bluuebunny/crossref_metadata_2025_split huggingface dataset:
Features of ChIP-seq data peak calling algorithms with good operating characteristics
Authors: Thomas Reuben , Thomas Sean , Holloway Alisha K , Pollard Katherine S 
Published: January 2016

Author descriptionReuben Thomas is a Staff Research Scientist in the Bioinformatics Core at Gladstone InstitutesSean Thomas is a Staff Research Scientist in the Bioinformatics Core at Gladstone InstitutesAlisha K Holloway is the Director of Bioinformatics at Phylos Biosciences, visiting scientist at Gladstone Institutes and Adjunct Assistant Professor in Biostatistics at the University of California, San Francisco.Katherine S Pollard is a Senior Investigator at Gladstone Institutes and Professor of Biostatistics at University of California, San Francisco.Key PointsPeak-calling using Chip-seq data consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance.Twelve features of the two sub-problems of peak-calling methods are identified.Methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not.Methods that use windows of different sizes to scan the genome for potential peaks are more powerful than ones that do not.Methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test.AbstractChromatin immunoprecipitation followed by sequencing (ChIP-seq) is an important tool for studying gene regulatory proteins, such as transcription factors and histones. Peak calling is one of the first steps in analysis of these data. Peak-calling consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance. We surveyed 30 methods and identified 12 features of the two sub-problems that distinguish methods from each other. We picked six methods (GEM, MACS2, MUSIC, BCP, TM and ZINBA) that span this feature space and used a combination of 300 simulated ChIP-seq data sets, 3 real data sets and mathematical analyses to identify features of methods that allow some to perform better than others. We prove that methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not. Methods that use windows of different sizes are more powerful than ones that do not. For statistical testing of candidate peaks, methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test. BCP and MACS2 have the best operating characteristics on simulated transcription factor binding data. GEM has the highest fraction of the top 500 peaks containing the binding motif of the immunoprecipitated factor, with 50% of its peaks within 10 base pairs (bp) of a motif. BCP and MUSIC perform best on histone data. These findings provide guidance and rationale for selecting the best peak caller for a given application.
Transcription factor loads tend to decrease the robustness of stable gene transcription networks
Authors: Mou Shaoshuai , Del Vecchio Domitilla 
Published: January 2016

AbstractRobustness of a system’s behavior to changes in parameter values is a remarkable property of natural systems and especially desirable when designing de novo synthetic gene circuits. Loads on transcription factors resulting from binding to target promoters have been shown to significantly affect the effective time constants of gene transcription networks and to thus alter the overall system’s behavior. Here, we employ models that explicitly account for load effects to investigate how these impact the robustness of a stable gene transcription network to parameter perturbations. By employing a combination of sampling-based methods and analytical tools from control theory, we demonstrate that the presence of loading shrinks the region of parameter space where a gene circuit performs the desired function. A number of multi-module synthetic gene circuits are analyzed to demonstrate this point, including an event detector and a molecular signature classifier. These results indicate that for designing genetic circuits that are robust to parameter uncertainty it is highly desirable to find ways to mitigate the effects of transcription factor loading.Author SummaryEfforts to understand how loads affect gene transcription networks have been underway in the past decade. Here we perform a numerical investigation on three synthetic gene circuits to show that loads tend to decrease the robustness of stable gene transcriptional networks. We complement the numerical findings with analytical derivations that employ the stability radius to compare the robustness of different networks to parameter perturbations near an equilibrium point. Consistent with the numerical finding, the analytical results support that systems with substantial transcription factor loading have smaller stability radius (less robustness) than systems without loading.
Stress affects the epigenetic marks added by natural transposable element insertions inDrosophila melanogaster
Authors: Guio Lain , Vieira Cristina , González Josefa 
Published: January 2016

ABSTRACTTransposable elements are emerging as an important source of cis-acting regulatory sequences and epigenetic marks that could influence gene expression. However, few studies have dissected the role of specific transposable element insertions on epigenetic gene regulation.Bari-Jhehis a natural transposon that mediates resistance to oxidative stress by adding cis-regulatory sequences that affect expression of nearby genes. In this work, we integrated publicly available data with chromatin immunoprecipitation experiments to get a more comprehensive picture ofBari-Jhehmolecular effects. We showed thatBari-Jhehwas enriched for H3K9me3 in nonstress conditions, and for H3K9me3, H3K4me3 and H3K27me3 in oxidative stress conditions, which is consistent with expression changes in adjacent genes. We further showed that under oxidative stress conditions, H3K4me3 and H3K9me3 spread to the promoter region ofJheh1gene. Finally, another insertion of theBari1family was associated with increased H3K27me3 in oxidative stress conditions suggesting thatBari1histone marks are copy-specific. We concluded that besides adding cis-regulatory sequences,Bari-Jhehinfluences gene expression by affecting the local chromatin state.
Search calls long duration puts the bat on the tympanate moth's radar. A new perspective on how Noctuoidea's auditory cells drive evasive manoeuvres
Authors: Thevenon Herve , Pfuhl Gerit 
Published: January 2016

ABSTRACTThe auditory stimulation method used in experiments on moth A cell(s) is generally believed to be adequate to characterise the encoding of echolocation signals. The stimulation method hosts, though, several bias. Their compounded effects can explain a range of discrepancies between the reported electrophysiological recordings and significantly alter the current interpretation. To test the hypothesis that the bias may significantly alter our current understanding of the moth’s auditory transducer characteristics, papers using the same auditory stimulation method and reporting on either spiking threshold or spiking activity of the moth’s A cells were analysed. The consistency of the reported data was assessed. A range of corrections issued from best practices and theoretical background were applied to the data in an attempt to re-interpret the data. We found that it is not possible to apply a posteriori corrections to all data and bias. However the corrected data indicates that the A cell’s spiking may be (i) independent of the repetition rate, (ii) maximum when detecting the long and low intensity pulses of the bat in searching mode, and (iii) steadily reduce as the bat closes on the moth. These observations raise the possibility that a fixed action pattern drives the moths’s erratic evasive manoeuvres until the final moment. In depth investigation of the potential bias also suggest that the auditory transducer’s response may be constant for a larger frequency range than thought so far, and provide clues to explain the negative taxis in response to the searching bats’s calls detection.
Reference-free deconvolution of DNA methylation data and mediation by cell composition effects
Authors: Houseman E. Andres , Kile Molly L. , Christiani David C. , Ince Tan A. , Kelsey Karl T. , Marsit Carmen J. 
Published: January 2016

AbstractWe propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying methylomes, the number of these constituent cell types, as well as a method for evaluating the extent to which the underlying methylomes reflect specific types of cells. We have demonstrated these methods in an analysis of 23 Infinium data sets from 13 distinct data collection efforts; these empirical evaluations show that our algorithm can reasonably estimate the number of constituent types, return cell proportion estimates that demonstrate anticipated associations with underlying phenotypic data; and methylomes that reflect the underlying biology of constituent cell types. Thus the methodology permits an explicit quantitation of the mediation of phenotypic associations with DNA methylation by cell composition effects. Although more work is needed to investigate functional information related to estimated methylomes, our proposed method provides a novel and useful foundation for conducting DNA methylation studies on heterogeneous tissues lacking reference data.
A method for identifying genetic heterogeneity within phenotypically-defined disease subgroups
Authors: Liley James , Todd John A , Wallace Chris 
Published: January 2016

AbstractMany common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in the two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximising power in comparison to a standard variant by variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post-hoc identification of the contributing genetic variants.We demonstrate the method on a range of simulated and test datasets where expected results are already known. We investigate subgroups of type 1 diabetes (T1D) cases defined by autoantibody positivity, establishing evidence for differential genetic architecture with thyroid peroxidase antibody positivity, driven generally by variants in known T1D associated regions.
Incorporating and compensating cerebrospinal fluid in surface-based forward models of magneto– and electroencephalography
Authors: Stenroos Matti , Nummenmaa Aapo 
Published: January 2016

AbstractMEG/EEG source imaging is usually done using a three-shell (3-S) or a simpler head model. Such models omit cerebrospinal fluid (CSF) that strongly affects the volume currents. We present a four-compartment (4-C) boundary-element (BEM) model that incorporates the CSF and is computationally efficient and straightforward to build using freely available software. We propose a way for compensating the omission of CSF by decreasing the skull conductivity of the 3-S model, and study the robustness of the 4-C and 3-S models to errors in skull conductivity.We generated dense boundary meshes using MRI datasets and automated SimNIBS pipeline. Then, we built a dense 4-C reference model using Galerkin BEM, and 4-C and 3-S test models using coarser meshes and both Galerkin and collocation BEMs. We compared field topographies of cortical sources, applying various skull conductivities and fitting conductivities that minimized the relative error in 4-C and 3-S models. When the CSF was left out from the EEG model, our compensated, unbiased approach improved the accuracy of the 3-S model considerably compared to the conventional approach, where CSF is neglected without any compensation (mean relative error < 20% vs. > 40%). The error due to the omission of CSF was of the same order in MEG and compensated EEG. EEG has, however, large overall error due to uncertain skull conductivity.Our results show that a realistic 4-C MEG/EEG model can be implemented using standard tools and basic BEM, without excessive workload or computational burden. If the CSF is omitted, compensated skull conductivity should be used in EEG.
A comparison of ancestral state reconstruction methods for quantitative characters
Authors: Royer-Carenzi Manuela , Didier Gilles 
Published: January 2016

AbstractChoosing an ancestral state reconstruction method among the alternatives available for quantitative characters may be puzzling. We present here a comparison of five of them, namely the maximum likelihood, restricted maximum likelihood, generalized least squares, phylogenetic independent contrasts and squared parsimony methods.A review of the relations between these methods shows that the first three ones infer the same ancestral states and can only be distinguished by the distributions accounting for the reconstruction uncertainty which they provide.The respective accuracy of the methods is assessed over character evolution simulated under a Brownian motion with (and without) drift. We start by giving the general form of ancestral state distributions conditioned on leaf states under the simulation model.Ancestral distributions are used first, to give a theoretical lower bound of the expected reconstruction error, and second, to develop an original evaluation scheme which is more efficient than comparing the reconstructed and the simulated states.Our simulations show that: (i) the methods do not perform well as the evolution drift increases; (ii) the maximum likelihood method is generally the most accurate and (iii) not all the distributions of the reconstruction uncertainty provided by the methods are equally relevant.
Identification and Functional Characterization of Muscle Satellite Cells in Drosophila
Authors: Chaturvedi Dhananjay , Reichert Heinrich , Gunage Rajesh , VijayRaghavan K. 
Published: January 2016

AbstractWork on genetic model systems such as Drosophila and mouse has shown that the fundamental mechanisms of myogenesis are remarkably similar in vertebrates and invertebrates. Strikingly however, satellite cells, the adult muscle stem cells that are essential for the regeneration of damaged muscles in vertebrates, have not been reported in invertebrates. In this study we show that lineal descendants of muscle stem cells are present in adult muscle of Drosophila as small, unfused cells located superficially and in close proximity to the mature muscle fibers. Normally quiescent, following muscle fiber injury, we show that these cells express Zfh1- cells and engage in Notch-Delta dependent proliferative activity and generate lineal descendant populations, which fuse with the injured muscle fiber. In view of strikingly similar morphological and functional features, we consider these novel cells to be the Drosophila equivalent of vertebrate muscle satellite cells.
Using Genome Wide Estimates of Heritability to Examine the Relevance of Gene-Environment Interplay
Authors: Domingue Ben , Boardmani Jason 
Published: January 2016

AbstractWe use genome-wide data from the third generation respondents of the Framing-ham Heart Study to estimate heritability in body mass index using different quantities of the measured genotype. Heritability decreases rapidly when SNPs implicated by a genome-wide association study are removed but shows essentially no decline when SNPs implicated by a gene-environment interaction in a second genome-wide analysis are removed. This second result is highlighted by our additional finding that the SNPs which explain heritability amongst a subsample defined by higher educational attainment explain no heritability of the heritability in the lower education group, and vice-versa. Finally, we do find consistent heritability estimates when we compare family-based estimates versus those based on measured genotype.
“Validating silicon polytrodes with paired juxtacellular recordings: method and dataset”
Authors: Neto Joana P. , Lopes Gonçalo , Frazão João , Nogueira Joana , Lacerda Pedro , Baião Pedro , Aarts Arno , Andrei Alexandru , Musa Silke , Fortunato Elvira , Barquinha Pedro , Kampff Adam R. 
Published: January 2016

AbstractCross-validating new methods for recording neural activity is necessary to accurately interpret and compare the signals they measure. Here we describe a procedure for precisely aligning two probes forin vivo“paired-recordings” such that the spiking activity of a single neuron is monitored with both a dense extracellular silicon polytrode and a juxtacellular micro-pipette. Our new method allows for efficient, reliable, and automated guidance of both probes to the same neural structure with micron resolution. We also describe a new dataset of paired-recordings, which is available online. We propose that our novel targeting system, and ever expanding cross-validation dataset, will be vital to the development of new algorithms for automatically detecting/sorting single-units, characterizing new electrode materials/designs, and resolving nagging questions regarding the origin and nature of extracellular neural signals.
Evolutionary inference across eukaryotes identifies multiple pressures favoring mitochondrial gene retention
Authors: Johnston Iain G. , Williams Ben P. 
Published: January 2016

AbstractSince their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modelling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mitochondrial DNA (mtDNA) gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present day species.
On Post-Acquisition Motion Compensation for Prostate Perfusion Analysis
Authors: Wollny Gert , Casanova Isabel , Ledesma-Carbayo María-J. , Santos Andrés 
Published: January 2016

AbstractDynamic Contrast enhance magnetic resonance imaging has been established as an accurate method to detect and localize prostate cancer. Time series of three-dimensional datasets of the prostate are acquired and used to obtain per-voxel signal-intensity vs. time curves. These are then used to differentiate cancerous from non-cancerous tissue. However, rectal peristalsis and patient movement may result in spatial-mismatching of the serial datasets and therefore, incorrect enhancement curves. In this work, we discuss and test four methods based on image registration to compensate for these movements. These methods include a serial approach that uses the registration of consecutive images and the accumulation of the obtained transformations, an all-to one registration approach, an approach that first aligns a sub-set of images that are already closely aligned, and then uses synthetic references to register the remaining images, and an approach that usesindependent component analysis(ICA) to create synthetic references and register the images to these. We conclude that the method based on ICA does not provide a viable approach for motion compensation in prostate perfusion imaging, and that the serial approach fails when motion artifacts are present in the series. The other two approaches provide qualitatively pleasing results.
Dichotomy of cellular inhibition by small-molecule inhibitors revealed by single-cell analysis
Authors: Vogel Robert , Erez Amir , Altan-Bonnet Grégoire 
Published: January 2016

AbstractDespite progress in developing small molecule inhibitors, a quantitative understanding of drug action in the physiological context of cells is lacking. Here, we apply single-cell analysis of signal transduction and proliferation to probe cellular responses to small molecule inhibitors. We use the model of cellular activation of T lymphocytes responding to cytokines and antigens. We uncover two distinct modes of drug action, in terms of signaling inhibition: digital inhibition (e.g. when the fraction of activated cells diminishes upon drug treatment, but cells remaining active appear unperturbed), and analog inhibition (e.g. when the fraction of activated cells is unperturbed while their overall activation is diminished). We introduce a computational model of the signaling cascade in order to account for such dichotomy. We test the predictions of our model in terms of the phenotypic variability of cellular responses under drug inhibition. Finally, we demonstrate that the digital/analog dichotomy of cellular response as revealed on short timescales with signal transduction, translates into similar dichotomy on long timescales. Overall, our analysis of drug action at the single cell level illustrates the strength of quantitative approaches to translate the promise ofin vitropharmacology into functionally-relevant cellular settings.
Sex-dependent and sex-independent brain resting-state functional connectivity in children with autism spectrum disorder
Authors: Di Xin , Biswal Bharat B. 
Published: January 2016

AbstractBackgroundMales are more likely to suffer from autism spectrum disorder (ASD) than females. As to whether females with ASD have similar brain alterations remain an open question. The current study aimed to examine sex-dependent as well as sex-independent alterations in resting-state functional connectivity in individuals with ASD compared with typically developing (TD) individuals.MethodResting-state functional MRI data were acquired from the Autism Brain Imaging Data Exchange (ABIDE). Subjects between 6 to 20 years of age were included for analysis. After matching the intelligence quotient between groups for each dataset, and removing subjects due to excessive head motion, the resulting effective sample contained 28 females with ASD, 49 TD females, 129 males with ASD, and 141 TD males, with a two (diagnosis) by two (sex) design. Functional connectivity among 153 regions of interest (ROIs) comprising the whole brain was computed. Two by two analysis of variance was used to identify connectivity that showed diagnosis by sex interaction or main effects of diagnosis.ResultsThe main effects of diagnosis were found mainly between visual cortex and other brain regions, indicating sex-independent connectivity alterations. We also observed two connections whose connectivity showed diagnosis by sex interaction between the precuneus and medial cerebellum as well as the precunes and dorsal frontal cortex. While males with ASD showed higher connectivity in these connections compared with TD males, females with ASD had lower connectivity than their counterparts.ConclusionsBoth sex-dependent and sex-independent functional connectivity alterations are present in ASD.