A universally applicable method of operon map prediction on minimally annotated genomes using conserved genomic context.

An important step in understanding the regulation of a prokaryotic genome is the generation of its transcription unit map. The current strongest operon predictor depends on the distributions of intergenic distances (IGD) separating adjacent genes within and between operons. Unfortunately, experimental data on these distance distributions are limited to Escherichia coli and Bacillus subtilis. We suggest a new graph algorithmic approach based on comparative genomics to identify clusters of conserved genes independent of IGD and conservation of gene order. As a consequence, distance distributions of operon pairs for any arbitrary prokaryotic genome can be inferred. For E.coli, the algorithm predicts 854 conserved adjacent pairs with a precision of 85%. The IGD distribution for these pairs is virtually identical to the E.coli operon pair distribution. Statistical analysis of the predicted pair IGD distribution allows estimation of a genome-specific operon IGD cut-off, obviating the requirement for a training set in IGD-based operon prediction. We apply the method to a representative set of eight genomes, and show that these genome-specific IGD distributions differ considerably from each other and from the distribution in E.coli

Observations of the Origin of Downward Terrestrial Gamma-Ray Flashes

In this paper we report the first close, high-resolution observations of downward-directed terrestrial gamma-ray flashes (TGFs) detected by the large-area Telescope Array cosmic ray observatory, obtained in conjunction with broadband VHF interferometer and fast electric field change measurements of the parent discharge. The results show that the TGFs occur during strong initial breakdown pulses (IBPs) in the first few milliseconds of negative cloud-to-ground and low-altitude intracloud flashes and that the IBPs are produced by a newly identified streamer-based discharge process called fast negative breakdown. The observations indicate the relativistic runaway electron avalanches (RREAs) responsible for producing the TGFs are initiated by embedded spark-like transient conducting events (TCEs) within the fast streamer system and potentially also by individual fast streamers themselves. The TCEs are inferred to be the cause of impulsive sub-pulses that are characteristic features of classic IBP sferics. Additional development of the avalanches would be facilitated by the enhanced electric field ahead of the advancing front of the fast negative breakdown. In addition to showing the nature of IBPs and their enigmatic sub-pulses, the observations also provide a possible explanation for the unsolved question of how the streamer to leader transition occurs during the initial negative breakdown, namely, as a result of strong currents flowing in the final stage of successive IBPs, extending backward through both the IBP itself and the negative streamer breakdown preceding the IBP

Timing Calibration and Windowing Technique Comparison for Lightning Mapping Arrays

Since their introduction 22 years ago, lightning mapping arrays (LMA) have played a central role in the investigation of lightning physics. Even in recent years with the proliferation of digital interferometers and the introduction of the LOw Frequency ARray (LOFAR) radio telescope, LMAs still play an important role in lightning science. LMA networks use a simple windowing technique that records the highest pulse in either 80 μs or 10 μs fixed windows in order to apply a time-of-arrival location technique. In this work, we develop an LMA-emulator that uses lightning data recorded by LOFAR to simulate an LMA, and we use it to test three new styles of pulse windowing. We show that they produce very similar results as the more traditional LMA windowing, implying that LMA lightning mapping results are relatively independent of windowing technique. In addition, each LMA station has its GPS-conditioned clock. While the timing accuracy of GPS receivers has improved significantly over the years, they still significantly limit the timing measurements of the LMA. Recently, new time-of-arrival techniques have been introduced that can be used to self-calibrate systematic offsets between different receiving stations. Applying this calibration technique to a set of data with 32 ns uncertainty, observed by the Colorado LMA, improves the timing uncertainty to 19 ns. This technique is not limited to LMAs and could be used to help calibrate future multi-station lightning interferometers

First High-Speed Video Camera Observations of a Lightning Flash Associated With a Downward Terrestrial Gamma-Ray Flash

In this paper, we present the first high-speed video observation of a cloud-to-ground lightning flash and its associated downward-directed Terrestrial Gamma-ray Flash (TGF). The optical emission of the event was observed by a high-speed video camera running at 40,000 frames per second in conjunction with the Telescope Array Surface Detector, Lightning Mapping Array, interferometer, electric-field fast antenna, and the National Lightning Detection Network. The cloud-to-ground flash associated with the observed TGF was formed by a fast downward leader followed by a very intense return stroke peak current of −154 kA. The TGF occurred while the downward leader was below cloud base, and even when it was halfway in its propagation to ground. The suite of gamma-ray and lightning instruments, timing resolution, and source proximity offer us detailed information and therefore a unique look at the TGF phenomena

Rapid Pathway Evolution Facilitated by Horizontal Gene Transfers across Prokaryotic Lineages

The evolutionary history of biological pathways is of general interest, especially in this post-genomic era, because it may provide clues for understanding how complex systems encoded on genomes have been organized. To explain how pathways can evolve de novo, some noteworthy models have been proposed. However, direct reconstruction of pathway evolutionary history both on a genomic scale and at the depth of the tree of life has suffered from artificial effects in estimating the gene content of ancestral species. Recently, we developed an algorithm that effectively reconstructs gene-content evolution without these artificial effects, and we applied it to this problem. The carefully reconstructed history, which was based on the metabolic pathways of 160 prokaryotic species, confirmed that pathways have grown beyond the random acquisition of individual genes. Pathway acquisition took place quickly, probably eliminating the difficulty in holding genes during the course of the pathway evolution. This rapid evolution was due to massive horizontal gene transfers as gene groups, some of which were possibly operon transfers, which would convey existing pathways but not be able to generate novel pathways. To this end, we analyzed how these pathways originally appeared and found that the original acquisition of pathways occurred more contemporaneously than expected across different phylogenetic clades. As a possible model to explain this observation, we propose that novel pathway evolution may be facilitated by bidirectional horizontal gene transfers in prokaryotic communities. Such a model would complement existing pathway evolution models

Mining phenotypes for gene function prediction

<p>Abstract</p> <p>Background</p> <p>Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships.</p> <p>Results</p> <p>We present results on a study where we use a large set of phenotype data – in textual form – to predict gene annotation. To this end, we use text clustering to group genes based on their phenotype descriptions. We show that these clusters correlate well with several indicators for biological coherence in gene groups, such as functional annotations from the Gene Ontology (GO) and protein-protein interactions. We exploit these clusters for predicting gene function by carrying over annotations from well-annotated genes to other, less-characterized genes in the same cluster. For a subset of groups selected by applying objective criteria, we can predict GO-term annotations from the biological process sub-ontology with up to 72.6% precision and 16.7% recall, as evaluated by cross-validation. We manually verified some of these clusters and found them to exhibit high biological coherence, e.g. a group containing all available antennal Drosophila odorant receptors despite inconsistent GO-annotations.</p> <p>Conclusion</p> <p>The intrinsic nature of phenotypes to visibly reflect genetic activity underlines their usefulness in inferring new gene functions. Thus, systematically analyzing these data on a large scale offers many possibilities for inferring functional annotation of genes. We show that text clustering can play an important role in this process.</p

Stochasticity in Protein Levels Drives Colinearity of Gene Order in Metabolic Operons of Escherichia coli

Gene order in some bacterial metabolic operons reflects ordering in the metabolic pathway. That this is true uniquely for operons expressed at low levels highlights the selective importance of fluctuations in protein levels

Tracing data journeys through medical case reports: Conceptualizing case reports not as 'anecdotes' but productive epistemic constructs, or why zebras can be useful

Medical case reports provide an important example of data journeying: they are used to collect data and make them available for re-use to others in the field including clinicians, biomedical researchers, and health policymakers. In this paper, I explore how data journey in case reports, with particular focus on the earliest stages of the process, namely from creation and publication of case reports to the initial re-uses of them and data within them. I investigate key themes relating to case reporting and re-use, including factors which seem to smooth the path along which the data captured by a case report journey via broader citation patterns and detailed qualitative analysis of highly re-used case reports. This analysis reveals some of the key factors associated with the case reports whose data have greater amounts of journeying including publication in a general medical journal; that the data have broader implications and evidential value for topical or even urgent issues for instance in public health; and use in the case report of multiple research methods or concepts from diverse subfields. These findings along with standardization of case reporting are shown to have epistemological implications, particularly for how we understand the journeying of data.Rachel A. Anken