bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soil detrital inputs increase stimulate bacterial saprotrophs with different timing and intensity compared to fungal saprotrophs
Authors: Sukdeo Nicole , Teen Ewing , Michael Rutherford P. , Massicotte Hugues B. , Egger Keith N. 
Published: February 2018

AbstractSoils contain microbial inhabitants that differ in sensitivity to anthropogenic modification. Soil reclamation relies on monitoring these communities to evaluate ecosystem functions recovery post-disturbance. DNA metabarcoding and soil enzyme assays provide information about microbial functional guilds and organic matter decomposition activities respectively. However bacterial communities, fungal communities, and enzyme activities may not be equally informative for monitoring reclaimed soils. We compared effects of disturbance regimes applied to forest soils on fungal community composition, bacterial community composition, and potential hydrolase activities (N-acetyl-β-D-glucosaminidase, acid phosphatase, and cellobiohydrolase) at two times (14 days and 5 months post-disturbance) and depths (LFH versus mineral soil). Using disturbance versus control comparisons allowed us to identify genus-level disturbance-indicators and shifts in hydrolase activity levels. We observed declines in disturbed LFH fungal biomass (ergosterol) and declines in ectomycorrhizal fungi abundance across all disturbed samples, which prompted us to consider necromass-induced (fungal, root) saprotroph increases as disturbance indicators. Fungal community composition strongly shifted away from ecotmycorrhizal dominance to saprotroph dominance (i.e. increasedMortierella, andUmbelopsis) in disturbed plots at 5 months, while bacterial community composition did not shift to distinguish control plots from disturbed ones at either sampling time. Soil potential hydrolase data mainly indicated that mixing LFH material into mineral soil increases the measured activity levels compared to control and replaced mineral soil. Bacterial saprotrophs previously associated with mycelial necromass were detected across multiple regimes as disturbance indicators at 14 days post-disturbance. Our results confirm that ectomycorrhizal fungal genera are sensitive and persistently impacted by soil physical disturbances. Increases in saprotrophic bacterial genera are detectable 14 days pot-disturbance but only a few persist as disturbance indicators after several months. Potential hydrolase activities appear to be most useful for detecting the transfer of decomposition hotspots into mineral soils.
Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome
Authors: Aliaga Goltsman Daniela S. , Sun Christine L. , Proctor Diana M. , DiGiulio Daniel B. , Robaczewska Anna , Thomas Brian C. , Shaw Gary M. , Stevenson David K. , Holmes Susan P. , Banfield Jillian F. , Relman David A. 
Published: February 2018

ABSTRACTRecent studies suggest that the microbiome has an impact on gestational health and outcome. However, characterization of the pregnancy-associated microbiome has largely relied on 16S rRNA gene amplicon-based surveys. Here, we describe an assembly-driven, metagenomics-based, longitudinal study of the vaginal, gut, and oral microbiomes in 292 samples from ten subjects sampled every three weeks throughout pregnancy. 1.53 Gb of non-human sequence was assembled into scaffolds, and functional genes were predicted for gene-and pathway-based analyses. Vaginal assemblies were binned into 97 draft quality genomes. Redundancy analysis (RDA) of microbial community composition at all three body sites revealed gestational age to be a significant source of variation in patterns of gene abundance. In addition, health complications were associated with variation in community functional gene composition in the mouth and gut. The diversity of Lactobacillus iners-dominated communities in the vagina, unlike most other vaginal community types, significantly increased with gestational age. The genomes of co-occurring Gardnerella vaginalis strains with predicted distinct functions were recovered in samples from two subjects. In seven subjects, gut samples contained strains of the same Lactobacillus species that dominated the vaginal community of that same subject, and not other Lactobacillus species; however, these within-host strains were divergent. CRISPR spacer analysis suggested shared phage and plasmid populations across body sites and individuals. This work underscores the dynamic behavior of the microbiome during pregnancy and suggests the potential importance of understanding the sources of this behavior for fetal development and gestational outcome.
Family-Companion: analyse, visualise, browse, query and share your homology clusters
Authors: Cottret Ludovic , Briand Martial , Rancurel Corinne , Carrere Sébastien 
Published: February 2018

AbstractIdentifying homology groups in predicted proteomes from different biological sources allows biologists to address questions as diverse as inferring species-specific proteins or retracing the phylogeny of gene families. Nowadays, command-line software exists to infer homology clusters. However, computing and interpreting homology groups with this software remains challenging for biologists and requires computational skills.We propose Family-Companion, a web server dedicated to the computation, the analysis and the exploration of homology clusters. Family-Companion aims to fill the gap between analytic software and databases presenting orthologous groups based on a set of public data. It offers a user-friendly interface to launch or upload precomputed homology cluster analysis, to explore and share the results with other users. The exploration of the results is highly facilitated by interactive solutions to visualize proteome intersections via Venn diagrams, phylogenetic trees, multiple alignments, and also by querying the results by blast or by keywords.Family-Companion is available at http://family-companion.toulouse.inra.fr with a demo dataset and a set of video tutorials. Source code and installation protocol can be found at https://framagit.org/BBRIC/family-companion/. A container-based package simplifies the installation of the web-suite.
Dynamic embedding of salience coding in hippocampal spatial maps
Authors: Sato Masaaki , Mizuta Kotaro , Islam Tanvir , Kawano Masako , Takekawa Takashi , Gomez-Dominguez Daniel , Kim Karam , Yamakawa Hiroshi , Ohkura Masamichi , Fukai Tomoki , Nakai Junichi , Hayashi Yasunori 
Published: February 2018

SummaryHippocampal CA1 neurons participate in dynamic ensemble codes for space and memory. Prominent features of the environment are represented by an increased density of place cells, but cellular principles governing the formation and plasticity of such disproportionate maps are unknown. We thus imaged experience-dependent long-term changes in spatial representations at the cellular level in the CA1 deep sublayer in mice learning to navigate in a virtual-reality environment. The maps were highly dynamic but gradually stabilized as over-representations for motivational (reward) and environmental (landmark) salience emerged in different time courses by selective consolidation of relevant spatial representations. Relocation of the reward extensively reorganized pre-formed maps by a mechanism involving rapid recruitment of cells from the previous location followed by their re-stabilization, indicating that a subset of neurons encode reward-related information. The distinct properties of these CA1 cells may provide a substrate by which salient experience forms lasting and adaptable memory traces.
Evolutionary insights into Bean common mosaic necrosis virus and Cowpea aphid borne mosaic virus using global isolates and thirteen new near complete genomes from Kenya
Authors: Wainaina James M , Kubatko Laura , Harvey Jagger , Ateka Elijah , Makori Timothy , Karanja David , Boykin Laura M. , Kehoe Monica A. 
Published: February 2018

AbstractPlant viral diseases are one of the major limitations in legume production within sub Saharan Africa (SSA), as they account for up to 100 % in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out. The main aim was to gain insights into the selection pressure and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV), within symptomatic common beans and cowpeas. Eleven near complete genomes of BCMNV and two for CABMV sequences were obtained from SSA. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes was carried out. Three distinct well-supported clades were identified across the whole genome tree, and were in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. These results will contribute greatly to the knowledge gap surrounding the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and support the current breeding efforts towards resistance for BCMNV and CABMV.
Differential Expression of Coding and Long Noncoding RNAs in Keratoconus-affected Corneas
Authors: Khaled Mariam Lofty , Bykhovskaya Yelena , Yablonski Sarah E.R. , Li Hanzhou , Drewry Michelle D. , Aboobakar Inas F. , Estes Amy , Gao Xiaoyi , Stamer W. Daniel , Xu Hongyan , Allingham R. Rand , Hauser Michael A. , Rabinowitz Yaron S. , Liu Yutao 
Published: February 2018

AbstractPURPOSEKeratoconus (KC) is the most common corneal ectasia. We aimed to determine the differential expression of coding and long noncoding RNAs (lncRNAs) in human corneas affected with KC.METHODS200ng total RNA from the corneas of 10 KC patients and 8 non-KC normal controls was used to prepare sequencing libraries with the SMARTer Stranded RNA-Seq kit after ribosomal RNA depletion. Paired-end 50bp sequences were generated using Illumina HiSeq 2500 Sequencer. Differential analysis was done using TopHat and Cufflinks with a gene file from Ensembl and a lncRNA file from NONCODE. Pathway analysis was performed using WebGestalt. Using the expression level of differentially expressed coding and noncoding RNAs in each sample, we correlated their expression levels in KC and controls separately and identified significantly different correlations in KC against controls followed by visualization using Cytoscape.RESULTSUsing |fold change| ≥ 2 and a false discovery rate ≤ 0.05, we identified 436 coding RNAs and 584 lncRNAs with differential expression in the KC-affected corneas. Pathway analysis indicated the enrichment of genes involved in extracellular matrix, protein binding, glycosaminoglycan binding, and cell migration. Our correlation analysis identified 296 pairs of significant KC-specific correlations containing 117 coding genes enriched in functions related with cell migration/motility, extracellular space, cytokine response, and cell adhesion, suggesting the potential functions of these correlated lncRNAs, especially those with multiple pairs of correlations.CONCLUSIONSOur RNA-Seq based differential expression and correlation analyses have identified many potential KC contributing coding and noncoding RNAs.
FALCON-meta: a method to infer metagenomic composition of ancient DNA
Authors: Pratas Diogo , Pinho Armando J. , Silva Raquel M. , Rodrigues João M. O. S. , Hosseini Morteza , Caetano Tânia , Ferreira Paulo J. S. G. 
Published: February 2018

The general approaches to detect and quantify metagenomic sample composition are based on the alignment of the reads, according to an existing database containing reference microbial sequences. However, without proper parameterization, these methods are not suitable for ancient DNA. Quantifying somewhat dissimilar sequences by alignment methods is problematic, due to the need of fine-tuned thresholds, considering relaxed edit distances and the consequent increase of computational cost. Additionally, the choice of the thresholds poses the problem of how to quantify similarity without producing overestimated measures. We propose FALCON-meta, a compression-based method to infer metagenomic composition of next-generation sequencing samples. This unsupervised alignment-free method runs efficiently on FASTQ samples. FALCON-meta quickly learns how to give importance to the models that cooperate to predict similarity, incorporating parallelism and flexibility for multiple hardware characteristics. It shows substantial identification capabilities in ancient DNA without overestimation. In one of the examples, we found and authenticated an ancient Pseudomonas bacteria in a Mammoth mitogenome.FALCON-meta can be accessed at https://github.com/pratas/falcon.
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Authors: Chan Jeffrey , Perrone Valerio , Spence Jeffrey P. , Jenkins Paul A. , Mathieson Sara , Song Yun S. 
Published: February 2018

AbstractAn explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniques exist for more realistic, complex models. To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables. These challenges are traditionally tackled by likelihood-free methods that use scientific simulators to generate datasets and reduce them to hand-designed, permutation-invariant summary statistics, often leading to inaccurate inference. In this work, we develop an exchangeable neural network that performs summary statistic-free, likelihood-free inference. Our frame-work can be applied in a black-box fashion across a variety of simulation-based tasks, both within and outside biology. We demonstrate the power of our approach on the recombination hotspot testing problem, outperforming the state-of-the-art.
Gene expression is stronger associated with behaviour than with age and fertility in ant workers
Authors: Kohlmeier Philip , Alleman Austin R , Libbrecht Romain , Foitzik Susanne , Feldmeyer Barbara 
Published: February 2018

AbstractThe ecological success of social insects is based on division of labour, not only between queens and workers, but also among workers. Whether a worker tends the brood or forages is strongly influenced by age, fertility and nutritional status, with brood carers being younger, more fecund and corpulent. Here, we experimentally disentangle behaviour from age and fertility inTemnothorax longispinosusant workers and analyse how these parameters are linked to whole-body gene expression. Our transcriptome analysis reveals four times more genes associated with behaviour than with age and only few fertility-associated genes. Brood carers exhibited an upregulation of genes involved in lipid biosynthesis, whereas foragers invested in metabolism. Additional simulations revealed that the experimental disassociation of co-varying factors reduces transcriptomic noise, potentially explaining discrepancies between transcriptomic studies on worker behaviour in other social insects. Our study highlights the influence of nutritional status on task choice in ant workers.
Divergent genetic mechanism leads to spiny hair in rodents
Authors: Gonçalves Gislene L. , Maestri Renan , Moreira Gilson R. P. , Jacobi Marly A. M. , Freitas Thales R. O. , Hoekstra Hopi E. 
Published: February 2018

AbstractSpines, or modified hairs, have evolved multiple times in mammals, particularly in rodents. In this study, we investigated the evolution of spines in six rodent families. We first measured and compared the morphology and physical properties of hairs between paired spiny and non-spiny sister lineages. We found two distinct hair morphologies had repeatedly evolved in spiny rodents: hairs with a grooved cross-section and a second near cylindrical form. Compared to the ancestral elliptical-shaped hairs, spiny hairs had higher tension and stiffness, and overall, hairs with similar morphology had similar functional properties. To examine the genetic basis of this convergent evolution, we tested whether a single amino acid change (V370A) in theEcdysoplasin A receptor (Edar)gene is associated with spiny hair, as this substitution causes thicker and straighter hair in East Asian human populations. We found that most mammals have the common amino acid valine at position 370, but two species, the kangaroo rat (non-spiny) and spiny pocket mouse (spiny), have an isoleucine. Importantly, none of the variants we identified are associated with differences in rodent hair morphology. Thus, the specificEdarmutation associated with variation in human hair does not seem to play a role in modifying hairs in wild rodents, suggesting that different mutations inEdarand/or other genes are responsible for variation in the spiny hair phenotypes we observed within rodents.
GENOME REPORT: High-quality genome assemblies of 15 Drosophila species generated using Nanopore sequencing
Authors: Miller Danny E. , Staber Cynthia , Zeitlinger Julia , Hawley R. Scott 
Published: February 2018

ABSTRACTThe Drosophila genus is a unique group containing a wide range of species that occupy diverse ecosystems. In addition to the most widely studied species, Drosophila melanogaster, many other members in this genus also possess a well-developed set of genetic tools. Indeed, high-quality genomes exist for several species within the genus, facilitating studies of the function and evolution of cis-regulatory regions and proteins by allowing comparisons across at least 50 million years of evolution. Yet, the available genomes still fail to capture much of the substantial genetic diversity within the Drosophila genus. We have therefore tested protocols to rapidly and inexpensively sequence and assemble the genome from any Drosophila species using single-molecule sequencing technology from Oxford Nanopore. Here, we use this technology to present high-quality genome assemblies of 15 Drosophila species: 10 of the 12 originally sequenced Drosophila species (ananassae, erecta, mojavensis, persimilis, pseudoobscura, sechellia, simulans, virilis, willistoni, and yakuba), four additional species that had previously reported assemblies (biarmipes, bipectinata, eugracilis, and mauritiana), and one novel assembly (triauraria). Genomes were generated from an average of 29x depth-of-coverage data that after assembly resulted in an average contig N50 of 4.4 Mb. Subsequent alignment of contigs from the published reference genomes demonstrates that our assemblies could be used to close over 60% of the gaps present in the currently published reference genomes. Importantly, the materials and reagents cost for each genome was approximately $1,000 (USD). This study demonstrates the power and cost-effectiveness of long-read sequencing for genome assembly in Drosophila and provides a framework for the affordable sequencing and assembly of additional Drosophila genomes.
Maps of variability in cell lineage trees
Authors: Hicks Damien G. , Speed Terence P. , Yassin Mohammed , Russell Sarah M. 
Published: February 2018

AbstractNew approaches to lineage tracking allow the study of cell differentiation over many generations of cells during development in multicellular organisms. Understanding the variability observed in these lineage trees requires new statistical methods. Whereas invariant cell lineages, such as that for the nematodeCaenorhabditis elegans, can be described using a lineage map, defined as the fixed pattern of phenotypes overlaid onto the binary tree structure, the variability of cell lineages from higher organisms makes it impossible to draw a single lineage map. Here, we introduce lineage variability maps which describe the pattern of second-order variation throughout the lineage tree. These maps can be undirected graphs of the partial correlations between every lineal position or directed graphs showing the dynamics of bifurcated patterns in each subtree. By using the symmetry invariance of a binary tree to develop a generalized spectral analysis for cell lineages, we show how to infer these graphical models for lineages of any depth from sample sizes of only a few pedigrees. When tested on pedigrees fromC. elegansexpressing a marker for pharyngeal differentiation potential, the maps recover essential features of the known lineage map. When applied to highly-variable pedigrees monitoring cell size in T lymphocytes, the maps show how most of the phenotype is set by the founder naive T cell. Lineage variability maps thus elevate the concept of the lineage map to the population level, addressing questions about the potency and dynamics of cell lineages and providing a way to quantify the progressive restriction of cell fate with increasing depth in the tree.Author summaryMulticellular organisms develop from a single fertilized egg by sequential cell divisions. The progeny from these divisions adopt different traits that are transmitted and modified through many generations. By tracking how cell traits change with each successive cell division throughout the family, or lineage, tree, it has been possible to understand where and how these modifications are controlled at the single-cell level, thereby addressing questions about, for example, the developmental origin of tissues, the sources of differentiation in immune cells, or the relationship between primary tumors and metastases. Such lineages often show large variability, with apparently identical founder cells giving rise to different patterns of descendants. Fundamental scientific questions, such as about the range of possible cell types a cell can give rise to, are often about this variability. To characterize this variation, and thus understand the lineage at the population level, we introduce lineage variability maps. Using data from worm and mammalian cell lineages we show how these maps provide quantifiable answers to questions about any developing lineage, such as the potency of founder cells and the progressive restriction of cell fate at each stage in the tree.