bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expression analysis of defense-related genes in cucumber (Cucumis sativusL.) againstPhytophthora melonis
Authors: Hashemi Lida , Golparvar Ahmad Reza , Esfahani Mehdi Nasr , Golabadi Maryam 
Published: May 2020

AbstractPhytophthora melonisis the causal agent of damping-off or crown rot, one of the most destructive cucumber diseases that causes severe economic losses in Iran and some other parts of the world. Despite intense research efforts made in the past years, no permanent cure currently exists for this disease. With the aim to understand the molecular mechanisms of defense againstP. melonis, root collars and leaves of four cucumber genotypes consisting of resistant Ramezz; moderately resistant Baby and very susceptible Mini 6-23 and Extrem, were monitored for quantitative gene expression analysis of five antifungal and/or anti-oomycete genes (CsWRKY20, CsLecRK6.1, PR3, PR1-1aandLOX1) at three points after inoculation withP. melonis. The gene expression analysis indicated thatP. melonisstrongly enhanced the expression of these genes after inoculation in both leaves and root collars. Further, not only the transcript levels of these genes were significantly higher in the resistant and moderately resistance genotypes, but also the time point of the highest relative expression ratio for the five genes was different in the four cucumber genotypes.CsWRKY20andPR3showed the maximum expression in Ramezz at 48 hours post inoculation (hpi) whileCsLecRK6.1, andLOX1showed the highest expression at 72 hpi. In addition,PR1-1ashowed the maximum expression in the Baby at 72 hpi. Root collars responded faster than leaves and some responses were more strongly up-regulated in root collars than in leaves. The genes found to be involved in disease resistance in two different organs of cucumber after pathogen infection. The results suggest that increased expression of these genes led to activation of defense pathways and could be responsible for a reducedP. meloniscolonization capacity in Ramezz and Baby. Overall, this work represents a valuable resource for future functional genomics studies to unravel the molecular mechanisms ofC. sativus-P. melonisinteraction.
Wood structure explained by complex spatial source-sink interactions
Authors: Friend Andrew D. 
Published: May 2020

AbstractWood is a remarkable material. It is responsible for the sequestration of significant anthropogenic CO21, aids understanding of past climates2, has unique acoustic, thermal, and strength properties, and is an endlessly renewable source of energy3. However, we lack a general integrated understanding of how its structure is created. A theoretical framework of wood formation is presented here that explains a diverse range of poorly understood observations, including: (i) the anatomy of growth rings, with a transition from low-density earlywood to high-density latewood; (ii) the high sensitivity of latewood density to temperature; (iii) cell-size regulation; and (iv) relationships between growth and temperature. These features arise from interactions in time and space between the production of cells, the dynamics of developmental zones, and the supply of carbohydrates. Carbohydrate distribution is critical for the final density profile, challenging current theory which emphasises compensation between the rates and durations of cell enlargement and wall thickening. These findings have implications for our understanding of how growth responds to environmental variability and the interpretation of tree rings as proxies of past climates. In addition, they provide a framework for the incorporation of explicit growth processes into models, such as those used to predict the role of vegetation in the future global carbon cycle. Finally, divergent responses in volume and mass with increasing temperature suggest caution in interpreting observations based on volume alone.
Probabilistic Approach to Understand Errors in Sequencing and its based Applications
Authors: Singh Anuj 
Published: May 2020

AbstractNext Generation Sequencing has been applied in many areas of biology, including quantification of gene expression, Genome-Wide Association Study (GWAS), gene finding, Motif discovery and much more. Due to the vast area of application and importance in key findings in the field, massive genomic data is being generated using high throughput sequencing. Therefore, sequencing quality also needs to be evaluated in light of different applications. In order to develop effective diagnostic and therapeutic approaches, we need to accurately characterize and identify sequencing errors and distinguish these errors from their true genetic variant in sequencing, i.e. misreads follow a binomial distribution and it further can be approximated to the Poisson process for longer sequences. However, the insertion and deletion rates are 1000 times lower than substitution error rates and, therefore, less significant. The model assumes that error arrival at a position is not dependent on an error at other positions. Furthermore, errors in sequences can cause an error in studies based on multiple sequences and they also follow Binomial – Poisson Distribution (for example – Alignment is a merging of two Binomial processes for short sequences and it further can be approximated to Poisson for long sequences (for example – genomic sequence). It provides a systematic way to evaluate the accuracy in sequencing-based applications. Many error suppressing algorithms or techniques are there, and our Binomial Poisson model can provide a further systematic understanding of error behavior in short sequences so that more techniques for error removal can be developed with much efficient suppression rates.
NuMA interaction with chromatin is vital for proper nuclear architecture in human cells
Authors: Rajeevan Ashwathi , Keshri Riya , Kotak Sachin 
Published: May 2020

AbstractNuMA is an abundant long-coiled-coil protein that plays a prominent role in spindle organization during mitosis. In interphase, NuMA is localized to the nucleus and hypothesized to control gene expression and chromatin organization. However, because of the prominent mitotic phenotype upon NuMA loss, its precise function in the interphase nucleus remains elusive. Here, we report that NuMA is associated with chromatin in interphase and prophase but released upon nuclear envelope breakdown(NEBD) by the action of Cdk1. We uncovered that NuMA directly interacts with DNA via evolutionarily conserved sequences in its C-terminus. Notably, the expression of the DNA-binding mutant of NuMA affects chromatin decondensation at the mitotic exit, and nuclear shape in interphase. The impact on nuclear shape by mutant NuMA expression is due to its potential to polymerize into high-order fibrillar structures. This study links the chromatin binding ability of NuMA with the maintenance of nuclear shape and architecture, which has a well-studied role in regulating gene expression during development and diseases.
Structure of the full kinetoplastids mitoribosome and insight on its large subunit maturation
Authors: Soufari Heddy , Waltz Florent , Parrot Camila , Durrieu Stéphanie , Bochler Anthony , Kuhn Lauriane , Sissler Marie , Hashem Yaser 
Published: May 2020

AbstractKinetoplastids are unicellular eukaryotic parasites responsible for human pathologies such as Chagas disease, sleeping sickness or Leishmaniasis1. They possess a single large mitochondrion, essential for the parasite survival2. In kinetoplastids mitochondrion, most of the molecular machineries and gene expression processes have significantly diverged and specialized, with an extreme example being their mitochondrial ribosomes3. These large complexes are in charge of translating the few essential mRNAs encoded by mitochondrial genomes4,5. Structural studies performed inTrypanosoma bruceialready highlighted the numerous peculiarities of these mitoribosomes and the maturation of their small subunit3,6. However, several important aspects mainly related to the large subunit remain elusive, such as the structure and maturation of its ribosomal RNA3. Here, we present a cryo-electron microscopy study of the protozoansLeishmania tarentolaeandTrypanosoma cruzimitoribosomes. For both species, we obtained the structure of their mature mitoribosomes, complete rRNA of the large subunit as well as previously unidentified ribosomal proteins. Most importantly, we introduce the structure of an LSU assembly intermediate in presence of 16 identified maturation factors. These maturation factors act both on the intersubunit and solvent sides of the LSU, where they refold and chemically modify the rRNA and prevent early translation before full maturation of the LSU.
Enhanced FGFR3 activity in post-mitotic principal neurons during brain development results in cortical dysplasia and axon miswiring
Authors: Huang Jui-Yen , Krebs Bruna Baumgarten , Miskus Marisha Lynn , Russell May Lin , Duffy Eamonn Patrick , Graf Jason Michael , Lu Hui-Chen 
Published: May 2020

AbstractAbnormal levels of fibroblast growth factors (FGFs) and FGF receptors (FGFRs) have been detected in various neurological disorders. The potent impact of FGF-FGFR in multiple embryonic developmental processes makes it challenging to elucidate their roles in post-mitotic neurons. Taking an alternative approach, we directly examined the impact of aberrant FGFR function after neurogenesis by generating a FGFR gain-of-function (GOF) transgenic mouse which expresses constitutively activated FGFR3 (FGFR3K650E) in post-mitotic glutamatergic neurons. We found that enhanced FGFR activity in glutamatergic neurons results in abnormal radial migration and axonal miswiring. Regarding the lamination phenotype in GOF brains, we found later-born Cux1-positive neurons are dispersed throughout the GOF cortex. Such a cortical migration deficit is likely caused, at least in part, by a significant reduction of the radial processes normally projecting from the radial glia cells (RGCs). In addition, FGFR3 GOF also results in the misrouting of several long-range axonal projections, including the corpus callosum, anterior commissure, and postcommissural fornix. RNA-sequencing analysis of the GOF embryonic cortex reveals significant alterations in several pathways involved in cell cycle regulation and axonal pathfinding. Collectively, our results suggest that FGFR hyperfunction in post-mitotic neurons at the late embryonic stage result in cortical dysplasia and circuit miswiring.
Structural basis for control of antibiotic production by bacterial hormones
Authors: Zhou Shanshan , Bhukya Hussain , Malet Nicolas , Harrison Peter J. , Rea Dean , Belousoff Matthew J. , Venugopal Hariprasad , Sydor Paulina K. , Styles Kathryn M. , Song Lijiang , Cryle Max J. , Alkhalaf Lona M. , Fülöp Vilmos , Challis Gregory L. , Corre Christophe 
Published: May 2020

SummaryActinobacteria produce numerous antibiotics and other specialised metabolites with important applications in medicine and agriculture. Diffusible hormones frequently control the production of such metabolites by binding TetR family transcriptional repressors (TFTRs), but the molecular basis for this remains unclear. The production of methylenomycin antibiotics inStreptomyces coelicolorA3(2) is initiated by binding of 2-alkyl-4-hydroxymethylfuran-3-carboxylic acid (AHFCA) hormones to the TFTR MmfR. Here, we report the X-ray crystal structure of an MmfR-AHFCA complex, establishing the structural basis for hormone recognition. We also elucidate the mechanism for DNA release upon hormone binding by single particle cryo-electron microscopy of an MmfR-operator complex. Electrophoretic mobility shift assays with MmfR mutants and synthetic AHFCA analogues illuminate the role played by individual amino acid residues and hormone functional groups in ligand recognition and DNA release. These findings will facilitate the exploitation of Actinobacterial hormones and their associated TFTRs in synthetic biology and novel antibiotic discovery.
Multiethnic catalog of structural variants and their translational impact for disease phenotypes across 19,652 genomes
Authors: Sedlazeck Fritz J. , Yu Bing , Mansfield Adam J. , Chen Han , Krasheninina Olga , Tin Adrienne , Qi Qibin , Zarate Samantha , Traynelis Joshua L. , Menon Vipin ,   BCM HGSC Sequencing Lab, Hu Jianhong , Doddapaneni Harsha , Metcalf Ginger A. , Coresh Josef , Kaplan Robert C. , Muzny Donna M. , Jun Goo , Gibbs Richard A. , Salerno William J. , Boerwinkle Eric 
Published: May 2020

AbstractGenome sequencing at population scale provides unprecedented access to the genetic foundations of human phenotypic diversity, but genotype-phenotype association analyses limited to small variants have failed to comprehensively characterize the genetic architecture of human health and disease because they ignore structural variants (SVs) known to contribute to phenotypic variation and pathogenic conditions1–3. Here we demonstrate the significance of SVs when assessing genotype-phenotype associations and the importance of ethnic diversity in study design by analyzing SVs across 19,652 individuals and the translational impact on 4,156 aptamerbased proteomic measurements across 4,021 multi-ethnic samples. The majority of 304,533 SVs detected are rare, although we identified 2,336 protein-coding genes impacted by common SVs.\We identified 64 significant SV-protein associations that comprise 36 cis- and 28 trans-acting relationships, and 21 distinct SV regions overlapped with genome-wide association study loci. These findings represent a more comprehensive mapping of regulatory and translational endophenotypes underlying health and disease.
Inferring entire spiking activity from local field potentials with deep learning
Authors: Ahmadi Nur , Constandinou Timothy G. , Bouganis Christos-Savvas 
Published: May 2020

ABSTRACTExtracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. Understanding the relationship between these two signals is essential for gaining deeper insight into neuronal coding and information processing in the brain and is also relevant to brain-machine interface (BMI) research. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can be inferred solely from LFPs with moderately good accuracy. These spiking activities that are typically extracted via threshold-based technique may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another spiking activity in the form of a continuous signal, referred to as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to better performance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim to address this issue by employing a deep learning method to infer ESA from LFPs intracortically recorded from the motor cortex area of two monkeys performing different tasks. Results from long-term recording sessions and across different tasks revealed that the inference accuracy of ESA yielded consistently and significantly higher accuracy than that of SUA and MUA. In addition, local motor potential (LMP) was found to be the most highly predictive feature compared to other LFP features. The overall results indicate that LFPs contain substantial information about the spikes, particularly ESA, which could be useful for the development of LFP-based BMIs. The results also suggest the potential use of ESA as an alternative neuronal population activity measure for analysing neural responses to stimuli or behavioural tasks.
Predicting the activation of the androgen receptor by mixtures of ligands using Generalized Concentration Addition
Authors: Schlezinger Jennifer J , Heiger-Bernays Wendy , Webster Thomas F 
Published: May 2020

AbstractConcentration/dose addition (CA) is widely used for compounds that act by similar mechanisms. But, CA cannot make predictions for mixtures of full and partial agonists for effect levels above that of the least efficacious component. As partial agonists are common, we developed Generalized Concentration Addition (GCA), which has been successfully applied to systems in which ligands compete for a single binding site. Here, we applied a pharmacodynamic model for a system with two binding sites, the androgen receptor (AR). AR acts according to the classic homodimer activation model: each cytoplasmic AR protein binds ligand, undergoes a conformational change that relieves inhibition of dimerization, and binds to DNA response elements as a dimer. We generated individual dose-response data for full (dihydroxytestosterone, BMS564929) and partial (TFM-4AS-1) agonists and a competitive antagonist (MDV3100) using reporter data generated in the MDA-kb2 cell line. We used the Schild method to estimate the binding affinity of AR for MDV3100. Data for individual compounds fit the AR pharmacodynamic model well. The partial agonist had agonistic effects at low effect levels and antagonistic effects at high levels, as predicted by pharmacological theory. The GCA model fit the empirical mixtures data—full/full agonist, full/partial agonist and full agonist/antagonist—as well or better than relative potency factors (a special case of CA) or effect summation. The ability of generalized concentration addition to predict the activity of mixtures of different types of androgen receptor ligands is important as a number of environmental compounds act as partial AR agonists or antagonists.
Inside-out regulation of E-cadherin conformation and adhesion
Authors: Koirala Ramesh , Priest Andrew Vae , Yen Chi-Fu , Cheah Joleen S. , Pannekoek Willem-Jan , Gloerich Martijn , Yamada Soichiro , Sivasankar Sanjeevi 
Published: May 2020

ABSTRACTCadherin cell-cell adhesion proteins play key roles in tissue morphogenesis and wound healing. Cadherin ectodomains bind in two conformations, X-dimers and strand-swap dimers, with different adhesive properties. However, the mechanisms by which cells regulate ectodomain conformation are unknown. Cadherin intracellular regions associate with several actin-binding proteins including vinculin, which are believed to tune cell-cell adhesion by remodeling the actin cytoskeleton. Here, we show at the single molecule level, that vinculin association with the cadherin cytoplasmic region allosterically converts weak X-dimers into strong strand-swap dimers, and that this process is mediated by myosin II dependent changes in cytoskeletal tension. We also show that in epithelial cells, ∼70% of apical cadherins exist as strand-swap dimers while the remaining form X-dimers, providing two cadherin pools with different adhesive properties. Our results demonstrate, for the first time, the inside-out regulation of cadherin conformation and establish a mechanistic role for vinculin in this process.SIGNIFICANCE STATEMENTCadherin cell-cell adhesion proteins play key roles in the formation and maintenance of tissues. Their adhesion is carefully regulated to orchestrate complex movement of cells. While cadherin ectodomains bind in two conformations with different adhesive properties, the mechanisms by which cells regulate the conformation (and consequently adhesion) of individual cadherins are unknown. Here, we demonstrate that the association of intracellular vinculin to the cadherin cytoplasmic region, regulates cadherin adhesion by switching ectodomains from a weak binding to the strongly adhesive conformation. In contrast with the prevailing view which suggests that vinculin regulates adhesion solely by remodeling the cytoskeleton, we show that vinculin can directly modulate single cadherin ectodomain conformation and that this process is mediated by changes in cytoskeletal tension.
A novel method for classification of tabular data using convolutional neural networks
Authors: Buturović Ljubomir , Miljković Dejan 
Published: May 2020

ABSTRACTConvolutional neural networks (CNNs) represent a major breakthrough in image classification. However, there has not been similar progress in applying CNNs, or neural networks of any kind, to classification of tabular data. We developed and evaluated a novel method, TAbular Convolution (TAC), for classification of such data using CNNs by transforming tabular data to images and then classifying the images using CNNs. The transformation is performed by treating each row of tabular data (i.e., vector of features) as an image filter (kernel), and applying the filter to a fixed base image. A CNN is then trained to classify the filtered images. We applied TAC to classification of gene expression data derived from blood samples of patients with bacterial or viral infections. Our results demonstrate that off-the-shelf ResNet can classify the gene expression data as accurately as the current non-CNN state-of-the-art classifiers.
Infanticide by females is a leading source of juvenile mortality in a large social carnivore
Authors: Brown Ally K , Pioon Malit O , Holekamp Kay E , Strauss Eli D 
Published: May 2020

AbstractSocial animals benefit from their groupmates, so why do they sometimes kill each other’s offspring? Using 30 years of data from multiple groups of wild spotted hyenas, we address three critical aims for understanding infanticide in any species: (1) quantify the contribution of infanticide to overall mortality (2) describe the circumstances under which infanticide occurs and (3) evaluate hypotheses about the evolution of infanticide. We find that, although observed only rarely, infanticide is in fact a leading source of juvenile mortality. Infanticide accounted for 24% of juvenile mortality, and 1 in 10 hyenas born in our population perished due to infanticide. In all observed cases of infanticide, killers were adult females, but victims could be of both sexes. Of four hypotheses regarding the evolution of infanticide, we found the most support for the hypothesis that infanticide in spotted hyenas reflects competition over social status among matrilines.
Understanding potential drivers of aquatic metabolism in a subtropical treatment wetland
Authors: Julian Paul , Osborne Todd Z. 
Published: May 2020

AbstractChanges of dissolved oxygen (DO) in aquatic ecosystems integrates dynamic biological, physical and chemical processes that control the rate of ecosystem metabolism. Aquatic ecosystem metabolism can be characterized by the diel change in DO changes over time and is expressed as the net aquatic productivity (NAP). This study investigated aquatic metabolism of dominant emergent and submerged aquatic vegetation (EAV and SAV, respectively) within two treatment flow-ways (FW) of Stormwater Treatment Area 2 (STA-2) in the Everglades ecosystem. The hypothesis of this study is that aquatic metabolism will differ between aquatic vegetation communities with SAV communities will have a greater GPP and ER rate than EAV communities driven by biophysical, hydrodynamic and biogeochemical differences between systems. Aquatic metabolism observed in this study vary spatially (along FWs) and temporally (diel to days) controlled by different effects related biological, physical and chemical processes. This study suggests that ecosystem metabolism is controlled differently across FWs with varying levels of response to loading/transport and water column attributes resulting in differences in organic matter accumulation, C turnover and phosphorus cycling.