bluuebunny/crossref_metadata_2025_split huggingface dataset:
TheC. elegansfemale state: Decoupling the transcriptomic effects of aging and sperm-status
Authors: Angeles-Albores David , Leighton Daniel H. W. , Tsou Tiffany , Khaw Tiffany H. , Antoshechkin Igor , Sternberg Paul W. 
Published: October 2016

AbstractUnderstanding genome and gene function in a whole organism requires us to fully comprehend the life cycle and the physiology of the organism in question. AlthoughC. elegansis traditionally thought of as a hermaphrodite, XX animals exhaust their sperm and become endogenous females after 3days of egg-laying. Themolecular physiology of this state has not been as intensely studied as other parts of the life cycle, despite documented changes in behavior and metabolism that occur at this stage. To study the female state ofC. elegans, we measured the transcriptomes of 1st day adult hermaphrodites; endogenous, 6th day adult females; and at the same time points, mutantfog-2(lf)worms that have a feminized germline phenotype. At these time points, we could separate the effects of biological aging from the transition into the female state.fog-2(lf)mutants partially phenocopy 6 day adult wild-type animals and exhibit fewer differentially expressed genes as they age throughout these 6 days. Therefore,fog-2is epistatic to age as assessed by this transcriptomic phenotype, which indicates that both factors act on sperm status to mediate entry into the female state. These changes are enriched in transcription factors canonically associated with neuronal development and differentiation. Our data provide a high-quality picture of the changes that happen in global gene expression throughout the period of early aging in the worm.
Pooled CRISPR screening with single-cell transcriptome read-out
Authors: Datlinger Paul , Schmidl Christian , Rendeiro André F , Traxler Peter , Klughammer Johanna , Schuster Linda , Bock Christoph 
Published: October 2016

AbstractCRISPR-based genetic screens have revolutionized the search for new gene functions and biological mechanisms. However, widely used pooled screens are limited to simple read-outs of cell proliferation or the production of a selectable marker protein. Arrayed screens allow for more complex molecular read-outs such as transcriptome profiling, but they provide much lower throughput. Here we demonstrate CRISPR genome editing together with single-cell RNA sequencing as a new screening paradigm that combines key advantages of pooled and arrayed screens. This approach allowed us to link guide-RNA expression to the associated transcriptome responses in thousands of single cells using a straightforward and broadly applicable screening workflow.
Predictive representations can link model-based reinforcement learning to model-free mechanisms
Authors: Russek Evan M. , Momennejad Ida , Botvinick Matthew M. , Gershman Samuel J. , Daw Nathaniel D. 
Published: October 2016

AbstractHumans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.Author SummaryAccording to standard models, when confronted with a choice, animals and humans rely on two separate, distinct processes to come to a decision. One process deliberatively evaluates the consequences of each candidate action and is thought to underlie the ability to flexibly come up with novel plans. The other process gradually increases the propensity to perform behaviors that were previously successful and is thought to underlie automatically executed, habitual reflexes. Although computational principles and animal behavior support this dichotomy, at the neural level, there is little evidence supporting a clean segregation. For instance, although dopamine — famously implicated in drug addiction and Parkinson’s disease — currently only has a well-defined role in the automatic process, evidence suggests that it also plays a role in the deliberative process. In this work, we present a computational framework for resolving this mismatch. We show that the types of behaviors associated with either process could result from a common learning mechanism applied to different strategies for how populations of neurons could represent candidate actions. In addition to demonstrating that this account can produce the full range of flexible behavior observed in the empirical literature, we suggest experiments that could detect the various approaches within this framework.
Time dependent genetic analysis links field and controlled environment phenotypes in the model C4grassSetaria
Authors: Feldman Max J. , Paul Rachel E. , Banan Darshi , Barrett Jennifer F. , Sebastian Jose , Yee Muh-Ching , Jiang Hui , Lipka Alexander E. , Brutnell Thomas P. , Dinneny José R. , Leakey Andrew D.B. , Baxter Ivan 
Published: October 2016

AbstractVertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed twelve controlled growth trials of an interspecificSetaria italicaxSetaria viridisrecombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The nondestructive nature of plant height measurements has enabled us to monitor vertical growth throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height inSetaria.In this population, alleles inherited from the weedyS. viridisparent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticatedS. italicaparent collectively act to increase plant height later in development.
The transcriptional repressor HIC1 regulates intestinal immune homeostasis
Authors: Burrows Kyle , Antignano Frann , Bramhall Michael , Chenery Alistair , Scheer Sebastian , Korinek Vladimir , Underhill T. Michael , Zaph Colby 
Published: October 2016

ABSTRACTThe intestine is a unique immune environment that must respond to infectious organisms but remain tolerant to commensal microbes and food antigens. However, the molecular mechanisms that regulate immune cell function in the intestine remain unclear. Here we identify the POK/ZBTB family transcription factor Hypermethylated in cancer 1 (HIC1, ZBTB29) as a central component of immunity and inflammation in the intestine. HIC1 is specifically expressed in immune cells in the intestinal lamina propria (LP) in the steady state and mice with a T cell-specific deletion of HIC1 have reduced numbers of T cells in the LP. HIC1 expression is regulated by the Vitamin A metabolite retinoic acid, as mice raised on a Vitamin A-deficient diet lack HIC1-positive cells in the intestine. HIC1-deficient T cells overproduce IL-17A in vitro and in vivo, and fail to induce intestinal inflammation, identifying a critical role for HIC1 in the regulation of T cell function in the intestinal microenvironment under both homeostatic and inflammatory conditions.
A defensive body plan was pre-adaptive for termitophily in the rove beetle tribe Termitohospitini (Staphylinidae: Aleocharinae)
Authors: Kanao T. , Eldredge K.T. , Maruyama M. 
Published: October 2016

AbstractTermitophily—the symbiosis of organisms with termite societies—has evolved a disproportionate number of times within the rove beetle subfamily Aleocharinae (Staphylinidae). Among aleocharine termitophiles, defensive (limuloid) and mimetic (physogastric & physothoracic) body forms have evolved convergently, but due to lack of a comprehensive aleocharine phylogeny, the context in which termitophily and associated adaptations evolve is unknown. We present the first example of a robust, morphology-based phylogenetic placement of an exclusively termitophilous tribe, the Termitohospitini. Termitohospitini is recovered to be nested within Myllaeninisensu nov, and sister to Myllaena (new synonymy). Furthermore, we also recovered the small tribe Masuriini nested within Myllaeninisensu nov(new status).Reconstructing ecological transitions within this clade, we present evidence that the stem lineage of Myllaenini sensu nov invaded intertidal marine habitats, the common ancestor for Myllaena + Termitohospitini then transitioned to freshwater riparian habitats, with Termitohospitini alone subsequently shifting to termitophily. We conclude that: (1) Termitohospitini was ancestrally a limuloid-bodied riparian inhabitant; (2) a limuloid form may have been pre-adaptive for defense against host attack during the evolution of termitophily; (3) the strongly tapered abdomen of an ancestral limuloid body was a constraint on the evolution of physogastry, leading to the emergence of the unusual physothoracic body form observed in termitohospitines that likely integrates these obligate termitophiles to life inside termite colonies.“one of the most astonishing spectacles in all natural history.” — Richard Dawkins
Cultural transmission and biological markets
Authors: Loverdo Claude , Viciana Hugo 
Published: October 2016

AbstractActive cultural transmission of fitness-enhancing behavior can be seen as a costly strategy, one whose evolutionary stability poses a Darwinian puzzle. In this article, we offer a biological market model of cultural transmission that substitutes or complements existing kin-selection based theories for the evolution of cultural capacities. We explicitly formulate how a biological market can account for the evolution of deference and prestige-related phenomena, as well as how it can affect the dynamics of cumulative culture. We show that, under certain conditions, teaching evolves even when innovations are not sufficiently opaque and can be acquired by emulators via inadvertent transmission. Furthermore, teaching in a biological market is a precondition for enhanced individual learning abilities.
FSTand kinship for arbitrary population structures I: Generalized definitions
Authors: Ochoa Alejandro , Storey John D. 
Published: October 2016

AbstractFSTis a fundamental measure of genetic differentiation and population structure, currently defined for subdivided populations.FSTin practice typically assumesindependent, non-overlapping subpopulations, which all split simultaneously from their last common ancestral population so that genetic drift in each subpopulation is probabilistically independent of the other subpopulations. We introduce a generalizedFSTdefinition for arbitrary population structures, where individuals may be related in arbitrary ways, allowing for arbitrary probabilistic dependence among individuals. Our definitions are built on identity-by-descent (IBD) probabilities that relate individuals through inbreeding and kinship coefficients. We generalizeFSTas the mean inbreeding coefficient of the individuals’ local populations relative to their last common ancestral population. We show that the generalized definition agrees with Wright’s original and the independent subpopulation definitions as special cases. We define a novel coancestry model based on “individual-specific allele frequencies” and prove that its parameters correspond to probabilistic kinship coefficients. Lastly, we extend the Pritchard-Stephens-Donnelly admixture model in the context of our coancestry model and calculate itsFST. To motivate this work, we include a summary of analyses we have carried out in follow-up papers, where our new approach has been applied to simulations and global human data, showcasing the complexity of human population structure, demonstrating our success in estimating kinship andFST, and the shortcomings of existing approaches. The probabilistic framework we introduce here provides a theoretical foundation that extendsFSTin terms of inbreeding and kinship coefficients to arbitrary population structures, paving the way for new estimators and novel analyses.Note: This article is Part I of two-part manuscripts. We refer to these in the text as Part I and Part II, respectively.Part I:Alejandro Ochoa and John D. Storey. “FSTand kinship for arbitrary population structures I: Generalized definitions”.bioRxiv(10.1101/083915) (2019).https://doi.org/10.1101/083915. First published 2016-10-27.Part II:Alejandro Ochoa and John D. Storey. “FSTand kinship for arbitrary population structures II: Method of moments estimators”.bioRxiv(10.1101/083923) (2019).https://doi.org/10.1101/083923. First published 2016-10-27.
The Identification of Source and Vector of a Prolific Marine Invader
Authors: Krueger-Hadfield Stacy A. , Kollars Nicole M. , Strand Allan E. , Byers James E. , Shainker Sarah J. , Terada Ryuta , Greig Thomas W. , Hammann Mareike , Murray David C. , Weinberger Florian , Sotka Erik E. 
Published: October 2016

ABSTRACTThe source and vector of an introduced species inform its ecological and evolutionary history and may guide management that seeks to prevent future introductions. Surprisingly, few studies have successfully used genetic tools to independently inform the specific source and pathway of biological invasions. The ecological history of many introduced species, including their origins and vectors, is often based on suppositions or educated guesses. Here, we used mitochondrial and microsatellite genotyping to trace the invasion of the Asian seaweedGracilaria vermiculophylla(Rhodophyta) along the three coastlines of the Northern Hemisphere to which it has been introduced: the western coast of North America, eastern coast of the United States and the coasts of Europe and northwest Africa. Analyzing 37 native and 53 introduced sites, we identified the Pacific coastline of northeastern Japan as the ultimate source of the Northern Hemisphere invasion. Coincidentally, most exports of the oysterCrassostrea gigashistorically originated from this region and both species often grow in close proximity. Based on genetic signatures, each of the three coastlines likely received thalli directly from Japan, as well as material from another introduced coastline (i.e., a secondary invasion). Our ability to document a source region, which was enabled by a robust sampling of locations and loci that previous studies lacked, reflected strong phylogeographic structure along native coastlines. We suggestGracilaria vermiculophyllais an important representative example of many species likely exported out of Japan by the oyster trade and its genetic signatures that may be a hallmark of oyster introduction legacies.
Transposable element exaptation is the primary source of novelty in the primate gene regulatory landscape
Authors: Trizzino Marco , Park YoSon , Holsbach-Beltrame Marcia , Aracena Katherine , Mika Katelyn , Caliskan Minal , Perry George H. , Lynch Vincent J. , Brown Christopher D. 
Published: October 2016

AbstractGene regulation plays a critical role in the evolution of phenotypic diversity. We investigated the evolution of liver promoters and enhancers in six primate species. We performed ChlP-seq for two histone modifications and RNA-seq to profile cis-regulatory element (CRE) activity and gene expression. The primate regulatory landscape is largely conserved across the lineage. Conserved CRE function is associated with sequence conservation, proximity to coding genes, cell type specificity of CRE function, and transcription factor binding. Newly evolved CREs are enriched in immune response and neurodevelopmental functions, while conserved CREs bind master regulators. Transposable elements (TEs) are the primary source of novelty in primate gene regulation. Newly evolved CREs are enriched in young TEs that affect gene expression. However, only 17% of conserved CREs overlap a TE, suggesting that target gene expression is under strong selection. Finally, we identified specific genomic features driving the functional recruitment of newly inserted TEs.
Mocap: Large-scale inference of transcription factor binding sites from chromatin accessibility
Authors: Chen Xi , Yu Bowen , Carriero Nicholas , Silva Claudio , Bonneau Richard 
Published: October 2016

AbstractDifferential binding of transcription factors (TFs) atcis-regulatory loci drives the differentiation and function of diverse cellular lineages. Understanding the regulatory interactions that underlie cell fate decisions requires characterizing TF binding sites (TFBS) across multiple cell types and conditions. Techniques, e.g. ChIP-Seq can reveal genome-wide patterns of TF binding, but typically requires laborious and costly experiments for each TF-cell-type (TFCT) condition of interest. Chromosomal accessibility assays can connect accessible chromatin in one cell type to many TFs through sequence motif mapping. Such methods, however, rarely take into account that the genomic context preferred by each factor differs from TF to TF, and from cell type to cell type. To address the differences in TF behaviors, we developed Mocap, a method that integrates chromatin accessibility, motif scores, TF footprints, CpG/GC content, evolutionary conservation and other factors in an ensemble of TFCT-specific classifiers. We show that integration of genomic features, such as CpG islands improves TFBS prediction in some TFCT. Further, we describe a method for mapping new TFCT, for which no ChIP-seq data exists, onto our ensemble of classifiers and show that our cross-sample TFBS prediction method outperforms several previously described methods.
A lexicon based approach for classifying Arabic multi-labeled text
Authors: Hmeidi Ismail , Al-Ayyoub Mahmoud , Mahyoub Nizar A. , Shehab Mohammed A. 
Published: October 2016

Purpose
Multi-label Text Classification (MTC) is one of the most recent research trends in data mining and information retrieval domains because of many reasons such as the rapid growth of online data and the increasing tendency of internet users to be more comfortable with assigning multiple labels/tags to describe documents, emails, posts, etc. The dimensionality of labels makes MTC more difficult and challenging compared with traditional single-labeled text classification (TC). Because it is a natural extension of TC, several ways are proposed to benefit from the rich literature of TC through what is called problem transformation (PT) methods. Basically, PT methods transform the multi-label data into a single-label one that is suitable for traditional single-label classification algorithms. Another approach is to design novel classification algorithms customized for MTC. Over the past decade, several works have appeared on both approaches focusing mainly on the English language. This work aims to present an elaborate study of MTC of Arabic articles.

Design/methodology/approach
This paper presents a novel lexicon-based method for MTC, where the keywords that are most associated with each label are extracted from the training data along with a threshold that can later be used to determine whether each test document belongs to a certain label.

Findings
The experiments show that the presented approach outperforms the currently available approaches. Specifically, the results of our experiments show that the best accuracy obtained from existing approaches is only 18 per cent, whereas the accuracy of the presented lexicon-based approach can reach an accuracy level of 31 per cent.

Originality/value
Although there exist some tools that can be customized to address the MTC problem for Arabic text, their accuracies are very low when applied to Arabic articles. This paper presents a novel method for MTC. The experiments show that the presented approach outperforms the currently available approaches.
Learning to rank with click-through features in a reinforcement learning framework
Authors: Keyhanipour Amir Hosein , Moshiri Behzad , Piroozmand Maryam , Oroumchian Farhad , Moeini Ali 
Published: October 2016

Purpose
Learning to rank algorithms inherently faces many challenges. The most important challenges could be listed as high-dimensionality of the training data, the dynamic nature of Web information resources and lack of click-through data. High dimensionality of the training data affects effectiveness and efficiency of learning algorithms. Besides, most of learning to rank benchmark datasets do not include click-through data as a very rich source of information about the search behavior of users while dealing with the ranked lists of search results. To deal with these limitations, this paper aims to introduce a novel learning to rank algorithm by using a set of complex click-through features in a reinforcement learning (RL) model. These features are calculated from the existing click-through information in the data set or even from data sets without any explicit click-through information.

Design/methodology/approach
The proposed ranking algorithm (QRC-Rank) applies RL techniques on a set of calculated click-through features. QRC-Rank is as a two-steps process. In the first step, Transformation phase, a compact benchmark data set is created which contains a set of click-through features. These feature are calculated from the original click-through information available in the data set and constitute a compact representation of click-through information. To find most effective click-through feature, a number of scenarios are investigated. The second phase is Model-Generation, in which a RL model is built to rank the documents. This model is created by applying temporal difference learning methods such as Q-Learning and SARSA.

Findings
The proposed learning to rank method, QRC-rank, is evaluated on WCL2R and LETOR4.0 data sets. Experimental results demonstrate that QRC-Rank outperforms the state-of-the-art learning to rank methods such as SVMRank, RankBoost, ListNet and AdaRank based on the precision and normalized discount cumulative gain evaluation criteria. The use of the click-through features calculated from the training data set is a major contributor to the performance of the system.

Originality/value
In this paper, we have demonstrated the viability of the proposed features that provide a compact representation for the click through data in a learning to rank application. These compact click-through features are calculated from the original features of the learning to rank benchmark data set. In addition, a Markov Decision Process model is proposed for the learning to rank problem using RL, including the sets of states, actions, rewarding strategy and the transition function.