Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists.

Comparative co-expression analysis in plant biology.

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.

Dissecting plant genomes with the PLAZA comparative genomics platform.

With the arrival of low-cost, next-generation sequencing, a multitude of new plant genomes are being publicly released, providing unseen opportunities and challenges for comparative genomics studies. Here, we present PLAZA 2.5, a user-friendly online research environment to explore genomic information from different plants. This new release features updates to previous genome annotations and a substantial number of newly available plant genomes as well as various new interactive tools and visualizations. Currently, PLAZA hosts 25 organisms covering a broad taxonomic range, including 13 eudicots, five monocots, one lycopod, one moss, and five algae. The available data consist of structural and functional gene annotations, homologous gene families, multiple sequence alignments, phylogenetic trees, and colinear regions within and between species. A new Integrative Orthology Viewer, combining information from different orthology prediction methodologies, was developed to efficiently investigate complex orthology relationships. Cross-species expression analysis revealed that the integration of complementary data types extended the scope of complex orthology relationships, especially between more distantly related species. Finally, based on phylogenetic profiling, we propose a set of core gene families within the green plant lineage that will be instrumental to assess the gene space of draft or newly sequenced plant genomes during the assembly or annotation phase.

Genome-scale computational analysis of DNA curvature and repeats in Arabidopsis and rice uncovers plant-specific genomic properties.

BACKGROUND: Due to its overarching role in genome function, sequence-dependent DNA curvature continues to attract great attention. The DNA double helix is not a rigid cylinder, but presents both curvature and flexibility in different regions, depending on the sequence. More in depth knowledge of the various orders of complexity of genomic DNA structure has allowed the design of sophisticated bioinformatics tools for its analysis and manipulation, which, in turn, have yielded a better understanding of the genome itself. Curved DNA is involved in many biologically important processes, such as transcription initiation and termination, recombination, DNA replication, and nucleosome positioning. CpG islands and tandem repeats also play significant roles in the dynamics and evolution of genomes. RESULTS: In this study, we analyzed the relationship between these three structural features within rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana) genomes. A genome-scale prediction of curvature distribution in rice and Arabidopsis indicated that most of the chromosomes of both genomes have maximal chromosomal DNA curvature adjacent to the centromeric region. By analyzing tandem repeats across the genome, we found that frequencies of repeats are higher in regions adjacent to those with high curvature value. Further analysis of CpG islands shows a clear interdependence between curvature value, repeat frequencies and CpG islands. Each CpG island appears in a local minimal curvature region, and CpG islands usually do not appear in the centromere or regions with high repeat frequency. A statistical evaluation demonstrates the significance and non-randomness of these features. CONCLUSIONS: This study represents the first systematic genome-scale analysis of DNA curvature, CpG islands and tandem repeats at the DNA sequence level in plant genomes, and finds that not all of the chromosomes in plants follow the same rules common to other eukaryote organisms, suggesting that some of these genomic properties might be considered as specific to plants.

Comparative network analysis reveals that tissue specificity and gene function are important factors influencing the mode of expression evolution in Arabidopsis and rice.

Microarray experiments have yielded massive amounts of expression information measured under various conditions for the model species Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Expression compendia grouping multiple experiments make it possible to define correlated gene expression patterns within one species and to study how expression has evolved between species. We developed a robust framework to measure expression context conservation (ECC) and found, by analyzing 4,630 pairs of orthologous Arabidopsis and rice genes, that 77% showed conserved coexpression. Examples of nonconserved ECC categories suggested a link between regulatory evolution and environmental adaptations and included genes involved in signal transduction, response to different abiotic stresses, and hormone stimuli. To identify genomic features that influence expression evolution, we analyzed the relationship between ECC, tissue specificity, and protein evolution. Tissue-specific genes showed higher expression conservation compared with broadly expressed genes but were fast evolving at the protein level. No significant correlation was found between protein and expression evolution, implying that both modes of gene evolution are not strongly coupled in plants. By integration of cis-regulatory elements, many ECC conserved genes were significantly enriched for shared DNA motifs, hinting at the conservation of ancestral regulatory interactions in both model species. Surprisingly, for several tissue-specific genes, patterns of concerted network evolution were observed, unveiling conserved coexpression in the absence of conservation of tissue specificity. These findings demonstrate that orthologs inferred through sequence similarity in many cases do not share similar biological functions and highlight the importance of incorporating expression information when comparing genes across species.

CORNET: a user-friendly tool for data mining and integration.

As an overwhelming amount of functional genomics data have been generated, the retrieval, integration, and interpretation of these data need to be facilitated to enable the advance of (systems) biological research. For example, gathering and processing microarray data that are related to a particular biological process is not straightforward, nor is the compilation of protein-protein interactions from numerous partially overlapping databases identified through diverse approaches. However, these tasks are inevitable to address the following questions. Does a group of differentially expressed genes show similar expression in diverse microarray experiments? Was an identified protein-protein interaction previously detected by other approaches? Are the interacting proteins encoded by genes with similar expression profiles and localization? We developed CORNET (for CORrelation NETworks) as an access point to transcriptome, protein interactome, and localization data and functional information on Arabidopsis (Arabidopsis thaliana). It consists of two flexible and versatile tools, namely the coexpression tool and the protein-protein interaction tool. The ability to browse and search microarray experiments using ontology terms and the incorporation of personal microarray data are distinctive features of the microarray repository. The coexpression tool enables either the alternate or simultaneous use of diverse expression compendia, whereas the protein-protein interaction tool searches experimentally and computationally identified protein-protein interactions. Different search options are implemented to enable the construction of coexpression and/or protein-protein interaction networks centered around multiple input genes or proteins. Moreover, networks and associated evidence are visualized in Cytoscape. Localization is visualized in pie charts, thereby allowing multiple localizations per protein. CORNET is available at http://bioinformatics.psb.ugent.be/cornet.

Effect of small, acid-soluble proteins on spore resistance and germination under a combination of pressure and heat treatment.

To find the range of pressure required for effective high-pressure inactivation of bacterial spores and to investigate the role of alpha/beta-type small, acid-soluble proteins (SASP) in spores under pressure treatment, mild heat was combined with pressure (room temperature to 65 degrees C and 100 to 500 MPa) and applied to wild-type and SASP-alpha-/beta- Bacillus subtilis spores. On the one hand, more than 4 log units of wild-type spores were reduced after pressurization at 100 to 500 MPa and 65 degrees C. On the other hand, the number of surviving mutant spores decreased by 2 log units at 100 MPa and by more than 5 log units at 500 MPa. At 500 MPa and 65 degrees C, both wild-type and mutant spore survivor counts were reduced by 5 log units. Interestingly, pressures of 100, 200, and 300 MPa at 65 degrees C inactivated wild-type SASP-alpha+/beta+ spores more than mutant SASP-alpha-/beta- spores, and this was attributed to less pressure-induced germination in SASP-alpha-/beta- spores than in wild-type SASP-alpha+/beta+ spores. However, there was no difference in the pressure resistance between SASP-alpha+/beta+ and SASP-alpha-/beta- spores at 100 MPa and ambient temperature (approximately 22 degrees C) for 30 min. A combination of high pressure and high temperature is very effective for inducing spore germination, and then inactivation of the germinated spore occurs because of the heat treatment. This study showed that alpha/beta-type SASP play a role in spore inactivation by increasing spore germination under 100 to 300 MPa at high temperature.

Cold shock response in sporulating Bacillus subtilis and its effect on spore heat resistance.

Cold shock and ethanol and puromycin stress responses in sporulating Bacillus subtilis cells have been investigated. We show that a total of 13 proteins are strongly induced after a short cold shock treatment of sporulating cells. The cold shock pretreatment affected the heat resistance of the spores formed subsequently, with spores heat killed at 85 or 90 degrees C being more heat resistant than the control spores while they were more heat sensitive than controls that were heat treated at 95 or 100 degrees C. However, B. subtilis spores with mutations in the main cold shock proteins, CspB, -C, and -D, did not display decreased heat resistance compared to controls, indicating that these proteins are not directly responsible for the increased heat resistance of the spores. The disappearance of the stress proteins later in sporulation suggests that they cannot be involved in repairing heat damage during spore germination and outgrowth but must alter spore structure in a way which increases or decreases heat resistance. Since heat, ethanol, and puromycin stress produce similar proteins and similar changes in spore heat resistance while cold shock is different in both respects, these alterations appear to be very specific.