bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infino: a Bayesian hierarchical model improves estimates of immune infiltration into tumor microenvironment
Authors: Zaslavsky Maxim , Novik Jacqueline Buros , Chang Eliza , Hammerbacher Jeffrey 
Published: December 2017

AbstractRobust quantification of immune cell infiltration into the tumor microenvironment may shed light on why only a small proportion of patients benefit from checkpoint therapy. The immune cells surrounding a tumor have been suggested to mediate an effective response to immunotherapy. However, traditional measurement of immune cell content around a tumor by immunohistochemistry, flow cytometry, or mass cytometry allows measurement of only up to a few dozen markers at a time, limiting the number of immune cell types identified. Immune cell type abundances may instead be estimatedin silicoby deconvolving gene expression mixtures from bulk RNA sequencing of tumor tissue. By measuring tens of thousands of transcripts at once, bulk RNA-seq provides a rich input to algorithms that quantify cell type abundances in the tumor microenvironment, affording the potential to quantify the states of a greater number of immune cell types (given adequate training data). Here, we first review existing methods for deconvolution and evaluate their performance on synthetic mixtures. Then we develop a Bayesian inference approach, namedinfino, that learns to distinguish immune cell expression phenotypes and deconvolve mixtures. In contrast to earlier approaches,infinoaccepts RNA sequencing data, models transcript expression variability, and exploits the relationships between cell types to improve deconvolution accuracy and allow interrogation from the level of broad categories to the level of finest granularity. The resulting probability distributions of immune infiltration could be applied to numerous questions concerning the diverse ecology of immune cell types, including assessment of the association of immune infiltration with response to immunotherapy, and study of the expression profile and presence of elusive T cell subcompartments, such as T cell exhaustion.
A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease
Authors: Greenfield Ben K. , Rajan Jayant , McKone Thomas E. 
Published: December 2017

AbstractBackgroundThe health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination.MethodsWe performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden.ResultsCalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs.ConclusionsThis study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.
Active sampling state dynamically enhances olfactory bulb odor representation
Authors: Jordan Rebecca , Fukunaga Izumi , Kollo Mihaly , Schaefer Andreas T. 
Published: December 2017

SummaryThe olfactory bulb (OB) is the very first site of odor information processing, yet a wealth of contextual and learned information has been described in its activity. To investigate the mechanistic basis of contextual modulation, we use whole-cell recordings to measure odor responses across rapid (<30 min) learning episodes in identified mitral/tufted cells (MTCs). Across these learning episodes, we found that diverse response changes occur already during the first sniff cycle. Motivated mice develop active sniffing strategies across learning, and it is this change of active sampling state that dynamically modulates odor responses, resulting in enhanced discriminability and detectability of odor representation with learning. Evoking fast sniffing in different behavioral states demonstrates that response changes during active sampling exceed those predicted from purely feed-forward input. Finally, response changes are highly correlated in tufted cells, but not mitral cells, indicating cell-type specificity in the effect of active sampling, and resulting in increased odor detectability in the tufted and enhanced discriminability in the mitral cell population over the rapid learning episodes. Altogether, we show that active sampling state is a crucial component in modulating and enhancing olfactory bulb responsiveness on rapid timescales.
Gene expression imputation across multiple brain regions reveals schizophrenia risk throughout development
Authors: Huckins Laura M. , Dobbyn Amanda , Ruderfer Douglas M. , Hoffman Gabriel , Wang Weiqing , Pardinas Antonio , Rajagopal Veera M , Als Thomas D. , Nguyen Hoang , Girdhar Kiran , Boocock James , Roussos Panos , Fromer Menachem , Kramer Robin , Domencini Enrico , Gamazon Eric , Purcell Shaun ,   CommonMind Consortium, the Schizophrenia Working Group of the Psychiatric Genomics Consortium, iPSYCH-GEMS Schizophrenia Working Group, Ditte Demontis, Børglum Anders D. , Walters James , O’Donovan Michael , Sullivan Patrick , Owen Michael , Devlin Bernie , Sieberts Solveig K. , Cox Nancy , Im Hae Kyung , Sklar Pamela , Stahl Eli A. 
Published: December 2017

AbstractTranscriptomic imputation approaches offer an opportunity to test associations between disease and gene expression in otherwise inaccessible tissues, such as brain, by combining eQTL reference panels with large-scale genotype data. These genic associations could elucidate signals in complex GWAS loci and may disentangle the role of different tissues in disease development. Here, we use the largest eQTL reference panel for the dorso-lateral pre-frontal cortex (DLPFC), collected by the CommonMind Consortium, to create a set of gene expression predictors and demonstrate their utility. We applied these predictors to 40,299 schizophrenia cases and 65,264 matched controls, constituting the largest transcriptomic imputation study of schizophrenia to date. We also computed predicted gene expression levels for 12 additional brain regions, using publicly available predictor models from GTEx. We identified 413 genic associations across 13 brain regions. Stepwise conditioning across the genes and tissues identified 71 associated genes (67 outside the MHC), with the majority of associations found in the DLPFC, and of which 14/67 genes did not fall within previously genome-wide significant loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple pathways associated with porphyric disorders. We investigated developmental expression patterns for all 67 non-MHC associated genes using BRAINSPAN, and identified groups of genes expressed specifically pre-natally or post-natally.
Transcriptomic Imputation of Bipolar Disorder and Bipolar subtypes reveals 29 novel associated genes
Authors: Huckins Laura M. , Dobbyn Amanda , McFadden Whitney , Wang Weiqing , Ruderfer Douglas M. , Hoffman Gabriel , Rajagopal Veera , Nguyen Hoang T. , Roussos Panos , Fromer Menachem , Kramer Robin , Domenci Enrico , Gamazon Eric ,   CommonMind Consortium, the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, iPSYCH Consortium, Ditte Demontis, Børglum Anders , Devlin Bernie , Sieberts Solveig K. , Cox Nancy , Im Hae Kyung , Sklar Pamela , Stahl Eli A. 
Published: December 2017

AbstractBipolar disorder is a complex neuropsychiatric disorder presenting with episodic mood disturbances. In this study we use a transcriptomic imputation approach to identify novel genes and pathways associated with bipolar disorder, as well as three diagnostically and genetically distinct subtypes. Transcriptomic imputation approaches leverage well-curated and publicly available eQTL reference panels to create gene-expression prediction models, which may then be applied to “impute” genetically regulated gene expression (GREX) in large GWAS datasets. By testing for association between phenotype and GREX, rather than genotype, we hope to identify more biologically interpretable associations, and thus elucidate more of the genetic architecture of bipolar disorder.We applied GREX prediction models for 13 brain regions (derived from CommonMind Consortium and GTEx eQTL reference panels) to 21,488 bipolar cases and 54,303 matched controls, constituting the largest transcriptomic imputation study of bipolar disorder (BPD) to date. Additionally, we analyzed three specific BPD subtypes, including 14,938 individuals with subtype 1 (BD-I), 3,543 individuals with subtype 2 (BD-II), and 1,500 individuals with schizoaffective subtype (SAB).We identified 125 gene-tissue associations with BPD, of which 53 represent independent associations after FINEMAP analysis. 29/53 associations were novel; i.e., did not lie within 1Mb of a locus identified in the recent PGC-BD GWAS. We identified 37 independent BD-I gene-tissue associations (10 novel), 2 BD-II associations, and 2 SAB associations. Our BPD, BD-I and BD-II associations were significantly more likely to be differentially expressed in post-mortem brain tissue of BPD, BD-I and BD-II cases than we might expect by chance. Together with our pathway analysis, our results support long-standing hypotheses about bipolar disorder risk, including a role for oxidative stress and mitochondrial dysfunction, the post-synaptic density, and an enrichment of circadian rhythm and clock genes within our results.
Inter- and intracellular colonization of Arabidopsis roots by endophytic actinobacteria and the impact of plant hormones on their antimicrobial activity
Authors: van der Meij Anne , Willemse Joost , Schneijderberg Martinus A. , Geurts René , Raaijmakers Jos M. , van Wezel Gilles P. 
Published: December 2017

ABSTRACTMany actinobacteria live in close association with eukaryotes like fungi, insects, animals and plants. Plant-associated actinobacteria display (endo)symbiotic, saprophytic or pathogenic life styles, and can make up a substantial part of the endophytic community. Here, we characterised endophytic actinobacteria isolated from root tissue ofArabidopsis thaliana(Arabidopsis) plants grown in soil from a natural ecosystem. Many of these actinobacteria belong to the family ofStreptomycetaceaewithStreptomyces olivochromogenesandStreptomyces claviferas well represented species. When seeds of Arabidopsis were inoculated with spores ofStreptomycesstrain coa1, which shows high similarity toS. olivochromogenes, roots were colonised intercellularly and, unexpectedly, also intracellularly. Subsequent exposure of endophytic isolates to plant hormones typically found in root and shoot tissues of Arabidopsis led to altered antibiotic production againstEscherichia coliandBacillus subtilis. Taken together, our work reveals remarkable colonization patterns of endophytic streptomycetes with specific traits that may allow a competitive advantage inside root tissue.
k-mer grammar uncovers maize regulatory architecture
Authors: Mejía-Guerra María Katherine , Buckler Edward S 
Published: December 2017

ABSTRACTOnly a small percentage of the genome sequence is involved in regulation of gene expression, but to biochemically identify this portion is expensive and laborious. In species like maize, with diverse intergenic regions and lots of repetitive elements, this is an especially challenging problem. While regulatory regions are rare, they do have characteristic chromatin contexts and sequence organization (the grammar) with which they can be identified. We developed a computational framework to exploit this sequence arrangement. The models learn to classify regulatory regions based on sequence features -k-mers. To do this, we borrowed two approaches from the field of natural language processing: (1) “bag-of-words” which is commonly used for differentially weighting key words in tasks like sentiment analyses, and (2) a vector-space model using word2vec (vector-k-mers), that captures semantic and linguistic relationships between words. We built “bag-of-k-mers” and “vector-k-mers” models that distinguish between regulatory and non-regulatory regions with an accuracy above 90%. Our “bag-of-k-mers” achieved higher overall accuracy, while the “vector-k-mers” models were more useful in highlighting key groups of sequences within the regulatory regions. These models now provide powerful tools to annotate regulatory regions in other maize lines beyond the reference, at low cost and with high accuracy.
Airway IRF7hiversus IRF7lomolecular response patterns determine clinical phenotypes in children with acute wheezing
Authors: Khoo Siew-Kim , Read James , Franks Kimberley , Zhang Guicheng , Bizzintino Joelene , Coleman Laura , McCrae Christopher , Öberg Lisa , Troy Niamh , Prastanti Franciska , Everard Janet , Oo Stephen , Borland Meredith L , Maciewicz Rose A , Le Souëf Peter N , Laing Ingrid A , Bosco Anthony 
Published: December 2017

SummaryAsthma exacerbations are triggered by rhinovirus infections. We employed a systems biology approach to delineate upper airway gene network patterns underlying asthma exacerbation phenotypes in children. Cluster analysis unveiled distinct IRF7hiversus IRF7lomolecular phenotypes, the former exhibiting robust upregulation of Th1/type I interferon responses and the latter an alternative signature marked by upregulation of cytokine and growth factor signalling and downregulation of interferon gamma. The two phenotypes also produced distinct clinical phenotypes. For IRF7loversus IRF7hi: symptom duration prior to hospital presentation was more than twice as long from initial symptoms (p=0.011) and nearly three times as long for cough (p<0.001); the odds ratio of admission to hospital was increased more than four-fold (p=0.018); and time to recurrence was shorter (p=0.015). In summary, our findings demonstrate that asthma exacerbations in children can be divided into IRF7hiversus IRF7lophenotypes with associated differences in clinical phenotypes.AbbreviationsAHR, airway hyperresponsiveness; ARG1, Arginase 1, CSF3, Colony Stimulating Factor 3; CD38, Cluster of Differentiation 38; CD163, Cluster of Differentiation 163; cDCs, conventional (or myeloid) dendritic cells; DDX60, DExD/H-Box Helicase 60; ED, Emergency Department; EGF, Epidermal Growth Factor; ERK, Extracellular signal-Regulated Kinase; FCER1G, Fc Fragment Of IgE Receptor Ig; HMBS, Hydroxymethylbilane Synthase; IFNg, Interferon Gamma; IFNL1, Interferon Lambda 1; IL-1R2, Interleukin 1 Receptor Type 2; IRF7, Interferon Regulatory Factor 7; ISG15, Interferon-stimulated gene 15; MDA5, Melanoma Differentiation-Associated protein 5; MX1, Myxovirus Resistance Protein 1; NAD, nicotinamide adenine dinucleotide; NCR1, Natural cytotoxicity triggering receptor 1; OSM, Oncostatin M; PD-L1, Programmed Death-Ligand 1; PPIA, Peptidylprolyl Isomerase A; PPIB Peptidylprolyl Isomerase B; RSAD2, Radical S-adenosyl methionine domain-containing protein 2; RSV, respiratory syncytial virus; RT-qPCR, quantitative reverse transcription PCR; RV, rhinovirus; sPLA2, secretory Phospholipase A2; TGFb, Transforming Growth Factor beta; THBS1, Thrombospondin 1; TNF, Tumor Necrosis Factor; TLR2, Toll-like Receptor 2.
Development of anin vitropre-mRNA splicing assay using plant nuclear extract
Authors: Albaqami Mohammed , Reddy Anireddy S. N. 
Published: December 2017

AbstractBackgroundPre-mRNA splicing is an essential post-transcriptional process in all eukaryotes.In vitrosplicing systems using nuclear or cytoplasmic extracts from mammalian cells, yeast, andDrosophilahave provided a wealth of mechanistic insights into assembly and composition of the spliceosome, splicing regulatory proteins and mechanisms of pre-mRNA splicing in non-plant systems. The lack of anin vitrosplicing system prepared from plant cells has been a major limitation in splicing research in plants.ResultsHere we report anin vitrosplicing assay system using plant nuclear extract. Several lines of evidence indicate that nuclear extract (NE) derived fromArabidopsisseedlings can convert pre-mRNA substrate (LHCB3) into a spliced product. These include: i) generation of an RNA product that corresponds to the size of expected mRNA, ii) a junction-mapping assay using S1 nuclease revealed that the two exons are spliced together, iii) the reaction conditions are similar to those found with non-plant extracts and iv) finally mutations in conserved donor and acceptor sites abolished the production of the spliced product.ConclusionsThis first report on the plantin vitrosplicing assay opens new avenues to investigate plant spliceosome assembly and composition, and splicing regulatory mechanisms specific to plants.
A Web-resource for Nutrient Use Efficiency related Genes, QTLs, and microRNA in important cereals and model plants
Authors: Kumar Anuj , Pandeya Ajay , Malik Girik , Hima Kumari P , Anil Kumar S , Sharma Mansi , Gahlaut Vijay , Gajula MNV Prasad , Suravajhala Prashanth , Singh Krishna Pal , Balyan Harindra Singh , Gupta Pushpendra K 
Published: December 2017

ABSTRACTCereals are the key contributors to global food security. Genes involved in uptake (transport), assimilation and utilization of macro- and micro-nutrients are responsible for their content in grain and straw. Although many cereal genomic databases are available, currently there is no cohesive web-resource of manually curated nutrient use efficiency (NtUE) related genes and QTLs, etc. In this study, we present a web-resource containing information on NtUE related genes/QTLs and the corresponding available microRNAs for some of these genes in four major cereal crops [wheat (Triticum aestivum), rice (Oryza sativa), maize (Zea mays), barley (Hordeum vulgare)], two alien species (Triticum urartu and Aegilops tauschii) related to wheat, and two model species including Brachypodium distachyon and Arabidopsis thaliana. Gene annotations integrated in the current web-resource were collected from the existing databases and the available literature. The primary goal of developing this web-resource is to provide descriptions of the NtUE related genes and their functional annotation. MicroRNA targeting some of the NtUE related genes and the quantitative trait loci (QTLs) for NtUE related traits are also included. The available information in the web-resource should help the users to readily search the desired information.Web-resource URLhttp://bioclues.org/NtUE/
LRX Proteins play a crucial role in pollen grain and pollen tube cell wall development
Authors: Fabrice Tohnyui Ndinyanka , Vogler Hannes , Draeger Christian , Munglani Gautam , Gupta Shibu , Herger Aline G. , Knox Paul , Grossniklaus Ueli , Ringli Christoph 
Published: December 2017

AbstractLeucine-rich repeat extensins (LRXs) are chimeric proteins containing an N-terminal leucine-rich repeat (LRR) and a C-terminal extensin domain. LRXs are involved in cell wall formation in vegetative tissues and required for plant growth. However, the nature of their role in these cellular processes remains to be elucidated. Here, we used a combination of molecular techniques, light microscopy, and transmission electron microscopy to characterize mutants of pollen-expressedLRXsinArabidopsis thaliana. Mutations in multiple pollen-expressedlrxgenes causes severe defects in pollen germination and pollen tube (PT) growth, resulting in a reduced seed set. Physiological experiments demonstrate that manipulating Ca2+availability partially suppresses the PT growth defects, suggesting that LRX proteins influence Ca2+-related processes. Furthermore, we show that LRX protein localizes to the cell wall, and its LRR-domain (which likely mediates protein-protein interactions) is associated with the plasma membrane. Mechanical analyses by cellular force microscopy and finite element method-based modelling revealed significant changes in the material properties of the cell wall and the fine-tuning of cellular biophysical parameters in the mutants compared to the wild type. The results indicate that LRX proteins might play a role in cell wall-plasma membrane communication, influencing cell wall formation and cellular mechanics.
YAMP: a containerised workflow enabling reproducibility in metagenomics research
Authors: Visconti Alessia , Martin Tiphaine C. , Falchi Mario 
Published: December 2017

AbstractYAMP is a user-friendly workflow that enables the analysis of whole shotgun metagenomic data while using containerisation to ensure computational reproducibility and facilitate collaborative research. YAMP can be executed on any UNIX-like system, and offers seamless support for multiple job schedulers as well as for Amazon AWS cloud. Although YAMP has been developed to be ready-to-use by non-experts, bioinformaticians will appreciate its flexibility, modularisation, and simple customisation.The YAMP script, parameters, and documentation are available athttps://github.com/alesssia/YAMP.
A Rice Dual-localized Pentatricopeptide Repeat Protein is involved in Organellar RNA Editing with MORFs
Authors: Xiao Haijun , Xu Yanghong , Ni Chenzi , Zhang Qiannan , Zhong Feiya , Huang Jishuai , Zhu Yingguo , Hu Jun 
Published: December 2017

AbstractFlowering plants engage in diverse RNA editing events in mitochondrion and chloroplast on post-transcriptional process. Although several PPRs and MORFs were identified as RNA editing factors, the underlying mechanism of PPRs and the cooperation among them are still obscure. Here, we identified a rice dual-localized PPR mutant Ospgl1. Loss-of-function of OsPGLl resulted in defect of chloroplast RNA editing at ndhD-878 and mitochondrial RNA editing at ccmFc-543, which can be restored via complementary validation. Despite the synonymous editing on ccmFc-543, loss of editing at ndhD-878 caused failure of conversion from serine to leucine, leading to the dysfunction of chloroplast and defective in photosynthetic complex, further studies demonstrated OsPGL1 directly bound to both two transcripts. The interaction between three MORFs (MORF2/8/9) and OsPGL1 were confirmed in vitro and in vivo, implied OsPGL1 functioned on RNA editing via an editosome. It also suggested MORFs assisted and contributed to the flexible PPR-RNA recognition model during RNA editing through the cooperation with PPRs. These results provide new insight into the relationship between RNA editing and plant development on chloroplast.HighlightWe firstly characterized a dual-localized PPR protein which is required for RNA editing in mitochondrion and chloroplast simultaneously. OsPGL1 binds to two distinguish target transcripts directly and cooperated with MORFs.