996 resultados para Genome resources


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BACKGROUND: Parrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learning birds. They can imitate human speech, synchronize their body movements to a rhythmic beat, and understand complex concepts of referential meaning to sounds. However, little is known about the genetics of these traits. Elucidating the genetic bases would require whole genome sequencing and a robust assembly of a parrot genome. FINDINGS: We present a genomic resource for the budgerigar, an Australian Parakeet (Melopsittacus undulatus) -- the most widely studied parrot species in neuroscience and behavior. We present genomic sequence data that includes over 300× raw read coverage from multiple sequencing technologies and chromosome optical maps from a single male animal. The reads and optical maps were used to create three hybrid assemblies representing some of the largest genomic scaffolds to date for a bird; two of which were annotated based on similarities to reference sets of non-redundant human, zebra finch and chicken proteins, and budgerigar transcriptome sequence assemblies. The sequence reads for this project were in part generated and used for both the Assemblathon 2 competition and the first de novo assembly of a giga-scale vertebrate genome utilizing PacBio single-molecule sequencing. CONCLUSIONS: Across several quality metrics, these budgerigar assemblies are comparable to or better than the chicken and zebra finch genome assemblies built from traditional Sanger sequencing reads, and are sufficient to analyze regions that are difficult to sequence and assemble, including those not yet assembled in prior bird genomes, and promoter regions of genes differentially regulated in vocal learning brain regions. This work provides valuable data and material for genome technology development and for investigating the genomics of complex behavioral traits.

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Mitchell et al. argue that divergence-time estimates for our avian phylogeny were too young because of an "inappropriate" maximum age constraint for the most recent common ancestor of modern birds and that, as a result, most modern bird orders diverged before the Cretaceous-Paleogene mass extinction event 66 million years ago instead of after. However, their interpretations of the fossil record and timetrees are incorrect.

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Limited data are available regarding the molecular epidemiology of Mycobacterium tuberculosis (Mtb) strains circulating in Guatemala. Beijing-lineage Mtb strains have gained prevalence worldwide and are associated with increased virulence and drug resistance, but there have been only a few cases reported in Central America. Here we report the first whole genome sequencing of Central American Beijing-lineage strains of Mtb. We find that multiple Beijing-lineage strains, derived from independent founding events, are currently circulating in Guatemala, but overall still represent a relatively small proportion of disease burden. Finally, we identify a specific Beijing-lineage outbreak centered on a poor neighborhood in Guatemala City.

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Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.

We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.

We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.

Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.

This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.

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Physarum polycephalum is a well-studied microbial eukaryote with unique experimental attributes relative to other experimental model organisms. It has a sophisticated life cycle with several distinct stages including amoebal, flagellated, and plasmodial cells. It is unusual in switching between open and closed mitosis according to specific life-cycle stages. Here we present the analysis of the genome of this enigmatic and important model organism and compare it with closely related species. The genome is littered with simple and complex repeats and the coding regions are frequently interrupted by introns with a mean size of 100 bases. Complemented with extensive transcriptome data, we define approximately 31,000 gene loci, providing unexpected insights into early eukaryote evolution. We describe extensive use of histidine kinase-based two-component systems and tyrosine kinase signaling, the presence of bacterial and plant type photoreceptors (phytochromes, cryptochrome, and phototropin) and of plant-type pentatricopeptide repeat proteins, as well as metabolic pathways, and a cell cycle control system typically found in more complex eukaryotes. Our analysis characterizes P. polycephalum as a prototypical eukaryote with features attributed to the last common ancestor of Amorphea, that is, the Amoebozoa and Opisthokonts. Specifically, the presence of tyrosine kinases in Acanthamoeba and Physarum as representatives of two distantly related subdivisions of Amoebozoa argues against the later emergence of tyrosine kinase signaling in the opisthokont lineage and also against the acquisition by horizontal gene transfer.

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This paper introduces new results obtained from a statistical investigation into a 3071-observation data set collected from a Vietnamese nationwide entrepreneurship survey. From established relationships, such factors as preparedness, financial resources and participation in social networks are confirmed to have significant effects on entrepreneurial decisions. Entrepreneurs, both financially constrained and unconstrained, who have a business plan tend to start their entrepreneurial ventures earlier. Also, financial constraints have a profound impact on the entrepreneurial decisions. When perceiving the likelihood of success to be high, an entrepreneur shows the tendency for prompt action on business ideas. But when seeing the risk of prolonging the waiting time to first revenue, a prospective entrepreneur would be more likely to wait for more favorable conditions despite the vagueness of "favorable". Additionally, empirical computations indicate that there is a 41.3% probability that an extant entrepreneur who is generating revenue sees high chance of success. Past work and entrepreneurial experiences also have positive impacts on both the entrepreneurial decisions and perceived chance of success.

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The TET enzymes convert methylcytosine to the newly discovered base hydroxymethylcytosine. While recent reports suggest that TETs may play a role in response to oxidative stress, this role remains uncertain, and results lack in vivo models. Here we show a global decrease of hydroxymethylcytosine in cells treated with buthionine sulfoximine, and in mice depleted for the major antioxidant enzymes GPx1 and 2. Furthermore, genome-wide profiling revealed differentially hydroxymethylated regions in coding genes, and intriguingly in microRNA genes, both involved in response to oxidative stress. These results thus suggest a profound effect of in vivo oxidative stress on the global hydroxymethylome.

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This article documents the addition of 220 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Allanblackia floribunda, Amblyraja radiata, Bactrocera cucurbitae, Brachycaudus helichrysi, Calopogonium mucunoides, Dissodactylus primitivus, Elodea canadensis, Ephydatia fluviatilis, Galapaganus howdenae howdenae, Hoplostethus atlanticus, Ischnura elegans, Larimichthys polyactis, Opheodrys vernalis, Pelteobagrus fulvidraco, Phragmidium violaceum, Pistacia vera, and Thunnus thynnus. These loci were cross-tested on the following species: Allanblackia gabonensis, Allanblackia stanerana, Neoceratitis cyanescens, Dacus ciliatus, Dacus demmerezi, Bactrocera zonata, Ceratitis capitata, Ceratitis rosa, Ceratits catoirii, Dacus punctatifrons, Ephydatia mülleri, Spongilla lacustris, Geodia cydonium, Axinella sp. Ischnura graellsii, Ischnura ramburii, Ischnura pumilio, Pistacia integerrima and Pistacia terebinthus. © 2010 Blackwell Publishing Ltd.

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"Im Zuge der weiteren Verbreitung der Social Media und der internetbasierten Lehre, gewinnen eLearning Inhalte immer mehr an Bedeutung. In den Kontext von eLearning und internetbasierter Lehre gehören auch Open Educational Resources (OER). OER sind digitale Lern- und Lehrmaterialien, die frei für Lehrende und Studierende zugänglich sind und auch frei verbreitet werden dürfen. [...] Um OER auszutauschen, zu finden, zu beschaffen und sie auf einer breiten Basis zugänglich zu machen, insbesondere auch über Suchmaschinen und dadurch verwenden zu können, werden für die jeweiligen Materialien Metadaten benötigt. [...] Um die Frage nach dem Handlungs- und Forschungsbedarf zum Thema Metadaten für Open Educational Resources zu untersuchen, wird zunächst ein Überblick über die momentan bestehenden nationalen und internationalen Metadatenstandards für eLearning Objekte gegeben. [...] Hieraus ergeben sich Empfehlungen, welche Metadaten-Standards für die weitere Nutzung und Förderung geeignet sein könnten. Es werden außerdem die Möglichkeiten der Erstellung eines neuen Metadaten-Standards sowie eines gemeinsamen Portals für OER erörtert. Hierbei wird vor allem auf die zu erwartenden Probleme und die damit verbundenen Anforderungen eingegangen." (DIPF/Orig.)

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Objectives: To evaluate the empirical evidence linking nursing resources to patient outcomes in intensive care settings as a framework for future research in this area. Background: Concerns about patient safely and the quality of care are driving research on the clinical and cost-effectiveness of health care interventions, including the deployment of human resources. This is particularly important in intensive care where a large proportion of the health care budget is consumed and where nursing staff is the main item of expenditure. Recommendations about staffing levels have been trade but may not be evidence based and may not always be achieved in practice. Methods: We searched systematically for studies of the impact of nursing resources (e.g. nurse-patient ratios, nurses' level of education, training and experience) on patient Outcomes, including mortality and adverse events, in adult intensive care. Abstracts of articles were reviewed and retrieved if they investigated the relationship between nursing resources and patient Outcomes. Characteristics of the studies were tabulated and the quality of the Studies assessed. Results: Of the 15 studies included in this review, two reported it statistical relationship between nursing resources and both mortality and adverse events, one reported ail association to mortality only, seven studies reported that they Could not reject the null hypothesis of no relationship to mortality and 10 studies (out of 10 that tested the hypothesis) reported a relationship to adverse events. The main explanatory mechanisms were the lack of time for nurses to perform preventative measures, or for patient surveillance. The nurses' role in pain control was noted by One author. Studies were mainly observational and retrospective and varied in scope from 1 to 52 units. Recommendations for future research include developing the mechanisms linking nursing resources to patient Outcomes, and designing large multi-centre prospective Studies that link patient's exposure to nursing care oil a shift-by-shift basis over time. (C) 2007 Elsevier Ltd. All rights reserved.

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The proliferation of smartphones in the last decade and the number of publications in the field of authoring systems for computer-assisted learning depict a scenario that needs to be explored in order to facilitate the scaffolding of learning activities across contexts. Learning resources are traditionally designed in desktop-based authoring systems where the context is mostly restricted to the learning objective, capturing relevant case characteristics, or virtual situation models. Mobile authoring tools enable learners and teachers to foster universal access to educational resources not only providing channels to share, remix or re-contextualize these, but also capturing the context in-situ and in-time. As a further matter, authoring educational resources in a mobile context is an authentic experience where authors can link learning with their own daily life activities and reflections. The contribution of this manuscript is fourfold: first, the main barriers for ubiquitous and mobile authoring of educational resources are identified; second, recent research on mobile authoring tools is reviewed, and 10 key shortcomings of current approaches are identified; third, the design of a mobile environment to author educational resources (MAT for ARLearn) is presented, and the results of an evaluation of usability and hedonic quality are presented; fourth, conclusions and a research agenda for mobile authoring are discussed.