137 research outputs found

    Increasing the Power to Detect Causal Associations by Combining Genotypic and Expression Data in Segregating Populations

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    To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships among variables of interest. Given the complexity of molecular networks underlying common human disease traits, and the fact that biological networks can change depending on environmental conditions and genetic factors, large datasets, generally involving multiple perturbations (experiments), are required to reconstruct and reliably extract information from these networks. With limited resources, the balance of coverage of multiple perturbations and multiple subjects in a single perturbation needs to be considered in the experimental design. Increasing the number of experiments, or the number of subjects in an experiment, is an expensive and time-consuming way to improve network reconstruction. Integrating multiple types of data from existing subjects might be more efficient. For example, it has recently been demonstrated that combining genotypic and gene expression data in a segregating population leads to improved network reconstruction, which in turn may lead to better predictions of the effects of experimental perturbations on any given gene. Here we simulate data based on networks reconstructed from biological data collected in a segregating mouse population and quantify the improvement in network reconstruction achieved using genotypic and gene expression data, compared with reconstruction using gene expression data alone. We demonstrate that networks reconstructed using the combined genotypic and gene expression data achieve a level of reconstruction accuracy that exceeds networks reconstructed from expression data alone, and that fewer subjects may be required to achieve this superior reconstruction accuracy. We conclude that this integrative genomics approach to reconstructing networks not only leads to more predictive network models, but also may save time and money by decreasing the amount of data that must be generated under any given condition of interest to construct predictive network models

    Ein neues, unkompliziertes Verfahren zur Bestimmung der Zusammensetzung binärer Flüssigkeitsgemische

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    Ein neues Verfahren zur Bestimmung der Zusammensetzung binärer Flüssigkeitsgemische mit Hilfe solvatochromer Farbstoffe wird beschrieben. Die Analyse erfolgt durch einfache UV/VIS-Absorptionsmessung und ist unter Verwendung einer Zwei-Parameter-Gleichung ein exakter Schnelltest

    Flowering Time Diversification and Dispersal in Central Eurasian Wild Wheat Aegilops tauschii Coss.: Genealogical and Ecological Framework

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    Timing of flowering is a reproductive trait that has significant impact on fitness in plants. In contrast to recent advances in understanding the molecular basis of floral transition, few empirical studies have addressed questions concerning population processes of flowering time diversification within species. We analyzed chloroplast DNA genealogical structure of flowering time variation in central Eurasian wild wheat Aegilops tauschii Coss. using 200 accessions that represent the entire species range. Flowering time measured as days from germination to flowering varied from 144.0 to 190.0 days (average 161.3 days) among accessions in a common garden/greenhouse experiment. Subsequent genealogical and statistical analyses showed that (1) there exist significant longitudinal and latitudinal clines in flowering time at the species level, (2) the early-flowering phenotype evolved in two intraspecific lineages, (3) in Asia, winter temperature was an environmental factor that affected the longitudinal clinal pattern of flowering time variation, and (4) in Transcaucasus-Middle East, some latitudinal factors affected the geographic pattern of flowering time variation. On the basis of palaeoclimatic, biogeographic, and genetic evidence, the northern part of current species' range [which was within the temperate desert vegetation (TDV) zone at the Last Glacial Maximum] is hypothesized to have harbored species refugia. Postglacial southward dispersal from the TDV zone seems to have been driven by lineages that evolved short-flowering-time phenotypes through different genetic mechanisms in Transcaucasus-Middle East and Asia

    Large Scale Benchmark of Materials Design Methods

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    Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboar

    A survey of visualization tools for biological network analysis

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    The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneity provides a challenge for the visualization of the data. There are a wide variety of graph representations available, which most often map the data on 2D graphs to visualize biological interactions. These methods are applicable to a wide range of problems, nevertheless many of them reach a limit in terms of user friendliness when thousands of nodes and connections have to be analyzed and visualized. In this study we are reviewing visualization tools that are currently available for visualization of biological networks mainly invented in the latest past years. We comment on the functionality, the limitations and the specific strengths of these tools, and how these tools could be further developed in the direction of data integration and information sharing

    Genomic microsatellites identify shared Jewish ancestry intermediate between Middle Eastern and European populations

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    <p>Abstract</p> <p>Background</p> <p>Genetic studies have often produced conflicting results on the question of whether distant Jewish populations in different geographic locations share greater genetic similarity to each other or instead, to nearby non-Jewish populations. We perform a genome-wide population-genetic study of Jewish populations, analyzing 678 autosomal microsatellite loci in 78 individuals from four Jewish groups together with similar data on 321 individuals from 12 non-Jewish Middle Eastern and European populations.</p> <p>Results</p> <p>We find that the Jewish populations show a high level of genetic similarity to each other, clustering together in several types of analysis of population structure. Further, Bayesian clustering, neighbor-joining trees, and multidimensional scaling place the Jewish populations as intermediate between the non-Jewish Middle Eastern and European populations.</p> <p>Conclusion</p> <p>These results support the view that the Jewish populations largely share a common Middle Eastern ancestry and that over their history they have undergone varying degrees of admixture with non-Jewish populations of European descent.</p

    Multilocus Microsatellite Typing (MLMT) of Strains from Turkey and Cyprus Reveals a Novel Monophyletic L. donovani Sensu Lato Group

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    In eastern Mediterranean, leishmaniasis represents a major public health problem with considerable impact on morbidity and potential to spread. Cutaneous leishmaniasis (CL) caused by L. major or L. tropica accounts for most cases in this region although visceral leishmaniasis (VL) caused by L. infantum is also common. New foci of human CL caused by L. donovani complex strains were recently described in Cyprus and Turkey. Herein we analyzed Turkish strains from human CL foci in Çukurova region (north of Cyprus) and a human VL case in Kuşadasi. These were compared to Cypriot strains that were previously typed by Multilocus Enzyme Electrophoresis (MLEE) as L. donovani MON-37. Nevertheless, they were found genetically distinct from MON-37 strains of other regions and therefore their origin remained enigmatic. A population study was performed by Multilocus Microsatellite Typing (MLMT) and the profile of the Turkish strains was compared to previously analyzed L. donovani complex strains. Our results revealed close genetic relationship between Turkish and Cypriot strains, which form a genetically distinct L. infantum monophyletic group, suggesting that Cypriot strains may originate from Turkey. Our analysis indicates that the epidemiology of leishmaniasis in this region is more complicated than originally thought

    Sex, Subdivision, and Domestic Dispersal of Trypanosoma cruzi Lineage I in Southern Ecuador

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    Trypanosoma cruzi is transmitted by blood sucking insects known as triatomines. This protozoan parasite commonly infects wild and domestic mammals in South and Central America. However, triatomines also transmit the parasite to people, and human infection with T. cruzi is known as Chagas disease, a major public health concern in Latin America. Understanding the complex dynamics of parasite spread between wild and domestic environments is essential to design effective control measures to prevent the spread of Chagas disease. Here we describe T. cruzi genetic diversity and population dynamics in southern Ecuador. Our findings indicate that the parasite circulates in two largely independent cycles: one corresponding to the sylvatic environment and one related to the domestic/peridomestic environment. Furthermore, our data indicate that human activity might promote parasite dispersal among communties. This information is the key for the design of control programmes in Southern Ecuador. Finally, we have encountered evidence of a sexual reproductive mode in the domestic T. cruzi population, which constitutes a new and intriguing finding with regards to the biology of this parasite

    The Evolutionary Dynamics of the Lion Panthera leo Revealed by Host and Viral Population Genomics

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    The lion Panthera leo is one of the world's most charismatic carnivores and is one of Africa's key predators. Here, we used a large dataset from 357 lions comprehending 1.13 megabases of sequence data and genotypes from 22 microsatellite loci to characterize its recent evolutionary history. Patterns of molecular genetic variation in multiple maternal (mtDNA), paternal (Y-chromosome), and biparental nuclear (nDNA) genetic markers were compared with patterns of sequence and subtype variation of the lion feline immunodeficiency virus (FIVPle), a lentivirus analogous to human immunodeficiency virus (HIV). In spite of the ability of lions to disperse long distances, patterns of lion genetic diversity suggest substantial population subdivision (mtDNA ΦST = 0.92; nDNA FST = 0.18), and reduced gene flow, which, along with large differences in sero-prevalence of six distinct FIVPle subtypes among lion populations, refute the hypothesis that African lions consist of a single panmictic population. Our results suggest that extant lion populations derive from several Pleistocene refugia in East and Southern Africa (∼324,000–169,000 years ago), which expanded during the Late Pleistocene (∼100,000 years ago) into Central and North Africa and into Asia. During the Pleistocene/Holocene transition (∼14,000–7,000 years), another expansion occurred from southern refugia northwards towards East Africa, causing population interbreeding. In particular, lion and FIVPle variation affirms that the large, well-studied lion population occupying the greater Serengeti Ecosystem is derived from three distinct populations that admixed recently
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