bluuebunny/crossref_metadata_2025_split huggingface dataset:
rSeqTU – a machine-learning based R package for prediction of bacterial transcription units
Authors: Niu Sheng-Yong , Liu Binqiang , Ma Qin , Chou Wen-Chi 
Published: February 2019

AbstractA transcription unit (TU) is composed of one or multiple adjacent genes on the same strand that are co-transcribed in mostly prokaryotes. Accurate identification of TUs is a crucial first step to delineate the transcriptional regulatory networks and elucidate the dynamic regulatory mechanisms encoded in various prokaryotic genomes. Many genomic features, e.g., gene intergenic distance, and transcriptomic features including continuous and stable RNA-seq reads count signals, have been collected from a large amount of experimental data and integrated into classification techniques to computationally predict genome-wide TUs. Although some tools and web servers are able to predict TUs based on bacterial RNA-seq data and genome sequences, there is a need to have an improved machine-learning prediction approach and a better comprehensive pipeline handling QC, TU prediction, and TU visualization. To enable users to efficiently perform TU identification on their local computers or high-performance clusters and provide a more accurate prediction, we develop an R package, named rSeqTU. rSeqTU uses a random forest algorithm to select essential features describing TUs and then uses support vector machine (SVM) to build TU prediction models. rSeqTU (available at https://s18692001.github.io/rSeqTU/) has six computational functionalities including read quality control, read mapping, training set generation, random-forest-based feature selection, TU prediction, and TU visualization.
Does Long-Term Selection for Development Time Result in Canalization: A Test UsingDrosophila melanogaster
Authors: Ghosh Shampa M. , Satish K. M. , Mohan J. , Joshi Amitabh 
Published: February 2019

AbstractCanalization denotes the robustness of a trait against genetic or environmental perturbation. Plasticity, in contrast indicates the environmental sensitivity of a trait. Stabilizing selection is thought to increase canalization of a trait, whereas directional selection is often thought to lead to decanalization. However, the relationship between selection, canalization and plasticity remains largely unclear. Experimental evolution is a powerful approach for addressing fundamental questions in evolution. Here, we ask whether long-term directional selection for reduced pre-adult development time inDrosophila melanogasterresults in the evolution of increased canalization for development time, the trait under primary selection. We additionally investigate whether pre-adult survivorship, a trait only secondarily under selection in this experimental regime, also evolves to become canalized. We examine canalization both in terms of stability of population means and of within population variability across two environmental axes. We used four large outbred populations ofD. melanogasterselected for rapid pre-adult development and early reproduction for 295 generations, and four corresponding ancestral control populations that were not under conscious selection for development time or early reproduction. The selected populations had evolved 25% reduction in both development time and pre-adult survivorship at the time of this study. We studied development time and pre-adult survivorship of the selected populations and controls across various combinations ofrearing temperature and larval density. Development time in the selected populations had become more canalized than controls with regard to density, but not temperature. Canalization of development time across density appears to have evolved due to evolutionary changes in the lifehistory and physiology of the selected populations. Pre-adult survivorship, only a secondary correlate of fitness in the selected populations, did not show any clear trend in terms of canalization with regard to either density or temperature, and, overall variation in the trait was greater compared to development time within and across environments. Whether long-term directional selection canalizes or not, therefore, appears to be dependent in a complex way on specific interactions of trait, selection regime and environmental factor in the context of the ecology and physiology of the popualtions under study.
An Array of 60,000 Antibodies for Proteome-Scale Antibody Generation and Target Discovery
Authors: Wang Zhaohui , Li Yang , Hou Bing , Pronobis Mira I. , Wang Yuemeng , Wang Mingqiao , Cheng Guangcun , Zhang Zhe , Weng Weining , Wang Yiqiang , Tang Yanfang , Xu Xuefan , Pan Rong , Lin Fei , Wang Nan , Chen Ziqing , Wang Shiwei , Ma Luyan zulie , Li Yangrui , Huang Dongliang , Jiang Li , Wang Zhiqiang , Zeng Wenfang , Zhang Ying , Du Xuemei , Lin Ying , Li Zhiqing , Xia Qingyou , Geng Jing , Dai Huaping , Wang Chen , Yu Yuan , Zhao Xiaodong , Yuan Zheng , Yan Jian , Ren Bing , Nie Qinghua , Zhang Xiquan , Wang Kun , Chen Fuling , Zhang Qin , Zhu Yuxian , Poss Kenneth D. , Tao Shengce , Meng Xun 
Published: February 2019

AbstractAntibodies are essential for elucidating the roles of genes decoded by genome sequencing. However, affordable technology for proteome-scale antibody generation does not exist. To address this, we developed the Proteome Epitope Tag Antibody Library (PETAL) and its array. PETAL consists of 62,208 mAbs against 15,199 peptides from diverse proteomes. PETAL harbors binders for a great multitude of proteins in nature due to antibody multispecificity, an intrinsic feature of an antibody. Distinctive combinations of 10,000-20,000 mAbs were found to target specific proteomes by array screening. Phenotype-specific mAb-target pairs were discovered for maize and zebrafish samples. Immunofluorescence and flow cytometry mAbs for human membrane proteins and ChIP-seq mAbs for transcription factors were identified from respective proteome-binding PETAL mAbs. Differential screening of cell surface proteomes of tumor and normal tissues discovered internalizing tumor antigens for antibody-drug conjugates. By discovering high affinity mAbs at a fraction of current time and cost, PETAL enables proteome-scale antibody generation and target discovery.
Optimization of graph construction can significantly increase the power of structural brain network studies
Authors: Messaritaki Eirini , Dimitriadis Stavros I. , Jones Derek K. 
Published: February 2019

AbstractStructural brain networks derived from diffusion magnetic resonance imaging data have been used extensively to describe the human brain, and graph theory has allowed quantification of their network properties. Schemes used to construct the graphs that represent the structural brain networks differ in the metrics they use as edge weights and the algorithms they use to define the network topologies. In this work, twenty graph construction schemes were considered. The schemes use the number of streamlines, the fractional anisotropy, the mean diffusivity or other attributes of the tracts to define the edge weights, and either an absolute threshold or a data-driven algorithm to define the graph topology. The test-retest data of the Human Connectome Project were used to compare the reproducibility of the graphs and their various attributes (edges, topologies, graph theoretical metrics) derived through those schemes, for diffusion images acquired with three different diffusion weightings. The impact of the scheme on the statistical power of the study and on the number of participants required to detect a difference between populations or an effect of an intervention was also calculated.The reproducibility of the graphs and their attributes depended heavily on the graph construction scheme. Graph reproducibility was higher for schemes that used thresholding to define the graph topology, while data-driven schemes performed better at topology reproducibility. Additionally, schemes that used thresholding resulted in better reproducibility for local graph theoretical metrics, while data-driven schemes performed better for global metrics. Crucially, the number of participants required to detect a difference between populations or an effect of an intervention could change by a large factor depending on the scheme used, affecting the power of studies to reveal the effects of interest.
EWAS-Galaxy: a tools suite for population epigenetics integrated into Galaxy
Authors: Murat Katarzyna , Grüning Björn , Poterlowicz Paulina Wiktoria , Westgate Gillian , Tobin Desmond J , Poterlowicz Krzysztof 
Published: February 2019

AbstractBackgroundEpigenome-wide association studies (EWAS) analyse genome-wide activity of epigenetic marks in cohorts of different individuals to find associations between epigenetic variation and phenotype. One of the most common technique used in EWAS studies is the Infinium Methylation Assay, which quantifies the DNA methylation level of over 450k loci. Although a number of bioinformatics tools have been developed to analyse the assay they require some programming skills and experience to use them.ResultsWe have developed a collection of user-friendly tools for the Galaxy platform for those without experience aimed at DNA methylation analysis using the Infinium Methylation Assay. Our tool suite is integrated into Galaxy (http://galaxyproject.org), web based platform. This allows users to analyse data from the Infinium Methylation Assay in the easiest possible way.ConclusionsThe EWAS suite provides a group of integrated tools that combine analytical methods into a range of handy analysis pipelines. Our tool suite is available from the Galaxy test toolshed, GitHub repository and also as a Docker image. The aim of this project is to make EWAS analysis more flexible and accessible to everyone.
Neural network-based alterations during repeated heat pain stimulation in major depression
Authors: Bilek Edda , Zang Zhenxiang , Wolf Isabella , Henrich Florian , Mößnang Carolin , Braun Urs , Treede Rolf-Detlef , Magerl Walter , Meyer-Lindenberg Andreas , Tost Heike 
Published: February 2019

AbstractThe current study aimed to identify alterations in brain activation and connectivity related to nociceptive processing and pain sensitization in major depressive disorder (MDD), using repeated heat pain stimulation during functional magnetic resonance imaging (fMRI) in 37 MDD patients and 33 healthy controls. Regional activation did not differ between groups, but functional connectivity was significantly decreased in MDD in a neural network connecting frontal, temporal and occipital areas (family-wise error (FWE)-corrected pFWE = 0.045). Supplemental analyses suggested a significant association between network connectivity and trait neuroticism (p = 0.007) but not with the clinical state or familiar risk of MDD (all p values > 0.13). Our data relate a network-based phenotype for altered pain processing and antinociceptive control to MDD and encourage future studies on the shared intermediate neural psychological risk architecture of MDD and chronic pain.
Bat-fruit networks structure resist habitat modification but species roles change in the most transformed habitats
Authors: Castaño John Harold , Andrés Carranza-Quiceno Jaime , Pérez-Torres Jairo 
Published: February 2019

AbstractSpecies do not function as isolated entities, rather they are organized in complex networks of interactions. These networks develop the ecological processes that provide ecosystem services for human societies. Understanding the causes and consequences of changes in ecological networks due to landscape modification would allow us to understand the consequences of ecological processes. However, there is still theoretical controversy and few empirical data on the effects of network characteristics on the loss of natural environments. We investigate how bat–fruit networks respond to three landscapes representing the gradient of modification from pre-montane forest to a heterogeneous agricultural landscape in the Colombian Andes (continuous forests, forest fragments, and crops). We found that forest contained smaller bat–fruit networks than forest fragments and crops. Modified landscapes had similar ecological network structures to forest (nestedness and modularity), but crops contained less specialized networks compared to forests and fragments and the species role in these habitats change. The networks in the rural coffee landscape maintain their structure in the different transformation scenarios, indicating that seed dispersal services are maintained even in the most transformed scenarios. This could be related to the high heterogeneity present in this rural landscape. Although the number of species does not decrease due to transformations, species change their roles in the most transformed habitats. This result sheds light on the way that biodiversity responds to anthropogenic transformations, showing higher stability than theoretically predicted.
A primer on high-dimensional data analysis workflows for studying visual cortex development and plasticity
Authors: Balsor Justin L. , Jones David G. , Murphy Kathryn M. 
Published: February 2019

AbstractNew techniques for quantifying large numbers of proteins or genes are transforming the study of plasticity mechanisms in visual cortex (V1) into the era of big data. With those changes comes the challenge of applying new analytical methods designed for high-dimensional data. Studies of V1, however, can take advantage of the known functions that many proteins have in regulating experience-dependent plasticity to facilitate linking big data analyses with neurobiological functions. Here we discuss two workflows and provide example R code for analyzing high-dimensional changes in a group of proteins (or genes) using two data sets. The first data set includes 7 neural proteins, 9 visual conditions, and 3 regions in V1 from an animal model for amblyopia. The second data set includes 23 neural proteins and 31 ages (20d-80yrs) from human post-mortem samples of V1. Each data set presents different challenges and we describe using PCA, tSNE, and various clustering algorithms including sparse high-dimensional clustering. Also, we describe a new approach for identifying high-dimensional features and using them to construct aplasticity phenotypethat identifies neurobiological differences among clusters. We include an R package “v1hdexplorer” that aggregates the various coding packages and custom visualization scripts written in R Studio.
Transcript expression-aware annotation improves rare variant discovery and interpretation
Authors: Cummings Beryl B. , Karczewski Konrad J. , Kosmicki Jack A. , Seaby Eleanor G. , Watts Nicholas A. , Singer-Berk Moriel , Mudge Jonathan M. , Karjalainen Juha , Satterstrom F. Kyle , O’Donnell-Luria Anne , Poterba Timothy , Seed Cotton , Solomonson Matthew , Alföldi Jessica ,   The Genome Aggregation Database Production Team,   The Genome Aggregation Database Consortium, Daly Mark J. , MacArthur Daniel G. 
Published: February 2019

AbstractThe acceleration of DNA sequencing in patients and population samples has resulted in unprecedented catalogues of human genetic variation, but the interpretation of rare genetic variants discovered using such technologies remains extremely challenging. A striking example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Through manual curation of putative loss of function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)(1), we show that one explanation for this paradox involves alternative mRNA splicing, which allows exons of a gene to be expressed at varying levels across cell types. Currently, no existing annotation tool systematically incorporates this exon expression information into variant interpretation. Here, we develop a transcript-level annotation metric, the proportion expressed across transcripts (pext), which summarizes isoform quantifications for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression project(2) (GTEx) and show that it clearly differentiates between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder (ASD) and developmental disorders and intellectual disability (DD/ID) to show that pLoF variants in weakly expressed regions have effect sizes similar to those of synonymous variants, while pLoF variants in highly expressed exons are most strongly enriched among cases versus controls. Our annotation is fast, flexible, and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for rare disease diagnosis, rare variant burden analyses in complex disorders, and curation and prioritization of variants in recall-by-genotype studies.
Control of Hematopoietic Stem and Progenitor Cell Function Through Epigenetic Regulation of Energy Metabolism and Genome Integrity
Authors: Yang Zhenhua , Shah Kushani , Khodadadi-Jamayran Alireza , Jiang Hao 
Published: February 2019

SUMMARYIt remains largely unclear how stem cells regulate bioenergetics and genome integrity to ensure tissue homeostasis. Here, our integrative gene analyses suggest metabolic and genotoxic stresses may underlie the common functional defects of both fetal and adult hematopoietic stem and progenitor cells (HSPCs) upon loss of DPY30, an epigenetic modulator that facilitates H3K4 methylation. DPY30 directly regulates expression of several key glycolytic genes, and its loss in HSPCs critically impaired energy metabolism, including both glycolytic and mitochondrial pathways. We also found significant increase in DNA breaks as a result of impaired DNA repair upon DPY30 loss, and inhibition of DNA damage response partially rescued clonogenicity of the DPY30-deficient HSPCs. Moreover, CDK inhibitor p21 was upregulated in DPY30-deficient HSPCs, and p21 deletion alleviated their functional defect. These results demonstrate that epigenetic mechanisms by H3K4 methylation play a crucial role in HSPC function through control of energy metabolism and protecting genome integrity.
Spatial heterogeneity and organization of tumor mutation burden and immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer
Authors: Xu Hongming , Park Sunho , Clemenceau Jean René , Choi Jinhwan , Radakovich Nathan , Lee Sung Hak , Hwang Tae Hyun 
Published: February 2019

AbstractHigh-TMB (TMB-H) could result in an increased number of neoepitopes from somatic mutations expressed by a patient’s own tumor cell which can be recognized and targeted by neighboring tumor-infiltrating lymphocytes (TILs). Deeper understanding of spatial heterogeneity and organization of tumor cells and their neighboring immune infiltrates within tumors could provide new insights into tumor progression and treatment response. Here we developed and applied computational approaches using digital whole slide images (WSIs) to investigate spatial heterogeneity and organization of regions harboring TMB-H tumor cells and TILs within tumors, and its prognostic utility. In experiments using WSIs from The Cancer Genome Atlas bladder cancer (BLCA), our findings show that WSI-based approaches can reliably predict patient-level TMB status and delineate spatial TMB heterogeneity and co-organization with TILs. TMB-H patients with low spatial heterogeneity enriched with high TILs show improved overall survival indicating a prognostic role of spatial TMB and TILs information in BLCA.
A chromatin modulator sustains self-renewal and enables differentiation of postnatal neural stem and progenitor cells
Authors: Shah Kushani , King Gwendalyn D. , Jiang Hao 
Published: February 2019

ABSTRACTIt remains unknown whether H3K4 methylation, an epigenetic modification associated with gene activation, regulates fate determination of the postnatal neural stem and progenitor cells (NSCs and NPCs, or NSPCs). Here we show that the Dpy30 subunit of the major H3K4 methyltransferase complexes is preferentially expressed at a high level in NSCs and NPCs. By genetically inactivating Dpy30 in specific regions of mouse brain, we demonstrate a crucial role of efficient H3K4 methylation in maintaining both the self-renewal and differentiation capacity of postnatal NSPCs. Dpy30 inactivation results in deficiency in global H3K4 methylation, and disrupts development of hippocampus and especially the dentate gyrus and subventricular zone, the major regions for postnatal NSC activities. By in vitro assays on neurospheres from mouse brains as well as human and mouse NPCs, we show that Dpy30 is indispensable for sustaining the self-renewal and proliferation of NSPCs in a cell-intrinsic manner, and also enables the differentiation of mouse and human NPCs to neuronal and glial lineages. Dpy30 directly regulates H3K4 methylation and the induction of several genes critical in neurogenesis. These findings link a prominent epigenetic mechanism of gene expression to the fundamental properties of NSPCs, and may have implications in neurodevelopmental disorders.SIGNIFICANCE STATEMENTAs a highly prominent epigenetic mark that is associated with gene activation and a number of neurodevelopmental disorders in human, the role of histone H3K4 methylation in the fate determination of neural stem cells is unclear. Result of this study uncover a profound role of this epigenetic modification in the fundamental properties of postnatal neural stem cells, including self-renewal and differentiation, and may have implications for a better understanding and treatment of a broad spectrum of neurodevelopmental disorders associated with H3K4 methylation modulators.
TheDrosophila melanogasterPIF1 helicase promotes survival during replication stress and processive DNA synthesis during double-strand gap repair
Authors: Kocak Ece , Dykstra Sarah , Nemeth Alexandra , Coughlin Catherine G. , Rodgers Kasey , McVey Mitch 
Published: February 2019

AbstractPIF1 is a 5’ to 3’ DNA helicase that can unwind double-stranded DNA and disrupt nucleic acid-protein complexes. InSaccharomyces cerevisiae, Pif1 plays important roles in mitochondrial and nuclear genome maintenance, telomere length regulation, unwinding of G-quadruplex structures, and DNA synthesis during break-induced replication. Some, but not all, of these functions are shared with other eukaryotes. To gain insight into the evolutionarily conserved functions of PIF1, we createdpif1null mutants inDrosophila melanogasterand assessed their phenotypes throughout development. We found thatpif1mutant larvae exposed to high concentrations of hydroxyurea, but not other DNA damaging agents, experience reduced survival to adulthood. Embryos lacking PIF1 fail to segregate their chromosomes efficiently during early nuclear divisions, consistent with a defect in DNA replication. Furthermore, loss of the BRCA2 protein, which is required for stabilization of stalled replication forks in metazoans, causes synthetic lethality in third instar larvae lacking either PIF1 or the polymerase delta subunit POL32. Interestingly,pif1mutants have a reduced ability to synthesize DNA during repair of a double-stranded gap, but only in the absence of POL32. Together, these results support a model in which Drosophila PIF1 functions with POL32 during times of replication stress but acts independently of POL32 to promote synthesis during double-strand gap repair.