bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased frequency of travel in the presence of cross-immunity may act to decrease the chance of a global pandemic
Authors: Thompson R. N. , Thompson C. P. , Pelerman O. , Gupta S. , Obolski U. 
Published: May 2019

The high frequency of modern travel has led to concerns about a devastating pandemic since a lethal pathogen strain could spread worldwide quickly. Many historical pandemics have arisen following pathogen evolution to a more virulent form. However, some pathogen strains invoke immune responses that provide partial cross-immunity against infection with related strains. Here, we consider a mathematical model of successive outbreaks of two strains—a low virulence (LV) strain outbreak followed by a high virulence (HV) strain outbreak. Under these circumstances, we investigate the impacts of varying travel rates and cross-immunity on the probability that a major epidemic of the HV strain occurs, and the size of that outbreak. Frequent travel between subpopulations can lead to widespread immunity to the HV strain, driven by exposure to the LV strain. As a result, major epidemics of the HV strain are less likely, and can potentially be smaller, with more connected subpopulations. Cross-immunity may be a factor contributing to the absence of a global pandemic as severe as the 1918 influenza pandemic in the century since.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
Systematic re-annotation of 191 genes associated with early-onset epilepsy unmasks de novo variants linked to Dravet syndrome in novel SCN1A exons
Authors: Steward Charles A. , Roovers Jolien , Suner Marie-Marthe , Gonzalez Jose M. , Uszczynska-Ratajczak Barbara , Pervouchine Dmitri , Fitzgerald Stephen , Viola Margarida , Stamberger Hannah , Hamdan Fadi F. , Ceulemans Berten , Leroy Patricia , Nava Caroline , Lepine Anne , Tapanari Electra , Keiller Don , Abbs Stephen , Sanchis-Juan Alba , Grozeva Detelina , Rogers Anthony S. , Wright James , Choudhary Jyoti , Diekhans Mark , Guigó Roderic , Petryszak Robert , Minassian Berge A. , Cavalleri Gianpiero , Vitsios Dimitrios , Petrovski Slavé , Harrow Jennifer , Flicek Paul , Raymond F. Lucy , Lench Nicholas J. , De Jonghe Peter , Mudge Jonathan M. , Weckhuysen Sarah , Sisodiya Sanjay M. , Frankish Adam 
Published: May 2019

AbstractThe early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.
Mammary mechanobiology: mechanically-activated ion channels in lactation and involution
Authors: Stewart Teneale A. , Hughes Katherine , Stevenson Alexander J. , Marino Natascia , Ju Adler L. , Morehead Michael , Davis Felicity M. 
Published: May 2019

AbstractA mother’s ability to produce a nutritionally-complete neonatal food source has provided a powerful evolutionary advantage to mammals. Milk production by secretory mammary epithelial cells is adaptive, its release is exquisitely timed and its own glandular stagnation with the permanent cessation of suckling triggers the programmed cell death and tissue remodeling that enables female mammals to nurse successive progeny. Both chemical and mechanical signals control epithelial expansion, function and remodeling. Despite this duality of input, however, the nature and function of mechanical forces in the mammary gland remain unknown. Here, we characterize the mammary force landscape and the capacity of luminal and basal epithelial cells to experience and exert force. We explore the molecular instruments for force-sensing in the mammary gland and the physiological requirement for PIEZO1 in lactation and involution. Our study supports the existence of a multifaceted system of chemical and mechanical sensing in the mammary gland, and a protective redundancy that ensures continued lactational competence and offspring survival.
Dentate gyrus neurons that are born at the peak of development, but not before or after, die in adulthood
Authors: Ciric Tina , Cahill Shaina P. , Snyder Jason S. 
Published: May 2019

AbstractIn the dentate gyrus of the rodent hippocampus, neurogenesis begins prenatally and continues to the end of life. Adult-born neurons often die in the first few weeks after mitosis, but then survive indefinitely. In contrast, neurons born at the peak of development are initially stable but can die later in adulthood. Physiological and pathological changes in hippocampal structure may therefore result from both the addition of new neurons and the loss of older neurons. However, it is unknown whether neurons born at other stages of development also undergo delayed cell death. Here, we used BrdU to label dentate granule cells that were born in rats on embryonic day 19 (E19; before the developmental peak), postnatal day 6 (P6; peak) and P21 (after the peak). We quantified BrdU+ neurons in separate groups of rats at 2 and 6 months post-BrdU injection. Consistent with previous work, there was a 15% loss of P6-born neurons between 2 and 6 months of age. In contrast, E19- or P21-born neurons were stable throughout young adulthood. Delayed death of P6-born neurons suggests they may play a unique role in hippocampal plasticity and pathology in adulthood.
Modeling binary and graded cone cell fate patterning in the mouse retina
Authors: Eldred Kiara C. , Avelis Cameron , Johnston Robert J. , Roberts Elijah 
Published: May 2019

AbstractNervous systems are incredibly diverse, with myriad neuronal subtypes defined by gene expression. How binary and graded fate characteristics are patterned across tissues is poorly understood. Expression of opsin photopigments in the cone photoreceptors of the mouse retina provides an excellent model to address this question. Individual cones express S-opsin only, M-opsin, or both S-opsin and M-opsin. These cell populations are patterned along the dorsal-ventral axis, with greater M-opsin expression in the dorsal region and greater S-opsin expression in the ventral region. Thyroid hormone signaling plays a critical role in activating M-opsin and repressing S-opsin. Here, we developed an image analysis approach to identify individual cone cells and evaluate their opsin expression from immunofluorescence imaging tiles spanning roughly 6 mm along the D-V axis of the mouse retina. From analyzing the opsin expression of ∼250,000 cells, we found that cones make a binary decision between S-opsin only and co-expression competent fates. Co-expression competent cells express graded levels of S- and M-opsins, depending nonlinearly on their position in the dorsal-ventral axis. M- and S-opsin expression display differential, inverse patterns. Using these single-cell data we developed a quantitative, stochastic model of cone cell decisions in the retinal tissue based on thyroid hormone signaling activity. The model recovers the probability distribution for cone fate patterning in the mouse retina and describes a minimal set of interactions that are necessary to reproduce the observed cell fates. Our study provides a paradigm describing how differential responses to regulatory inputs generate complex patterns of binary and graded cell fates.Author SummaryThe development of a cell in a mammalian tissue is governed by a complex regulatory network that responds to many input signals to give the cell a distinct identity, a process referred to as cell-fate specification. Some of these cell fates have binary on-or-off gene expression patterns, while others have graded gene expression that changes across the tissue. Differentiation of the photoreceptor cells that sense light in the mouse retina provides a good example of this process. Here, we explore how complex patterns of cell fates are specified in the mouse retina by building a computational model based on analysis of a large number of photoreceptor cells from microscopy images of whole retinas. We use the data and the model to study what exactly it means for a cell to have a binary or graded cell fate and how these cell fates can be distinguished from each other. Our study shows how tens-of-thousands of individual photoreceptor cells can be patterned across a complex tissue by a regulatory network, creating a different outcome depending upon the received inputs.
Impaired Social Learning Predicts Reduced Real-life Motivation in Individuals with Depression: A Computational fMRI Study
Authors: Frey Anna-Lena , McCabe Ciara 
Published: May 2019

AbstractBackgroundMajor depressive disorder is associated with altered social functioning and impaired learning, on both the behavioural and the neural level. These deficits are likely related, considering that successful social interactions require learning to predict other people’s emotional responses. Yet, there is little research examining this relation.MethodsForty-three individuals with high (HD; N=21) and low (LD; N=22) depression scores answered questions regarding their real-life social experiences and performed a social learning task during fMRI scanning. As part of the task, subjects learned associations between name cues and rewarding (happy faces) or aversive (fearful faces) social outcomes. Using computational modelling, behavioural and neural correlates of social learning were examined and related to real-life social experiences.ResultsHD participants reported reduced motivation to engage in real-life social activities and demonstrated elevated uncertainty about social outcomes in the task. Moreover, HD subjects displayed altered encoding of social reward predictions in the insula, temporal lobe and parietal lobe. Interestingly, across all subjects, higher task uncertainty and reduced parietal prediction encoding were associated with decreased motivation to engage in real-life social activities.LimitationsThe size of the included sample was relatively small. The results should thus be regarded as preliminary and replications in larger samples are called for.ConclusionTaken together, our findings suggest that reduced learning from social outcomes may impair depressed individuals’ ability to predict other people’s responses in real life, which renders social situations uncertain. This uncertainty, in turn, may contribute to reduced social engagement (motivation) in depression.
De novo transcriptome analysis of dermal tissue from the rough-skinned newt, Taricha granulosa, enables investigation of tetrodotoxin expression
Authors: Glass Haley C. , Melin Amanda D. , Vamosi Steven M. 
Published: May 2019

AbstractBackgroundTetrodotoxin (TTX) is a potent neurotoxin used in anti-predator defense by several aquatic species, including the rough-skinned newt, Taricha granulosa. While several possible biological sources of newt TTX have been investigated, mounting evidence suggests a genetic, endogenous origin. We present here a de novo transcriptome assembly and annotation of dorsal skin samples from the tetrodotoxin-bearing species T. granulosa, to facilitate the study of putative genetic mechanisms of TTX expression.FindingsApproximately 211 million read pairs were assembled into 245,734 transcripts using the Trinity de novo assembly method. Of the assembled transcripts, we were able to annotate 34% by comparing them to databases of sequences with known functions, suggesting that many transcripts are unique to the rough-skinned newt. Our assembly has near-complete sequence information for an estimated 83% of genes based on Benchmarking Universal Single Copy Orthologs. We also utilized other comparative methods to assess the quality of our assembly. The T. granulosa assembly was compared with that of the Japanese fire-belly newt, Cynops pyrrhogaster, and they were found to share a total of 30,556 orthologous sequences (12.9% gene set).ConclusionsWe provide a reference assembly for Taricha granulosa that will enable downstream differential expression and comparative transcriptomics analyses. This publicly available transcriptome assembly and annotation dataset will facilitate the investigation of a wide range of questions concerning amphibian adaptive radiation, and the elucidation of mechanisms of tetrodotoxin defense in Taricha granulosa and other TTX-bearing species.
mPFC Spindle Cycles Organize Sparse Thalamic Activation and Recently Active CA1 cells During non-REM Sleep
Authors: Varela C , Wilson MA 
Published: May 2019

AbstractSleep oscillations in neocortex and hippocampus are critical for the integration of new episodic memories into stable generalized representations in neocortex. However, the role of the thalamus in this process is poorly understood.To determine the thalamic contribution to non-REM oscillations (sharp-wave ripples, SWRs; slow/delta; spindles), we recorded units and local field potentials (LFPs) simultaneously in the limbic thalamus, mPFC, and CA1 in rats. We report that the cycles of neocortical spindles provide a key temporal window that coordinates CA1 SWRs with sparse but consistent activation of thalamic units. Thalamic units were phase-locked to delta and spindles in mPFC, and fired at consistent lags with other thalamic units within spindles, while CA1 units that were active during spatial exploration were engaged in SWR-coupled spindles after behavior. The sparse thalamic firing could promote an incremental integration of recently acquired memory traces into neocortical schemas through the interleaved activation of thalamocortical cells.
PyBSASeq: a novel, simple, and effective algorithm for BSA-Seq data analysis
Authors: Zhang Jianbo , Panthee Dilip R. 
Published: May 2019

Bulked segregant analysis (BSA), coupled with next generation sequencing (NGS), allows the rapid identification of both qualitative and quantitative trait loci (QTL), and this technique is referred to as BSA-Seq here. The current SNP index method and G-statistic method for BSA-Seq data analysis require relatively high sequencing coverage to detect major single nucleotide polymorphism (SNP)-trait associations, which leads to high sequencing cost. Here we developed a simple and effective algorithm for BSA-Seq data analysis and implemented it in Python, the program was named PyBSASeq. Using PyBSASeq, the likely trait-associated SNPs (ltaSNPs) were identified via Fisher’s exact test and then the ratio of the ltaSNPs to total SNPs in a chromosomal interval was used to identify the genomic regions that condition the trait of interest. The results obtained this way are similar to those generated by the current methods, but with more than five times higher sensitivity, which can reduce the sequencing cost by ~80% and makes BSA-Seq more applicable for the species with a large genome.Significance StatementBSA-Seq can be utilized to rapidly identify DNA polymorphismtrait associations, and PyBSASeq allows the detection of such associations at much lower sequencing coverage than the current methods, leading to lower sequencing cost and making BSA-Seq more accessible to the research community and more applicable to the species with a large genome.
OPTIMOS PRIME: An R package for autoecological (optima and tolerance range) data calculation
Authors: Sathicq María Belén , Nicolosi Gelis María Mercedes , Cochero Joaquín 
Published: May 2019

ABSTRACTCalculation of autoecological data, such as optima and tolerance ranges to environmental variables, can be useful to establish the distribution and abundance of the species. These calculations, although mathematically not complex, can be prone to error when using a large database.We present an R package (“optimos.prime”) that uses species’ abundance data and environmental data to calculate the optimum value and tolerance range of each species to each environmental factor, by weighted average. Additionally, the package can create caterpillar plots to show the results.Using sample data from a phytoplankton database, we exemplify the use of the R package and its functions. A stand-alone version for Windows is also provided, and source code and documents are freely available on GitHub to encourage collaborative work.
An Accurate Bioinformatics Tool For Anti-Cancer Peptide Generation Through Deep Learning Omics
Authors: Kaushik Aman Chandra , Li Mengyang , Wei Dong-Qing 
Published: May 2019

ABSTRACTThe Anti-cancer targets play crucial role in signalling processes of cells. We have developed an Anti-Cancer Scanner (ACS) tool for identification of Anti-cancer targets in form of peptides. ACS tool also allows fast fingerprinting of the Anti-cancer targets of significance in the current bioinformatics research. There are tools currently available which predicts the above-mentioned features in single platform. In the present work, we have compared the features predicted by ACS with other on-line available methods and evaluated the performance of the ACS tool. ACS scanned the Anti-cancer target protein sequences provided by the user against the Anti-cancer target data-sets. It has been developed in PERL language and it is scalable having an extensible application in bioinformatics with robust coding architecture. It achieves a prediction accuracy of 95%, which is much higher than the existing tools.
Nuclear actin regulates inducible transcription by enhancing RNA polymerase II clustering
Authors: Wei Mian , Fan Xiaoying , Ding Miao , Li Ruifeng , Shao Shipeng , Hou Yingping , Meng Shaoshuai , Tang Fuchou , Li Cheng , Sun Yujie 
Published: May 2019

AbstractGene expression in response to external stimuli underlies a variety of fundamental cellular processes. However, how the transcription machinery is regulated under these scenarios is largely unknown. Here, we discover a novel role of nuclear actin in inducible transcriptional regulation using next-generation transcriptome sequencing and super-resolution microscopy. The RNA-seq data reveal that nuclear actin is required for the establishment of the serum-induced transcriptional program. Using super-resolution imaging, we found a remarkable enhancement of RNA polymerase II (Pol II) clustering upon serum stimulation and this enhancement requires the presence of nuclear actin. To study the molecular mechanisms, we firstly observed that Pol II clusters co-localized with the serum-response genes and nuclear actin polymerized in adjacent to Pol II clusters upon serum stimulation. Furthermore, N-WASP and Arp2/3 are reported to interact with Pol II, and we demonstrated N-WASP is required for serum-enhanced Pol II clustering. Importantly, using an optogenetic tool, we revealed that N-WASP phase-separated with the carboxy-terminal domain of Pol II and nuclear actin. In addition to serum stimulation, we found nuclear actin also essential in enhancing Pol II clustering upon interferon-γ treatment. Taken together, our work unveils nuclear actin promotes the formation of transcription factory on inducible genes, acting as a general mechanism underlying the rapid response to environmental cues.
CLADES: a programmable sequence of reporters for lineage analysis
Authors: Garcia-Marques Jorge , Yang Ching-Po , Espinosa-Medina Isabel , Koyama Minoru , Lee Tzumin 
Published: May 2019

AbstractWe present CLADES (Cell Lineage Access Driven by an Edition Sequence), a technology for cell lineage studies based on CRISPR/Cas9. CLADES relies on a system of genetic switches to activate and inactivate reporter genes in a pre-determined order. Targeting CLADES to progenitor cells allows the progeny to inherit a sequential cascade of reporters, coupling birth order with reporter expression. This gives us temporal resolution of lineage development that can be used to deconstruct an extended cell lineage by tracking the reporters expressed in the progeny. When targeted to the germ line, the same cascade progresses across animal generations, marking each generation with the corresponding combination of reporters. CLADES thus offers an innovative strategy for making programmable cascades of genes that can be used for genetic manipulation or to record serial biological events.One Sentence SummaryA sequence of reporters for lineage analysis
NMR-based analysis of nucleotide π-stacking in a crowded environment: Implications for prebiotic reactions
Authors: Bapat Niraja V. , Paithankar Harshad , Chugh Jeetender , Rajamani Sudha 
Published: May 2019

AbstractThe inherent heterogeneity of the prebiotic milieu is often overlooked when studying nonenzymatic reactions. However, it is important to note that the prebiotic soup of a putative ‘RNA World’ would have been replete with a plethora of molecules resulting from complex chemical syntheses, as well as exogeneous delivery. The presence of such background molecules could lead to pertinent phenomenon such as molecular crowding, which can potentially affect how a reaction would advent in a crowded milieu. In the current study, we have analyzed the effect of crowding on the stacking ability of the RNA monomers, using Nuclear Magnetic Resonance (NMR) spectroscopy. Our findings corroborate that the purine monomers possess better stacking efficiency than pyrimidine based monomers. Significantly, this competence is further enhanced in the presence of a crowding agent. Interestingly, this enhanced stacking could result in higher sequestration of the purine monomers, putting their ready availability for relevant nonenzymatic polymerization and replication reactions into question. Taken together, this study demonstrates the need for systematic biophysical characterization of molecular crowding in the context of prebiotically pertinent processes. Unravelling such phenomena is essential to gather a real understanding of how the transition from abiotic to biotic, would have happened during the origin of life.