bluuebunny/crossref_metadata_2025_split huggingface dataset:
ClassifyingDrosophilaOlfactory Projection Neuron Subtypes by Single-cell RNA Sequencing
Authors: Li Hongjie , Horns Felix , Wu Bing , Xie Qijing , Li Jiefu , Li Tongchao , Luginbuhl David , Quake Stephen R. , Luo Liqun 
Published: June 2017

AbstractHow a neuronal cell type is defined and how this relates to its transcriptome are still open questions. TheDrosophilaolfactory projection neurons (PNs) are among the best-characterized neuronal types: Different PN classes target dendrites to distinct olfactory glomeruli and PNs of the same class exhibit indistinguishable anatomical and physiological properties. Using single-cell RNA-sequencing, we comprehensively characterized the transcriptomes of 40 PN classes and unequivocally identified transcriptomes for 6 classes. We found a new lineage-specific transcription factor that instructs PN dendrite targeting. Transcriptomes of closely-related PN classes exhibit the largest difference during circuit assembly, but become indistinguishable in adults, suggesting that neuronal subtype diversity peaks during development. Genes encoding transcription factors and cell-surface molecules are the most differentially expressed, indicating their central roles in specifying neuronal identity. Finally, we show that PNs use highly redundant combinatorial molecular codes to distinguish subtypes, enabling robust specification of cell identity and circuit assembly.
Polyclonal HIV envelope-specific breast milk antibodies limit founder SHIV acquisition and cell-associated virus loads in infant rhesus monkeys
Authors: Himes Jonathon E. , Goswami Ria , Mangan Riley J. , Kumar Amit , Jeffries Thomas L. , Eudailey Joshua A. , Heimsath Holly , Nguyen Quang N. , Pollara Justin , LaBranche Celia , Chen Meng , Vandergrift Nathan A. , Peacock James W. , Schiro Faith , Midkiff Cecily , Ferrari Guido , Montefiori David C. , Alvarez-Hernandez Xavier , Aye Pyone Pyone , Permar Sallie R. 
Published: June 2017

AbstractVertical HIV-1 transmission via breastfeeding is the predominant contributor to pediatric infections that are ongoing in this era of highly effective antiretroviral therapy (ART). Remarkably, only ~10% of infants chronically exposed to the virus via breastfeeding from untreated HIV-infected mothers become infected, suggesting the presence of naturally protective factors in breast milk. HIV-specific maternal antibodies are obvious candidates as potential contributors to this protection. This study assessed the protective capacity of common HIV envelope-specific non-broadly neutralizing antibodies isolated from breast milk of HIV-infected women in an infant rhesus monkey (RM), tier 2 SHIV oral challenge model. Prior to oral SHIV challenge, infant RMs were i.v. infused with either a single weakly-neutralizing monoclonal antibody (mAb), a tri-mAb cocktail with neutralizing and ADCC functionalities, or an anti-influenza HA control mAb. Of these groups, the fewest tri-mAb-treated infants developed plasma viremia (2/6, 3/6, and 6/8 animals viremic in tri-mAb, single-mAb, and control mAb groups, respectively). Tri-mAb-treated infants demonstrated significantly fewer transmitted/founder SHIV variants in plasma and decreased peripheral CD4+ T cell proviral loads at 8 week post-challenge compared to control mAb-treated infants. Abortive infection was observed as detectable CD4+ T cell provirus in non-viremic control mAb- and single-mAb-, but not tri-mAb-treated animals. Taken together, these results support the potential viability of maternal or infant vaccine strategies that elicit non-broadly neutralizing antibodies to prevent vertical transmission of HIV through breastfeeding.
Discovery of the first genome-wide significant risk loci for ADHD
Authors: Demontis Ditte , Walters Raymond K. , Martin Joanna , Mattheisen Manuel , Als Thomas D. , Agerbo Esben , Belliveau Rich , Bybjerg-Grauholm Jonas , Bækvad-Hansen Marie , Cerrato Felecia , Chambert Kimberly , Churchhouse Claire , Dumont Ashley , Eriksson Nicholas , Gandal Michael , Goldstein Jacqueline , Grove Jakob , Hansen Christine S. , Hauberg Mads E. , Hollegaard Mads V. , Howrigan Daniel P. , Huang Hailiang , Maller Julian , Martin Alicia R. , Moran Jennifer , Pallesen Jonatan , Palmer Duncan S. , Pedersen Carsten B. , Pedersen Marianne G. , Poterba Timothy , Poulsen Jesper B. , Ripke Stephan , Robinson Elise B. , Satterstrom Kyle F. , Stevens Christine , Turley Patrick , Won Hyejung ,   ADHD Working Group of the Psychiatric Genomics Consortium (PGC), Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, 23andMe Research Team, Andreassen Ole A. , Burton Christie , Boomsma Dorret , Cormand Bru , Dalsgaard Søren , Franke Barbara , Gelernter Joel , Geschwind Daniel , Hakonarson Hakon , Haavik Jan , Kranzler Henry , Kuntsi Jonna , Langley Kate , Lesch Klaus-Peter , Middeldorp Christel , Reif Andreas , Rohde Luis A. , Roussos Panos , Schachar Russell , Sklar Pamela , Sonuga-Barke Edmund , Sullivan Patrick F. , Thapar Anita , Tung Joyce , Waldman Irwin , Nordentoft Merete , Hougaard David M. , Werge Thomas , Mors Ole , Mortensen Preben B. , Daly Mark J. , Faraone Stephen V. , Børglum Anders D. , Neale Benjamin M. 
Published: June 2017

AbstractAttention-Deficit/Hyperactivity Disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of school-age children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no individual variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, revealing new and important information on the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes, as well as around brain-expressed regulatory marks. These findings, based on clinical interviews and/or medical records are supported by additional analyses of a self-reported ADHD sample and a study of quantitative measures of ADHD symptoms in the population. Meta-analyzing these data with our primary scan yielded a total of 16 genome-wide significant loci. The results support the hypothesis that clinical diagnosis of ADHD is an extreme expression of one or more continuous heritable traits.
Improving the value of public RNA-seq expression data by phenotype prediction
Authors: Ellis Shannon E. , Collado-Torres Leonardo , Leek Jeffrey T. 
Published: June 2017

AbstractBackgroundPublicly available genomic data are a valuable resource for studying normal human variation and disease, but these data are often not well labeled or annotated. The lack of phenotype information for public genomic data severely limits their utility for addressing targeted biological questions.ResultsWe develop anin silico phenotypingapproach for predicting critical missing annotation directly from genomic measurements using, well-annotated genomic and phenotypic data produced by consortia like TCGA and GTEx as training data. We applyin silico phenotypingto a set of 70,000 RNA-seq samples we recently processed on a common pipeline as part of therecount2project (https://jhubiostatistics.shinyapps.io/recount/). We use gene expression data to build and evaluate predictors for both biological phenotypes (sex, tissue, sample source) and experimental conditions (sequencing strategy). We demonstrate how these predictions can be used to study cross-sample properties of public genomic data, select genomic projects with specific characteristics, and perform downstream analyses using predicted phenotypes. The methods to perform phenotype prediction are available in thephenopredictR package (https://github.com/leekgroup/phenopredict) and the predictions forrecount2are available from therecountR package (https://bioconductor.org/packages/release/bioc/html/recount.html)ConclusionHaving leveraging massive public data sets to generate a well-phenotyped set of expression data for more than 70,000 human samples, expression data is available for use on a scale that was not previously feasible.
Chondroitin Sulfate Flourishes Gut Sulfatase-Secreting Bacteria To Damage Mucus Layers, Leak Bacterial Debris, And Trigger Inflammatory Lesions In Mice
Authors: Liao Tao , Chen Yan-Ping , Tan Li-Li , Li Chang-Qing , Wang Qi , Huang Shui-Qing , Huang Xin-An , Xu Qin , Zeng Qing-Ping 
Published: June 2017

AbstractBackgroundAn interaction of the food types with the gut microbiota changes is deeply implicated in human health and disease. To verify whether animal-based diets would lead to gut dysbiosis, systemic inflammation and inflammatory pathogenesis, we fed mice with chondroitin sulfate (CS), a sulfate-containingO-glycan naturally occurring in livestock and poultry products, and monitored the dynamic changes of microbial flores, inflammatory signatures, and pathogenic hallmarks.ResultsA metagenomic gut microbiota analysis revealed the overgrowth of sulfatase-secreting bacteria and sulfate-reducing bacteria in the gastrointestinal tracts of mice upon daily CS feeding. Sulfatase-secreting bacteria compromise gut integrity through prompting mucin degradation and mucus lesions, which were evident from the upregulation of secretary leukocyte protease inhibitor (SLPI) and mucin 1/4 (MUC-1/4). A synchronous elevation of lipopolysaccharide (LPS) and tumor necrosis factor α (TNF-α) levels in the serum as well as cerebral, hepatic, cardiac and muscular tissues suggests bacterial endotoxinemia, chronic low-grade inflammation and mitochondrial dysfunction, eventually leading to the onset of global inflammatory pathogenesis towards arthritis, dementia, tumor, and fatty liver.ConclusionsCS triggers the early-phase and multi-systemic pathogenesis like arthritis, dementia, tumor, and fatty liver by enhancing gut opportunistic infection and evoking low-grade inflammation in mice. A plausible reason for the inconsistency of CS in treatment of osteoarthritis (OA) was also discussed.
Tandem histone-binding domains enhance the activity of a synthetic chromatin effector
Authors: Tekel Stefan J. , Vargas Daniel , Song Lusheng , LaBaer Joshua , Haynes Karmella A. 
Published: June 2017

ABSTRACTFusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than DNA sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. We have previously reported the development and validation of the “Polycomb-based transcription factor” (PcTF), a fusion protein that recognizes histone modifications through a protein-protein interaction between its polycomb chromodomain (PCD) motif and trimethylated lysine 27 of histone H3 (H3K27me3) at genomic sites. We demonstrated that PcTF activates genes at methyl-histone-enriched loci in cancer-derived cell lines. However, PcTF induces modest activation of a methyl-histone associated reporter compared to a DNA-binding activator. Therefore, we modified PcTF to enhance its target affinity. Here, we demonstrate the activity of a modified regulator called Pc2TF, which has two tandem copies of the H3K27me3-binding PCD at the N-terminus. Pc2TF shows higher affinity for H3K27me3in vitroand shows enhanced gene activation in HEK293 cells compared to PcTF. These results provide compelling evidence that the intrinsic histone-binding activity of the PCD motif can be used to tune the activity of synthetic histone-binding transcriptional regulators.
Widespread signatures of negative selection in the genetic architecture of human complex traits
Authors: Zeng Jian , de Vlaming Ronald , Wu Yang , Robinson Matthew R , Lloyd-Jones Luke , Yengo Loic , Yap Chloe , Xue Angli , Sidorenko Julia , McRae Allan F , Powell Joseph E , Montgomery Grant W , Metspalu Andres , Esko Tonu , Gibson Greg , Wray Naomi R , Visscher Peter M , Yang Jian 
Published: June 2017

AbstractEstimation of the joint distribution of effect size and minor allele frequency (MAF) for genetic variants is important for understanding the genetic basis of complex trait variation and can be used to detect signature of natural selection. We develop a Bayesian mixed linear model that simultaneously estimates SNP-based heritability, polygenicity (i.e. the proportion of SNPs with nonzero effects) and the relationship between effect size and MAF for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N= 126,752), and show that on average across 28 traits, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (p < 0.05/28 =1.8×10−3) signatures of natural selection for 23 out of 28 traits including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. We further apply the method to 27,869 gene expression traits (N= 1,748), and identify 30 genes that show significant (p < 2.3×10−6) evidence of natural selection. All the significant estimates of the relationship between effect size and MAF in either complex traits or gene expression traits are consistent with a model of negative selection, as confirmed by forward simulation. We conclude that natural selection acts pervasively on human complex traits shaping genetic variation in the form of negative selection.
GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank
Authors: You Ronghui , Zhang Zihan , Xiong Yi , Sun Fengzhu , Mamitsuka Hiroshi , Zhu Shangfeng 
Published: June 2017

AbstractMotivation: Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only ¡1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multi-label classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore, homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-calleddifficultproteins, which have ¡60% sequence identity to proteins with annotations already. Thus, the vital and challenging problem now is to develop a method for SAFP, particularly for difficult proteins.Methods: The key of this method is to extract not only homology information but also diverse, deep-rooted information/evidence from sequence inputs and integrate them into a predictor in an efficient and also effective manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a new paradigm of machine learning, especially powerful for multi-label classification.Results: The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods.Contact:zhusf@fudan.edu.cn
Gene Regulatory Divergence Between Locally Adapted Ecotypes in Their Native Habitats
Authors: Gould Billie A. , Chen Yani , Lowry David B. 
Published: June 2017

ABSTRACTLocal adaptation is a key driver of ecological specialization and the formation of new species. Despite its importance, the evolution of gene regulatory divergence among locally-adapted populations is poorly understood, especially how that divergence manifests in nature. Here, we evaluate gene expression divergence and allele-specific gene expression responses for locally-adapted coastal perennial and inland annual accessions of the yellow monkeyflower,Mimulus guttatus, in a field reciprocal transplant experiment. Overall, 6765 (73%) of surveyed genes were differentially expressed between coastal and inland habitats, while 7213 (77%) were differentially expressed between the coastal perennial and inland annual accessions. Further, 18% of transcripts had significant genotype x site (GxE) effects. Habitat-specific differential expression was found for 62% of the GxE transcripts (differential expression in one habitat, but not the other), while only 94 (∼5%) GxE transcripts had crossing reaction norms.Cis-regulatory variation was pervasive, affecting 79% (5532) of differentially expressed genes. We detectedtranseffects for 52% (3611) of differentially expressed genes. Consistent with the supergene hypothesis of chromosome inversion evolution, a locally adaptive inversion was enriched forcis-regulatory divergence. These results provide multiple new insights into the evolution of transcriptome-wide gene regulatory divergence and plasticity among locally adapted populations.
Spike-timing pattern operates as gamma-distribution across cell types, regions and animal species and is essential for naturally-occurring cognitive states
Authors: Li Meng , Xie Kun , Kuang Hui , Liu Jun , Wang Deheng , Fox Grace E. , Wei Wei , Li Xiaojian , Li Yuhui , Zhao Fang , Chen Liang , Shi Zhifeng , Cui He , Mao Ying , Tsien Joe Z. 
Published: June 2017

AbstractSpike-timing patterns - crucial for synaptic plasticity and neural computation - are often modeled as Poisson-like random processes, log-normal distribution or gamma-distribution patterns, each with different underlying assumptions that may or may not be biologically true. However, it is not entirely clear whether (and how well) these different models would or would not capture spike-timing statistical patterns across different neurons, regions, animal species and cognitive states. Here, we examine statistical patterns of spike-timing irregularity in 13 different cortical and subcortical regions from mouse, hamster, cat and monkey brains. In contrast to the widely-assumed Poisson or log-normal distribution patterns, we show that spike-timing patterns of various projection neurons-including cortical excitatory principal cells, hippocampal pyramidal cells, inhibitory striatal medium spiny neurons and dopaminergic neurons, as well as fast-spiking interneurons – all invariantly conform to the gamma-distribution model. While higher regularity in spike-timing patterns are observed in a few cases, such as mouse DA neurons and monkey motor cortical neurons, there is no clear tendency in increased firing regularity from the sensory and subcortical neurons to prefrontal or motor cortices, as previously entertained. Moreover, gamma shapes of spike-timing patterns remain robust over various natural cognitive states, such as sleep, awake periods, or during fearful episodic experiences. Interestingly, ketamine-induced general anesthesia or unconsciousness is associated with the breakdown of forebrain spike patterns from a singular gamma distribution into two distinct subtypes of gamma distributions, suggesting the importance of this spike-timing pattern in supporting natural cognitive states. These results suggest that gamma-distribution patterns of spike timing reflect not only a fundamental property conserved across different neurons, regions and animal species, but also an operation crucial for supporting natural cognitive states. Such gamma-distribution-based spike-timing patterns can also have important implications for real-time neural coding and realistic neuromorphic computing.
Dynamical predictors of an imminent phenotypic switch in bacteria
Authors: Wang Huijing , Ray J. Christian J. 
Published: June 2017

AbstractSingle cells can stochastically switch across thresholds imposed by regulatory networks. Such thresholds can act as a tipping point, drastically changing global phenotypic states. In ecology and economics, imminent transitions across such tipping points can be predicted using dynamical early warning indicators. A typical example is "flickering" of a fast variable, predicting a longer-lasting switch from a low to a high state or vice versa. Considering the different timescales between metabolite and protein fluctuations in bacteria, we hypothesized that metabolic early warning indicators predict imminent transitions across a network threshold caused by enzyme saturation. We used stochastic simulations to determine if flickering predicts phenotypic transitions, accounting for a variety of molecular physiological parameters, including enzyme affinity, burstiness of enzyme gene expression, homeostatic feedback, and rates of metabolic precursor influx. In most cases, we found that metabolic flickering rates are robustly peaked near the enzyme saturation threshold. The degree of fluctuation was amplified by product inhibition of the enzyme. We conclude that sensitivity to flickering in fast variables may be a possible natural or synthetic strategy to prepare physiological states for an imminent transition.
Epigenetic resetting of human pluripotency
Authors: Guo Ge , Meyenn Ferdinand von , Rostovskaya Maria , Clarke James , Dietmann Sabine , Baker Duncan , Sahakyan Anna , Myers Samuel , Bertone Paul , Reik Wolf , Plath Kathrin , Smith Austin 
Published: June 2017

SUMMARYMuch attention has focussed on conversion of human pluripotent stem cells (PSC) to a more naive developmental status. Here we provide a method for resetting via transient histone deacetylase inhibition. The protocol is effective across multiple PSC lines and can proceed without karyotype change. Reset cells can be expanded without feeders with a doubling time of around 24 hours. WNT inhibition stabilises the resetting process. The transcriptome of reset cells diverges markedly from primed PSC and shares features with human inner cell mass (ICM). Reset cells activate expression of primate-specific transposable elements. DNA methylation is globally reduced to the level in the ICM but is non-random, with gain of methylation at specific loci. Methylation imprints are mostly lost, however. Reset cells can be re-primed to undergo tri-lineage differentiation and germline specification. In female reset cells, appearance of bi-allelic X-linked gene transcription indicates re-activation of the silenced X chromosome. On re-conversion to primed status, XIST-induced silencing restores monoallelic gene expression. The facile and robust conversion routine with accompanying data resources will enable widespread utilisation, interrogation, and refinement of candidate naïve cells.