoming popular in identification of candidate genes. The present article reviews recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their application in plants.
Members of the Wheat-Induced Resistance 1 (TaWIR1) gene family are highly induced in response to a wide range of pathogens. Homologues have been identified in barley, but not in Brachypodium, whereas, in rice, only distant WIR1 candidates are known. Phylogenetic analysis placed TaWIR1a and TaWIR1b within a distinct clade of wheat transcripts, whereas TaWIR1c clustered with HvWIR1 genes. Transcripts of all three TaWIR1 genes were strongly induced by a wheat-adapted isolate of Magnaporthe oryzae. Virus-induced gene silencing of the TaWIR1 gene family had no effect on the initial penetration of epidermal cells by M. oryzae. However, following the establishment of an infection site, the fungus was able to grow more extensively within the leaf tissue, relative to control leaves, indicating a role for the TaWIR1 gene family in the cell-to-cell movement of M. oryzae. In contrast, the silencing of TaWIR1 transcripts had no effect on epidermal cell penetration by a wheat-adapted isolate of Blumeria graminis, or on the subsequent growth of hyphae. Differential transcription of TaWIR1 genes was also seen in epidermal peels, relative to the remaining leaf tissue, following inoculation with M. oryzae.
Motivation: The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these
new methods are widely used.
Results: The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. The package is currently in its second release, affy provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe
intensity data. In this paper, we present the main classes and functions in the package and demonstrate how they can be used
to process probe-level data. We also demonstrate the importance of probe-level analysis when using the Affymetrix GeneChip platform.