bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetics of single-cell protein abundance variation in large yeast populations
Authors: Albert Frank W. , Treusch Sebastian , Shockley Arthur H. , Bloom Joshua S. , Kruglyak Leonid 
Published: November 2013

SummaryMany DNA sequence variants influence phenotypes by altering gene expression. Our understanding of these variants is limited by sample sizes of current studies and by measurements of mRNA rather than protein abundance. We developed a powerful method for identifying genetic loci that influence protein expression in very large populations of the yeastSaccharomyes cerevisiae. The method measures single-cell protein abundance through the use of green-fluorescent-protein tags. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci cluster at hotspot locations that influence multiple proteins—in some cases, more than half of those examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.
Designing Robustness to Temperature in a Feedforward Loop Circuit
Authors: Sen Shaunak , Kim Jongmin , Murray Richard M. 
Published: November 2013

Abstract‘Incoherent feedforward loops’ represent important biomolecular circuit elements capable of a rich set of dynamic behavior including adaptation and pulsed responses. Temperature can modulate some of these properties through its effect on the underlying reaction rate parameters. It is generally unclear how to design such a circuit where the properties are robust to variations in temperature. Here, we address this issue using a combination of tools from control and dynamical systems theory as well as preliminary experimental measurements towards such a design. We formalize temperature as an uncertainty acting on system dynamics, exploring both structured and unstructured uncertainty representations. Next, we analyze a standard incoherent feedforward loop circuit, noting mechanisms that intrinsically confer temperature robustness to some of its properties. Further, we explore different negative feedback configurations that can enhance the robustness to temperature. Finally, we find that the response of an incoherent feedforward loop circuit in cells can change with temperature. These results present groundwork for the design of a temperature-robust incoherent feedforward loop circuit.
Functional Annotation Signatures of Disease Susceptibility Loci Improve SNP Association Analysis
Authors: Iversen Edwin S. , Lipton Gary , Clyde Merlise A. , Monteiro Alvaro N. A. 
Published: November 2013

AbstractWe describe the development and application of a Bayesian statistical model for the prior probability of phenotype–genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs housed in the GWAS Catalog (GC). The set of functional predictors we examined includes measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super–track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants included in the Database of Genomic Variants (DGV) and known regulatory elements included in the Open Regulatory Annotation database (ORegAnno), PolyPhen–2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotation variables would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non–informative predictors and evaluated the model’s ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP’s presence in the GC. Further, using data from a genome–wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome–wide scale and improves power to detect associations.
A Complete Public Domain Family Genomics Dataset
Authors: Corpas Manuel , Cariaso Mike , Coletta Alain , Weiss David , Harrison Andrew , Moran Federico , Yang Huanming 
Published: November 2013

BackgroundThe availability of open access genomic data is essential for the personal genomics field. Public genomic data allow comparative analyses, testing of new tools and genotype-phenotype association studies. Personal genomics data of unrelated individuals are available in the public domain, notably the Personal Genome Project; however, to date genomics family data and metadata are severely lacking, mainly due to cost, privacy concerns or restricted access to Next Generation Sequencing (NGS) technology. Family data have a lot to offer as they allow the study of heritability, something which is impossible to do just by using unrelated individuals.FindingsA whole family from Southern Spain decided to genotype, sequence and analyse their personal genomes making them publicly available under a Creative Commons 0 license (CC0; commonly denominated as public domain). These data include a) five 23andMe SNP chip genotype bed files, b) four raw exomes with their assorted bam files and VCF files, c) a metagenomic raw sequencing data file and d) derived data of likely phenotypes using SNPedia-derived tools.ConclusionsTo our knowledge this is the first CC0 released set of genomic, phenotypic and metagenomic data for a whole family. This dataset is also unique in that it was obtained through direct-to-consumer genetic tests. Hence any ordinary citizen with enough budget and samples should be able to reproduce this experiment. We envisage this dataset to be a useful resource for a variety of applications in the personal genomics field as a) negative control data for trait association discovery, b) testing data for development of new software and c) sample data for heritability studies. We encourage prospective users to share with us derived results so that they can be added to our existing collection.
Water and the biology of prions and plaques
Authors: Steel Graham K. , Wiggins Philippa M. 
Published: November 2013

AbstractThis is an attempt to account for the insolubility and/or aggregation of prions and plaques in terms of a model of water consisting of an equilibrium between high density and low density microdomains. Hydrophobic molecules, including proteins, accumulate selectively into stable populations, enriched in high density water, at charged sites on biopolymers. In enriched high density water, proteins are probably partially unfolded and may precipitate out when released. All extracellular matrices contain such charged polymers. Prions, which have been shown to accumulate in soils and clays containing silicates and aluminates also probably accumulate in extracellular matrices.Release of proteins follows hydrolysis of the charged groups by highly reactive high density water. This is normally a slow process but is greatly accelerated by urea. Plaques may form with age and disease because of accumulation of urea and, perhaps, glucose in the blood. This favours precipitation of proteins emerging from matrices, rather than refolding and solution. Dialysis should, therefore, interfere with plaque formation and impede the development of some age-related diseases.
On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles
Authors: Wan Ying-Wooi , Mach Claire M. , Allen Genevera I. , Anderson Matthew L. , Liu Zhandong 
Published: November 2013

AbstractDysregulated microRNA (miRNA) expression is a well-established feature of human cancer. However, the role of specific miRNAs in determining cancer outcomes remains unclear. Using Level 3 expression data from the Cancer Genome Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12 miRNAs that are associated with survival when miRNAs were profiled in the same specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly, only 1 miRNA transcript is associated with ovarian cancer survival in both datasets. Our analyses indicate that this discrepancy is due to the fact that miRNA levels reported by the two platforms correlate poorly, even after correcting for potential issues inherent to signal detection algorithms. Further investigation is warranted.
Filling up the tree: considering the self-organization of avian roosting behavior
Authors: Alicea Bradly 
Published: November 2013

AbstractIn this paper, models for understanding bird roosting will be considered for purposes of developing better Artificial Life models of complex behavior. Roosting involves multiple flocks of birds picking a single tree limb to rest on for the night, and can be considered an iterative, time-dependent process that unfolds over a 45-minute interval roughly corresponding to twilight. Two models will be used to better understand the main components of this behavior. The constrained dynamics model, which represents continuous random absorption on a one-dimensional lattice, will be used to characterize the dynamics of crowding in the tree structure over time. A second approach involves the relationships between complex networks and roosting behaviors, in particular the evolution of structured networks via rules of incorporation and interaction. Finally, the percolation model will be proposed as a way to bridge behaviors explained by the constrained dynamics and complex network models.
Sampling principles for biodiversity study
Authors: Pan Xubin 
Published: November 2013

AbstractSampling is a fundamental tool in ecology and critical for biodiversity measurement. However, basic principles of biodiversity sampling have been overlooked for many years. In this paper, I proposed and explored five principles of sampling for a specific area and biodiversity study. The first principle of sampling,species increasing with area, is that the number of species increases with the area. The second principle of sampling,individuals increasing with area, is that the number of individuals increases with the area. The third principle of sampling,sum of species number, is that the sum of species number in one area and species number in another area is no less than the total species number in the two areas. The fourth principle of sampling,individual complement, is that the sum of the mathematical expectation of individual number of one or several species in the areaaand that of the same one or several species in the areaA-ais the total individual numberNof the same one or several species in the total areaA. The fifth principle of sampling,species-area theory, is that the sum of the mathematical expectation of number of species in the areaaand that of number of species lost if areaA-ais cleared is the total species numberMin the total areaA.
The Origin of Human-infecting Avian Influenza A H6N1 Virus
Authors: Zhang Liangsheng , Zhang Zhenguo 
Published: November 2013

SummaryIn this study, we retraced the origin of the reported avian influenza A H6N1 virus infecting a 20-year-old woman in Taiwan. As we know, this is the first reported case of human infection by the H6N1 virus, because this subtype virus usually circulates in birds and poultry. Therefore it is crucial to know how this virus attained the ability to infect humans. Using phylogenetic analysis, we found that this virus was derived from reassortments of multiple lineages of H6N1 viruses and H5N2 viruses. The results deepen our understanding of how the new human-infecting virus originated and based on these we discussed possible explanations for the H6N1 infection of humans. Our results, together with recent studies of H7N9 viruses which result in severe disorders, suggest that reassortments among avian-type viruses are quite often, which may sometimes result in fatal infections in humans. Thus a close watch on the circulation of avian influenza viruses is pretty necessary.
The evolution of sex differences in disease genetics
Authors: Gilks William P. , Abbott Jessica K. , Morrow Edward H. 
Published: November 2013

AbstractThere are significant differences in the biology of males and females, ranging from biochemical pathways to behavioural responses, which are relevant to modern medicine. Broad-sense heritability estimates differ between the sexes for many common medical disorders, indicating that genetic architecture can be sex-dependent. Recent genome-wide association studies (GWAS) have successfully identified sex-specific and sex-biased effects, where in addition to sex-specific effects on gene expression, twenty-two medical traits have sex-specific or sex-biased loci. Sex-specific genetic architecture of complex traits is also extensively documented in model organisms using genome-wide linkage or association mapping, and in gene disruption studies. The evolutionary origins of sex-specific genetic architecture and sexual dimorphism lie in the fact that males and females share most of their genetic variation yet experience different selection pressures. At the extreme is sexual antagonism, where selection on an allele acts in opposite directions between the sexes. Sexual antagonism has been repeatedly identified via a number of experimental methods in a range of different taxa. Although the molecular basis remains to be identified, mathematical models predict the maintenance of deleterious variants that experience selection in a sex-dependent manner. There are multiple mechanisms by which sexual antagonism and alleles under sex-differential selection could contribute toward the genetics of common, complex disorders. The evidence we review clearly indicates that further research into sex-dependent selection and the sex-specific genetic architecture of diseases would be rewarding. This would be aided by studies of laboratory and wild animal populations, and by modelling sex-specific effects in genome-wide association data with joint, gene-by-sex interaction tests. We predict that even sexually monomorphic diseases may harbour cryptic sex-specific genetic architecture. Furthermore, empirical evidence suggests that investigating sex-dependent epistasis may be especially rewarding. Finally, the prevalent nature of sex-specific genetic architecture in disease offers scope for the development of more effective, sex-specific therapies.FundingThis work was supported by the European Research Council (WPG and EHM; Starting Grant #280632), a Royal Society University Research Fellowship (EHM), the Swedish Research Council (JKA), and the Volkswagen Foundation (JKA). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Competing interestsThe authors declare that they have no competing financial interests.
On the optimal trimming of high-throughput mRNA sequence data
Authors: MacManes Matthew D. 
Published: November 2013

AbstractThe widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose Phredscore<2 or<5, is optimal for most studies across a wide variety of metrics.
Design and implementation of a synthetic biomolecular concentration tracker
Authors: Hsiao Victoria , de los Santos Emmanuel LC , Whitaker Weston R. , Dueber John E. , Murray Richard M. 
Published: November 2013

AbstractAs a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we design, model, and implement a biomolecular concentration tracker, in which an output protein tracks the concentration of an input protein. Using synthetic scaffolds built from small, modular protein-protein interaction domains to colocalize a two-component system, the circuit design relies on a single negative feedback loop to modulate the production of the output protein. Using a combination of modeling and experimental work, we show that the circuit achieves real-time protein concentration tracking inEscherichia coliand that steady state outputs can be tuned.
A data repository and analysis framework for spontaneous neural activity recordings in developing retina
Authors: Eglen Stephen John , Weeks Michael , Jessop Mark , Simonotto Jennifer , Jackson Tom , Sernagor Evelyne 
Published: November 2013

AbstractBackgroundDuring early development, neural circuits fire spontaneously, generating activity episodes with complex spatiotemporal patterns. Recordings of spontaneous activity have been made in many parts of the nervous system over the last 25 years, reporting developmental changes in activity patterns and the effects of various genetic perturbations.ResultsWe present a curated repository of multielectrode array recordings of spontaneous activity in developing mouse and ferret retina. The data have been annotated with minimal metadata and converted into HDF5. This paper describes the structure of the data, along with examples of reproducible research using these data files. We also demonstrate how these data can be analysed in the CARMEN workflow system. This article is written as a literate programming document; all programs and data described here are freely available.Conclusions1. We hope this repository will lead to novel analysis of spontaneous activity recorded in different laboratories. 2. We encourage published data to be added to the repository. 3. This repository serves as an example of how multielectrode array recordings can be stored for long-term reuse.
Unexpected links reflect the noise in networks
Authors: Yambartsev Anatoly , Perlin Michael , Kovchegov Yevgeniy , Shulzhenko Natalia , Mine Karina L. , Morgun Andrey 
Published: November 2013

AbstractGene regulatory networks are commonly used for modeling biological processes and revealing underlying molecular mechanisms. The reconstruction of gene regulatory networks from observational data is a challenging task, especially, considering the large number of involved players (e.g. genes) and much fewer biological replicates available for analysis. Herein, we proposed a new statistical method of estimating the number of erroneous edges that strongly enhances the commonly used inference approaches. This method is based on special relationship between correlation and causality, and allows to identify and to remove approximately half of erroneous edges. Using the mathematical model of Bayesian networks and positive correlation inequalities we established a mathematical foundation for our method. Analyzing real biological datasets, we found a strong correlation between the results of our method and the commonly used false discovery rate (FDR) technique. Furthermore, the simulation analysis demonstrates that in large networks, our new method provides a more precise estimation of the proportion of erroneous links than FDR.
Lack of evidence for the presence of an interferon in invertebrate
Authors: Wang Pei-Hui 
Published: November 2013

AbstractIn vertebrates, the interferon (IFN) response is the primary form of innate antiviral defense. Previously (2005), a partial cDNA which could encode an interferon-like protein (IntlP) is reported in shrimp, later Rosa et al. (2008) argue that this partial cDNA should encode a portion of insect mitochondrial ATP synthase (MAS) B-chain. Recently (2009), it is demonstrated IntlP also possess antibacterial activity beside antiviral activity reported before. Lacking of a consensus opinion to the question of whether this gene encodes IntlP or MAS, we try to provide more evidences to identify this gene exactly. Here we obtain the full length cDNAs of IntlP/ MAS inLitopenaeus vannamei, and perform the tissue distribution and induced expression analysis. Our results confirm that IntlP is coded by a mistaken ORF and the actual protein indeed is aL. vannameimitochondrial ATP synthase (LvMAS) whose function is unknown in antiviral responses.
Pathways to social evolution: reciprocity, relatedness, and synergy
Authors: Cleve Jeremy Van , Akçay Erol 
Published: November 2013

AbstractMany organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to non-additive ecological and fitness effects. Social evolution theory has long recognized that all of these factors can lead to different selection pressures but has only recently attempted to synthesize how these factors interact. Using models for both discrete and continuous phenotypes, we show that analyzing these factors in a consistent framework reveals that they interact with one another in ways previously overlooked. Specifically, behavioral responses (reciprocity), genetic relatedness, and synergy interact in non-trivial ways that cannot be easily captured by simple summary indices of assortment. We demonstrate the importance of these interactions by showing how they have been neglected in previous synthetic models of social behavior both within and between species. These interactions also affect the level of behavioral responses that can evolve in the long run; proximate biological mechanisms are evolutionarily stable when they generate enough responsiveness relative to the level of responsiveness that exactly balances the ecological costs and benefits. Given the richness of social behavior across taxa, these interactions should be a boon for empirical research as they are likely crucial for describing the complex relationship linking ecology, demography, and social behavior.