Simulations of slow positron production using a low energy electron accelerator

Monte Carlo simulations of slow positron production via energetic electron interaction with a solid target have been performed. The aim of the simulations was to determine the expected slow positron beam intensity from a low energy, high current electron accelerator. By simulating (a) the fast positron production from a tantalum electron-positron converter and (b) the positron depth deposition profile in a tungsten moderator, the slow positron production probability per incident electron was estimated. Normalizing the calculated result to the measured slow positron yield at the present AIST LINAC the expected slow positron yield as a function of energy was determined. For an electron beam energy of 5 MeV (10 MeV) and current 240 $\mu$A (30 $\mu$A) production of a slow positron beam of intensity 5 $\times$ 10$^{6}$ s$^{-1}$ is predicted. The simulation also calculates the average energy deposited in the converter per electron, allowing an estimate of the beam heating at a given electron energy and current. For low energy, high-current operation the maximum obtainable positron beam intensity will be limited by this beam heating.Comment: 11 pages, 15 figures, submitted to Review of Scientific Instrument

LOCATE: a mouse protein subcellular localization database

We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set. Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing >1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for ∼40% of the mouse proteome. It is available at

Heterotachy in Mammalian Promoter Evolution

We have surveyed the evolutionary trends of mammalian promoters and upstream sequences, utilising large sets of experimentally supported transcription start sites (TSSs). With 30,969 well-defined TSSs from mouse and 26,341 from human, there are sufficient numbers to draw statistically meaningful conclusions and to consider differences between promoter types. Unlike previous smaller studies, we have considered the effects of insertions, deletions, and transposable elements as well as nucleotide substitutions. The rate of promoter evolution relative to that of control sequences has not been consistent between lineages nor within lineages over time. The most pronounced manifestation of this heterotachy is the increased rate of evolution in primate promoters. This increase is seen across different classes of mutation, including substitutions and micro-indel events. We investigated the relationship between promoter and coding sequence selective constraint and suggest that they are generally uncorrelated. This analysis also identified a small number of mouse promoters associated with the immune response that are under positive selection in rodents. We demonstrate significant differences in divergence between functional promoter categories and identify a category of promoters, not associated with conventional protein-coding genes, that has the highest rates of divergence across mammals. We find that evolutionary rates vary both on a fine scale within mammalian promoters and also between different functional classes of promoters. The discovery of heterotachy in promoter evolution, in particular the accelerated evolution of primate promoters, has important implications for our understanding of human evolution and for strategies to detect primate-specific regulatory elements

Clusters of internally primed transcripts reveal novel long noncoding RNAs

Non- protein- coding RNAs ( ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25- nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases ( Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full- length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine- rich regions within longer parental transcripts. We therefore conducted a genome- wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty- six regions were identified, each of which mapped outside known protein- coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/ or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT- PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air

Alternate transcription of the Toll-like receptor signaling cascade

BACKGROUND: Alternate splicing of key signaling molecules in the Toll-like receptor (Tlr) cascade has been shown to dramatically alter the signaling capacity of inflammatory cells, but it is not known how common this mechanism is. We provide transcriptional evidence of widespread alternate splicing in the Toll-like receptor signaling pathway, derived from a systematic analysis of the FANTOM3 mouse data set. Functional annotation of variant proteins was assessed in light of inflammatory signaling in mouse primary macrophages, and the expression of each variant transcript was assessed by splicing arrays. RESULTS: A total of 256 variant transcripts were identified, including novel variants of Tlr4, Ticam1, Tollip, Rac1, Irak1, 2 and 4, Mapk14/p38, Atf2 and Stat1. The expression of variant transcripts was assessed using custom-designed splicing arrays. We functionally tested the expression of Tlr4 transcripts under a range of cytokine conditions via northern and quantitative real-time polymerase chain reaction. The effects of variant Mapk14/p38 protein expression on macrophage survival were demonstrated. CONCLUSION: Members of the Toll-like receptor signaling pathway are highly alternatively spliced, producing a large number of novel proteins with the potential to functionally alter inflammatory outcomes. These variants are expressed in primary mouse macrophages in response to inflammatory mediators such as interferon-γ and lipopolysaccharide. Our data suggest a surprisingly common role for variant proteins in diversification/repression of inflammatory signaling

The frequent evolutionary birth and death of functional promoters in mouse and human

Promoters are central to the regulation of gene expression. Changes in gene regulation are thought to underlie much of the adaptive diversification between species and phenotypic variation within populations. In contrast to earlier work emphasizing the importance of enhancer evolution and subtle sequence changes at promoters, we show that dramatic changes such as the complete gain and loss (collectively, turnover) of functional promoters are common. Using quantitative measures of transcription initiation in both humans and mice across 52 matched tissues, we discriminate promoter sequence gains from losses and resolve the lineage of changes. We also identify expression divergence and functional turnover between orthologous promoters, finding only the latter is associated with local sequence changes. Promoter turnover has occurred at the majority (>56%) of protein-coding genes since humans and mice diverged. Tissue-restricted promoters are the most evolutionarily volatile where retrotransposition is an important, but not the sole, source of innovation. There is considerable heterogeneity of turnover rates between promoters in different tissues, but the consistency of these in both lineages suggests that the same biological systems are similarly inclined to transcriptional rewiring. The genes affected by promoter turnover show evidence of adaptive evolution. In mice, promoters are primarily lost through deletion of the promoter containing sequence, whereas in humans, many promoters appear to be gradually decaying with weak transcriptional output and relaxed selective constraint. Our results suggest that promoter gain and loss is an important process in the evolutionary rewiring of gene regulation and may be a significant source of phenotypic diversification

Distinct roles of the RasGAP family proteins in C. elegans associative learning and memory

The Ras GTPase activating proteins (RasGAPs) are regulators of the conserved Ras/MAPK pathway. Various roles of some of the RasGAPs in learning and memory have been reported in different model systems, yet, there is no comprehensive study to characterize all gap genes in any organism. Here, using reverse genetics and neurobehavioural tests, we studied the role of all known genes of the rasgap family in C. elegans in associative learning and memory. We demonstrated that their proteins are implicated in different parts of the learning and memory processes. We show that gap-1 contribute redundantly with gap-3 to the chemosensation of volatile compounds, gap-1 plays a major role in associative learning, while gap-2 and gap-3 are predominantly required for short- and long-term associative memory. Our results also suggest that the C. elegans Ras orthologue let-60 is involved in multiple processes during learning and memory. Thus, we show that the different classes of RasGAP proteins are all involved in cognitive function and their complex interplay ensures the proper formation and storage of novel information in C. elegans

Large-scale clustering of CAGE tag expression data

Background: Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. We have identified a huge number of TSSs mapped onto the mouse genome using the cap analysis of gene expression (CAGE) method. The standard hierarchical clustering algorithm, which gives us easily understandable graphical tree images, has difficulties in processing such huge amounts of TSS data and a better method to calculate and display the results is needed. Results: We use a combination of hierarchical and non-hierarchical clustering to cluster expression profiles of TSSs based on a large amount of CAGE data to profit from the best of both methods. We processed the genome-wide expression data, including 159,075 TSSs derived from 127 RNA samples of various organs of mouse, and succeeded in categorizing them into 70-100 clusters. The clusters exhibited intriguing biological features: a cluster supergroup with a ubiquitous expression profile, tissue-specific patterns, a distinct distribution of non-coding RNA and functional TSS groups. Conclusion: Our approach succeeded in greatly reducing the calculation cost, and is an appropriate solution for analyzing large-scale TSS usage data

High Sensitivity TSS Prediction: Estimates of Locations Where TSS Cannot Occur

Although transcription in mammalian genomes can initiate from various genomic positions (e.g., 3′UTR, coding exons, etc.), most locations on genomes are not prone to transcription initiation. It is of practical and theoretical interest to be able to estimate such collections of non-TSS locations (NTLs). The identification of large portions of NTLs can contribute to better focusing the search for TSS locations and thus contribute to promoter and gene finding. It can help in the assessment of 5′ completeness of expressed sequences, contribute to more successful experimental designs, as well as more accurate gene annotation.Using comprehensive collections of Cap Analysis of Gene Expression (CAGE) and other transcript data from mouse and human genomes, we developed a methodology that allows us, by performing computational TSS prediction with very high sensitivity, to annotate, with a high accuracy in a strand specific manner, locations of mammalian genomes that are highly unlikely to harbor transcription start sites (TSSs). The properties of the immediate genomic neighborhood of 98,682 accurately determined mouse and 113,814 human TSSs are used to determine features that distinguish genomic transcription initiation locations from those that are not likely to initiate transcription. In our algorithm we utilize various constraining properties of features identified in the upstream and downstream regions around TSSs, as well as statistical analyses of these surrounding regions.