bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ketamine’s pharmacogenomic network in human brain contains sub-networks associated with glutamate neurotransmission and with neuroplasticity
Authors: Higgins Gerald A. , Handelman Samuel A. , Allyn-Feuer Ari , Ade Alex S. , Burns James S. , Omenn Gilbert S. , Athey Brian D. 
Published: April 2020

AbstractThe pharmacogenomic network responsible for the rapid antidepressant action of ketamine and concomitant adverse events in patients has been poorly defined. Integrative, multi-scale biological data analytics helps explain ketamine’s action. Using a validated computational pipeline, candidate ketamine-response genes and regulatory RNAs from published literature, binding affinity studies, and single nucleotide polymorphisms (SNPs) from genomewide association studies (GWAS), we identified 108 SNPs associated with 110 genes and regulatory RNAs. All of these SNPs are classified as enhancers, and additional chromatin interaction mapping in human neural cell lines and tissue shows enhancer-promoter interactions involving other network members. Pathway analysis and gene set optimization identified three composite sub-networks within the broader ketamine pharmacogenomic network. Expression patterns of ketamine network genes within the postmortem human brain are concordant with ketamine neurocircuitry based on the results of 24 published functional neuroimaging studies. The ketamine pharmacogenomic network is enriched in forebrain regions known to be rapidly activated by ketamine, including cingulate cortex and frontal cortex, and is significantly regulated by ketamine (p=6.26E-33; Fisher’s exact test). The ketamine pharmacogenomic network can be partitioned into distinct enhancer sub-networks associated with: (1) glutamate neurotransmission, chromatin remodeling, smoking behavior, schizophrenia, pain, nausea, vomiting, and post-operative delirium; (2) neuroplasticity, depression, and alcohol consumption; and (3) pharmacokinetics. The component sub-networks explain the diverse action mechanisms of ketamine and its analogs. These results may be useful for optimizing pharmacotherapy in patients diagnosed with depression, pain or related stress disorders.One Sentence SummaryThe ketamine network in the human brain consists of sub-networks associated with glutamate neurotransmission, neuroplasticity, and pharmacokinetics.
Effects of L-DOPA on gene expression in the frontal cortex of rats with unilateral lesion of midbrain dopaminergic neurons
Authors: Radlicka Anna , Kamińska Kinga , Borczyk Malgorzata , Piechota Marcin , Korostyński Michał , Pera Joanna , Lorenc-Koci Elżbieta , Parkitna Jan Rodriguez 
Published: April 2020

AbstractThe development of Parkinson’s disease (PD) causes dysfunction of the frontal cortex, which contributes to hallmark motor symptoms and is regarded as one of the primary causes of the affective and cognitive impairments observed in PD. Treatment with L-DOPA alleviates motor symptoms but has mixed efficacy in restoring normal cognitive functions, which is further complicated by the psychoactive effects of the drug. In this study, we investigated how L-DOPA affects gene expression in the frontal cortex in an animal model of unilateral PD. We performed an RNA-seq analysis of gene expression in the frontal cortex of rats with 6-hydroxydopamine (6-OHDA)-induced unilateral dopaminergic lesion that were treated with L-3,4-dihydroxyphenylalanine (L-DOPA), for 2 weeks. We used analysis of variance to identify differentially expressed genes and found 48 genes with significantly altered transcript abundance after L-DOPA treatment. We also performed a weighted gene coexpression network analysis (WGCNA), which resulted in the detection of 5 modules consisting of genes with similar expression patterns. The analyses led to three primary observations. First, the changes in gene expression induced by L-DOPA were bilateral, although only one hemisphere was lesioned. Second, the changes were not restricted to neurons but also appeared to emerge in immune or endothelial cells. Finally, comparisons with databases of drug-induced gene expression signatures revealed multiple nonspecific effects, which indicates that a part of the observed response is a common pattern activated by multiple types of pharmaceuticals in different target tissues. Taken together, our results identify cellular mechanisms in the frontal cortex that are involved in the response to L-DOPA treatment.
SNP genotyping and population analysis of five indigenous Kazakh sheep breeds
Authors: Pozharskiy Alexandr , Khamzina Aigerim , Gritsenko Dilyara , Khamzina Zhangylsyn , Kassymbekova Shinara , Karimov Nurlybek , Karymsakov Talgat , Tlevlesov Nurlan 
Published: April 2020

AbstractSheep husbandry is an important branch of agriculture in Kazakhstan. Modern agrarian and breeding science demands inclusion of molecular genetic and genomic data to supplement traditional methods. Here we used medium-scale SNP genotyping for the first time to determine the population structure of five local sheep breeds in Kazakhstan and their relation to global sheep diversity.Principal component analysis and model-based structure analysis of general population markers revealed two breed groups. The first group included Akzhayik and Kazak Fine-wool sheep and the second group had Edilbay, Saryarka and Kazakh Semi-coarse wool sheep. High heterogeneity of different populations of Akzhayik and Kazakh Semi-coarse wool sheep was observed. A neighborjoining tree comparing Kazakh sheep data with the dataset generated by the Sheep HapMap project supported a close relationship between Kazakh sheep varieties and ancient domestic sheep ancestors.
Extensive transcriptional and chromatin changes underlie astrocyte maturationin vivoand in culture
Authors: Lattke Michael , Goldstone Robert , Guillemot Francois 
Published: April 2020

SummaryAstrocytes have diverse functions in brain homeostasis. Many of these functions are acquired during late stages of differentiation when astrocytes become fully mature. The mechanisms underlying astrocyte maturation are not well understood. Here we identified extensive transcriptional changes that occur during astrocyte maturation and are accompanied by chromatin remodelling at enhancer elements. Investigating astrocyte maturation in a cell culture model revealed thatin vitro-differentiated astrocytes lacked expression of many mature astrocyte-specific genes, including genes for the transcription factors Rorb, Dbx2, Lhx2 and Fezf2. Forced expression of these factorsin vitroinduced distinct sets of mature astrocytes-specific transcripts. Culturing astrocytes with FGF2 in a three-dimensional gel induced expression ofRorb,Dbx2andLhx2and improved their maturity based on transcriptional and chromatin profiles. Therefore extrinsic signals orchestrate the expression of multiple intrinsic regulators, which in turn induce in a modular manner the transcriptional and chromatin changes underlying astrocyte maturation.
Predicting the potency of anti-Alzheimer drug combinations using machine learning
Authors: Anastasio Thomas J 
Published: April 2020

ABSTRACTBACKGROUNDClinical trials of single drugs for the treatment of Alzheimer Disease (AD) have been notoriously unsuccessful. Combinations of repurposed drugs could provide effective treatments for AD. The challenge is to identify potentially potent combinations.OBJECTIVETo use machine learning (ML) to extract the knowledge from two leading AD databases, and then use the machine to predict which combinations of the drugs in common between the two databases would be the most effective as treatments for AD.METHODSThree-layered neural networks (NNs) having compound, gated units in their internal layer were trained using ML to predict the cognitive scores of participants in either database, given the other data fields including age, demographic variables, comorbidities, and drugs taken.RESULTSThe predictions from the separately trained NNs were strongly correlated. The best drug combinations, jointed determined from both sets of predictions, were high in NSAID, anticoagulant, lipid-lowering, and antihypertensive drugs, and female hormones.CONCLUSIONThe results suggest that AD, as a multifactorial disorder, could be effectively treated using a combination of repurposed drugs.
Aspects of the ecology ofBartramia hallerianaandCrossocalyx hellerianusin oceanic deciduous woodland
Authors: Callaghan Des A. , Bevan Jamie 
Published: April 2020

AbstractIntroductionThis study investigates the ecology of two boreal-montane bryophytes, the saxicolous mossBartramia hallerianaand the epixylic liverwortCrossocalyx hellerianus, at the edge of their ranges, in oceanic deciduous woodland.MethodsThe study site comprises two adjoining woodlands, Allt Penyrhiw-iar (canopy trees ca. 100 yr old) and Allt Rhyd Groes (ca. 200 yr), Carmarthenshire, UK. The distribution and abundance ofB. hallerianaandC. hellerianuswas surveyed, relevés sampled to record habitat and community composition, and sporophyte frequency and stage of development measured. Light climate ofB. hallerianawas investigated via hemispherical photography, and abundance of large rotten logs used as a measure of habitat quality forC. hellerianus.Results and discussionFour subpopulations ofB. hallerianaoccur, comprising 21 individual-equivalents (occupied 1 m grid cells), all on mildly base-rich mudstone of north-facing rockfaces, with very little direct solar radiation and a diverse assemblage of bryophytes. Sporophyte are scarce. A total of 143 individual-equivalents (occupied logs or trees) ofC. hellerianuswas recorded, an exceptional population in Wales. Most of the population is within Allt Rhyd Groes, where large rotten logs are much more abundant due to greater woodland age. The liverwort mainly occupied the sides of decorticated rotten logs, amongst a sparse community composed mainly of other small liverworts andCladonialichens. Neither sporophytes nor perianths were found. Further research could usefully focus on the description and measurement of favourable habitat for each species and associated physiological tolerances.
On the fitness of informative cues in complex environments
Authors: Mafessoni Fabrizio , Lachmann Michael , Gokhale Chaitanya S. 
Published: April 2020

AbstractTo be able to deal with uncertainty is of primary importance to most living organisms. When cues provide information about the state of the environment, organisms can use them to respond flexibly. Life forms have evolved complex adaptations and sensory mechanisms to use these environmental cues and extract valuable information about the environment. Previous work has shown a theoretical limit to the amount of fitness benefit possible to be extracted from the cues. We show that the previously used information theoretical approaches can be generalised to scenarios involving any potential relationship between the number of possible phenotypes and environmental states. Such cases are relevant when physiological constraints or complex ecological scenarios lead to the number of environmental states exceeding potential phenotypes. We illustrate cases in which these scenarios can emerge: along environmental gradients, such as geographical transects or complex environments, where organisms adopt different bet-hedging strategies, switching stochastically between phenotypes or developing intermediate ones. In conclusion, we develop an information-theoretic extensible approach for investigating and quantifying fitness in ecological studies.
A central amygdala-globus pallidus circuit conveys unconditioned stimulus information and controls fear learning
Authors: Giovanniello Jacqueline , Yu Kai , Furlan Alessandro , Nachtrab Gregory Thomas , Sharma Radhashree , Chen Xiaoke , Li Bo 
Published: April 2020

AbstractThe central amygdala (CeA) is critically involved in a range of adaptive behaviors. In particular, the somatostatin-expressing (Sst+) neurons in the CeA are essential for classic fear conditioning. These neurons send long-range projections to several extra-amygdala targets, but the functions of these projections remain elusive. Here, we found in mice that a subset of Sst+CeA neurons send projections to the globus pallidus external segment (GPe), and constitute essentially the entire GPe-projecting CeA population. Notably, chronic inhibition of GPe-projecting CeA neurons completely blocks auditory fear conditioning. These neurons are selectively excited by the unconditioned stimulus (US) during fear conditioning, and transient inactivation or activation of these neurons during US presentation impairs or promotes, respectively, fear learning. Our results suggest that a major function of Sst+CeA neurons is to represent and convey US information through the CeA-GPe circuit, thereby instructing learning in fear conditioning.
Diversity begets diversity in human cultures and mammal species
Authors: Hamilton Marcus J. , Walker Robert S. , Kempes Chris 
Published: April 2020

AbstractA key feature of the distribution of life on Earth is the positive correlation between environmental productivity and biodiversity. This correlation also characterizes the distribution of human cultural diversity, which is highest near the equator and decreases exponentially toward the poles. Moreover, it is now understood that the tropics house more biodiversity than would be expected from energy availability alone suggesting “diversity begets diversity”. Here we show the same is also true for human cultural diversity. This convergence is particularly striking because while the dynamics of biological and cultural evolution may be similar in principle the mechanisms and time scales involved are very different. However, a common currency underlying all forms of diversity is ecological kinetics; the temperature-dependent fluxes of energy and biotic interactions that sustain life at all levels of biological and social organization. Using macroecological theory and the analysis of global databases we show both mammal diversity and cultural diversity scale superlinearly with environmental productivity at rates predicted by the ecological kinetics of environmental productivity. Diversity begets diversity in human cultures and mammal species because the kinetics of energy availability and biotic interactions result in superlinear scaling with environmental productivity.
Super-selective reconstruction of causal and direct connectivity with application toin-vitroiPSC neuronal networks
Authors: Puppo Francesca , Pré Deborah , Bang Anne , Silva Gabriel A. 
Published: April 2020

AbstractDespite advancements in the development of cell-basedin-vitroneuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility ofin-vitrolocal neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective - direct and causal - connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then, reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect and apparent links. Our method can be generally applied to the functional characterization of anyin-vitroneuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development ofin-vitroiPSC-derived neuronal cultures.
How spiders make their eyes: Systemic paralogy and function of retinal determination network homologs in arachnids
Authors: Gainett Guilherme , Ballesteros Jesús A. , Kanzler Charlotte R. , Zehms Jakob T. , Zern John M. , Aharon Shlomi , Gavish-Regev Efrat , Sharma Prashant P. 
Published: April 2020

AbstractArachnids are important components of cave ecosystems and display many examples of troglomorphisms, such as blindness, depigmentation, and elongate appendages. Little is known about how the eyes of arachnids are specified genetically, let alone the mechanisms for eye reduction and loss in troglomorphic arachnids. Additionally, paralogy of Retinal Determination Gene Network (RDGN) homologs in spiders has convoluted functional inferences extrapolated from single-copy homologs in pancrustacean models. Here, we investigated a sister species pair of Israeli cave whip spiders (Arachnopulmonata, Amblypygi,Charinus) of which one species has reduced eyes. We generated the first embryonic transcriptomes for Amblypygi, and discovered that several RDGN homologs exhibit duplications. We show that paralogy of RDGN homologs is systemic across arachnopulmonates (arachnid orders that bear book lungs), rather than being a spider-specific phenomenon. A differential gene expression (DGE) analysis comparing the expression of RDGN genes in field-collected embryos of both species identified candidate RDGN genes involved in the formation and reduction of eyes in whip spiders. To ground bioinformatic inference of expression patterns with functional experiments, we interrogated the function of three candidate RDGN genes identified from DGE in a spider, using RNAi in the spiderParasteatoda tepidariorum.We provide functional evidence that one of these paralogs,sine oculis/Six1 A(soA), is necessary for the development of all arachnid eye types. Our results support the conservation of at least one RDGN component across Arthropoda and establish a framework for investigating the role of gene duplications in arachnid eye diversity.
Predicting sites of epitranscriptome modifications using unsupervised representation learning based on generative adversarial networks
Authors: Salekin Sirajul , Mostavi Milad , Chiu Yu-Chiao , Chen Yidong , Zhang Jianqiu (Michelle) , Huang Yufei 
Published: April 2020

ABSTRACTEpitranscriptome is an exciting area that studies different types of modifications in transcripts and the prediction of such modification sites from the transcript sequence is of significant interest. However, the scarcity of positive sites for most modifications imposes critical challenges for training robust algorithms. To circumvent this problem, we propose MR-GAN, a generative adversarial network (GAN) based model, which is trained in an unsupervised fashion on the entire pre-mRNA sequences to learn a low dimensional embedding of transcriptomic sequences. MR-GAN was then applied to extract embeddings of the sequences in a training dataset we created for eight epitranscriptome modifications, including m6A, m1A, m1G, m2G, m5C, m5U, 2′-O-Me, Pseudouridine (Ψ) and Dihydrouridine (D), of which the positive samples are very limited. Prediction models were trained based on the embeddings extracted by MR-GAN. We compared the prediction performance with the one-hot encoding of the training sequences and SRAMP, a state-of-the-art m6A site prediction algorithm and demonstrated that the learned embeddings outperform one-hot encoding by a significant margin for up to 15% improvement. Using MR-GAN, we also investigated the sequence motifs for each modification type and uncovered known motifs as well as new motifs not possible with sequences directly. The results demonstrated that transcriptome features extracted using unsupervised learning could lead to high precision for predicting multiple types of epitranscriptome modifications, even when the data size is small and extremely imbalanced.
Escherichia colihas a Unique Transcriptional Program in Long-Term Stationary Phase
Authors: Kram Karin E. , Henderson Autumn , Finkel Steven E. 
Published: April 2020

AbstractMicrobes live in complex and consistently changing environments, but it is difficult to replicate this in the laboratory.Escherichia colihas been used as a model organism in experimental evolution studies for years; specifically, we and others have used it to study evolution in complex environments by incubating the cells into long-term stationary phase (LTSP) in rich media. In LTSP, cells experience a variety of stresses and changing conditions. While we have hypothesized that this experimental system is more similar to natural environments than some other lab conditions, we do not yet know how cells respond to this environment biochemically or physiologically. In this study, we begin to unravel the cells’ responses to this environment by characterizing the transcriptome of cells during LTSP. We found that cells in LTSP have a unique transcriptional program, and that several genes are uniquely upregulated or downregulated in this phase. Further, we identified two genes,cspBandcspI, which are most highly expressed in LTSP, even though these genes are primarily known to respond to cold-shock. When competed with wild-type cells, these genes are also important for survival during LTSP. These data allow us to compare biochemical responses to multiple environments and identify useful model systems, identify gene products that may play a role in survival in this complex environment, and identify novel functions of proteins.ImportanceExperimental evolution studies have elucidated evolutionary processes, but usually in chemically well-defined and/or constant environments. Using complex environments is important to begin to understand how evolution may occur in natural environments, such as soils or within a host. However, characterizing the stresses cells experience in these complex environments can be challenging. One way to approach this is by determining how cells biochemically acclimate to heterogenous environments. In this study we begin to characterize physiological changes by analyzing the transcriptome of cells in a dynamic complex environment. By characterizing the transcriptional profile of cells in long-term stationary phase, a heterogenous and stressful environment, we can begin to understand how cells physiologically and biochemically react to the laboratory environment, and how this compares to more natural conditions.
ARBitR: An overlap-aware genome assembly scaffolder for linked reads
Authors: Hiltunen Markus , Ryberg Martin , Johannesson Hanna 
Published: April 2020

Abstract10X Genomics Chromium linked reads contain information that can be used to link sequences together into scaffolds in draft genome assemblies. Existing software for this purpose perform the scaffolding by joining sequences together with a gap between them, not considering potential contig overlaps. Such overlaps can be particularly prominent in genome drafts assembled from long-read sequencing data where an overlap-layout-consensus (OLC) algorithm has been used. Ignoring overlapping contig ends may result in genes and other features being incomplete or fragmented in the resulting scaffolds. We developed the application ARBitR to generate scaffolds from genome drafts using 10X Chromium data, with a focus on minimizing the number of gaps in resulting scaffolds by incorporating an OLC step to resolve junctions between linked contigs. We tested the performance of ARBitR on three published and simulated datasets and compared to the previously published tools ARCS and ARKS. The results revealed that ARBitR performed similarly considering contiguity statistics, and the advantage of the overlapping step was revealed by fewer long and short variants in ARBitR produced scaffolds, in addition to a higher proportion of completely assembled LTR retrotransposons. We expect ARBitR to have broad applicability in genome assembly projects that utilize 10X Chromium linked reads.Availability and implementationARBitR is written and implemented in Python3 for Unix-like operative systems. All source code is available athttps://github.com/markhilt/ARBitRunder the GNU General Public License v3.Contactmarkus.hiltunen@ebc.uu.seSupplementary informationavailable online