bluuebunny/crossref_metadata_2025_split huggingface dataset:
Complex population structure of the Atlantic puffin revealed by whole genome analyses
Authors: Kersten Oliver , Star Bastiaan , Leigh Deborah M. , Anker-Nilssen Tycho , Strøm Hallvard , Danielsen Jóhannis , Descamps Sébastien , Erikstad Kjell E. , Fitzsimmons Michelle G. , Fort Jérôme , Hansen Erpur S. , Harris Mike P. , Irestedt Martin , Kleven Oddmund , Mallory Mark L. , Jakobsen Kjetill S. , Boessenkool Sanne 
Published: November 2020

AbstractThe factors underlying gene flow and genomic population structure in vagile seabirds are notoriously difficult to understand due to their complex ecology with diverse dispersal barriers and extensive periods at sea. Yet, such understanding is vital for conservation management of seabirds that are globally declining at alarming rates. Here, we elucidate the population structure of the Atlantic puffin (Fratercula arctica) by assembling its reference genome and analyzing genome-wide resequencing data of 72 individuals from 12 colonies. We identify four large, genetically distinct clusters, observe isolation-by-distance between colonies within these clusters, and obtain evidence for a secondary contact zone. These observations disagree with the current taxonomy, and show that a complex set of contemporary biotic factors impede gene flow over different spatial scales. Our results highlight the power of whole genome data to reveal unexpected population structure in vagile marine seabirds and its value for seabird taxonomy, evolution and conservation.
Expectancy-based rhythmic entrainment as continuous Bayesian inference
Authors: Cannon Jonathan 
Published: November 2020

AbstractWhen presented with complex rhythmic auditory stimuli, humans are able to track underlying temporal structure (e.g., a “beat”), both covertly and with their movements. This capacity goes far beyond that of a simple entrained oscillator, drawing on contextual and enculturated timing expectations and adjusting rapidly to perturbations in event timing, phase, and tempo. Previous modeling work has described how entrainment to rhythms may be shaped by event timing expectations, but sheds little light on any underlying computational principles that could unify the phenomenon of expectation-based entrainment with other brain processes. Inspired by the predictive processing framework, we propose that the problem of rhythm tracking is naturally characterized as a problem of continuously estimating an underlying phase and tempo based on precise event times and their correspondence to timing expectations. We present two inference problems formalizing this insight: PIPPET (Phase Inference from Point Process Event Timing) and PATIPPET (Phase and Tempo Inference). Variational solutions to these inference problems resemble previous “Dynamic Attending” models of perceptual entrainment, but introduce new terms representing the dynamics of uncertainty and the influence of expectations in the absence of sensory events. These terms allow us to model multiple characteristics of covert and motor human rhythm tracking not addressed by other models, including sensitivity of error corrections to inter-event interval and perceived tempo changes induced by event omissions. We show that positing these novel influences in human entrainment yields a range of testable behavioral predictions. Guided by recent neurophysiological observations, we attempt to align the phase inference framework with a specific brain implementation. We also explore the potential of this normative framework to guide the interpretation of experimental data and serve as building blocks for even richer predictive processing and active inference models of timing.
Identifying latent behavioral states in animal movement with M4, a non-parametric Bayesian method
Authors: Cullen Joshua A , Poli Caroline L , Fletcher Robert J , Valle Denis 
Published: November 2020

AbstractUnderstanding animal movement often relies upon telemetry and biologging devices. These data are frequently used to estimate latent behavioral states to help understand why animals move across the landscape. While there are a variety of methods that make behavioral inferences from biotelemetry data, some features of these methods (e.g., analysis of a single data stream, use of parametric distributions) may limit their generality to reliably discriminate among behavioral states.To address some of the limitations of existing behavioral state estimation models, we introduce a non-parametric Bayesian framework called the mixed-membership method for movement (M4), which is available within the open-sourcebayesmoveR package. This framework can analyze multiple data streams (e.g., step length, turning angle, acceleration) without relying on parametric distributions, which may capture complex behaviors more successfully than current methods. We tested our Bayesian framework using simulated trajectories and compared model performance against two segmentation methods (behavioral change point analysis (BCPA) and segclust2d), one machine learning method (expectation-maximization binary clustering (EMbC)), and one type of state-space model (hidden Markov model (HMM)). We also illustrated this Bayesian framework using movements of juvenile snail kites (Rostrhamus sociabilis) in Florida, USA.The Bayesian framework estimated breakpoints more accurately than the other segmentation methods for tracks of different lengths. Likewise, the Bayesian framework provided more accurate estimates of behavior than the other state estimation methods when simulations were generated from less frequently considered distributions (e.g., truncated normal, beta, uniform). Three behavioral states were estimated from snail kite movements, which were labeled as ‘encamped’, ‘area-restricted search’, and ‘transit’. Changes in these behaviors over time were associated with known dispersal events from the nest site, as well as movements to and from possible breeding locations.Our non-parametric Bayesian framework estimated behavioral states with comparable or superior accuracy compared to the other methods when step lengths and turning angles of simulations were generated from less frequently considered distributions. Since the most appropriate parametric distributions may not be obviousa priori, methods (such as M4) that are agnostic to the underlying distributions can provide powerful alternatives to address questions in movement ecology.
Epigenetic dynamics of centromeres and neocentromeres inCryptococcus deuterogattii
Authors: Schotanus Klaas , Yadav Vikas , Heitman Joseph 
Published: November 2020

AbstractDeletion of native centromeres in the human fungal pathogenCryptococcus deuterogattiileads to neocentromere formation. Native centromeres span truncated transposable elements, while neocentromeres do not and instead span actively expressed genes. To explore the epigenetic organization of neocentromeres, we analyzed the distribution of the heterochromatic histone modification H3K9me2, 5mC DNA methylation and the euchromatin mark H3K4me2. Native centromeres are enriched for both H3K9me2 and 5mC DNA methylation marks and are devoid of H3K4me2, while neocentromeres do not exhibit any of these features. Neocentromeres incen10Δ mutants are unstable and chromosome-chromosome fusions occur. After chromosome fusion, the neocentromere is inactivated and the native centromere of the chromosome fusion partner remains as the sole, active centromere. In the present study, the active centromere of a fused chromosome was deleted to investigate if epigenetic memory promoted the re-activation of the inactive neocentromere. Our results show that the inactive neocentromere is not re-activated and instead a novel neocentromere forms directly adjacent to the deleted centromere of the fused chromosome. To study the impact of transcription on centromere stability, the actively expressedURA5gene was introduced into the CENP-A bound regions of a native centromere. The introduction of theURA5gene led to a loss of CENP-A from the native centromere, and a neocentromere formed adjacent to the native centromere location. Remarkably, the inactive, native centromere remained enriched for heterochromatin, yet the integrated gene was expressed and devoid of H3K9me2. A cumulative analysis of multiple CENP-A distribution profiles revealed centromere drift inC. deuterogattii, a previously unreported phenomenon in fungi. The CENP-A-binding shifted within the ORF-free regions and showed a possible association with a truncated transposable element. Taken together, our findings reveal that neocentromeres inC. deuterogattiiare highly unstable and are not marked with an epigenetic memory, distinguishing them from native centromeres.
Modeling CRISPR gene drives for suppression of invasive rodents
Authors: Champer Samuel E. , Oakes Nathan , Sharma Ronin , García-Díaz Pablo , Champer Jackson , Messer Philipp W. 
Published: November 2020

ABSTRACTInvasive rodent populations pose a threat to biodiversity across the globe. When confronted with these new invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse. Such systems might be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit and allows for overlapping generations and a fluctuating population size. Our model includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, but only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning for identifying the key parameters and processes that determine the population dynamics of a complex evolutionary system.
MicroRNA-511-3p mediated modulation of the peroxisome proliferator-activated receptor gamma (PPARγ) controls LPS-induced inflammatory responses in human monocyte derived DCs
Authors: Awuah Dennis , Ruisinger Alisa , Alobaid Meshal , Mbadugha Chidimma , Ghaemmaghami Amir M. 
Published: November 2020

AbstractThe peroxisome proliferator activated receptor gamma (PPARγ) is a ligand activated transcription factor expressed in dendritic cells (DCs), where it exerts anti-inflammatory responses against TLR4-induced inflammation. Recently, microRNA-511 (miR-511) has also emerged as a key player in controlling TLR4-mediated signalling, and in regulating the function of DCs. Interestingly, PPARγ has been previously highlighted as a putative target of miR-511 activity; however the link between miR-511 and PPARγ and its influence on human DC function within the context of LPS-induced inflammatory responses is unknown. Using a selection of miR-511-3p-specific inhibitors and mimics, we demonstrate for the first time that up or downregulation of miR-511-3p inversely correlates with PPARγ mRNA levels and transcriptional activity following treatment with PPARγ synthetic agonist rosiglitazone (RSG), in the presence or absence of LPS. Additionally, we show that PPARγ activation with RSG modulates LPS-induced DC activation and downregulates pro-inflammatory cytokine production following downregulation of miR-511-3p. Lastly, PPARγ activation was shown to suppress LPS-mediated induction of indoleamine 2,3-dioxygenase (IDO) activity in DCs, most likely due to changes in miR-511-3p expression. These data suggest that PPARγ-induced modulation of DC phenotype and function is influenced by miR-511-3p expression, which may serve as a potential therapeutic target against inflammatory diseases.
Auditory Stimulus-response Modeling with a Match-Mismatch Task
Authors: de Cheveigné Alain , Slaney Malcolm , Fuglsang Søren A. , Hjortkjaer Jens 
Published: November 2020

AbstractAn auditory stimulus can be related to the brain response that it evokes by a stimulus-response model fit to the data. This offers insight into perceptual processes within the brain and is also of potential use for devices such as Brain Computer Interfaces (BCI). The quality of the model can be quantified by measuring the fit with a regression problem, or by applying it to a classification task and measuring its performance. Here we focus on a match-mismatch (MM) task that entails deciding whether a segment of brain signal matches, via a model, the auditory stimulus that evoked it. The MM task allows stimulus-response models to be evaluated in the limit of very high model accuracy, making it an attractive alternative to the more commonly used task of auditory attention detection (AAD). The MM task does not require class labels, so it is immune to mislabeling, and it is applicable to data recorded in listening scenarios with only one sound source, thus it is cheap to obtain large quantities of training and testing data. Performance metrics from this task, associated with regression accuracy, provide complementary insights into the relation between stimulus and response, as well as information about discriminatory power directly applicable to BCI applications. Using these metrics, we describe a range of models of increasing complexity that we compare to methods in the literature, showing state-of-the-art performance. We document in detail one particular implementation, calibrated on a publicly-available database, that can serve as a robust reference to evaluate future developments.
Human visual motion perception shows hallmarks of Bayesian structural inference
Authors: Yang Sichao , Bill Johannes , Drugowitsch Jan , Gershman Samuel J. 
Published: November 2020

AbstractMotion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about the computations underlying the identification of visual motion structure by humans. We addressed this gap in two psychophysics experiments and found that participants identified hierarchically organized motion relations in close correspondence with Bayesian structural inference. We demonstrate that, for our tasks, a choice model based on the Bayesian ideal observer can accurately match many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specific differences, and subjective decision confidence, particularly when motion scenes are ambiguous. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception.
A longitudinal analysis of puberty-related cortical development
Authors: Vijayakumar Nandita , Youssef George , Allen Nicholas B , Anderson Vicki , Efron Daryl , Hazell Philip , Mundy Lisa , Nicholson Jan M , Patton George , Seal Marc L , Simmons Julian G , Whittle Sarah , Silk Tim 
Published: November 2020

AbstractThe brain undergoes extensive structural changes during adolescence, concurrent to puberty-related physical and hormonal changes. While animal research suggests these biological processes are related to one another, our knowledge of brain development in humans is largely based on age-related processes. Thus, the current study characterized puberty-related changes in human brain structure, by combining data from two longitudinal neuroimaging cohorts. Beyond normative changes in cortical thickness, we examined whether individual differences in the rate of pubertal maturation (or “pubertal tempo”) was associated with variations in cortical trajectories. Participants (N = 192; scans = 366) completed up to three waves of MRI assessments between 8.5 and 14.5 years of age, as well as questionnaire assessments of pubertal stage at each wave. Generalized additive mixture models were used to characterize trajectories of cortical development. Results revealed widespread linear puberty-related changes across much of the cortex. Many of these changes, particularly within the frontal and parietal cortices, were independent of age-related development. Males exhibiting faster pubertal tempo demonstrated greater thinning in the precuneus and frontal cortices than same-aged and -sex peers. Findings suggest that the unique influence of puberty on cortical development may be more extensive than previously identified, and also emphasize important individual differences in the coupling of these developmental processes.
Utility of polygenic embryo screening for disease depends on the selection strategy
Authors: Lencz Todd , Backenroth Daniel , Granot-Hershkovitz Einat , Green Adam , Gettler Kyle , Cho Judy H. , Weissbrod Omer , Zuk Or , Carmi Shai 
Published: November 2020

AbstractPolygenic risk scores (PRSs) have been offered since 2019 to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. Here we predict, based on the liability threshold model, the expected reduction in complex disease risk following polygenic embryo screening for a single disease. Our main finding is that a strong determinant of the potential utility of such screening is the selection strategy, a factor that has not been previously studied. Specifically, when only embryos with a very high PRS are excluded, the achieved risk reduction is minimal. In contrast, selecting the embryo with the lowest PRS can lead to substantial relative risk reductions, given a sufficient number of viable embryos. For example, a relative risk reduction of ≈50% for schizophrenia can be achieved by selecting the embryo with the lowest PRS out of five viable embryos. We systematically examine the impact of several factors on the utility of screening, including the variance explained by the PRS, the number of embryos, the disease prevalence, the parental PRSs, and the parental disease status. When quantifying the utility, we consider both relative and absolute risk reductions, as well as population-averaged and per-couple risk reductions. We also examine the risk of pleiotropic effects. Finally, we confirm our theoretical predictions by simulating “virtual” couples and offspring based on real genomes from schizophrenia and Crohn’s disease case-control studies. We discuss the assumptions and limitations of our model, as well as the potential emerging ethical concerns.
Cortical feedback and gating in odor discrimination and generalization
Authors: Tavoni Gaia , Chen Kersen David E. , Balasubramanian Vijay 
Published: November 2020

AbstractA central question in neuroscience is how context changes perception of sensory stimuli. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.
emiRIT: A text-mining based resource for microRNA information
Authors: Roychowdhury Debarati , Gupta Samir , Qin Xihan , Arighi Cecilia N. , Vijay-Shanker K. 
Published: November 2020

AbstractMotivationmicroRNAs (miRNAs) are essential gene regulators and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications, and developing new hypotheses built on previous knowledge. Here, we present emiRIT, a text mining-based resource, which presents miRNA information mined from the literature through a user-friendly interface.ResultsWe collected 149,233 miRNA-PubMed ID pairs from Medline between January 1997 to May 2020. emiRIT currently containsmiRNA-generegulation (60,491 relations);miRNA-disease (cancer)(12,300 relations);miRNA-biological process and pathways(23,390 relations); and circulatorymiRNAs in extracellular locations(3,782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively.ConclusionWe provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large-scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, in the absence of gold standards, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of diseases. Database URL:https://research.bioinformatics.udel.edu/emirit/
Developing a broadly applicablepyrF-based genetic manipulation system inAcinetobacter baumannii
Authors: Xu Run , Gao Can , Wu Shuqi , Su Mengjiao , Sun Chengfu , Jia Xu , Wang Rui 
Published: November 2020

AbstractAcinetobacter baumanniiis an emergency pathogenic bacterium for its multidrug-resistance and high mortality rates after infection. In-depth genetic analysis ofA. baumanniivirulence and drug-resistant genes is highly desirable. Existing methods for genetic manipulation ofA. baumanniimainly rely on the use of antibiotic as the selectable marker, and thesacB/sucrose as the counter-selectable marker, which is inconvenient and inappropriate for all research ofA. baumannii. Based on the highly conservedpyrFgene and its conserved 500bp-flanking sequence, we quickly and easily generated thepyrF-deleted mutants as the uracil auxotrophic host strain in three model strains and 11 clinical strains. ThepyrF-carried vectors constructed for gene editing with pyrF/5-FOA as the counter-selection were conveniently and time-saving in thesepyrF-deleted mutants. Utilizing thepyrF-based genetic manipulation system, we easily and efficiently modified thecasgene and CRISPR sequence of I-F CRISPR-Cas system inA. baumanniiAYE, and detected the CRISPR interference and adaptation in these mutants. In summary, thepyrF-based genetic manipulation system could be broadly applicable used for efficiently maker-less gene editing in mostA. baumanniistrains.