The structure of the tetraploid sour cherry 'Schattenmorelle' (Prunus cerasus L.) genome reveals insights into its segmental allopolyploid nature.

Sour cherry (Prunus cerasus L.) is an important allotetraploid cherry species that evolved in the Caspian Sea and Black Sea regions from a hybridization of the tetraploid ground cherry (Prunus fruticosa Pall.) and an unreduced pollen of the diploid sweet cherry (P. avium L.) ancestor. Details of when and where the evolution of this species occurred are unclear, as well as the effect of hybridization on the genome structure. To gain insight, the genome of the sour cherry cultivar 'Schattenmorelle' was sequenced using Illumina NovaSeqTM and Oxford Nanopore long-read technologies, resulting in a ~629-Mbp pseudomolecule reference genome. The genome could be separated into two subgenomes, with subgenome PceS_a originating from P. avium and subgenome PceS_f originating from P. fruticosa. The genome also showed size reduction compared to ancestral species and traces of homoeologous sequence exchanges throughout. Comparative analysis confirmed that the genome of sour cherry is segmental allotetraploid and evolved very recently in the past.

A PARTHENOGENESIS allele from apomictic dandelion can induce egg cell division without fertilization in lettuce.

Apomixis, the clonal formation of seeds, is a rare yet widely distributed trait in flowering plants. We have isolated the PARTHENOGENESIS (PAR) gene from apomictic dandelion that triggers embryo development in unfertilized egg cells. PAR encodes a K2-2 zinc finger, EAR-domain protein. Unlike the recessive sexual alleles, the dominant PAR allele is expressed in egg cells and has a miniature inverted-repeat transposable element (MITE) transposon insertion in the promoter. The MITE-containing promoter can invoke a homologous gene from sexual lettuce to complement dandelion LOSS OF PARTHENOGENESIS mutants. A similar MITE is also present in the promoter of the PAR gene in apomictic forms of hawkweed, suggesting a case of parallel evolution. Heterologous expression of dandelion PAR in lettuce egg cells induced haploid embryo-like structures in the absence of fertilization. Sexual PAR alleles are expressed in pollen, suggesting that the gene product releases a block on embryogenesis after fertilization in sexual species while in apomictic species PAR expression triggers embryogenesis in the absence of fertilization.

MOTIFATOR: detection and characterization of regulatory motifs using prokaryote transcriptome data.

SUMMARY: Unraveling regulatory mechanisms (e.g. identification of motifs in cis-regulatory regions) remains a major challenge in the analysis of transcriptome experiments. Existing applications identify putative motifs from gene lists obtained at rather arbitrary cutoff and require additional manual processing steps. Our standalone application MOTIFATOR identifies the most optimal parameters for motif discovery and creates an interactive visualization of the results. Discovered putative motifs are functionally characterized, thereby providing valuable insight in the biological processes that could be controlled by the motif. AVAILABILITY: MOTIFATOR is freely available at http://www.motifator.nl.

DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites.

BACKGROUND: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted with the seemingly arbitrary choice between numerous algorithms to perform cluster analysis. RESULTS: We developed an exploratory application that benchmarks the results of clustering methods using functional annotations. In addition, a de novo DNA motif discovery algorithm is integrated in our program which identifies overrepresented DNA binding sites in the upstream DNA sequences of genes from the clusters that are indicative of sites of transcriptional control. The performance of our program was evaluated by comparing the original results of a time course experiment with the findings of our application. CONCLUSION: DISCLOSE assists researchers in the prokaryotic research community in systematically evaluating results of the application of a range of clustering algorithms to transcriptome data. Different performance measures allow to quickly and comprehensively determine the best suited clustering approach for a given dataset.

Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources.

BACKGROUND: Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes. RESULTS: We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website. CONCLUSION: The Prosecutor software and supplementary datasets available at http://www.prosecutor.nl allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

FIVA: Functional Information Viewer and Analyzer extracting biological knowledge from transcriptome data of prokaryotes.

UNLABELLED: FIVA (Function Information Viewer and Analyzer) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software assists in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes. AVAILABILITY: http://bioinformatics.biol.rug.nl/standalone/fiva/

Time-resolved transcriptomics and bioinformatic analyses reveal intrinsic stress responses during batch culture of Bacillus subtilis.

We have determined the time-resolved transcriptome of the model gram-positive organism B. subtilis during growth in a batch fermentor on rich medium. DNA microarrays were used to monitor gene transcription using 10-minute intervals at 40 consecutive time points. From the growth curve and analysis of all gene expression levels, we identified 4 distinct growth phases and one clear transition point: a lag phase, an exponential growth phase, the transition point and the very clearly separated early and late stationary growth phases. The gene expression profiles suggest the occurrence of stress responses at specific times although no external stresses were applied. The first one is a small induction of the SigB regulon that occurs at the transition point. Remarkably, a very strong response is observed for the SigW regulon, which is highly upregulated at the onset of the late stationary phase. Bioinformatic analyses that were performed on our data set suggest several novel putative motifs for regulator binding. In addition, the expression profiles of several genes appeared to correlate with the oxygen concentration. This data set of the expression profiles of all B. subtilis genes during the entire growth curve on rich medium constitutes a rich repository that can be further mined by the scientific community.

MOVE: a multi-level ontology-based visualization and exploration framework for genomic networks.

Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e. g., proteins, genes). These interactions exist among others on genomic, transcriptomic, proteomic and metabolomic levels. The levels themselves are heavily interconnected, resulting in complex networks of different interacting biological entities. Currently, various bioinformatics tools exist which are able to perform a particular analysis on a particular type of network. Unfortunately, each tool has its own disadvantages hampering it to be used consistently for different types of networks or analytical methods. This paper describes the conceptual development of an open source extensible software framework that supports visualization and exploration of highly complex genomic networks, like metabolic or gene regulatory networks. The focus is on the conceptual foundations, starting from requirements, a description of the state of the art of network visualization systems, and an analysis of their shortcomings. We describe the implementation of some initial modules of the framework and apply them to a biological test case in bacterial regulation, which shows the relevance and feasibility of the proposed approach.

Production and secretion stress caused by overexpression of heterologous alpha-amylase leads to inhibition of sporulation and a prolonged motile phase in Bacillus subtilis.

Transcriptome analysis was used to investigate the global stress response of the gram-positive bacterium Bacillus subtilis caused by overproduction of the well-secreted AmyQ alpha-amylase from Bacillus amyloliquefaciens. Analyses of the control and overproducing strains were carried out at the end of exponential growth and in stationary phase, when protein secretion from B. subtilis is optimal. Among the genes that showed increased expression were htrA and htrB, which are part of the CssRS regulon, which responds to high-level protein secretion and heat stress. The analysis of the transcriptome profiles of a cssS mutant compared to the wild type, under identical secretion stress conditions, revealed several genes with altered transcription in a CssRS-dependent manner, for example, citM, ylxF, yloA, ykoJ, and several genes of the flgB operon. However, high-affinity CssR binding was observed only for htrA, htrB, and, possibly, citM. In addition, the DNA macroarray approach revealed that several genes of the sporulation pathway are downregulated by AmyQ overexpression and that a group of motility-specific (sigmaD-dependent) transcripts were clearly upregulated. Subsequent flow-cytometric analyses demonstrate that, upon overproduction of AmyQ as well as of a nonsecretable variant of the alpha-amylase, the process of sporulation is severely inhibited. Similar experiments were performed to investigate the expression levels of the hag promoter, a well-established reporter for sigmaD-dependent gene expression. This approach confirmed the observations based on our DNA macroarray analyses and led us to conclude that expression levels of several genes involved in motility are maintained at high levels under all conditions of alpha-amylase overproduction.

Iron starvation triggers the stringent response and induces amino acid biosynthesis for bacillibactin production in Bacillus subtilis.

Iron deprivation in bacteria causes the derepression of genes controlled by the ferric uptake regulator (Fur). The present microarray analysis of iron-starved Bacillus subtilis cells grown in minimal medium unveils additional physiological effects on a large number of genes linked to stringent-response regulation and to genes involved in amino acid biosynthesis associated with pathways essential for bacillibactin production.