bluuebunny/crossref_metadata_2025_split huggingface dataset:
A model of compound heterozygous, loss-of-function alleles is broadly consistent with observations from complex-disease GWAS datasets
Authors: Sanjak Jaleal S. , Long Anthony D. , Thornton Kevin R. 
Published: April 2016

AbstractThe genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect-sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation.Author SummaryGene action determines how mutations affect phenotype. When placed in an evolutionary context, the details of the genotype-to-phenotype model can impact the maintenance of genetic variation for complex traits. Likewise, non-equilibrium demographic history may affect patterns of genetic variation. Here, we explore the impact of genetic model and population growth on distribution of genetic variance across the allele frequency spectrum underlying risk for a complex disease. Using forward-in-time population genetic simulations, we show that the genetic model has important impacts on the composition of variation for complex disease risk in a population. We explicitly simulate genome-wide association studies (GWAS) and perform heritability estimation on population samples. A particular model of gene-based partial recessivity, based on allelic non-complementation, aligns well with empirical results. This model is congruent with the dominance variance estimates from both SNPs and twins, and the minor allele frequency distribution of GWAS hits.
A simple offspring-to-mother size ratio predicts post-reproductive lifespan
Authors: Maliha George , Murphy Coleen T. 
Published: April 2016

AbstractWhy do many animals live well beyond their reproductive period? This seems counter to the theory that the fraction of life spent reproducing should be maximized in order to maximize the number of offspring produced in each generation. To resolve this paradox, hypotheses have been developed that evoke parental or grandparental care as reasons for post-reproductive life (e.g., the Mother and Grandmother Hypotheses). However, these hypotheses fail to explain the presence of post-reproductive life in organisms that do not care for their young, such asCaenorhabditis elegans. Here we show that a candidate proxy of the stress of childbirth explains a large portion of the variance in post-reproductive lifespans across many species. A remarkably simple metric, the “offspring ratio” (ratio of the size or weight of offspring to that of the mother) explained 77% of the variance of the post-reproductive lifespan in a sample drawn from widely dispersed taxa. Our results suggest that the stress of childbirth is an important and conserved determinant of post-reproductive lifespan. Thus, long post-reproductive lifespan may simply be a byproduct of the somatic health required for reproduction of large progeny, regardless of parental care.
k-BOOM: A Bayesian approach to ontology structure inference, with applications in disease ontology construction
Authors: Mungall Christopher J. , Koehler Sebastian , Robinson Peter , Holmes Ian , Haendel Melissa 
Published: April 2016

ABSTRACTOne strategy for building ontologies covering domains such as disease or anatomy is to weave together existing knowledge sources (databases, vocabularies and ontologies) into single cohesive whole. A first step in this process is to generatemappingsbetween the elements of these different sources. There are a number of well-known techniques for generating mappings (also known asontology alignemnt), both manual and automatic[7]. Sometimes mappings are seen as an end in themselves, with the sources remaining in a loosely connected state. However, if we want to take the next step and use the mappings to integrate the different sources into a cohesive reference ontology, then we need to translate the mappings into precise logical relationships. This will allow us to safely merge equivalent concepts, creating a unified ontology. This translation is a non-trivial step, as each mapping can be interpreted as multiple different logical relationships, with each interpretation affecting the likelihood of the others. There is a lack of automated methods to assist with this last step; this resolution is typically performed by expert ontologists.Here we describe an ontology construction technique that takes two or more ontologies linked by hypothetical axioms, and estimates the most likely unified logical ontology. Hypothetical axioms can themselves be derived from semantically loose mappings. The method combines deductive reasoning and probabilistic inference and is called Bayesian OWL Ontology Merging (BOOM). We describe a special form k-BOOM that works by factorizing the probabilistic ontology intoksubmodules. We also briefly describe a supplemental lexical and knowledge-based technique for generating a set of hypothetical axioms from loose mappings.We are currently using this technique to build a merged disease ontology (Monarch Disease Ontology; MonDO) that unifies a broad range of vocabularies into a consistent and coherent whole.
Enrichment of long DNA fragments from mixed samples for Nanopore sequencing
Authors: Eckert SE , Chan JZ-M , Houniet Darren ,   the PATHSEEK consortium, Breuer J , Speight G 
Published: April 2016

AbstractWhole-genome sequencing of pathogenic organisms directly from clinical samples combines detection and genotyping in one step. This can speed up diagnosis, especially for slow-growing organisms likeMycobacterium tuberculosis (Mtb), which need considerable time to grow in subculture, and can provide vital information for effective personalised treatment. Within the PATHSEEK project, we have developed a bait-capture approach to selectively enrich DNA/RNA from specific bacterial and viral pathogens present in clinical samples. Here, we present a variation of the method that allows enrichment of large fragments of target DNA for sequencing on an Oxford Nanopore MinIONTMsequencer. We enriched and sequenced cDNA from Influenza A (FluA), genomic DNA (gDNA) from human cytomegalovirus (CMV) and from two strains ofMtb, and present an evaluation of the method together with analysis of the sequencing results from a MinIONTMand an Illumina MiSeq sequencer. While unenriched FluA and CMV samples had no reads matching the target organism due to the high background of DNA from host cell lines, enriched samples had 56.7% and 90.9% on-target reads respectively for the best quality Nanopore reads.
Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts
Authors: Taylor Bradford P , Penington Catherine J , Weitz Joshua S. 
Published: April 2016

AbstractMultiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virusmicrobe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean-field model. We also observe longtails in the distribution of the multiplicity of infection (MOI) in contrast to mean-field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.
A comparative analysis of 5-azacytidine and zebularine induced DNA demethylation
Authors: Griffin Patrick T. , Niederhuth Chad E. , Schmitz Robert J. 
Published: April 2016

AbstractThe non-methylable cytosine analogs, 5-azacytidine and zebularine, are widely used to inhibit DNA methyltransferase activity and reduce genomic DNA methylation. In this study, whole-genome bisulfite sequencing is used to construct maps of DNA methylation with single base pair resolution inArabidopsis thalianaseedlings treated with each demethylating agent. We find that both inhibitor treatments result in nearly indistinguishable patterns of genome-wide DNA methylation and that 5-azacytidine had a slightly greater demethylating effect across the genome at higher concentrations. Transcriptome analyses revealed a substantial number of up-regulated genes, with an overrepresentation of transposable element genes, in particular CACTA-like elements. This demonstrates that chemical demethylating agents have a disproportionately large effect on loci that are otherwise silenced by DNA methylation.
C4photosynthesis and climate through the lens of optimality
Authors: Zhou Haoran , Helliker Brent R. , Akçay Erol 
Published: April 2016

AbstractCO2, temperature, water availability and light intensity were all potential selective pressures to propel the initial evolution and global expansion of C4photosynthesis over the last 30 million years. To tease apart how the primary selective pressures varied along this evolutionary trajectory, we coupled photosynthesis and hydraulics models while optimizing photosynthesis over stomatal resistance and leaf/fine-root allocation. We further examined the importance of resource (e.g. nitrogen) reallocation from the dark to the light reactions during and after the initial formation of C4syndrome. We show here that the primary selective pressures—all acting upon photorespiration in C3progenitors—changed through the course of C4evolution. The higher stomatal resistance and leaf-to-root allocation ratio enabled by the C4carbon-concentrating mechanism led to a C4advantage without any change in hydraulic properties, but selection on nitrogen reallocation varied. Water limitation was the primary driver for the initial evolution of C425-32 million years ago, and could positively select for C4evolution with atmospheric CO2as high as 600 ppm. Under these high CO2conditions, nitrogen reallocation was necessary. Low CO2and light intensity, but not nitrogen reallocation, were the primary drivers during the global radiation of C45-10 MYA. Finally, our results suggest that identifying the predominate selective pressures at the time C4first evolved within a lineage should help explain current biogeographical distributions.Statement of authorship:HZ, BH and EA conceptualized the study. HZ and EA built the model, HZ and BH put the idea in a general evolutionary context, HZ performed the modeling work and analyzed output data. HZ wrote the first draft, BH and EA contributed substantially to revisions.Significance StatementC4photosynthesis pathway had evolved more than 60 times independently across the terrestrial plants through mid-Oligocene (~30 MYA) and diversified at late Miocene (5 to 10 MYA). We use an optimal physiology model to examine the primary selective pressures along the evolutionary history. Water limitation was the primary driver for C4evolution from the initial evolutionary events 25-32 MYA until CO2became low enough to, along with light intensity, drive the global radiation of C45-10 MYA. This modeling framework can be used to investigate evolution of other physiological traits (e.g. N reallocation, hydraulics) after the initial formation of C4syndrome, which contributed to further increasing productivity of C4in historical and current environmental conditions.
plasmidSPAdes: Assembling Plasmids from Whole Genome Sequencing Data
Authors: Antipov Dmitry , Hartwick Nolan , Shen Max , Raiko Mikhail , Lapidus Alla , Pevzner Pavel A. 
Published: April 2016

ABSTRACTMotivationPlasmids are stably maintained extra-chromosomal genetic elements that replicate independently from the host cell’s chromosomes. Although plasmids harbor biomedically important genes, (such as genes involved in virulence and antibiotics resistance), there is a shortage of specialized software tools for extracting and assembling plasmid data from whole genome sequencing projects.ResultsWe present the plasmidSPAdes algorithm and software tool for assembling plasmids from whole genome sequencing data and benchmark its performance on a diverse set of bacterial genomes.Availability and implementationPLASMIDSPADESis publicly available athttp://spades.bioinf.spbau.ru/plasmidSPAdes/Contactd.antipov@spbu.ru
Time-resolved dual RNA-Seq reveals extensive rewiring of lung epithelial and pneumococcal transcriptomes during early infection
Authors: Aprianto Rieza , Slager Jelle , Holsappel Siger , Veening Jan-Willem 
Published: April 2016

AbstractStreptococcus pneumoniae(pneumococcus) is the main etiological agent of pneumonia. Pneumococcal pneumonia is initiated by bacterial adherence to lung epithelial cells. Infection to the epithelium is a disruptive interspecies interaction involving numerous transcription-mediated processes. Revealing transcriptional changes may provide valuable insights into pneumococcal disease. Dual RNA-Seq allows simultaneous monitoring of the transcriptomes of both host and pathogen. Here, we developed a time-resolved infection model of human lung alveolar epithelial cells byS. pneumoniaeand assessed transcriptome changes by dual RNA-Seq. Our data provide new insights into host-microbe interactions and show that the epithelial glutathione-detoxification pathway is activated by bacterial presence. We observed that adherent pneumococci, not free-floating bacteria, access host-associated carbohydrates and repress innate immune responses. In conclusion, we provide a dynamic dual-transcriptomics overview of early pneumococcal infection with easy online access (http://dualrnaseq.molgenrug.nl). Further database exploration may expand our understanding of epithelial-pneumococcal interaction, leading to novel antimicrobial strategies.Graphical Abstract
Allele Surfing Promotes Microbial Adaptation from Standing Variation
Authors: Gralka Matti , Stiewe Fabian , Farrell Fred , Möebius Wolfram , Waclaw Bartek , Hallatschek Oskar 
Published: April 2016

AbstractThe coupling of ecology and evolution during range expansions enables mutations to establish at expanding range margins and reach high frequencies. This phenomenon, called allele surfing, is thought to have caused revolutions in the gene pool of many species, most evidently in microbial communities. It has remained unclear, however, under which conditions allele surfing promotes or hinders adaptation. Here, using microbial experiments and simulations, we show that, starting with standing adaptive variation, range expansions generate a larger increase in mean fitness than spatially uniform population expansions. The adaptation gain results from ‘soft’ selective sweeps emerging from surfing beneficial mutations. The rate of these surfing events is shown to sensitively depend on the strength of genetic drift, which varies among strains and environmental conditions. More generally, allele surfing promotes the rate of adaptation per biomass produced, which could help developing biofilms and other resource-limited populations to cope with environmental challenges.
Random vibration analysis for coupled vehicle-track systems with uncertain parameters
Authors: Xiang Pan , Zhao Yan , Lin Jiahao , Kennedy D , Williams Fred W 
Published: April 2016

Purpose
The purpose of this paper is to present a new random vibration-based assessment method for coupled vehicle-track systems with uncertain parameters when subjected to random track irregularity.

Design/methodology/approach
The uncertain parameters of vehicle are described as bounded random variables. The track is regarded as an infinite periodic structure, and the dynamic equations of the coupled vehicle-track system, under mixed physical coordinates and symplectic dual coordinates, are established through wheel-rail coupling relationships. The random track irregularities at the wheel-rail contact points are converted to a series of deterministic harmonic excitations with phase lag by using the pseudo excitation method. Based on the polynomial chaos expansion of the pseudo response, a chaos expanded pseudo equation is derived, leading to the combined hybrid pseudo excitation method - polynomial chaos expansion method

Findings
The impact of uncertainty propagation on the random vibration analysis is assessed efficiently. According to GB5599-85, the reliability analysis for the stability index is implemented, which can grade the comfort level by the probability. Comparing to the deterministic analysis, it turns out that neglect of the parameter uncertainty will lead to potentially risky analysis results.

Originality/value
The proposed method is compared with Monte Carlo simulations, achieving good agreement. It is an effective means for random vibration analysis of uncertain coupled vehicle-track systems and has good engineering practicality
Squeeze film behavior in porous transversely circular stepped plates with a couple stress fluid
Authors: Narayanan Santhana Krishnan , Chamkha A , Kesavan Sundarammal 
Published: April 2016

Purpose
The purpose of this work is to carry our a study of the effect of surface roughness on squeeze film behavior between two transversely circular stepped plates with couple stress lubricant when the upper circular stepped plate has porous facing which approaches the lower plate with uniform velocity.

Design/methodology/approach
The modified Stochastic Reynolds equation is derived for Christensen Stochastic theory for the rough surfaces. Closed form solution of the Stochastic Reynolds equation is obtained in terms of Fourier-Bessel series.

Findings
It is found that the effect of couple stress fluid and surface roughness is more pronounced compared to classical case.

Originality/value
The problem is original that it consider a couple stress fluid in this type of applications.
Exchange rate volatility and exports: a panel data analysis
Authors: Vieira Flavio Vilela , MacDonald Ronald 
Published: April 2016

Purpose– The purpose of this paper is to empirically investigate the role of real effective exchange rate (REER) volatility on export volume and also to address the impact of the international financial crisis of 2008.Design/methodology/approach– The empirical methodology is based on System GMM estimation for a set of 106 countries for the period of 2000-2011.Findings– For the complete sample of countries and for a set of developing/emerging economies, there is evidence that an increase (decrease) in REER volatility reduces (increases) export volume. The results are not robust once the oil export countries are removed from the sample. The estimated coefficients for the financial crisis dummy are positive and statistically significant, indicating that export volume were 0.14 percent higher after the financial crisis of 2008 compared to the previous period (2000-2007). There is also evidence that the export volume is price (REER) and income (trade weighted) inelastic.Research limitations/implications– The empirical results are valid for the complete set of countries and for developing and emerging economies when including the oil export countries, suggesting that countries should reduce exchange rate volatility in order to foster their export volume and that oil export countries have an important role on these results.Practical implications– The paper suggests that policymakers should adopt different policies to minimize exchange rate volatility if they seek to increase export volume. The international financial crisis had a significant impact on export volume in all estimated models regardless of the set of countries used.Originality/value– One of the main novelties of this work is that it deals with possible endogeneity using GMM estimators and addresses the issue of instrument proliferation, which is not a common feature of previous empirical studies on exchange rate volatility and trade flows. Another original aspect of the research is the construction of trade weighted variables for foreign income and REER based on the major 20 export partners for each country used in the panel data estimation. The work also incorporates the years following the international financial crisis of 2008, which is an additional empirical novelty, in order to address the impact of the international financial crisis on the export volume.
Real exchange rate and investment in the Brazilian manufacturing industry
Authors: Baltar Carolina Troncoso , Hiratuka Celio , Lima Gilberto Tadeu 
Published: April 2016

Purpose– The purpose of this paper is to study the impact of the real exchange rate on investment in the Brazilian manufacturing industry.Design/methodology/approach– The authors develop an investment model that considers the effect of changes in the real exchange rate, taking into account that the effect of the real exchange rate on the Brazilian manufacturing investment operates through demand and cost channels. The composition of these effects varies across manufacturing sectors, with different repercussions on investment decisions, depending on sectoral characteristics. A panel data analysis is applied to estimate the model for the Brazilian manufacturing sectors from 1996 to 2010.Findings– One main result is that the responsiveness of the Brazilian manufacturing investment to real exchange rate varies considerably across manufacturing sectors. Overall, the results contribute to a better understanding of the relationship between exchange rate dynamics, manufacturing investment and industrial development, thus unveiling important empirical elements for the debate on industrial policies to stimulate manufacturing investment and production.Originality/value– As the (scant) empirical literature on real exchange rate and investment in Brazil has invariably been using aggregate data, this paper contributes to the literature by obtaining sectoral estimates of the responsiveness of manufacturing investment to exchange rate fluctuations that further the understanding of the complex relationship between these economic variables.