Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the 16 Present address:

Exit from the mitotic cell cycle and initiation of cell differentiation frequently coincides with the onset of endoreduplication, a modified cell cycle during which DNA continues to be duplicated in the absence of mitosis. Although the mitotic cell cycle and the endoreduplication cycle share much of the same machinery, the regulatory mechanisms controlling the transition between both cycles remain poorly understood. We show that the A-type cyclin-dependent kinase CDKA;1 and its specific inhibitor, the Kip-related protein, KRP2 regulate the mitosis-to-endocycle transition during Arabidopsis thaliana leaf development. Constitutive overexpression of KRP2 slightly above its endogenous level only inhibited the mitotic cell cyclespecific CDKA;1 kinase complexes, whereas the endoreduplication cycle-specific CDKA;1 complexes were unaffected, resulting in an increase in the DNA ploidy level. An identical effect on the endoreduplication cycle could be observed by overexpressing KRP2 exclusively in mitotically dividing cells. In agreement with a role for KRP2 as activator of the mitosisto-endocycle transition, KRP2 protein levels were more abundant in endoreduplicating than in mitotically dividing tissues. We illustrate that KRP2 protein abundance is regulated posttranscriptionally through CDK phosphorylation and proteasomal degradation. KRP2 phosphorylation by the mitotic cell cycle-specific CDKB1;1 kinase suggests a mechanism in which CDKB1;1 controls the level of CDKA;1 activity through regulating KRP2 protein abundance. In accordance with this model, KRP2 protein levels increased in plants with reduced CDKB1;1 activity. Moreover, the proposed model allowed a dynamical simulation of the in vivo observations, validating the sufficiency of the regulatory interactions between CDKA;1, KRP2, and CDKB1;1 in fine-tuning the mitosis-to-endocycle transition.

Organ growth results from the progression of component cells through subsequent phases of proliferation and expansion before reaching maturity. We combined kinematic analysis, flowcytometry, and microarray analysis to characterize cell cycle regulation during the growth process of leaves 1 and 2 of Arabidopsis (Arabidopsis thaliana). Kinematic analysis showed that the epidermis proliferates until day 12; thereafter, cells expand until day 19 when leaves reach maturity. Flowcytometry revealed that endoreduplication occurs from the time cell division rates decline until the end of cell expansion. Analysis of 10 time points with a 6k-cDNA microarray showed that transitions between the growth stages were closely reflected in the mRNA expression data. Subsequent genome-wide microarray analysis on the three main stages allowed us to categorize known cell cycle genes into three major classes: constitutively expressed, proliferative, and inhibitory. Comparison with published expression data obtained from root zones corresponding to similar developmental stages and from synchronized cell cultures supported this categorization and enabled us to identify a high confidence set of 131 proliferation genes. Most of those had an M phase-dependent expression pattern and, in addition to many known cell cycle-related genes, there were at least 90 that were unknown or previously not associated with proliferation.

At the onset of lateral root initiation in Arabidopsis thaliana, the phytohormone auxin activates xylem pole pericycle cells for asymmetric cell division. However, the molecular events leading from auxin to lateral root initiation are poorly understood, in part because the few responsive cells in the process are embedded in the root and are thus difficult to access. A lateral root induction system, in which most xylem pole pericycle cells were synchronously activated by auxin transport inhibition followed by auxin application, was used for microarray transcript profiling. Of 4,600 genes analyzed, 906 significantly differentially regulated genes were identified that could be grouped into six major clusters. Basically, three major patterns were discerned representing induced, repressed, and transiently expressed genes. Analysis of the coregulated genes, which were specific for each time point, provided new insight into the molecular regulation and signal transduction preceding lateral root initiation in Arabidopsis. The reproducible expression profiles during a time course allowed us to define four stages that precede the cell division in the pericycle. These early stages were characterized by G 1 cell cycle block, auxin perception, and signal transduction, followed by progression over G 1͞S transition and G2͞M transition. All these processes took place within 6 h after transfer from N-1-naphthylphthalamic acid to 1-naphthalene acetic acid. These results indicate that this lateral root induction system represents a unique synchronized system that allows the systematic study of the developmental program upstream of the cell cycle activation during lateral root initiation.auxin ͉ cell cycle ͉ microarray

The role of cell cycle regulation and cell division in plant growth and organ development is controversial. Some experimental data are most easily interpreted from the 'cellular perspective' that cell division drives growth, whereas other observations are more consistent with the 'organismal perspective' that cell division is merely a consequence of growth, and to a large extent facultative. Here we develop a model of cell cycle regulation in the context of leaf development based on literature, published kinematic analysis, flow-cytometric and transcriptomic data obtained from growing Arabidopsis leaves. We tested this model by comparing the in silico inhibition of the cell cycle progression with the experimental observations of transgenic plants overexpressing the cell cycle inhibitor Arath;KRP2. The model simulates the behaviour of proliferating cells quite well, but is inadequate in describing the effects on expanding cells. This may point to a difference in the nature of the expansion process during the proliferating and non-dividing phase of leaf development.

BackgroundMore than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible.ResultsWe created the OLSVis web application, a visualiser for browsing all ontologies available in the OLS database. OLSVis shows customisable subgraphs of the OLS ontologies. Subgraphs are animated via a real-time force-based layout algorithm which is fully interactive: each time the user makes a change, e.g. browsing to a new term, hiding, adding, or dragging terms, the algorithm performs smooth and only essential reorganisations of the graph. This assures an optimal viewing experience, because subsequent screen layouts are not grossly altered, and users can easily navigate through the graph. URL: http://ols.wordvis.comConclusionsThe OLSVis web application provides a user-friendly tool to visualise ontologies from the OLS repository. It broadens the possibilities to investigate and select ontology subgraphs through a smooth visualisation method.

Causal molecular interactions represent key building blocks used in computational modeling, where they facilitate the assembly of regulatory networks. Logical regulatory networks can be used to predict biological and cellular behaviors by system perturbations and in silico simulations. Today, broad sets of causal interactions are available in a variety of biological knowledge resources. However, different visions, based on distinct biological interests, have led to the development of multiple ways to describe and annotate causal molecular interactions. It can therefore be challenging to efficiently explore various resources of causal interaction and maintain an overview of recorded contextual information that ensures valid use of the data. This review lists the different types of public resources with causal interactions, the different views on biological processes that they represent, the various data formats they use for data representation and storage, and the data exchange and conversion procedures that are available to extract and download these interactions. This may further raise awareness among the targeted audience, i.e. logical modelers and other scientists interested in molecular causal interactions, but also database managers and curators, about the abundance and variety of causal molecular interaction data, and the variety of tools and approaches to convert them into one interoperable resource.

Abstract Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called ‘causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources. Availability The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST Supplementary information Supplementary data are available at Bioinformatics online.