Exploring the Genetic Basis of Variation in Gene Predictions with a Synthetic Association Study

Identifying DNA polymorphisms that affect molecular processes like transcription, splicing, or translation typically requires genotyping and experimentally characterizing tissue from large numbers of individuals, which remains expensive and time consuming. Here we introduce an alternative strategy: a “synthetic association study” in which we computationally predict molecular phenotypes on artificial genomes containing randomly sampled combinations of polymorphic alleles, and perform a classical association study to identify genotypes underlying variation in these computationally predicted annotations. We applied this method to characterize the effects on gene structure of 32,792 single-nucleotide polymorphisms between two strains of the antibiotic producing fungus Penicilium chrysogenum. Although these SNPs represent only 0.1 percent of the nucleotides in the genome, they collectively altered 1.8 percent of predicted gene models between these strains. To determine which SNPs or combinations of SNPs were responsible for this variation, we predicted protein-coding genes in 500 intermediate genomes, each identical except for randomly chosen alleles at each SNP position. Of 30,468 gene models in the genome, 557 varied across these 500 genomes. 226 of these polymorphic gene models (40%) were perfectly correlated with individual SNPs, all of which were within or immediately proximal to the affected gene. The genetic architectures of the other 321 were more complex, with several examples of SNP epistasis that would have been difficult to predict a priori. We expect that many of the SNPs that affect computational gene structure reflect a biologically unrealistic sensitivity of the gene prediction algorithm to sequence changes, and we propose that genome annotation algorithms could be improved by minimizing their sensitivity to natural polymorphisms. However, many of the SNPs we identified are likely to affect transcript structure in vivo, and the synthetic association study approach can be easily generalized to any computed genome annotation to uncover relationships between genotype and important molecular phenotypes

Comparative Composition, Diversity and Trophic Ecology of Sediment Macrofauna at Vents, Seeps and Organic Falls

Sediments associated with hydrothermal venting, methane seepage and large organic falls such as whale, wood and plant detritus create deep-sea networks of soft-sediment habitats fueled, at least in part, by the oxidation of reduced chemicals. Biological studies at deep-sea vents, seeps and organic falls have looked at macrofaunal taxa, but there has yet to be a systematic comparison of the community-level attributes of sediment macrobenthos in various reducing ecosystems. Here we review key similarities and differences in the sediment-dwelling assemblages of each system with the goals of (1) generating a predictive framework for the exploration and study of newly identified reducing habitats, and (2) identifying taxa and communities that overlap across ecosystems. We show that deep-sea seep, vent and organic-fall sediments are highly heterogeneous. They sustain different geochemical and microbial processes that are reflected in a complex mosaic of habitats inhabited by a mixture of specialist (heterotrophic and symbiont-associated) and background fauna. Community-level comparisons reveal that vent, seep and organic-fall macrofauna are very distinct in terms of composition at the family level, although they share many dominant taxa among these highly sulphidic habitats. Stress gradients are good predictors of macrofaunal diversity at some sites, but habitat heterogeneity and facilitation often modify community structure. The biogeochemical differences across ecosystems and within habitats result in wide differences in organic utilization (i.e., food sources) and in the prevalence of chemosynthesis-derived nutrition. In the Pacific, vents, seeps and organic-falls exhibit distinct macrofaunal assemblages at broad-scales contributing to ß diversity. This has important implications for the conservation of reducing ecosystems, which face growing threats from human activities

Acute-Phase-HDL Remodeling by Heparan Sulfate Generates a Novel Lipoprotein with Exceptional Cholesterol Efflux Activity from Macrophages

During episodes of acute-inflammation high-density lipoproteins (HDL), the carrier of so-called good cholesterol, experiences a major change in apolipoprotein composition and becomes acute-phase HDL (AP-HDL). This altered, but physiologically important, HDL has an increased binding affinity for macrophages that is dependent on cell surface heparan sulfate (HS). While exploring the properties of AP-HDL∶HS interactions we discovered that HS caused significant remodeling of AP-HDL. The physical nature of this change in structure and its potential importance for cholesterol efflux from cholesterol-loaded macrophages was therefore investigated. In the presence of heparin, or HS, AP-HDL solutions at pH 5.2 became turbid within minutes. Analysis by centrifugation and gel electrophoresis indicated that AP-HDL was remodeled generating novel lipid poor particles composed only of apolipoprotein AI, which we designate β2. This remodeling is dependent on pH, glycosaminoglycan type, is promoted by Ca2+ and is independent of protease or lipase activity. Compared to HDL and AP-HDL, remodeled AP-HDL (S-HDL-SAA), containing β2 particles, demonstrated a 3-fold greater cholesterol efflux activity from cholesterol-loaded macrophage. Because the identified conditions causing this change in AP-HDL structure and function can exist physiologically at the surface of the macrophage, or in its endosomes, we postulate that AP-HDL contains latent functionalities that become apparent and active when it associates with macrophage cell surface/endosomal HS. In this way initial steps in the reverse cholesterol transport pathway are focused at sites of injury to mobilize cholesterol from macrophages that are actively participating in the phagocytosis of damaged membranes rich in cholesterol. The mechanism may also be of relevance to aspects of atherogenesis

Are vaccination programmes delivered by lay health workers cost-effective? A systematic review

<p>Abstract</p> <p>Background</p> <p>A recently updated Cochrane systematic review on the effects of lay or community health workers (LHWs) in primary and community health care concluded that LHW interventions could lead to promising benefits in the promotion of childhood vaccination uptake. However, understanding of the costs and cost-effectiveness of involving LHWs in vaccination programmes remains poor. This paper reviews the costs and cost-effectiveness of vaccination programme interventions involving LHWs.</p> <p>Methods</p> <p>Articles were retrieved if the title, keywords or abstract included terms related to 'lay health workers', 'vaccination' and 'economics'. Reference lists of studies assessed for inclusion were also searched and attempts were made to contact authors of all studies included in the Cochrane review. Studies were included after assessing eligibility of the full-text article. The included studies were then reviewed against a set of background and technical characteristics.</p> <p>Results</p> <p>Of the 2616 records identified, only three studies fully met the inclusion criteria, while an additional 11 were retained as they included some cost data. Methodologically, the studies were strong but did not adequately address affordability and sustainability and were also highly heterogeneous in terms of settings and LHW outcomes, limiting their comparability. There were insufficient data to allow any conclusions to be drawn regarding the cost-effectiveness of LHW interventions to promote vaccination uptake. Studies focused largely on health outcomes and did illustrate to some extent how the institutional characteristics of communities, such as governance and sources of financial support, influence sustainability.</p> <p>Conclusion</p> <p>The included studies suggest that conventional economic evaluations, particularly cost-effectiveness analyses, generally focus too narrowly on health outcomes, especially in the context of vaccination promotion and delivery at the primary health care level by LHWs. Further studies on the costs and cost-effectiveness of vaccination programmes involving LHWs should be conducted, and these studies should adopt a broader and more holistic approach.</p

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Predicting environmental chemical factors associated with disease-related gene expression data

<p>Abstract</p> <p>Background</p> <p>Many common diseases arise from an interaction between environmental and genetic factors. Our knowledge regarding environment and gene interactions is growing, but frameworks to build an association between gene-environment interactions and disease using preexisting, publicly available data has been lacking. Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease.</p> <p>Methods</p> <p>We integrated publicly available disease-specific gene expression microarray data and curated chemical-gene interaction data to systematically predict environmental chemicals associated with disease. We derived chemical-gene signatures for 1,338 chemical/environmental chemicals from the Comparative Toxicogenomics Database (CTD). We associated these chemical-gene signatures with differentially expressed genes from datasets found in the Gene Expression Omnibus (GEO) through an enrichment test.</p> <p>Results</p> <p>We were able to verify our analytic method by accurately identifying chemicals applied to samples and cell lines. Furthermore, we were able to predict known and novel environmental associations with prostate, lung, and breast cancers, such as estradiol and bisphenol A.</p> <p>Conclusions</p> <p>We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature.</p

Ecology and Biogeography of Free-Living Nematodes Associated with Chemosynthetic Environments in the Deep Sea: A Review

Background: Here, insight is provided into the present knowledge on free-living nematodes associated with chemosynthetic environments in the deep sea. It was investigated if the same trends of high standing stock, low diversity, and the dominance of a specialized fauna, as observed for macro-invertebrates, are also present in the nematodes in both vents and seeps. Methodology: This review is based on existing literature, in combination with integrated analysis of datasets, obtained through the Census of Marine Life program on Biogeography of Deep-Water Chemosynthetic Ecosystems (ChEss). Findings: Nematodes are often thriving in the sulphidic sediments of deep cold seeps, with standing stock values ocassionaly exceeding largely the numbers at background sites. Vents seem not characterized by elevated densities. Both chemosynthetic driven ecosystems are showing low nematode diversity, and high dominance of single species. Genera richness seems inversely correlated to vent and seep fluid emissions, associated with distinct habitat types. Deep-sea cold seeps and hydrothermal vents are, however, highly dissimilar in terms of community composition and dominant taxa. There is no unique affinity of particular nematode taxa with seeps or vents. Conclusions: It seems that shallow water relatives, rather than typical deep-sea taxa, have successfully colonized the reduced sediments of seeps at large water depth. For vents, the taxonomic similarity with adjacent regular sediments is much higher, supporting rather the importance of local adaptation, than that of long distance distribution. Likely the ephemeral nature of vents, its long distance offshore and the absence of pelagic transport mechanisms, have prevented so far the establishment of a successful and typical vent nematode fauna. Some future perspectives in meiofauna research are provided in order to get a more integrated picture of vent and seep biological processes, including all components of the marine ecosystem

Enabling political legitimacy and conceptual integration for climate change adaptation research within an agricultural bureaucracy: a systemic inquiry

The value of using systems approaches, for situations framed as ‘super wicked’, is examined from the perspective of research managers and stakeholders in a state-based climate change adaptation (CCA) program (CliChAP). Polycentric drivers influencing the development of CCA research pre-2010 in Victoria, Australia are reflected on, using Soft Systems Methodology (SSM) to generate a boundary critique of CCA research as a human activity system. We experienced the complexity of purpose with research practices pulling in different directions, reflected on the appropriateness of agricultural bureaucracies’ historical new public management (NPM) practices, and focused on realigning management theory with emerging demands for adaptation research skills and capability. Our analysis conceptualised CliChAP as a subsystem, generating novelty in a wider system, concerned with socio-ecological co-evolution. Constraining/enabling conditions at the time dealing with political legitimacy and conceptual integration were observed as potential catalysts for innovation in research management towards better handling of uncertainty as a social process using systemic thinking in practice (StiP)