bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sexual stage-induced long noncoding RNAs in the filamentous fungus Fusarium graminearum
Authors: Kim Wonyong , Miguel-Rojas Cristina , Wang Jie , Townsend Jeffrey P , Trail Frances 
Published: February 2018

ABSTRACTLong noncoding RNA (lncRNA) plays important roles in morphological differentiation and development in eukaryotes. In filamentous fungi, however, little is known about lncRNAs and their roles in sexual development. Here we describe sexual stage-induced lncRNAs during the formation of perithecia, the sexual fruiting bodies of Fusarium graminearum. We have identified 547 lncRNAs whose expression was developmental stage-specific, with about 40% of which peaked during the development of asci, the sac-like structures containing meiospores. A large fraction of the lncRNAs were found to be antisense to mRNAs, forming 300 sense–antisense pairs. Although small RNAs (sRNAs) were produced from these overlapping loci, most of the antisense lncRNAs appeared not to be involved in gene silencing pathways. Genome-wide analysis of sRNA clusters identified many silenced loci at the meiotic stage. However, we found transcriptionally-active sRNA clusters, many of which were associated with lncRNAs. Also, we observed that many antisense lncRNAs and their respective sense transcripts were induced in parallel as the perithecia matured. To identify regulatory components for lncRNA expression, we analyzed mutants defective in the nonsense-mediated decay (NMD) pathway. A subset of the lncRNAs appeared to be targeted by the NMD before the perithecia formation, suggesting a suppressive role of the NMD in lncRNA expression during vegetative stage. This research provides fundamental genomic resources that will spur further investigations on developmental lncRNAs that may play important roles in shaping the fungal fruiting bodies.
YAP1 oncogene is a context-specific driver for pancreatic ductal adenocarcinoma
Authors: Tu Bo , Yao Jun , Ferri-Borgogno Sammy , Zhao Jun , Chen Shujuan , Wang Qiuyun , Yan Liang , Zhou Xin , Zhu Cihui , Bang Seungmin , Chang Qing , Bristow Christopher A. , Kang Ya’an , Zheng Hongwu , Wang Huamin , Fleming Jason B. , Kim Michael , Heffernan Timothy P. , Draetta Giulio F. , Pan Duojia , Maitra Anirban , Yao Wantong , Gupta Sonal , Ying Haoqiang 
Published: February 2018

AbstractTranscriptomic profiling classifies pancreatic ductal adenocarcinoma (PDAC) into several molecular subtypes with distinctive histological and clinical characteristics. However, little is known about the molecular mechanisms that define each subtype and their correlation with clinical outcome. Mutant KRAS is the most prominent driver in PDAC, present in over 90% of tumors, but the dependence of tumors on oncogenic KRAS signaling varies between subtypes. In particular, squamous subtype are relatively independent of oncogenic KRAS signaling and typically display much more aggressive clinical behavior versus progenitor subtype. Here, we identified that YAP1 activation is enriched in the squamous subtype and associated with poor prognosis. Activation of YAP1 in progenitor subtype cancer cells profoundly enhanced malignant phenotypes and transformed progenitor subtype cells into squamous subtype. Conversely, depletion of YAP1 specifically suppressed tumorigenicity of squamous subtype PDAC cells. Mechanistically, we uncovered a significant positive correlation between WNT5A expression and the YAP1 activity in human PDAC, and demonstrated that WNT5A overexpression led to YAP1 activation and recapitulated YAP1-dependent but Kras-independent phenotype of tumor progression and maintenance. Thus, our study identifies YAP1 oncogene as a major driver of squamous subtype PDAC and uncovers the role of WNT5A in driving PDAC malignancy through activation of the YAP pathway.
Optimized breath detection algorithm in Electrical Impedance Tomography
Authors: Khodadad D. , Nordebo S. , Müller B. , Waldmann A. , Yerworth R. , Becher T. , Frerichs I. , Sophocleous L. , van Kaam A. , Miedema M. , Seifnaraghi N. , Bayford R. 
Published: February 2018

AbstractObjectiveThis paper define a method for optimizing the breath delineation algorithms used in Electrical Impedance Tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern.ApproachOur approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project.Main resultsThree different algorithms are proposed that are improving the breath detector performance by adding conditions on 1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, 2) minimum tidal impedance amplitude and 3) minimum tidal breath rate obtained from Time-Frequency (TF) analysis.SignificanceBased on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the Receiver Operating Characterics (ROC). This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors.
nPIST: A Novel Actin Binding Protein of trans-Golgi Network
Authors: Das Swagata , Dutta Priyanka , Mazumder Mohit , Seal Soma , Duraivelan Kheerthana , Samanta Dibyendu , Gourinath Samudrala , Maiti Sankar 
Published: February 2018

Abstractnpist is the neuronal isoform of PIST, a trans-golgi associated protein involved in major modulation of vesicular trafficking. nPIST interacts with glutamate delta2 receptor (GluRδ2) in Purkinje cells. Our study shows nPIST as a novel actin binding protein. Our structure based sequence analysis shows nPIST contains one WH2-like domain. Further our experimental analysis illustrates that fragment of nPIST consisting of WH2-like domain binds to actin. Moreover it was found that nPIST contains several regions involved in interaction with actin. The binding of nPIST to actin through multiple actin binding regions facilitated actin filament stabilization in vitro. In vivo, nPIST localized actin in perinuclear region as a blotch when ectopically expressed.
Network hubs in root-associated fungal metacommunities
Authors: Toju Hirokazu , Tanabe Akifumi S. , Sato Hirotoshi 
Published: February 2018

AbstractBackgroundAlthough a number of recent studies have uncovered remarkable diversity of microbes associated with plants, understanding and managing dynamics of plant microbiomes remain major scientific challenges. In this respect, network analytical methods have provided a basis for exploring “hub” microbial species, which potentially organize community-scale processes of plant-microbe interactions.MethodsBy compiling Illumina sequencing data of root-associated fungi in eight forest ecosystems across the Japanese Archipelago, we explored hubs within “metacommunity-scale” networks of plant-fungus associations. In total, the metadata included 8,080 fungal operational taxonomic units (OTUs) detected from 227 local populations of 150 plant species/taxa.ResultsFew fungal OTUs were common across all the eight forests. However, in each metacommunity-scale network representing northern four localities or southern four localities, diverse mycorrhizal, endophytic, and pathogenic fungi were classified as “metacommunity hubs”, which were detected from diverse host plant taxa throughout a climatic region. Specifically,Mortierella(Mortierellales),Cladophialophora(Chaetothyriales),Ilyonectria(Hypocreales),Pezicula(Helotiales), andCadophora(incertae sedis) had broad geographic and host ranges across the northern (cool-temperate) region, whileSaitozyma/Cryptococcus(Tremellales/Trichosporonales) andMortierellaas well as some arbuscular mycorrhizal fungi were placed at the central positions of the metacommunity-scale network representing warm-temperate and subtropical forests in southern Japan.ConclusionsThe network theoretical framework presented in this study will help us explore prospective fungi and bacteria, which have high potentials for agricultural application to diverse plant species within each climatic region. As some of those fungal taxa with broad geographic and host ranges have been known to increase the growth and pathogen resistance of host plants, further studies elucidating their functional roles are awaited.
Bi-clustering interpretation and prediction of correlation between gene expression and protein abundance
Authors: Wang Xiaojun , Teng Lin , Zhang Haicang , Zhou Qian , Su Xiaoquan , Cui Xinping , Bu Dongbo , Gong Xinqi , Poetsch Ansgar , Ning Kang 
Published: February 2018

AbstractMost organisms’ transcript and protein level only moderately correlate for various reasons, such as regulation of transcription and protein degradation. Better prediction and understanding the correlation between gene expression and protein abundance has been possible by harnessing the matching RNA/protein datasets produced by modern high-throughput RNA-Seq and mass spectrometry methods. In this work, we have utilized some well-studied matching RNA/protein datasets, and explored for the first time a bi-clustering method to cluster genes that have consistent correlation patterns between gene expression and protein abundance. The clustering results have been interpreted from the perspective of both transcriptomic and proteomic features, which show that mRNA half-life, protein half-life and protein structure in concert significantly affect the correlation of gene expression and protein abundance. With these and other carefully selected features, a prediction model based on individual clusters, called Cluster-based Linear prediction Model (CLM), was built and tested on mouse liver mitochondrial, mouse brainstem mitochondrial, Saccharomyces cerevisiae and Danio rerio datasets. CLM could find genes for which protein abundance can be predicted from mRNA data. In summary, based on bi-clustering, feature selection and CLM model, we have established a new and valuable cluster-based protein abundance prediction method.
The fungal ligand chitin directly binds and signals inflammation dependent on oligomer size and TLR2
Authors: Fuchs Katharina , Gloria Yamel Cardona , Wolz Olaf-Oliver , Herster Franziska , Sharma Lokesh , Dillen Carly , Täumer Christoph , Dickhöfer Sabine , Bittner Zsofia , Dang Truong-Minh , Singh Anurag , Haischer Daniel , Schlöffel Maria A. , Koymans Kirsten J. , Sanmuganantham Tharmila , Krach Milena , Schilling Nadine A. , Frauhammer Felix , Miller Lloyd , Nürnberger Thorsten , LeibundGut-Landmann Salomé , Gust Andrea A. , Macek Boris , Frank Martin , Gouttefangeas Cécile , Dela Cruz Charles S. , Hartl Dominik , Weber Alexander N.R. 
Published: February 2018

AbstractChitin is a highly abundant polysaccharide and linked to fungal infection and asthma. Unfortunately, its polymeric structure has hampered the identification of immune receptors directly binding chitin and signaling immune activation and inflammation, because purity, molecular structure and molarity are not well definable for a polymer typically extracted from biomass. Therefore, by using defined chitin (N-acetyl-glucosamine) oligomers, we identified six subunit long chitin chains as the smallest immunologically active motif and the innate immune receptor Toll-like receptor (TLR) 2 as the primary fungal chitin receptor on human and murine immune cells. Chitin oligomers directly bound TLR2 with nanomolar affinity and showed both overlapping and distinct signaling outcomes compared to known mycobacterial TLR2 ligands. Conversely, chitin oligomers shorter than 6 subunits were inactive or showed antagonistic effects on chitin/TLR2-mediated signaling, hinting to a size-dependent sensing/activation system unexpectedly conserved in plants and humans. Since blocking the chitin-TLR2 interaction effectively prevented chitin-mediated inflammation in vitro and in vivo, our study highlights the chitin TLR2 interaction as a potential target for developing novel therapies in chitin-related pathologies and fungal disease.
SMuRF: Portable and accurate ensemble-based somatic variant calling
Authors: Huang Weitai , Guo Yu Amanda , Muthukumar Karthik , Baruah Probhonjon , Chang Meimei , Skanderup Anders Jacobsen 
Published: February 2018

ABSTARCTSummarySMuRF is an ensemble method for prediction of somatic point mutations (SNVs) and small insertions/deletions (indels) in cancer genomes. The method integrates predictions and auxiliary features from different somatic mutation callers using a Random Forest machine learning approach. SMuRF is trained on community-curated tumor whole genome sequencing data, is robust across cancer types, and achieves improved accuracy for both SNV and indel predictions of genome and exome-level data. The software is user-friendly and portable by design, operating as an add-on to the community-developed bcbio-nextgen somatic variant calling pipeline.Contactskanderupamj@gis.a-star.edu.sg
Amino acid stylization: a new approach for representing protein sequences and scoring protein alignments
Authors: Marino Stefano M. 
Published: February 2018

SynopsisThe amino acids (AA) stylization, introduced in this work, is a mean to obtain a qualitative and quantitative description of different AA; the goal is to allow, via a chemically meaningful representation, the analysis of protein similarity in multiple alignments, without any statistical and evolutionary information involved. The AA Stylization Matrix Method (aSMM) has been tested positively with different data sets, in line with most common statistically based approaches (e.g. BLOSUM62), while allowing the exploitation of some unique capabilities, e.g. to be rapidly configured for specific properties that can be (over-, or under-) weighted. Overall, applying ad hoc parameterization aSMM permits a tailored investigation to account for different types of substitutions in protein alignments.
Integrin signaling downregulates filopodia in muscle-tendon attachment
Authors: Richier Benjamin , Inoue Yoshiko , Dobramysl Ulrich , Friedlander Jonathan , Brown Nicholas H. , Gallop Jennifer L. 
Published: February 2018

AbstractCells in developing tissues need to sense their environment for their accurate targeting to specific destinations. This occurs in developing muscles, which need to attach to their respective tendon cell before muscle contractions can begin. Elongating myotube tips form filopodia, which are presumed to have sensory roles, and are later suppressed upon building the attachment site. Here, we use live imaging and quantitative image analysis of lateral transverse (LT) myotubes inDrosophilato show that filopodia suppression occurs as a result of integrin signaling. Loss of the integrin subunits αPS2 and βPS increased filopodia number and length at stages when they are normally suppressed. Conversely, inducing integrin signaling, achieved by expression of constitutively dimerised βPS cytoplasmic domain (diβ), prematurely suppressed filopodia. We discovered that the integrin signal is transmitted through the ArfGAP and scaffolding protein Git (G-protein receptor coupled interacting protein) and its downstream kinase Pak (p21-activated kinase). Absence of these proteins causes profuse filopodia formation and prevents filopodial inhibition by diβ. Thus, integrin signaling switches off the exploratory behaviour of myotubes seeking tendons, enabling the actin machinery to focus on forming a strong attachment and assembling the contractile apparatus.
Parentage assignment with genotyping-by-sequencing data
Authors: Whalen Andrew , Gorjanc Gregor , Hickey John M 
Published: February 2018

AbstractIn this paper we evaluate using genotype-by-sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low-coverage GBS data, it may not be possible to call the genotype at many loci, a critical first step for detecting opposing homozygous markers. Second, the amount of sequencing coverage may vary across individuals, making it challenging to directly compare the likelihood scores between putative parents. To address these issues we extend the probabilistic framework of Huisman (2017) and evaluate putative parents by comparing their (potentially noisy) genotypes to a series of proposal distributions. These distributions describe the expected genotype probabilities for the relatives of an individual. We assign putative parents as a parent if they are classified as a parent (as opposed to e.g., an unrelated individual), and if the assignment score passes a threshold. We evaluated this method on simulated data and found that (1) high-coverage GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (2) low-coverage GBS data (as low as 0.1x) can also be used, provided that it is obtained across a large number of markers. When analysing the low-coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.
Quantifying genetic, environmental and individual stochastic variability inPlantago lanceolata
Authors: Steiner Ulrich K. , Tuljapurkar Shripad , Roach Deborah A. 
Published: February 2018

AbstractPredicting ecological and evolutionary population dynamics requires understanding how genetic and environmental parameters influence variation in survival and reproduction among individuals. However such a focus often neglects the stochastic events that individuals experience throughout their lives that also influence survival and reproduction. With an illustrative example, we quantify and illustrate the influence of such non-selective demographic variability on population dynamics using size-structured matrix models of an experimental population ofPlantago lanceolata. Our analysis shows that variation in survival and reproduction among individuals explained by environment, genes, and their interaction was modest compared to the stochastic variation in lifespan and reproduction. We illustrate how expectations on population growth, based on expected lifetime reproduction and generation time, can be misleading when variance in reproduction among individuals of the same genotype (full sibs) was large. Such large within genotype variance can lower population growth, fitness. Our results accompany recent investigations that call for more focus on stochastic variation in survival and reproduction, rather than dismissal of this variation as uninformative noise.
Amplification and Suppression of Distinct Brain-wide Activity Patterns by Catecholamines
Authors: van den Brink RL , Nieuwenhuis S , Donner TH 
Published: February 2018

ABSTRACTThe widely projecting catecholaminergic (norepinephrine and dopamine) neurotransmitter systems profoundly shape the state of neuronal networks in the forebrain. Current models posit that the effects of catecholaminergic modulation on network dynamics are homogenous across the brain. However, the brain is equipped with a variety of catecholamine receptors with distinct functional effects and heterogeneous density across brain regions. Consequently, catecholaminergic effects on brain-wide network dynamics might be more spatially specific than assumed. We tested this idea through the analysis of functional magnetic resonance imaging (fMRI) measurements performed in humans (19 females, 5 males) at ‘rest’ under pharmacological (atomoxetine-induced) elevation of catecholamine levels. We used a linear decomposition technique to identify spatial patterns of correlated fMRI signal fluctuations that were either increased or decreased by atomoxetine. This yielded two distinct spatial patterns, each expressing reliable and specific drug effects. The spatial structure of both fluctuation patterns resembled the spatial distribution of the expression of catecholamine receptor genes: α1 norepinephrine receptors (for the fluctuation pattern: placebo > atomoxetine), ‘D2-like’ dopamine receptors (pattern: atomoxetine > placebo), and β norepinephrine receptors (for both patterns, with correlations of opposite sign). We conclude that catecholaminergic effects on the forebrain are spatially more structured than traditionally assumed and at least in part explained by the heterogeneous distribution of various catecholamine receptors. Our findings link catecholaminergic effects on large-scale brain networks to low-level characteristics of the underlying neurotransmitter systems. They also provide key constraints for the development of realistic models of neuromodulatory effects on large-scale brain network dynamics.SIGNIFICANCE STATEMENTThe catecholamines norepinephrine and dopamine are an important class of modulatory neurotransmitters. Because of the widespread and diffuse release of these neuromodulators, it has commonly been assumed that their effects on neural interactions are homogenous across the brain. Here, we present results from the human brain that challenge this view. We pharmacologically increased catecholamine levels and imaged the effects on the spontaneous covariations between brain-wide fMRI signals at ‘rest’. We identified two distinct spatial patterns of covariations: one that was amplified and another that was suppressed by catecholamines. Each pattern was associated with the heterogeneous spatial distribution of the expression of distinct catecholamine receptor genes. Our results provide novel insights into the catecholaminergic modulation of large-scale human brain dynamics.
Loss of embryonic neural crest cardiomyocytes causes adult hypertrophic cardiomyopathy
Authors: Abdul-Wajid Sarah , Demarest Bradley L , Yost H Joseph 
Published: February 2018

AbstractNeural crest cells migrate to the embryonic heart and transform into a small number of cardiomyocytes, but their functions in the developing and adult heart are unknown. Here, we map the fates of neural crest derived cardiomyocytes (NC-Cms) and genetically ablate them in embryogenesis in zebrafish. Specific NC-Cm ablation results in aberrant trabeculation patterns and altered Notch signaling, but is not detrimental to the development of the fish or early heart function. Strikingly, embryonic NC-Cm ablation results in adult fish that show severely hypertrabeculated hearts, altered cardiomyocyte size, diminished adult heart capacity and consequently poor physiological response to cardiac stress tests. Thus, we identify a novel developmental mechanism and genetic pathway that predisposes adults to hypertrophic cardiomyopathy and provides the first zebrafish model of adult-onset heart failure.