bluuebunny/crossref_metadata_2025_split huggingface dataset:
GeneWalk identifies relevant gene functions for a biological context using network representation learning
Authors: Ietswaart Robert , Gyori Benjamin M. , Bachman John A. , Sorger Peter K. , Churchman L. Stirling 
Published: September 2019

AbstractThe primary bottleneck in high-throughput genomics experiments is identifying the most important genes and their relevant functions from a list of gene hits. Existing methods such as Gene Ontology (GO) enrichment analysis provide insight at the gene set level. For individual genes, GO annotations are static and biological context can only be added by manual literature searches. Here, we introduce GeneWalk (github.com/churchmanlab/genewalk), a method that identifies individual genes and their relevant functions under a particular experimental condition. After automatic assembly of an experiment-specific gene regulatory network, GeneWalk quantifies the similarity between vector representations of each gene and its GO annotations through representation learning, yielding annotation significance scores that reflect their functional relevance for the experimental context. We demonstrate the use of GeneWalk analysis of RNA-seq and nascent transcriptome (NET-seq) data from human cells and mouse brains, validating the methodology. By performing gene- and condition-specific functional analysis that converts a list of genes into data-driven hypotheses, GeneWalk accelerates the interpretation of high-throughput genetics experiments.
Simplification of ribosomes in bacteria with tiny genomes
Authors: Nikolaeva Daria D. , Gelfand Mikhail S. , Garushyants Sofya K. 
Published: September 2019

AbstractThe ribosome is an essential cellular machine performing protein biosynthesis. Its structure and composition are highly conserved in all species. However, some bacteria have been reported to have an incomplete set of ribosomal proteins. We have analyzed ribosomal protein composition in 214 small bacterial genomes (< 1 Mb) and found that although the ribosome composition is fairly stable, some ribosomal proteins may be absent, especially in bacteria with dramatically reduced genomes. The protein composition of the large subunit is less conserved than that of the small subunit. We have identified the set of frequently lost ribosomal proteins and demonstrated that they tend to be situated on the ribosome surface and have fewer contacts to other ribosome components. Moreover, some proteins are lost in an evolutionary correlated manner. The reduction of rRNA is also common in bacteria with tiny genomes with deletions mostly occurring in free loops. Finally, the loss of the anti-Shine-Dalgarno sequence is associated with the genome reduction, the number of lost ribosomal proteins, and with the loss of bL9 and TF.
Short-term test-retest reliability of the human intrinsic functional connectome
Authors: Tozzi Leonardo , Fleming Scott L. , Taylor Zachary D. , Raterink Cooper D. , Williams Leanne M. 
Published: September 2019

ABSTRACTFunctional connectivity is frequently used to quantify the complex synchronous distributed fluctuations in neuronal activity derived from functional Magnetic Resonance Imaging and to generate network representations of human brain function. Such “functional connectomes” have great promise for mechanistic studies and for clinical translation. However, we do not know to what extent a functional connectome is stable over time for an individual. In the present work, we evaluate the short-term test-retest reliability of functional connectomes in a large publicly available sample of healthy participants (N=833) scanned on two consecutive days. We also assess the consequences on reliability of three methodological procedures for which a clear guideline in the community is lacking: atlas choice, global signal regression and thresholding. By adopting the intraclass correlation coefficient as a reliability metric, we demonstrate that a relatively small portion of the intrinsic functional connectome is characterized by good (4-6%) to excellent (0.08-1%) stability over time. In particular, connectivity between prefrontal, parietal and temporal areas appears to be especially stable over short timescales. Also, while unreliable edges of the functional connectome are generally weak in terms of average functional connectivity, reliable edges are not necessarily strong. Methodologically, we demonstrate that multimodal parcellation and averaging of connections within known networks are practices that improve reliability. Harnessing this knowledge, for example by honing in on the reliable portion of the connectome, offers one way forward for studies of trait-like features within the normative connectome and for discovery of biomarkers in clinical cohorts.
Refining modules to determine functionally significant clusters in molecular networks
Authors: Kaalia Rama , Rajapakse Jagath C. 
Published: September 2019

AbstractModule detection algorithms relying on modularity maximization suffer from an inherent resolution limit that hinders detection of small topological modules, especially in molecular networks where most biological processes are believed to form small and compact communities. We propose a novel modular refinement approach that helps finding functionally significant modules of molecular networks. The module refinement algorithm improves the quality of topological modules in protein-protein interaction networks by finding biologically functionally significant modules. The algorithm is based on the fact that functional modules in biology do not necessarily represent those corresponding to maximum modularity. Larger modules corresponding to maximal modularity are incrementally re-modularized again under specific constraints so that smaller yet topologically and biologically valid modules are recovered. We show improvement in quality and functional coverage of modules using experiments on synthetic and real protein-protein interaction networks. Results were also compared with six existing methods available for clustering biological networks. In conclusion, the proposed algorithm finds smaller but functionally relevant modules that are undetected by classical quality maximization approaches for modular detection. The refinement procedure helps to detect more functionally enriched modules in protein-protein interaction networks, which are also more coherent with functionally characterised gene sets.
Post-fire vegetation succession in the Siberian subarctic tundra over 45 years
Authors: Heim Ramona J. , Bucharova Anna , Brodt Leya , Kamp Johannes , Rieker Daniel , Soromotin Andrey V. , Yurtaev Andrey , Hölzel Norbert 
Published: September 2019

AbstractWildfires are relatively rare in subarctic tundra ecosystems, but they can strongly change ecosystem properties. Short-term fire effects on subarctic tundra vegetation are well documented, but long-term vegetation recovery has been studied less. The frequency of tundra fires will increase with climate warming. Understanding the long-term effects of fire is necessary to predict future ecosystem changes.We used a space-for-time approach to assess vegetation recovery after fire over more than four decades. We studied soil and vegetation patterns on three large fire scars (>44, 28 and 12 years old) in dry, lichen-dominated forest tundra in Western Siberia. On 60 plots, we determined soil temperature and permafrost thaw depth, sampled vegetation and measured plant functional traits. We assessed trends in NDVI to support the field-based results on vegetation recovery.Soil temperature, permafrost thaw depth and total vegetation cover had recovered to pre-fire levels after >44 years, as well as total vegetation cover. In contrast, after >44 years, functional groups had not recovered to the pre-fire state. Burnt areas had lower lichen and higher bryophyte and shrub cover. The dominating shrub species,Betula nana, exhibited a higher vitality (higher specific leaf area and plant height) on burnt compared with control plots, suggesting a fire legacy effect in shrub growth. Our results confirm patterns of shrub encroachment after fire that were detected before in other parts of the Arctic and Subarctic. In the so far poorly studied Western Siberian forest tundra we demonstrate for the first time, long-term fire-legacies on the functional composition of relatively dry shrub- and lichen-dominated vegetation.
NLIMED: Natural Language Interface for Model Entity Discovery in Biosimulation Model Repositories
Authors: Munarko Yuda , Sarwar Dewan M. , Rampadarath Anand , Atalag Koray , Gennari John H. , Neal Maxwell L. , Nickerson David P. 
Published: September 2019

AbstractSemantic annotation is a crucial step to assure reusability and reproducibility of biosimulation models in biology and physiology. For this purpose, the COmputational Modeling in BIology NEtwork (COMBINE) community recommends the use of the Resource Description Framework (RDF). This grounding in RDF provides the flexibility to enable searching for entities within models (e.g. variables, equations, or entire models) by utilising the RDF query language SPARQL. However, the rigidity and complexity of the SPARQL syntax and the nature of the tree-like structure of semantic annotations, are challenging for users. Therefore, we propose NLIMED, an interface that converts natural language queries into SPARQL. We use this interface to query and discover model entities from repositories of biosimulation models. NLIMED works with the Physiome Model Repository (PMR) and the BioModels database and potentially other repositories annotated using RDF. Natural language queries are first ‘chunked’ into phrases and annotated against ontology classes and predicates utilising different natural language processing tools. Then, the ontology classes and predicates are composed as SPARQL and finally ranked using our SPARQL Composer and our indexing system. We demonstrate that NLIMED’s approach for chunking and annotating queries is more effective than the NCBO Annotator for identifying relevant ontology classes in natural language queries. Comparison of NLIMED’s behaviour against historical query records in the PMR shows that it can adapt appropriately to queries associated with well-annotated models.
Fine-mapping of SNCA in REM sleep behavior disorder and overt synucleinopathies
Authors: Krohn Lynne , Wu Richard YJ , Heilbron Karl , Ruskey Jennifer A. , Laurent Sandra B. , Blauwendraat Cornelis , Alam Armaghan , Arnulf Isabelle , Hu Michele T.M. , Dauvilliers Yves , Högl Birgit , Toft Mathias , Bjørnarå Kari Anne , Stefani Ambra , Holzknecht Evi , Charley Monaca Christelle , Beatriz Abril , Plazzi Giuseppe , Antelmi Elena , Ferini-Strambi Luigi , Young Peter , Heidbreder Anna , Cochen De Cock Valérie , Mollenhauer Brit , Sixel-Döring Friederike , Trenkwalder Claudia , Sonka Karel , Kemlink David , Figorilli Michela , Puligheddu Monica , Dijkstra Femke , Viaene Mineke , Oertel Wolfang , Toffoli Marco , Gigli Gian Luigi , Valente Mariarosaria , Gagnon Jean-François , Nalls Mike A. , Singleton Andrew B. ,   23andMe Research Team, Desautels Alex , Montplaisir Jacques Y. , Cannon Paul , Ross Owen A. , Boeve Bradley F. , Dupré Nicolas , Fon Edward A. , Postuma Ronald B. , Pihlstrøm Lasse , Rouleau Guy A. , Gan-Or Ziv 
Published: September 2019

AbstractObjectiveREM-sleep behavior disorder (RBD) is a prodromal synucleinopathy, as >80% will eventually convert to overt synucleinopathy. We performed an in-depth analysis of the SNCA locus to identify RBD-specific risk variants.MethodsFull sequencing and genotyping of SNCA was performed in isolated/idiopathic RBD (iRBD, n=1,076), Parkinson’s disease (PD, n=1,013), and dementia with Lewy bodies (DLB, n=415), and in control subjects (n=6,155). A replication cohort from 23andMe of PD patients with probable RBD (pRBD) was also analyzed (cases n=1,782, controls n=131,250). Adjusted logistic regression models and meta-analyses were performed. Effects on conversion rate were analyzed in 432 RBD patients with available data using Kaplan-Meier survival analysis.ResultsA 5’-region SNCA variant (rs10005233) was associated with iRBD (OR=1.43, p=1.1E-08), which was replicated in pRBD. This variant is in linkage disequilibrium (LD) with other 5’ risk variants across the different synucleinopathies. An independent iRBD-specific suggestive association (rs11732740) was detected at the 3’ of SNCA (OR=1.32, p=4.7E-04, not statistically significant after Bonferroni correction). Homozygous carriers of both iRBD-specific SNPs were at highly increased risk for iRBD (OR=5.74, p=2E-06). The known top PD-associated variant (3’ variant rs356182) had an opposite direction of effect in iRBD compared to PD.InterpretationThere is a distinct pattern of association at the SNCA locus in RBD as compared to PD, with an opposite direction of effect at the 3’ of SNCA. Several 5’ SNCA variants are associated with iRBD and with pRBD in overt synucleinopathies, and may suggest a cognitive component to this region.
Single cell transcriptomics reveals a signaling roadmap coordinating endoderm and mesoderm diversification during foregut organogenesis
Authors: Han Lu , Chaturvedi Praneet , Kishimoto Keishi , Koike Hiroyuki , Nasr Talia , Iwasawa Kentaro , Giesbrecht Kirsten , Witcher Phillip C , Eicher Alexandra , Haines Lauren , Lee Yarim , Shannon John M , Morimoto Mitsuru , Wells James M , Takebe Takanori , Zorn Aaron M 
Published: September 2019

ABSTRACTVisceral organs, such as the lungs, stomach, liver and pancreas, are derived from the fetal foregut through a series of inductive interactions between the definitive endoderm (DE) and the surrounding splanchnic mesoderm (SM). While patterning of DE lineages has been fairly well studied, paracrine signaling controlling SM regionalization and how this is coordinated with the epithelial identity during organogenesis is obscure. Here we used single cell transcriptomics to generate a high-resolution cell state map of the embryonic mouse foregut. This uncovered an unexpected diversity in the SM cells that developed in close register with the organ-specific epithelium. From these data, we inferred a spatiotemporal signaling roadmap of the combinatorial endoderm-mesoderm interactions that orchestrate foregut organogenesis. We validated key predictions with mouse genetics, showing the importance of endoderm-derived signals in mesoderm patterning. Finally, leveraging the signaling road map we generated different SM subtypes from human pluripotent stem cells (hPSCs), which previously have been elusive. The single cell data can be explored at:https://research.cchmc.org/ZornLab-singlecell.
Microrheology for Hi-C Data Reveals the Spectrum of the Dynamic 3D Genome Organization
Authors: Shinkai Soya , Sugawara Takeshi , Miura Hisashi , Hiratani Ichiro , Onami Shuichi 
Published: September 2019

ABSTRACTThe 1-dimensional information of genomic DNA is hierarchically packed inside the eukaryotic cell nucleus and organized in 3-dimensional (3D) space. Genome-wide chromosome conformation capture (Hi-C) methods have uncovered the 3D genome organization and revealed multiscale chromatin domains of compartments and topologically associating domains (TADs). Moreover, single-nucleosome live-cell imaging experiments have revealed the dynamic organization of chromatin domains caused by stochastic thermal fluctuations. However, the mechanism underlying the dynamic regulation of such hierarchical and structural chromatin units within the micro-scale thermal medium remains unclear. Microrheology is a way to measure dynamic viscoelastic properties coupling between thermal microenvironment and mechanical response. Here, we propose, to our knowledge, a new microrheology for Hi-C data to analyze the compliance property as a barometer of rigidness and flexibility of genomic regions along with the time evolution. Our method allows conversion of a Hi-C matrix into the spectrum of the rheological property along the genomic coordinate of a single chromosome. To demonstrate the technique, we analyzed Hi-C data during the neural differentiation of mouse embryonic stem cells. We found that TAD boundaries behave as more rigid nodes than the intra-TAD region. The spectrum clearly shows the rheological property of the dynamic chromatin domain formations at an individual time scale. Furthermore, we characterized the appearance of synchronous and liquid-like inter-compartment interactions in differentiated cells. Together, our microrheology provides physical insights revealing the dynamic 3D genome organization from Hi-C data.SIGNIFICANCEGenomic DNA is hierarchically packed inside the eukaryotic cell nucleus, and the genome organization in 3D contributes to proper genome functions at the multiscale chromatin domains. Although thermal fluctuations inevitably drive movements of the genome molecules in the micro-scale cell environment, there is no method, as yet, to quantify such dynamic 3D genome organization of hierarchical and structural chromatin units. Here, we describe a method to calculate rheological properties as barometers of flexibility and liquid-like behavior of genomic regions. We show that biologically relevant boundaries between chromatin domains are more rigid than the inside at a particular time scale. Our method allows interpretation of static and population-averaged genome conformation data as dynamic and hierarchical 3D genome picture.
A conserved activity for cohesin in bridging DNA molecules
Authors: Gutierrez-Escribano Pilar , Newton Matthew D. , Llauró Aida , Huber Jonas , Tanasie Loredana , Davy Joseph , Aly Isabel , Aramayo Ricardo , Montoya Alex , Kramer Holger , Stigler Johannes , Rueda David S. , Aragon Luis 
Published: September 2019

AbstractEssential processes such as accurate chromosome segregation, regulation of gene expression and DNA repair rely on protein-mediated DNA tethering. Sister chromatid cohesion requires the SMC complex cohesin to act as a protein linker that holds replicated chromatids together (1, 2). The molecular mechanism by which cohesins hold sister chromatids has remained controversial. Here, we used a single molecule approach to visualise the activity of cohesin complexes as they hold DNA molecules. We describe a DNA bridging activity that requires ATP and is conserved from yeast to human cohesin. We show that cohesin can form two distinct classes of bridges at physiological conditions, a “permanent bridge” able to resists high force (over 80pN) and a “reversible bridge” that breaks at lower forces (5-40pN). Both classes of bridges require Scc2/Scc4 in addition to ATP. We demonstrate that bridge formation requires physical proximity of the DNA segments to be tethered and show that “permanent” cohesin bridges can move between two DNA molecules but cannot be removed from DNA when they occur in cis. This suggests that separate physical compartments in cohesin molecules are involved in the bridge. Finally, we show that cohesin tetramers, unlike condensin, cannot compact linear DNA molecules against low force, demonstrating that the core activity of cohesin tetramers is bridging DNA rather than compacting it. Our findings carry important implications for the understanding of the basic mechanisms behind cohesin-dependent establishment of sister chromatid cohesion and chromosome architecture.
The Secretome of Liver X Receptor Agonist Treated Early Outgrowth Cells Decreases Atherosclerosis inLdlr-/- Mice
Authors: Rasheed Adil , Shawky Sarah , Tsai Ricky , Jung Richard G , Simard Trevor , Hibbert Benjamin , Rayner Katey J , Cummins Carolyn L 
Published: September 2019

AbstractObjectiveEndothelial progenitor cells (EPCs) promote the maintenance of the endothelium by the secretion of vasoreparative factors. A population of EPCs known as early outgrowth cells (EOCs) are currently being investigated as novel cell-based therapies for the treatment of cardiovascular disease. We previously demonstrated that the absence of liver x receptors (LXRs) is detrimental to the formation and function of EOCs under hypercholesterolemic conditions. Here, we investigate whether LXR gain-of-function in EOCs is beneficial for the treatment of atherosclerosis.Approach and ResultsEOCs were differentiated from the bone marrow of wildtype (WT) and LXR-knockout (Lxrαβ-/-) mice in the presence of vehicle or LXR agonist (GW3965). WT EOCs treated with GW3965 throughout differentiation showed reduced expression of endothelial lineage markers (Cd144, Vegfr2) compared to WT vehicle andLxrαβ-/- cells. GW3965-treated EOCs produced secreted factors that reduced monocyte adhesion to activated endothelial cells in culture. When injected into atherosclerosis-proneLdlr-/- mice, GW3965-treated EOCs and concentrated conditioned media (CM) from GW3965-treated EOCs, reduced plaque burden within the aortic sinus. Furthermore, when CM from human EOCs (obtained from patients with established CAD) were treated with GW3965, monocyte to endothelial adhesion was decreased suggesting the translatability of the results.ConclusionsEx vivoLXR agonist treatment of EOCs produces a secretome that decreases early atherosclerosis inLdlr-/- mice. CM from human EOCs significantly inhibits monocyte to endothelial adhesion. Thus, active factor(s) within the GW3965-treated EOC secretome have the potential to be useful for the treatment of atherosclerosis.
Normal human lymph node T follicular helper cells and germinal center B cells accessed via fine needle aspirations
Authors: Havenar-Daughton Colin , Newton Isabel G. , Zare Somaye Y , Reiss Samantha M. , Suh Min Ji , Hasteh Farnaz , Crotty Shane 
Published: September 2019

ABSTRACTGerminal centers (GC) are critically important for the maturation of the antibody response and the generation of memory B cells, which are the basis for long-term protection from pathogens. Germinal centers only occur in lymphoid tissue, such as lymph nodes, and are not present in blood. Therefore, cells of the germinal center, including GC B cells and GC T follicular helper (TFH) cells, are not well-studied in humans under normal healthy conditions, due to the limited availability of healthy lymph node samples. We used a minimally invasive, routine clinical procedure, lymph node fine needle aspirations (LN FNAs), to obtain lymph node cells from healthy human subjects to establish benchmarks of GC cells under noninflammatory conditions. This study of 50 lymph nodes demonstrates that human LN FNAs are a safe and feasible technique for immunological research, and defines benchmarks for human GC biology. The findings indicate that assessment of the GC response via LN FNAs will have application to the study of human vaccination, allergy, and autoimmune disease.