First step toward gene expression data integration: transcriptomic data acquisition with COMMAND>_.

BACKGROUND: Exploring cellular responses to stimuli using extensive gene expression profiles has become a routine procedure performed on a daily basis. Raw and processed data from these studies are available on public databases but the opportunity to fully exploit such rich datasets is limited due to the large heterogeneity of data formats. In recent years, several approaches have been proposed to effectively integrate gene expression data for analysis and exploration at a broader level. Despite the different goals and approaches towards gene expression data integration, the first step is common to any proposed method: data acquisition. Although it is seemingly straightforward to extract valuable information from a set of downloaded files, things can rapidly get complicated, especially as the number of experiments grows. Transcriptomic datasets are deposited in public databases with little regard to data format and thus retrieving raw data might become a challenging task. While for RNA-seq experiments such problem is partially mitigated by the fact that raw reads are generally available on databases such as the NCBI SRA, for microarray experiments standards are not equally well established, or enforced during submission, and thus a multitude of data formats has emerged. RESULTS: COMMAND>_ is a specialized tool meant to simplify gene expression data acquisition. It is a flexible multi-user web-application that allows users to search and download gene expression experiments, extract only the relevant information from experiment files, re-annotate microarray platforms, and present data in a simple and coherent data model for subsequent analysis. CONCLUSIONS: COMMAND>_ facilitates the creation of local datasets of gene expression data coming from both microarray and RNA-seq experiments and may be a more efficient tool to build integrated gene expression compendia. COMMAND>_ is free and open-source software, including publicly available tutorials and documentation.

Time-Course Transcriptome Analysis of Arabidopsis Siliques Discloses Genes Essential for Fruit Development and Maturation.

Fruits protect the developing seeds of angiosperms and actively contribute to seed dispersion. Furthermore, fruit and seed development are highly synchronized and require exchange of information between the mother plant and the developing generations. To explore the mechanisms controlling fruit formation and maturation, we performed a transcriptomic analysis on the valve tissue of the Arabidopsis (Arabidopsis thaliana) silique using RNA sequencing. In doing so, we have generated a data set of differentially regulated genes that will help to elucidate the molecular mechanisms that underpin the initial phase of fruit growth and, subsequently, trigger fruit maturation. The robustness of our data set has been tested by functional genomic studies. Using a reverse genetics approach, we selected 10 differentially expressed genes and explored the consequences of their disruption for both silique growth and senescence. We found that genes contained in our data set play essential roles in different stages of silique development and maturation, indicating that our transcriptome-based gene list is a powerful tool for the elucidation of the molecular mechanisms controlling fruit formation in Arabidopsis.

COLOMBOS v3.0: leveraging gene expression compendia for cross-species analyses.

COLOMBOS is a database that integrates publicly available transcriptomics data for several prokaryotic model organisms. Compared to the previous version it has more than doubled in size, both in terms of species and data available. The manually curated condition annotation has been overhauled as well, giving more complete information about samples' experimental conditions and their differences. Functionality-wise cross-species analyses now enable users to analyse expression data for all species simultaneously, and identify candidate genes with evolutionary conserved expression behaviour. All the expression-based query tools have undergone a substantial improvement, overcoming the limit of enforced co-expression data retrieval and instead enabling the return of more complex patterns of expression behaviour. COLOMBOS is freely available through a web application at http://colombos.net/. The complete database is also accessible via REST API or downloadable as tab-delimited text files.

Dual RNA-Seq of Lysobacter capsici AZ78 - Phytophthora infestans interaction shows the implementation of attack strategies by the bacterium and unsuccessful oomycete defense responses.

Biological interactions in the microbial communities of the rhizosphere continuously shape the gene expression patterns of each individual microorganism. A dual RNA-Seq approach was applied to obtain a comprehensive overview of the molecular mechanisms activated during the interaction between the biocontrol rhizobacterium Lysobacter capsici AZ78 and the soilborne phytopathogenic oomycete Phytophthora infestans. The RNA-Seq transcriptional profile of L. capsici AZ78 was characterized by up-regulation of genes concerned in the biogenesis of type 4 pilus and lytic enzymes, involved, respectively, in host colonization and subsequent attack of the P. infestans cell wall. The activation of detoxification processes allowed L. capsici AZ78 to overcome the attempted defense processes of P. infestans. Moreover, the genes involved in antibiotic biosynthesis were up-regulated in L. capsici AZ78 and caused cell death in P. infestans, with the activation of putative apoptotic processes. The consequences of P. infestans cell death resulted in the down-regulation of primary metabolic pathways, such as carbohydrates, nucleic acids and protein metabolisms. Overall, the mechanism of action of L. capsici AZ78 was related to parasitism and predatory activities that cause the death of P. infestans.

Molecular analysis of the early interaction between the grapevine flower and Botrytis cinerea reveals that prompt activation of specific host pathways leads to fungus quiescence.

Grape quality and yield can be impaired by bunch rot, caused by the necrotrophic fungus Botrytis cinerea. Infection often occurs at flowering, and the pathogen stays quiescent until fruit maturity. Here, we report a molecular analysis of the early interaction between B. cinerea and Vitis vinifera flowers, using a controlled infection system, confocal microscopy and integrated transcriptomic and metabolic analysis of the host and the pathogen. Flowers from fruiting cuttings of the cultivar Pinot Noir were infected with green fluorescent protein (GFP)-labelled B. cinerea and studied at 24 and 96 hours post-inoculation (h.p.i.). We observed that penetration of the epidermis by B. cinerea coincided with increased expression of genes encoding cell-wall-degrading enzymes, phytotoxins and proteases. Grapevine responded with a rapid defence reaction involving 1193 genes associated with the accumulation of antimicrobial proteins, polyphenols, reactive oxygen species and cell wall reinforcement. At 96 h.p.i., the reaction appears largely diminished both in the host and in the pathogen. Our data indicate that the defence responses of the grapevine flower collectively are able to restrict invasive fungal growth into the underlying tissues, thereby forcing the fungus to enter quiescence until the conditions become more favourable to resume pathogenic development.

The grapevine VvibZIPC22 transcription factor is involved in the regulation of flavonoid biosynthesis.

In grapevine, flavonoids constitute one of the most abundant subgroups of secondary metabolites, influencing the quality, health value, and typicity of wines. Their synthesis in many plant species is mainly regulated at the transcriptional level by modulation of flavonoid pathway genes either by single regulators or by complexes of different regulators. In particular, bZIP and MYB factors interact synergistically in the recognition of light response units present in the promoter of some genes of the pathway, thus mediating light-dependent flavonoid biosynthesis. We recently identified VvibZIPC22, a member of clade C of the grapevine bZIP family, in a quantitative trait locus (QTL) specifically associated with kaemperol content in mature berries. Here, to validate the involvement of this candidate gene in the fine regulation of flavonol biosynthesis, we characterized its function by in vitro and in vivo experiments. A role for this gene in the control of flavonol biosynthesis was indeed confirmed by its highest expression at flowering and during UV light-mediated induction, paralleled by accumulation of the flavonol synthase 1 transcript and flavonol compounds. The overexpression of VvibZIPC22 in tobacco caused a significant increase in several flavonoids in the flower, via induction of general and specific genes of the pathway. In agreement with this evidence, VvibZIPC22 was able to activate the promoters of specific genes of the flavonoid pathway, alone or together with other factors, as revealed by transient reporter assays. These findings, supported by in silico indications, allowed us to propose VvibZIPC22 as a new regulator of flavonoid biosynthesis in grapevine.

Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome.

Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF). Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in bacterial pangenomes.

COLOMBOS v2.0: an ever expanding collection of bacterial expression compendia.

The COLOMBOS database (http://www.colombos.net) features comprehensive organism-specific cross-platform gene expression compendia of several bacterial model organisms and is supported by a fully interactive web portal and an extensive web API. COLOMBOS was originally published in PLoS One, and COLOMBOS v2.0 includes both an update of the expression data, by expanding the previously available compendia and by adding compendia for several new species, and an update of the surrounding functionality, with improved search and visualization options and novel tools for programmatic access to the database. The scope of the database has also been extended to incorporate RNA-seq data in our compendia by a dedicated analysis pipeline. We demonstrate the validity and robustness of this approach by comparing the same RNA samples measured in parallel using both microarrays and RNA-seq. As far as we know, COLOMBOS currently hosts the largest homogenized gene expression compendia available for seven bacterial model organisms.

MAGIC: access portal to a cross-platform gene expression compendium for maize.

To facilitate the exploration of publicly available Zea mays expression data, we constructed a maize expression compendium, making use of an integration methodology and a consistent probe to gene mapping based on the 5b.60 sequence release of Z. mays. The compendium is made available through a web portal MAGIC that hosts a variety of analysis tools to easily browse and analyze the data. Our compendium is different from previous initiatives in combining expression values across different experiments by providing a consistent gene annotation across different platforms.

Expression divergence between Escherichia coli and Salmonella enterica serovar Typhimurium reflects their lifestyles.

Escherichia coli K12 is a commensal bacteria and one of the best-studied model organisms. Salmonella enterica serovar Typhimurium, on the other hand, is a facultative intracellular pathogen. These two prokaryotic species can be considered related phylogenetically, and they share a large amount of their genetic material, which is commonly termed the "core genome." Despite their shared core genome, both species display very different lifestyles, and it is unclear to what extent the core genome, apart from the species-specific genes, plays a role in this lifestyle divergence. In this study, we focus on the differences in expression domains for the orthologous genes in E. coli and S. Typhimurium. The iterative comparison of coexpression methodology was used on large expression compendia of both species to uncover the conservation and divergence of gene expression. We found that gene expression conservation occurs mostly independently from amino acid similarity. According to our estimates, at least more than one quarter of the orthologous genes has a different expression domain in E. coli than in S. Typhimurium. Genes involved with key cellular processes are most likely to have conserved their expression domains, whereas genes showing diverged expression are associated with metabolic processes that, although present in both species, are regulated differently. The expression domains of the shared "core" genome of E. coli and S. Typhimurium, consisting of highly conserved orthologs, have been tuned to help accommodate the differences in lifestyle and the pathogenic potential of Salmonella.

Phenotypical and molecular responses of Arabidopsis thaliana roots as a result of inoculation with the auxin-producing bacterium Azospirillum brasilense.

The auxin-producing bacterium Azospirillum brasilense Sp245 can promote the growth of several plant species. The model plant Arabidopsis thaliana was chosen as host plant to gain an insight into the molecular mechanisms that govern this interaction. The determination of differential gene expression in Arabidopsis roots after inoculation with either A. brasilense wild-type or an auxin biosynthesis mutant was achieved by microarray analysis. Arabidopsis thaliana inoculation with A. brasilense wild-type increases the number of lateral roots and root hairs, and elevates the internal auxin concentration in the plant. The A. thaliana root transcriptome undergoes extensive changes on A. brasilense inoculation, and the effects are more pronounced at later time points. The wild-type bacterial strain induces changes in hormone- and defense-related genes, as well as in plant cell wall-related genes. The A. brasilense mutant, however, does not elicit these transcriptional changes to the same extent. There are qualitative and quantitative differences between A. thaliana responses to the wild-type A. brasilense strain and the auxin biosynthesis mutant strain, based on both phenotypic and transcriptomic data. This illustrates the major role played by auxin in the Azospirillum-Arabidopsis interaction, and possibly also in other bacterium-plant interactions.

Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli.

Recognition of genomic binding sites by transcription factors can occur through base-specific recognition, or by recognition of variations within the structure of the DNA macromolecule. In this article, we investigate what information can be retrieved from local DNA structural properties that is relevant to transcription factor binding and that cannot be captured by the nucleotide sequence alone. More specifically, we explore the benefit of employing the structural characteristics of DNA to create binding-site models that encompass indirect recognition for the Escherichia coli model organism. We developed a novel methodology [Conditional Random fields of Smoothed Structural Data (CRoSSeD)], based on structural scales and conditional random fields to model and predict regulator binding sites. The value of relying on local structural-DNA properties is demonstrated by improved classifier performance on a large number of biological datasets, and by the detection of novel binding sites which could be validated by independent data sources, and which could not be identified using sequence data alone. We further show that the CRoSSeD-binding-site models can be related to the actual molecular mechanisms of the transcription factor DNA binding, and thus cannot only be used for prediction of novel sites, but might also give valuable insights into unknown binding mechanisms of transcription factors.

COMODO: an adaptive coclustering strategy to identify conserved coexpression modules between organisms.

Increasingly large-scale expression compendia for different species are becoming available. By exploiting the modularity of the coexpression network, these compendia can be used to identify biological processes for which the expression behavior is conserved over different species. However, comparing module networks across species is not trivial. The definition of a biologically meaningful module is not a fixed one and changing the distance threshold that defines the degree of coexpression gives rise to different modules. As a result when comparing modules across species, many different partially overlapping conserved module pairs across species exist and deciding which pair is most relevant is hard. Therefore, we developed a method referred to as conserved modules across organisms (COMODO) that uses an objective selection criterium to identify conserved expression modules between two species. The method uses as input microarray data and a gene homology map and provides as output pairs of conserved modules and searches for the pair of modules for which the number of sharing homologs is statistically most significant relative to the size of the linked modules. To demonstrate its principle, we applied COMODO to study coexpression conservation between the two well-studied bacteria Escherichia coli and Bacillus subtilis. COMODO is available at: http://homes.esat.kuleuven.be/∼kmarchal/Supplementary_Information_Zarrineh_2010/comodo/index.html.

A COMPASS for VESPUCCI: A FAIR Way to Explore the Grapevine Transcriptomic Landscape.

Successfully integrating transcriptomic experiments is a challenging task with the ultimate goal of analyzing gene expression data in the broader context of all available measurements, all from a single point of access. In its second major release VESPUCCI, the integrated database of gene expression data for grapevine, has been updated to be FAIR-compliant, employing standards and created with open-source technologies. It includes all public grapevine gene expression experiments from both microarray and RNA-seq platforms. Transcriptomic data can be accessed in multiple ways through the newly developed COMPASS GraphQL interface, while the expression values are normalized using different methodologies to flexibly satisfy different analysis requirements. Sample annotations are manually curated and use standard formats and ontologies. The updated version of VESPUCCI provides easy querying and analyzing of integrated grapevine gene expression (meta)data and can be seamlessly embedded in any analysis workflow or tools. VESPUCCI is freely accessible and offers several ways of interaction, depending on the specific goals and purposes and/or user expertise; an overview can be found at https://vespucci.readthedocs.io/.

Query-based biclustering of gene expression data using Probabilistic Relational Models.

BACKGROUND: With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set. RESULTS: We applied ProBic on a large scale Escherichia coli compendium to extend partially described regulons with potentially novel members. We compared ProBic's performance with previously published query-based biclustering algorithms, namely ISA and QDB, from the perspective of bicluster expression quality, robustness of the outcome against noisy seed sets and biological relevance.This comparison learns that ProBic is able to retrieve biologically relevant, high quality biclusters that retain their seed genes and that it is particularly strong in handling noisy seeds. CONCLUSIONS: ProBic is a query-based biclustering algorithm developed in a flexible framework, designed to detect biologically relevant, high quality biclusters that retain relevant seed genes even in the presence of noise or when dealing with low quality seed sets.

A comparative transcriptome analysis of Rhizobium etli bacteroids: specific gene expression during symbiotic nongrowth.

Rhizobium etli occurs either in a nitrogen-fixing symbiosis with its host plant, Phaseolus vulgaris, or free-living in the soil. During both conditions, the bacterium has been suggested to reside primarily in a nongrowing state. Using genome-wide transcriptome profiles, we here examine the molecular basis of the physiological adaptations of rhizobia to nongrowth inside and outside of the host. Compared with exponentially growing cells, we found an extensive overlap of downregulated growth-associated genes during both symbiosis and stationary phase, confirming the essentially nongrowing state of nitrogen-fixing bacteroids in determinate nodules that are not terminally differentiated. In contrast, the overlap of upregulated genes was limited. Generally, actively growing cells have hitherto been used as reference to analyze symbiosis-specific expression. However, this prevents the distinction between differential expression arising specifically from adaptation to a symbiotic lifestyle and features associated with nongrowth in general. Using stationary phase as the reference condition, we report a distinct transcriptome profile for bacteroids, containing 203 induced and 354 repressed genes. Certain previously described symbiosis-specific characteristics, such as the downregulation of amino acid metabolism genes, were no longer observed, indicating that these features are more likely due to the nongrowing state of bacteroids rather than representing bacteroid-specific physiological adaptations.

Transcriptome analysis of the rhizosphere bacterium Azospirillum brasilense reveals an extensive auxin response.

The rhizosphere bacterium Azospirillum brasilense produces the auxin indole-3-acetic acid (IAA) through the indole-3-pyruvate pathway. As we previously demonstrated that transcription of the indole-3-pyruvate decarboxylase (ipdC) gene is positively regulated by IAA, produced by A. brasilense itself or added exogenously, we performed a microarray analysis to study the overall effects of IAA on the transcriptome of A. brasilense. The transcriptomes of A. brasilense wild-type and the ipdC knockout mutant, both cultured in the absence and presence of exogenously added IAA, were compared.Interfering with the IAA biosynthesis/homeostasis in A. brasilense through inactivation of the ipdC gene or IAA addition results in much broader transcriptional changes than anticipated. Based on the multitude of changes observed by comparing the different transcriptomes, we can conclude that IAA is a signaling molecule in A. brasilense. It appears that the bacterium, when exposed to IAA, adapts itself to the plant rhizosphere, by changing its arsenal of transport proteins and cell surface proteins. A striking example of adaptation to IAA exposure, as happens in the rhizosphere, is the upregulation of a type VI secretion system (T6SS) in the presence of IAA. The T6SS is described as specifically involved in bacterium-eukaryotic host interactions. Additionally, many transcription factors show an altered regulation as well, indicating that the regulatory machinery of the bacterium is changing.

Alternative experimental design with an applied normalization scheme can improve statistical power in 2D-DIGE experiments.

2D-DIGE experiments are a high-throughput technique for measuring protein abundances based on gel separation. Traditionally three samples are multiplexed per gel: two biological test samples and a third internal standard sample consisting of a pool of all test samples. We demonstrate that the use of an internal standard helps to account for technical variation caused by spatial intensity biases that exist in the gels and propose a novel data-preprocessing technique, a spatial intensity bias removal (SIBR), which can approximate these biases using only the data of biological replicates loaded on the gel. Using this technique, we show that by replacing the internal standard with additional biological replicates, a significant increase in statistical power can be achieved compared to traditional 2D-DIGE designs. This boost in statistical power can be used to reduce the false positive rate for identifying differential protein abundances without compromising sensitivity, or to improve sensitivity without compromising false positive rate. A software implementation of SIBR can be downloaded at http://ibiza.biw.kuleuven.be/SIBR .

The potential for pathogenicity was present in the ancestor of the Ascomycete subphylum Pezizomycotina.

BACKGROUND: Previous studies in Ascomycetes have shown that the function of gene families of which the size is considerably larger in extant pathogens than in non-pathogens could be related to pathogenicity traits. However, by only comparing gene inventories in extant species, no insights can be gained into the evolutionary process that gave rise to these larger family sizes in pathogens. Moreover, most studies which consider gene families in extant species only tend to explain observed differences in gene family sizes by gains rather than by losses, hereby largely underestimating the impact of gene loss during genome evolution. RESULTS: In our study we used a selection of recently published genomes of Ascomycetes to analyze how gene family gains, duplications and losses have affected the origin of pathogenic traits. By analyzing the evolutionary history of gene families we found that most gene families with an enlarged size in pathogens were present in an ancestor common to both pathogens and non-pathogens. The majority of these families were selectively maintained in pathogenic lineages, but disappeared in non-pathogens. Non-pathogen-specific losses largely outnumbered pathogen-specific losses. CONCLUSIONS: We conclude that most of the proteins for pathogenicity were already present in the ancestor of the Ascomycete lineages we used in our study. Species that did not develop pathogenicity seemed to have reduced their genetic complexity compared to their ancestors. We further show that expansion of gained or already existing families in a species-specific way is important to fine-tune the specificities of the pathogenic host-fungus interaction.

Genome-wide detection of predicted non-coding RNAs in Rhizobium etli expressed during free-living and host-associated growth using a high-resolution tiling array.

BACKGROUND: Non-coding RNAs (ncRNAs) play a crucial role in the intricate regulation of bacterial gene expression, allowing bacteria to quickly adapt to changing environments. In the past few years, a growing number of regulatory RNA elements have been predicted by computational methods, mostly in well-studied gamma-proteobacteria but lately in several alpha-proteobacteria as well. Here, we have compared an extensive compilation of these non-coding RNA predictions to intergenic expression data of a whole-genome high-resolution tiling array in the soil-dwelling alpha-proteobacterium Rhizobium etli. RESULTS: Expression of 89 candidate ncRNAs was detected, both on the chromosome and on the six megaplasmids encompassing the R. etli genome. Of these, 11 correspond to functionally well characterized ncRNAs, 12 were previously identified in other alpha-proteobacteria but are as yet uncharacterized and 66 were computationally predicted earlier but had not been experimentally identified and were therefore classified as novel ncRNAs. The latter comprise 17 putative sRNAs and 49 putative cis-regulatory ncRNAs. A selection of these candidate ncRNAs was validated by RT-qPCR, Northern blotting and 5' RACE, confirming the existence of 4 ncRNAs. Interestingly, individual transcript levels of numerous ncRNAs varied during free-living growth and during interaction with the eukaryotic host plant, pointing to possible ncRNA-dependent regulation of these specialized processes. CONCLUSIONS: Our data support the practical value of previous ncRNA prediction algorithms and significantly expand the list of candidate ncRNAs encoded in the intergenic regions of R. etli and, by extension, of alpha-proteobacteria. Moreover, we show high-resolution tiling arrays to be suitable tools for studying intergenic ncRNA transcription profiles across the genome. The differential expression levels of some of these ncRNAs may indicate a role in adaptation to changing environmental conditions.