bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges and recommendations to improve installability and archival stability of omics computational tools
Authors: Mangul Serghei , Mosqueiro Thiago , Abdill Richard J. , Duong Dat , Mitchell Keith , Sarwal Varuni , Hill Brian , Brito Jaqueline , Littman Russell Jared , Statz Benjamin , Lam Angela Ka-Mei , Dayama Gargi , Grieneisen Laura , Martin Lana S. , Flint Jonathan , Eskin Eleazar , Blekhman Ran 
Published: October 2018

AbstractDeveloping new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through URLs published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed “easy to install,” and 28% of the tools failed to be installed at all due to problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.
Exploratory analysis of multiple traits co-adaptations in the population history
Authors: Nakamichi Reiichiro , Kitada Shuichi , Kishino Hirohisa 
Published: October 2018

AbstractDuring the history of range expansion, the populations encounter with variety of environments. They respond to the local environments by modifying the mutually interacting traits. Therefore, to understand the whole life history of the populations, it is ideal to capture the history of their range expansion with reference to the series of surrounding environments and to infer the coadaptation of the multiple traits. Toward this end, we provide an exploratory analysis based on the features of populations: site frequency spectra of populations, population-specific FST, association between genes and environments, positive selections on traits mapped on the admixture graph, and GWAS results. Correspondence analysis of genes, environments, and traits provides a bird’s-eye view of the history of population differentiation and range expansion and various types of environmental selections at the times. Principal component analysis of the estimated trait-specific polygenic adaptations mapped on the admixture graph enables to understand the coadaptation of multiple traits. The potential usefulness was confirmed by analyzing a public dataset of wild poplar in northwestern America. In response to the northern cold temperature and longer daylength, the populations increased the photosynthetic activity and nutrient use efficiency at the expense of the risk of pathogen invasion, and in response to warm temperature, they increased the growth. At higher altitude, they shifted the maximum activity to earlier period in spring to reduce the activity in dry summer. The R codes for our representation method and simulations of population colonization used in this study are available as supplementary script.
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
Authors: Sinz Fabian H. , Ecker Alexander S. , Fahey Paul G. , Walker Edgar Y. , Cobos Erick , Froudarakis Emmanouil , Yatsenko Dimitri , Pitkow Xaq , Reimer Jacob , Tolias Andreas S. 
Published: October 2018

AbstractTo better understand the representations in visual cortex, we need to generate better predictions of neural activity in awake animals presented with their ecological input: natural video. Despite recent advances in models for static images, models for predicting responses to natural video are scarce and standard linear-nonlinear models perform poorly. We developed a new deep recurrent network architecture that predicts inferred spiking activity of thousands of mouse V1 neurons simulta-neously recorded with two-photon microscopy, while accounting for confounding factors such as the animal’s gaze position and brain state changes related to running state and pupil dilation. Powerful system identification models provide an opportunity to gain insight into cortical functions through in silico experiments that can subsequently be tested in the brain. However, in many cases this approach requires that the model is able to generalize to stimulus statistics that it was not trained on, such as band-limited noise and other parameterized stimuli. We investigated these domain transfer properties in our model and find that our model trained on natural images is able to correctly predict the orientation tuning of neurons in responses to artificial noise stimuli. Finally, we show that we can fully generalize from movies to noise and maintain high predictive performance on both stimulus domains by fine-tuning only the final layer’s weights on a network otherwise trained on natural movies. The converse, however, is not true.
Dopamine modulation of prefrontal cortex activity is manifold and operates at multiple temporal and spatial scales
Authors: Lohani Sweyta , Martig Adria K. , Deisseroth Karl , Witten Ilana B. , Moghaddam Bita 
Published: October 2018

AbstractWhile the function of dopamine in subcortical structures is largely limited to reward and movement, dopamine neurotransmission in the prefrontal cortex (PFC) is critical to a multitude of temporally and functionally diverse processes such as attention, working memory, behavioral flexibility, action selection, and stress adaptation. How does dopamine influence PFC computation of multiple temporally diverse functions? Here we find causation between sustained and burst patterns of phasic dopamine neuron activation and contemporaneous modulation of PFC neuronal activity at multiple spatio-temporal scales. These include a multidirectional and weak impact on individual PFC neuron rate activity and a robust influence on coordinated ensemble activity, gamma oscillations, and gamma-theta coupling that persisted for minutes. In addition, PFC network responses to burst pattern of dopamine firing were selectively strengthened in behaviorally active states. Thus, dopamine modulation of PFC is spatiotemporally diverse and is dictated by the pattern of dopamine neuron activation and behavioral state. These findings provide insight on the multiplex pattern of modulation by dopamine that may influence PFC computation of temporally diverse functions.
Orbitofrontal neuron ensembles contribute to inhibitory control
Authors: Priyadharsini Balasubramani Pragathi , Hayden Benjamin Y. 
Published: October 2018

SUMMARYStopping, or inhibition, is a form of self-control that is a core part of adaptive behavior. We hypothesize that inhibition commands originate, in part, from the orbitofrontal cortex (OFC). We recorded activity of OFC neurons in macaques performing a stop signal task. Decoding analyses revealed a clear difference in ensemble responses that distinguish successful from failed inhibition that begins after the stop signal and before the stop signal reaction time. We also found a different and unrelated ensemble pattern that distinguishes successful from failed stopping before the beginning of the trial. These signals were distinct from, and orthogonal to, value encoding, which was also observed in these neurons. The timing of the early and late signals was, respectively, consistent with the idea that OFC contributes both proactively and reactively to inhibition. These results support the view, inspired by anatomy, that OFC gathers diverse sensory inputs to compute early-stage executive signals.
Asymmetric dispersal is a critical element of concordance between biophysical dispersal models and spatial genetic structure in Great Barrier Reef corals
Authors: Riginos C , Hock K , Matias AM , Mumby PJ , van Oppen MJH , Lukoschek V. 
Published: October 2018

AbstractAimWidespread coral bleaching, crown-of-thorns seastar outbreaks, and tropical storms all threaten foundational coral species of the Great Barrier Reef, with impacts differing over time and space. Yet, dispersal via larval propagules could aid reef recovery by supplying new settlers and enabling the spread of adaptive variation among regions. Documenting and predicting spatial connections arising from planktonic larval dispersal in marine species, however, remains a formidable challenge.LocationThe Great Barrier Reef, AustraliaMethodsContemporary biophysical larval dispersal models were used to predict longdistance multigenerational connections for two common and foundational coral species (Acropora tenuisandAcropora millepora). Spatially extensive genetic surveys allowed us to infer signatures of asymmetric dispersal for these species and evaluate concordance against expectations from biophysical models using coalescent genetic simulations, directions of inferred gene flow, and spatial eigenvector modelling.ResultsAt long distances, biophysical models predicted a preponderance of north to south connections and genetic results matched these expectations: coalescent genetic simulations rejected an alternative scenario of historical isolation; the strongest signals of inferred gene flow were from north to south; and asymmetric eigenvectors derived from north to south connections in the biophysical models were significantly better predictors of spatial genetic patterns than eigenvectors derived from symmetric null spatial models.Main conclusionsResults are consistent with biophysical dispersal models yielding approximate summaries of past multigenerational gene flow conditioned upon directionality of connections. ForA. tenuisandA. millepora, northern and central reefs have been important sources to downstream southern reefs over the recent evolutionary past and should continue to provide southward gene flow. Endemic genetic diversity of southern reefs suggests substantial local recruitment and lack of long distance gene flow from south to north.
Bayesian learning ecosystem dynamics with delayed dependencies from incomplete multiple source data : an application to plant epidemiology
Authors: Dupas Stéphane 
Published: October 2018

AbstractEcosystem dynamics forecasting is central to major problems in ecology, society, and economy. The existing models serve as decision tools but their parameters valitity are usually not confronted to real data in a formalized approach. Dynamics bayesian network inference is promissing but limited when dealing with incomplete multiple source time series with delayed time dependencies. We propose here a temporal bayesian network with time delay and aproximate inference algorithm, to learn altogether cryptic ecosystem variables, missing data, and model parameters. The novelty in the approach is that it combines simulation-based and likelihood-based aproximate bayesian inference. The advantage of simulation based is that it allows to sample hidden processes. The advantage of likelihood based is that it provides a summary statistics that is really representing the model we are interested in. The ecosystem variables and the missing data are simulated from indicator variables using the probabilistic indicator-ecosystem model. The likelihood is estimated by averaging the probability of observed-simulated data over simulations, the parameter space is sampled with Metropolis Hasting algorithm. Another innovative proposition is to parametrize the network structure in order to learn model structure within a space provided by prior distribution. We apply to plant epidemiology.
A new method for enamel amino acid racemization dating: a closed system approach
Authors: Dickinson Marc R. , Lister Adrian M. , Penkman Kirsty E. H. 
Published: October 2018

AbstractAnalysis of the predictable breakdown of proteins and amino acids in ancient biominerals enables age estimation over the Quaternary. We postulate that enamel is a suitable biomineral for the long-term survival of endogenous amino acids. Analysis of multiple amino acids for geochronological studies is typically achieved using a RP-HPLC method. However, the low concentrations of amino acids coupled with high concentrations of inorganic species make accurate determination of amino concentrations challenging. We have developed a method for the routine preparation of multiple enamel samples using biphasic separation. Furthermore, we have shown that amino acids that exhibit effectively closed system behaviour can be isolated from enamel through an exposure time of 72 h to bleach. Elevated temperature experiments investigating the processes of intra-crystalline protein degradation (IcPD) do not appear to match the patterns from fossil samples, reinforcing the need for a comprehensive understanding of the underlying mechanisms of protein degradation. This novel preparative method isolates intra-crystalline amino acids suitable for the development of mammalian geochronologies based on enamel protein degradation. The lower rates of racemisation in enamel (cf.Bithyniaopercula) suggest that the enamel AAR may be able to be used as a relative dating technique over time scales > 2.8 Ma. Enamel AAR has the potential to estimate the age of mammalian remains past the limit of all other current direct dating methods, providing an invaluable tool for geochronological studies.
Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank
Authors: Tachmazidou Ioanna , Hatzikotoulas Konstantinos , Southam Lorraine , Esparza-Gordillo Jorge , Haberland Valeriia , Zheng Jie , Johnson Toby , Koprulu Mine , Zengini Eleni , Steinberg Julia , Wilkinson Jeremy M , Bhatnagar Sahir , Hoffman Joshua , Buchan Natalie , Süveges Dániel , Consortium arcOGEN , Yerges Armstrong Laura , Davey Smith George , Gaunt Tom R , Scott Robert A , McCarthy Linda C , Zeggini Eleftheria 
Published: October 2018

AbstractOsteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we perform the largest genome-wide association study for osteoarthritis to date (77,052 cases and 378,169 controls), analysing 4 phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discover 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine map to a single variant. We identify putative effector genes by integrating eQTL colocalization, fine-mapping, human rare disease, animal model, and osteoarthritis tissue expression data. We find enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organisation biological pathways. Ten of the likely effector genes, includingTGFB1,FGF18,CTSKandIL11have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.
ETDB-Caltech: a blockchain-based distributed public database for electron tomography
Authors: Ortega Davi R. , Oikonomou Catherine M. , Ding H. Jane , Rees-Lee Prudence , Alexandria  , Jensen Grant J. 
Published: October 2018

AbstractThree-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.
Integrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in temperate areas
Authors: Monteverde Eliana , Gutierrez Lucía , Blanco Pedro , de Vida Fernando Pérez , Rosas Juan E. , Bonnecarrère Victoria , Quero Gastón , McCouch Susan 
Published: October 2018

AbstractUnderstanding the genetic and environmental basis of genotype × environment interaction (G×E) is of fundamental importance in plant breeding. If we consider G×E in the context of genotype × year interactions (G×Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G×E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected several milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in temperate rice growing areas.
Access schedules mediate the impact of high fat diet on ethanol intake and insulin and glucose function in mice
Authors: Coker Caitlin R. , Aguilar Elizabeth A. , Snyder Angela E. , Bingaman Sarah S. , Graziane Nicholas M. , Browning Kirsteen N. , Arnold Amy C. , Silberman Yuval 
Published: October 2018

AbstractAlcoholism and high fat diet (HFD)-induced obesity individually promote insulin resistance and glucose intolerance in clinical populations, increasing risk for metabolic diseases. Conversely, animal studies, typically utilizing forced/continuous alcohol (EtOH) access, tend to show that EtOH intake mitigates HFD-induced effects on insulin and glucose function, while HFD decreases voluntary EtOH intake in continuous access models. However, the impact of HFD on intermittent EtOH intake and resultant changes to metabolic function are not well characterized. The present studies sought to determine if HFD alters EtOH intake in male C57Bl/6J mice given differing two-bottle choice EtOH access schedules, and to assess resultant impact on insulin sensitivity and glucose tolerance. In the first experiment, mice had Unlimited Access EtOH (UAE)+HFD (n=15; HFD=60% calories from fat, 10% EtOH v/v, ad libitum) or UAE+Chow (n=15; control diet=16% calories from fat, ad libitum) for 6 weeks. UAE+HFD mice had lower EtOH preference, consumed significantly less EtOH, and were insulin resistant and hyperglycemic compared with UAE+Chow mice. In the second experiment, mice had Limited Access EtOH (LAE, 4 hrs/d; 3 d/wk)+HFD (n=15) or LAE+Chow (n=15) with increasing EtOH concentrations (10%, 15%, 20%). LAE+HFD mice had no difference in total EtOH consumption compared to LAE+Chow mice, but exhibited hyperglycemia, insulin resistance, and glucose intolerance. In the third experiment, mice had intermittent HFD access (single 24 hr session/week) with limited access to EtOH (iHFD-E, 4hrs/d; 4 d/wk) (n=10). iHFD-E mice displayed binge eating behaviors and consumed significantly more EtOH than mice given ad libitum chow or HFD, suggesting transfer of binge eating to binge drinking behaviors. Although iHFD-E mice did not have significantly altered body composition, they developed insulin insensitivity and glucose intolerance. These results suggest that access schedules determine the impact of HFD on EtOH consumption and resultant metabolic dysfunction.
A Stu2-mediated intrinsic tension-sensing pathway promotes chromosome biorientation in vivo
Authors: Miller Matthew P. , Evans Rena K. , Zelter Alex , Geyer Elisabeth A. , MacCoss Michael J. , Rice Luke M. , Davis Trisha N. , Asbury Charles L. , Biggins Sue 
Published: October 2018

ABSTRACTAccurate segregation of chromosomes to daughter cells is a critical aspect of cell division. It requires the kinetochores on duplicated chromosomes to biorient, attaching to microtubules from opposite poles of the cell. Bioriented attachments come under tension, while incorrect attachments lack tension and must be destabilized. A well-studied error correction pathway is mediated by the Aurora B kinase, which destabilizes low tension-bearing attachments. We recently discovered that in vitro, kinetochores display an additional intrinsic tension-sensing pathway that utilizes Stu2. This pathway’s contribution to error correction in cells, however, was unknown. Here, we identify a Stu2 mutant that abolishes its kinetochore function and show that it causes error correction defects in vivo. We also show that this intrinsic tension-sensing pathway functions in concert with the Aurora B-mediated pathway. Together, our work indicates that cells employ at least two pathways to ensure biorientation and the accuracy of chromosome segregation.
Recent invasion of P transposable element intoDrosophila yakuba
Authors: Serrato-Capuchina Antonio , Zhang Stephania , Martin Wendy , Peede David , Earley Eric , Matute Daniel R. 
Published: October 2018

ABSTRACTTransposable elements (TEs) are self-replicating genetic units that are common across prokaryotes and eukaryotes. They have been implicated in the origin of new molecular functions and in some cases, new phenotypes. Yet, the processes that lead to their evolution and how they enter the genome of their hosts remain largely underexplored. The P-element is one of the most well-known TEs in Eukaryotes, due to its rapid expansion inDrosophila melanogasterin the 1960s and its faster invasion ofD. simulans, despite its fitness consequences in both species. Here, we describe a recent invasion of P-elements intoDrosophila yakuba. Overall, PEs were found inD. yakubawith no PEs detected across its sister species,D. teissieriandD. santomea. These findings are surprising due the lack of a genetic bridge betweenD. yakubaand otherDrosophilathat harbor PEs, implicating a horizontal gene transfer mechanism similar to the one that gave rise to the invasion of PEs inD. melanogasterandD. simulans. We also report that the presence of these PEs causes a mild hybrid dysgenesis phenomenon; namely they cause a reduction in female reproductive potential (lower number of ovaries and ovarioles), but only at 29°C and not at 23°C. Given the ability of PEs to cross species boundaries and the fact that bothD. santomeaandD. teissierihave the ability to produce fertile progeny withD. yakuba, theyakubaspecies complex provides an opportunity to study PE spread through vertical transmission.ARTICLE SUMMARYP-elements (PEs) are transposons found in NeotropicalDrosophilaspecies. PEs have previously invaded two AfricanDrosophilaspecies where they rapidly increased in population frequency and fixed. We found that PEs invaded the genome ofD. yakuba, an African species. In just 8 years, the frequency of the PEs increased from 0% to 18% but then decreased to 2%. This turnover shows that PE invasions can be transient. We found no evidence of full PEsin D. yakuba’ sister species,D. santomeaandD. teissieri. PEs in this species complex can reveal the interplay between transposable elements and hybridization in nature.