bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative evaluation of full-length isoform quantification from RNA-Seq
Authors: Sarantopoulou Dimitra , Brooks Thomas G. , Nayak Soumyashant , Mrcela Anthonijo , Lahens Nicholas F. , Grant Gregory R. 
Published: July 2019

AbstractFull-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.
Evolclust: automated inference of evolutionary conserved gene clusters in eukaryotes
Authors: Marcet-Houben Marina , Gabaldón Toni 
Published: July 2019

AbstractMotivationThe evolution and role of gene clusters in eukaryotes is poorly understood. Currently, most studies and computational prediction programs limit their focus to specific types of clusters, such as those involved in secondary metabolism.ResultsWe present Evolclust, a python-based tool for the inference of evolutionary conserved gene clusters from genome comparisons, independently of the function or gene composition of the cluster. Evolclust predicts conserved gene clusters from pairwise genome comparisons and infers families of related clusters from multiple (all vs all) genome comparisons.Availabilityhttps://github.com/Gabaldonlab/EvolClust/Contacttgabaldon@crg.es
Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks
Authors: Klimm Florian , Toledo Enrique M. , Monfeuga Thomas , Zhang Fang , Deane Charlotte M. , Reinert Gesine 
Published: July 2019

AbstractRecent advances in single-cell RNA sequencing (scRNA-seq) have allowed researchers to explore transcriptional function at a cellular level. In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks (PPINs) that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted PPINs, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As a case study, we investigate RNA-sequencing data from human liver spheroids but the techniques described here are applicable to other organisms and tissues. scPPIN allows us to expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the PPIN significantly enriched which represent biological pathways. In these pathways, scPPIN also identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differentially expressed gene analysis.
Sequencing, de novo assembly and annotation of the genome of the scleractinian coral, Pocillopora acuta
Authors: Vidal-Dupiol Jeremie , Chaparro Cristian , Pratlong Marine , Pontarotti Pierre , Grunau Christoph , Mitta Guillaume 
Published: July 2019

AbstractCoral reefs are the most divers marine ecosystem. However, under the pressure of global changes and anthropogenic disturbances corals and coral reefs are declining worldwide. In order to better predict and understand the future of these organisms all the tools of modern biology are needed today. However, many NGS based approaches are not feasible in corals because of the lack of reference genomes. Therefore we have sequenced, de novo assembled, and annotated, the draft genome of one of the most studied coral species, Pocillopora acuta (ex damicornis). The sequencing strategy was based on four libraries with complementary insert size and sequencing depth (180pb, 100x; 3Kb, 25x; 8kb, 12x and 20 kb, 12x). The de novo assembly was performed with Platanus (352 Mb; 25,553 scaffolds; N50 171,375 bp). 36,140 genes were annotated by RNA-seq data and 64,558 by AUGUSTUS (Hidden-Markov model). Gene functions were predicted through Blast and orthology based approaches. This new genomic resource will enable the development of a large array of genome wide studies but also shows that the de novo assembly of a coral genome is now technically feasible and economically realistic.
Hierarchical chromatin organization detected by TADpole
Authors: Soler-Vila Paula , Pons Pol Cuscó , Farabella Irene , Di Stefano Marco , Marti-Renom Marc A. 
Published: July 2019

ABSTRACTThe rapid development of chromosome conformation capture (3C-based) techniques as well as super-resolution imaging together with bioinformatics analyses has been fundamental for unveiling that chromosomes are organized into the so-called topologically associating domains or TADs. While these TADs appear as nested patterns in the 3C-based interaction matrices, the vast majority of available computational methods are based on the hypothesis that TADs are individual and unrelated chromatin structures. Here we introduce TADpole, a computational tool designed to identify and analyze the entire hierarchy of TADs in intra-chromosomal interaction matrices. TADpole combines principal component analysis and constrained hierarchical clustering to provide an unsupervised set of significant partitions in a genomic region of interest. TADpole identification of domains is robust to the data resolution, normalization strategy, and sequencing depth. TADpole domain borders are enriched in CTCF and cohesin binding proteins, while the domains are enriched in either H3K36me3 or H3k27me3 histone marks. We show TADpole usefulness by applying it to capture Hi-C experiments in wild-type and mutant mouse strains to pinpoint statistically significant differences in their topological structure.
Mast seeding promotes evolution of scatter-hoarding
Authors: Zwolak Rafał , Clement Dale , Sih Andrew , Schreiber Sebastian J. 
Published: July 2019

ABSTRACTMany plant species worldwide are dispersed by scatterhoarding granivores: animals that hide seeds in numerous, small caches for future consumption. Yet, the evolution of scatterhoarding is difficult to explain because undefended caches are at high risk of pilferage. Previous models have attempted to solve this problem by giving cache owners large advantages in cache recovery, by kin selection, or by introducing reciprocal pilferage of “shared” seed resources. However, the role of environmental variability has been so far overlooked in this context. One important form of such variability is masting, which is displayed by many plant species dispersed by scatterhoarders. We use a mathematical model to investigate the influence of masting on the evolution of scatter-hoarding. The model accounts for periodically varying annual seed fall, caching and pilfering behavior, and the demography of scatterhoarders. The parameter values are based mostly on research on European beech (Fagus sylvatica) and yellow-necked mice (Apodemus flavicollis). Starvation of scatterhoarders between mast years decreases the population density that enters masting events, which leads to reduced seed pilferage. Satiation of scatterhoarders during mast events lowers the reproductive cost of caching (i.e. the cost of caching for the future rather than using seeds for current reproduction). These reductions promote the evolution of scatter-hoarding behavior especially when interannual variation in seed fall and the period between masting events are large.
HLA upregulation during dengue virus infection suppresses the natural killer cell response
Authors: McKechnie Julia L. , Beltran Davis , Pitti Arcelys , Saenz Lisseth , Araúz Ana B. , Vergara Rosemary , Harris Eva , Lanier Lewis L. , Blish Catherine A. , López-Vergès Sandra 
Published: July 2019

AbstractDengue virus (DENV) is the most prevalent mosquito-borne virus in the world and a major cause of morbidity in the tropics and subtropics. Upregulation of HLA class I molecules has long been considered a feature of DENV infection, yet this has not been evaluated in the setting of natural infection. Natural killer (NK) cells, an innate immune cell subset critical for mounting an early response to viral infection, are inhibited by self HLA class I, suggesting that upregulation of HLA class I during DENV infection could dampen the NK cell response. Here we addressed whether upregulation of HLA class I molecules occurs duringin vivoDENV infection and, if so, whether this suppresses the NK cell response. We found that HLA class I expression was indeed upregulated during acute DENV infection across multiple cell lineagesin vivo. To better understand the role of HLA class I upregulation, we infected primary human monocytes, a major target of DENV infection,in vitro. Upregulation of total HLA class I is dependent on active viral replication and is mediated in part by cytokines and other soluble factors induced by infection, while upregulation of HLA-E occurs in the presence of replication-incompetent virus. Importantly, blocking DENV-infected monocytes with a pan-HLA class I Fab nearly doubles the frequency of degranulating NK cells, while blocking HLA-E does not significantly improve the NK cell response. These findings demonstrate that upregulation of HLA class I during DENV infection suppresses the NK cell response, potentially contributing to disease pathogenesis.
Relative model fit does not predict topological accuracy in single-gene protein phylogenetics
Authors: Spielman Stephanie J. 
Published: July 2019

AbstractIt is regarded as best practice in phylogenetic reconstruction to perform relative model selection to determine an appropriate evolutionary model for the data. This procedure ranks a set of candidate models according to their goodness-of-fit to the data, commonly using an information theoretic criterion. Users then specify the best-ranking model for inference. While it is often assumed that better-fitting models translate to increase accuracy, recent studies have shown that the specific model employed may not substantially affect inferences. We examine whether there is a systematic relationship between relative model fit and topological inference accuracy in protein phylogenetics, using simulations and real sequences. Simulations employed site-heterogeneous mechanistic codon models that are distinct from protein-level phylogenetic inference models. This strategy allows us to investigate how protein models performs when they are mis-specified to the data, as will be the case for any real sequence analysis. We broadly find that phylogenies inferred across models with vastly different fits to the data produce highly consistent topologies. We additionally find that all models infer similar proportions of false positive splits, raising the possibility that all available models of protein evolution are similarly misspecified. Moreover, we find that the parameter-richGTRmodel, whose amino-acid exchangeabilities are free parameters, performs similarly to models with fixed exchangeabilities, although the inference precision associated withGTRmodels was not examined. We conclude that, while relative model selection may not hinder phylogenetic analysis on protein data, it may not offer specific predictable improvements and is not a reliable proxy for accuracy.
Detection of simple and complexde novomutations without, with, or with multiple reference sequences
Authors: Garimella Kiran V , Iqbal Zamin , Krause Michael A. , Campino Susana , Kekre Mihir , Drury Eleanor , Kwiatkowski Dominic , Sa Juliana M. , Wellems Thomas E. , McVean Gil 
Published: July 2019

AbstractThe characterization ofde novomutations in regions of high sequence and structural diversity from whole genome sequencing data remains highly challenging. Complex structural variants tend to arise in regions of high repetitiveness and low complexity, challenging bothde novoassembly, where short-reads do not capture the long-range context required for resolution, and mapping approaches, where improper alignment of reads to a reference genome that is highly diverged from that of the sample can lead to false or partial calls. Long-read technologies can potentially solve such problems but are currently unfeasible to use at scale. Here we present Corticall, a graph-based method that combines the advantages of multiple technologies and prior data sources to detect arbitrary classes of genetic variant. We construct multi-sample, coloured de Bruijn graphs from shortread data for all samples, align long-read-derived haplotypes and multiple reference data sources to restore graph connectivity information, and call variants using graph path-finding algorithms and a model for simultaneous alignment and recombination. We validate and evaluate the approach using extensive simulations and use it to characterize the rate and spectrum ofde novomutation events in 119 progeny from fourPlasmodium falciparumexperimental crosses, using long-read data on the parents to inform reconstructions of the progeny and to detect several known and novel non-allelic homologous recombination events.
Engineering Phage Host-Range and Suppressing Bacterial Resistance Through Phage Tail Fiber Mutagenesis
Authors: Yehl Kevin , Lemire Sébastien , Yang Andrew C. , Ando Hiroki , Mimee Mark , Der Torossian Torres Marcelo , de la Fuente-Nunez Cesar , Lu Timothy K. 
Published: July 2019

SUMMARYThe rapid emergence of antibiotic-resistant infections is prompting increased interest in phage-based antimicrobials. However, acquisition of resistance by bacteria is a major issue in the successful development of phage therapies. Through natural evolution and structural modeling, we identified host-range determining regions (HRDR) in the T3 phage tail fiber protein and developed a high-throughput strategy to genetically engineer these regions through site-directed mutagenesis. Inspired by antibody specificity engineering, this approach generates deep functional diversity (>107different members), while minimizing disruptions to the overall protein structure, resulting in synthetic “phagebodies”. We showed that mutating HRDRs yields phagebodies with altered host-ranges. Select phagebodies enable long-term suppression of bacterial growth by preventing the appearance of resistance in vitro and are functional in vivo using a mouse skin infection model. We anticipate this approach may facilitate the creation of next-generation antimicrobials that slow resistance development and could be extended to other viral scaffolds for a broad range of applications.HighlightsVastly diverse phagebody libraries containing 107different members were created.Structure-informed engineering of viral tail fibers efficiently generated host-range alterations.Phagebodies prevented the development of bacterial resistance across long timescalesin vitroand are functionalin vivo.
Targeted demethylation of H3K9me3 and H3K36me3 improves somatic cell reprogramming into cloned preimplantation but not postimplantation bovine concepti
Authors: Meng Fanli , Stamms Kathrin , Bennewitz Romina , Green Andria , Oback Fleur , Turner Pavla , Wei Jingwei , Oback Björn 
Published: July 2019

ABSTRACTCorrect reprogramming of epigenetic marks in the donor nuclei is a prerequisite for successful cloning by somatic cell transfer. In several mammalian species, repressive histone (H) lysine (K) trimethylation (me3) marks, in particular H3K9me3, form a major barrier to somatic cell reprogramming into pluripotency and totipotency. We engineered bovine embryonic fibroblasts for the doxycycline-inducible expression of Kdm4b, a demethylase that removes histone 3 lysine 9 trimethylation (H3K9me3) and H3K36me3 marks. Upon inducing Kdm4b, H3K9me3 and H3K36me3 levels reduced ∼3-fold and ∼5-fold, respectively, compared to non-induced controls. Donor cell quiescence has been previously associated with reduced somatic trimethylation levels and increased cloning efficiency in cattle. Simultaneously inducing Kdm4b expression (via doxycycline) and quiescence (via serum starvation), further reduced global H3K9me3 and H3K36me3 levels by a total of 18-fold and 35-fold, respectively, compared to non-induced, non-starved control fibroblasts. Following somatic cell transfer, Kdm4b-BEF fibroblasts reprogrammed significantly better into cloned blastocysts than non-induced donor cells. However, detrimethylated donors and sustained Kdm4b-induction during embryo culture did not increase rates of post-blastocyst development from implantation to survival into adulthood. In summary, KDM4B only improved somatic cell reprogramming into early preimplantation stages, highlighting the need for alternative experimental approaches to reliably improve somatic cloning efficiency in cattle.
Model to link cell shape and polarity with organogenesis
Authors: Nielsen Bjarke Frost , Nissen Silas Boye , Sneppen Kim , Trusina Ala , Mathiesen Joachim 
Published: July 2019

AbstractHow do tubes — gut or neural tube — form from flat sheets of polarized cells? The prevalent view is that it is a two-step process: first cells wedge to bend the sheet, then cells intercalate and extend the initial invagination into a tube. We computationally challenged this model by asking if one mechanism (either cell wedging or intercalation) may suffice for the entire sheet-to-tube transition. Using a physical model with epithelial cells represented by polarized point particles, we show that either cell intercalation or wedging alone can be sufficient and each can both bend the sheet and extend the tube. When working in parallel, the two mechanisms increase the robustness of the tube formation. The successful simulations of Drosophila salivary gland, Sea urchin gastrulation and mammalian neurulation support the generality of our results.
Hippocampal-striatal functional connectivity supports processing of temporal expectations from associative memory
Authors: van de Ven Vincent , Lee Chanju , Lifanov Julia , Kochs Sarach , Jansma Henk , Weerd Peter De 
Published: July 2019

AbstractThe hippocampus and dorsal striatum are both associated with temporal processing, but they are thought to play distinct roles. The hippocampus has been reported to contribute to storing temporal structure of events in memory, whereas the striatum contributes to temporal motor preparation and reward anticipation. Here, we asked whether the striatum cooperates with the hippocampus in processing the temporal context of memorized visual associations. In our task, participants were trained to implicitly form temporal expectations for one of two possible time intervals associated to specific cue-target associations, and subsequently were scanned using 7T functional magnetic resonance imaging. During scanning, learned temporal expectations could be violated when the pairs were presented at either the learned or not-learned time intervals. When temporal expectations were not met during testing trials, activity in hippocampal subfields CA3/CA2 and CA1 decreased while right putamen activity increased, compared to when temporal expectations were met. Further, psycho-physiological interactions showed that functional connectivity between left CA1 and caudate, as well as between putamen and caudate, decreased when temporal expectations were not met. Our results indicate that the hippocampus and striatum cooperate to process implicit temporal expectation from mnemonic associations, with different but complementary contributions from caudate and putamen. Our findings provide further support for a hippocampal-striatal network in temporal associative processing.
Compaction dynamics during progenitor cell self-assembly reveal granular mechanics
Authors: Smeets Bart , Pešek Jiří , Deckers Thomas , Hall Gabriella Nilsson , Cuvelier Maxim , Ongenae Steven , Bloemen Veerle , Luyten Frank P , Papantoniou Ioannis , Ramon Herman 
Published: July 2019

AbstractWe study the self-assembly dynamics of human progenitor cells in agarose micro-wells that are used for production of chondrogenic organoids. Using image analysis on time-lapse microscopy, we estimate the aggregate area in function of time for a large number of aggregates. In control conditions, the aggregate radius follows an exponential relaxation that is consistent with the dewetting dynamics of a liquid film. Introducing Y-27632 Rho kinase inhibitor, the compatibility with the liquid model is lost, and slowed down relaxation dynamics are observed. We demonstrate that these aggregates behave as granular piles undergoing compaction, with a density relaxation that follows a stretched exponential. Using simulations with an individual cell-based model, we construct a phase diagram of cell aggregates that suggests that the aggregate in presence of Rho kinase inhibitor approaches the glass transition.
Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders – findings from a Danish population-based study
Authors: Liu Xueping , Nudel Ron , Thompson Wesley K. , Appadurai Vivek , Schork Andrew J. , Buil Alfonso , Rasmussen Simon , Allesøe Rosa L. , Werge Thomas , Mors Ole , Børglum Anders D. , Hougaard David M. , Mortensen Preben B. , Nordentoft Merete , Benros Michael E. 
Published: July 2019

AbstractBackgroundPrevious studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders.MethodsWe used diagnostic information for patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on two diseases. The genetic factors were investigated using GWAS and HLA imputation data based on iPSYCH cohort.ResultsAmong 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1,383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two diseases (P=2.67×10-7, OR=1.38, 95%CI=1.22-1.56), with an overall bidirectional association wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR=1.13, 95%CI: 1.07-1.21, P=7.95×10-5) and vice versa (HR=1.27, 95%CI=1.16-1.39, P=8.77×10-15). Though PRSs were significantly correlated with both types of diagnosis, PRSs had little effect on the bidirectional relationship. Importantly, we for the first time observed 12 human leukocyte antigen (HLA) loci and 20 HLA alleles strongly associated with overall autoimmune diseases, but we did not find significant evidence of their associations with overall mental disorders.ConclusionsOur findings confirm the overall comorbidity and bidirectionality between autoimmune and mental disorders and discover HLA genes which are significantly associated with overall autoimmune diseases, but not with overall mental disorders.