Martin Kuiper

BiNGO : a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological Networks

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscapes versatile visualization environment to produce an intuitive and customizable visual representation of the results.

Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project

The Minimum Information for Biological and Biomedical Investigations (MIBBI) project aims to foster the coordinated development of minimum-information checklists and provide a resource for those exploring the range of extant checklists.

Combined mapping of AFLP and RFLP markers in barley

AFLP marker technology allows efficient DNA fingerprinting and the analysis of large numbers of polymorphic restriction fragments on polyacrylamide gels. Using the doubled haploids from the F1 of the cross Proctor × Nudinka, 118 AFLP markers were mapped onto a barley (Hordeum vulgare L.) RFLP map, also including five microsatellite and four protein marker loci. The AFLP markers mapped to all parts of the barley chromosomes and filled in the gaps on barley chromosomes 2L, 4L and 6 in which no RFLP loci had been mapped. Interestingly, the AFLP markers seldom interrupted RFLP clusters, but grouped next to them. The combined map covers 1873 cM, with a total of 282 markers. The merging of AFLP and RFLP markers increased the total map length; 402 cM were added to the map at the tips of chromosomes or in regions corresponding to earlier gaps. Another 375 cM resulted from mapping AFLP markers near to RFLP clusters or in between non-clustered RFLP markers.

Two high-density AFLP® linkage maps of Zea mays L.: analysis of distribution of AFLP markers

Abstract This study demonstrates the relative ease of generating high-density linkage maps using the AFLP® technology. Two high-density AFLP linkage maps of Zea mays L. were generated based on: (1) a B73 × Mo17 recombinant inbred population and (2) a D32 × D145 immortalized F2 population. Although AFLP technology is in essence a mono-allelic marker system, markers can be scored quantitatively and used to deduce zygosity. AFLP markers were generated using the enzyme combinations EcoRI/MseI and PstI/MseI. A total of 1539 and 1355 AFLP markers have been mapped in the two populations, respectively. Among the mapped PstI/MseIAFLP markers we have included fragments bounded by a methylated PstI site (mAFLP markers). Mapping these mAFLP markers shows that the presence of C-methylation segregates in perfect accordance with the primary target sequence, leading to Mendelian inheritance. Simultaneous mapping of PstI/MseIAFLP and PstI/MseI mAFLP markers allowed us to identify a number of epi-alleles, showing allelic variation in the CpNpG methylation only. However, their frequency in maize is low. Map comparison shows that, despite some rearrangements, most of the AFLP markers that are common in both populations, map at similar positions. This would indicate that AFLP markers are predominantly single-locus markers. Changes in map order occur mainly in marker-dense regions. These marker-dense regions, representing clusters of mainly EcoRI/MseI AFLP and PstI/MseI mAFLP markers, co- localize well with the putative centromeric regions of the maize chromosomes. In contrast, PstI/MseImarkers are more uniformly distributed over the genome.

The Cyclin-Dependent Kinase Inhibitor KRP2 Controls the Onset of the Endoreduplication Cycle during Arabidopsis Leaf Development through Inhibition of Mitotic CDKA;1 Kinase Complexes

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 cycle–specific 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 mitosis-to-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.

Targeted interactomics reveals a complex core cell cycle machinery in Arabidopsis thaliana.

Cell proliferation is the main driving force for plant growth. Although genome sequence analysis revealed a high number of cell cycle genes in plants, little is known about the molecular complexes steering cell division. In a targeted proteomics approach, we mapped the core complex machinery at the heart of the Arabidopsis thaliana cell cycle control. Besides a central regulatory network of core complexes, we distinguished a peripheral network that links the core machinery to up‐ and downstream pathways. Over 100 new candidate cell cycle proteins were predicted and an in‐depth biological interpretation demonstrated the hypothesis‐generating power of the interaction data. The data set provided a comprehensive view on heterodimeric cyclin‐dependent kinase (CDK)–cyclin complexes in plants. For the first time, inhibitory proteins of plant‐specific B‐type CDKs were discovered and the anaphase‐promoting complex was characterized and extended. Important conclusions were that mitotic A‐ and B‐type cyclins form complexes with the plant‐specific B‐type CDKs and not with CDKA;1, and that D‐type cyclins and S‐phase‐specific A‐type cyclins seem to be associated exclusively with CDKA;1. Furthermore, we could show that plants have evolved a combinatorial toolkit consisting of at least 92 different CDK–cyclin complex variants, which strongly underscores the functional diversification among the large family of cyclins and reflects the pivotal role of cell cycle regulation in the developmental plasticity of plants.

Genetic Analysis of Variation in Gene Expression in Arabidopsis thaliana

In Arabidopsis thaliana, significant efforts to determine the extent of genomic variation between phenotypically divergent accessions are under way, but virtually nothing is known about variation at the transcription level. We used microarrays to examine variation in transcript abundance among three inbred lines and two pairs of reciprocal F1 hybrids of the highly self-fertilizing species Arabidopsis. Composite additive genetic effects for gene expression were estimated from pairwise comparisons of the three accessions Columbia (Col), Landsberg erecta (Ler), and Cape Verde Islands (Cvi). For the pair Col and Ler, 27.0% of the 4876 genes exhibited additive genetic effects in their expression (α = 0.001) vs. 32.2 and 37.5% for Cvi with Ler and Col, respectively. Significant differential expression ranged from 32.45 down to 1.10 in fold change and typically differed by a factor of 1.56. Maternal or paternal transmission affected only a few genes, suggesting that the reciprocal effects observed in the two crosses analyzed were minimal. Dominance effects were estimated from the comparisons of hybrids with the corresponding midparent value. The percentage of genes showing dominance at the expression level in the F1 hybrids ranged from 6.4 to 21.1% (α = 0.001). Breakdown of these numbers of genes according to the magnitude of the dominance ratio revealed heterosis for expression for on average 9% of the genes. Further advances in the genetic analysis of gene expression variation may contribute to a better understanding of its role in affecting quantitative trait variation at the phenotypic level.

Biological knowledge management: the emerging role of the Semantic Web technologies

New knowledge is produced at a continuously increasing speed, and the list of papers, databases and other knowledge sources that a researcher in the life sciences needs to cope with is actually turning into a problem rather than an asset. The adequate management of knowledge is therefore becoming fundamentally important for life scientists, especially if they work with approaches that thoroughly depend on knowledge integration, such as systems biology. Several initiatives to organize biological knowledge sources into a readily exploitable resourceome are presently being carried out. Ontologies and Semantic Web technologies revolutionize these efforts. Here, we review the benefits, trends, current possibilities, and the potential this holds for the biosciences.

Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis

Transcript profiling is crucial to study biological systems, and various platforms have been implemented to survey mRNAs at the genome scale. We have assessed the performance of the CATMA microarray designed for Arabidopsis (Arabidopsis thaliana) transcriptome analysis and compared it with the Agilent and Affymetrix commercial platforms. The CATMA array consists of gene-specific sequence tags of 150 to 500 bp, the Agilent (Arabidopsis 2) array of 60mer oligonucleotides, and the Affymetrix gene chip (ATH1) of 25mer oligonucleotide sets. We have matched each probe repertoire with the Arabidopsis genome annotation (The Institute for Genomic Research release 5.0) and determined the correspondence between them. Array performance was analyzed by hybridization with labeled targets derived from eight RNA samples made of shoot total RNA spiked with a calibrated series of 14 control transcripts. CATMA arrays showed the largest dynamic range extending over three to four logs. Agilent and Affymetrix arrays displayed a narrower range, presumably because signal saturation occurred for transcripts at concentrations beyond 1,000 copies per cell. Sensitivity was comparable for all three platforms. For Affymetrix GeneChip data, the RMA software package outperformed Microarray Suite 5.0 for all investigated criteria, confirming that the information provided by the mismatch oligonucleotides has no added value. In addition, taking advantage of replicates in our dataset, we conducted a robust statistical analysis of the platform propensity to yield false positive and false negative differentially expressed genes, and all gave satisfactory results. The results establish the CATMA array as a mature alternative to the Affymetrix and Agilent platforms.

Specific impact of tobamovirus infection on the Arabidopsis small RNA profile

Tobamoviruses encode a silencing suppressor that binds small RNA (sRNA) duplexes in vitro and supposedly in vivo to counteract antiviral silencing. Here, we used sRNA deep-sequencing combined with transcriptome profiling to determine the global impact of tobamovirus infection on Arabidopsis sRNAs and their mRNA targets. We found that infection of Arabidopsis plants with Oilseed rape mosaic tobamovirus causes a global size-specific enrichment of miRNAs, ta-siRNAs, and other phased siRNAs. The observed patterns of sRNA enrichment suggest that in addition to a role of the viral silencing suppressor, the stabilization of sRNAs might also occur through association with unknown host effector complexes induced upon infection. Indeed, sRNA enrichment concerns primarily 21-nucleotide RNAs with a 5′-terminal guanine. Interestingly, ORMV infection also leads to accumulation of novel miRNA-like sRNAs from miRNA precursors. Thus, in addition to canonical miRNAs and miRNA*s, miRNA precursors can encode additional sRNAs that may be functional under specific conditions like pathogen infection. Virus-induced sRNA enrichment does not correlate with defects in miRNA-dependent ta-siRNA biogenesis nor with global changes in the levels of mRNA and ta-siRNA targets suggesting that the enriched sRNAs may not be able to significantly contribute to the normal activity of pre-loaded RISC complexes. We conclude that tobamovirus infection induces the stabilization of a specific sRNA pool by yet unknown effector complexes. These complexes may sequester viral and host sRNAs to engage them in yet unknown mechanisms involved in plant:virus interactions.