bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal samples of bacterial genomes potentially bias evolutionary analyses
Authors: Arnold B.J. , Hanage W.P. 
Published: January 2017

AbstractSamples of bacteria collected over a period of time are attractive for several reasons, including the ability to estimate the molecular clock rate and to detect fluctuations in allele frequencies over time. However, longitudinal datasets are occasionally used in analyses that assume samples were collected contemporaneously. Using both simulations and genomic data fromNeisseria gonorrhoeae, Streptococcus mutans, Campylobacter jejuni, and Helicobacter pylori, we show that longitudinal samples (spanning more than a decade in real data) may suffer from considerable bias that inflates estimates of recombination and the number of rare mutations in a sample of genomic sequences. While longitudinal data are frequently accounted for using the serial coalescent, many studies use other programs or metrics, such as Tajima’s D, that are sensitive to these sampling biases and contain genomic data collected across many years. Notably, longitudinal samples from a population of constant size may exhibit evidence of exponential growth. We suggest that population genomic studies of bacteria should routinely account for temporal diversity in samples or provide evidence that longitudinal sampling bias does not affect conclusions.
Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions
Authors: Duong Dat , Ahmad Wasi Uddin , Eskin Eleazar , Chang Kai-Wei , Li Jingyi Jessica 
Published: January 2017

AbstractThe Gene Ontology (GO) database contains GO terms that describe biological functions of genes. Previous methods for comparing GO terms have relied on the fact that GO terms are organized into a tree structure. Under this paradigm, the locations of two GO terms in the tree dictate their similarity score. In this paper, we introduce two new solutions for this problem, by focusing instead on the definitions of the GO terms. We apply neural network based techniques from the natural language processing (NLP) domain. The first method does not rely on the GO tree, whereas the second indirectly depends on the GO tree. In our first approach, we compare two GO definitions by treating them as two unordered sets of words. The word similarity is estimated by a word embedding model that maps words into an N-dimensional space. In our second approach, we account for the word-ordering within a sentence. We use a sentence encoder to embed GO definitions into vectors and estimate how likely one definition entails another. We validate our methods in two ways. In the first experiment, we test the model’s ability to differentiate a true protein-protein network from a randomly generated network. In the second experiment, we test the model in identifying orthologs from randomly-matched genes in human, mouse, and fly. In both experiments, a hybrid of NLP and GO-tree based method achieves the best classification accuracy.
Model communities hint to promiscuous metabolic linkages between ubiquitous free-living freshwater bacteria
Authors: Garcia Sarahi L , Buck Moritz , Hamilton Joshua J. , Wurzbacher Christian , Rosenblad Magnus Alm , McMahon Katherine D. , Grossart Hans-Peter , Warnecke Falk , Eiler Alexander 
Published: January 2017

AbstractFree-living microorganisms with streamlined genomes are very abundant in the environment. Genome streamlining results in losses in the cell’s biosynthetic potential generating physiological dependencies between microorganisms. However, there exists no consensus on the specificity of these microbial associations. To verify specificity and extent of these associations, mixed cultures were established from three different freshwater environments. These cultures contained free-living streamlined organisms lacking multiple biosynthetic pathways. Among the co-occurring members of the mixed cultures, there was no clear recurring pattern of metabolic complementarity and dependencies. This, together with weak temporal co-occurrence patterns observed using time-series metagenomics, suggests that free-living freshwater bacteria form loose and unspecific cooperative loops. Comparative genomics suggests that the proportion of accessory genes in populations of streamlined bacteria allows for flexibility in interaction partners. Altogether this renders these free-living bacterial lineages functionally versatile despite their streamlining tendencies.
No evidence for avoidance of black rat scent by the presumably less competitive Natal multimammate mouse in a choice experiment
Authors: Cuypers Laura N. , Cuypers Wim L. , Gildemyn-Blomme Amélie , Abraham Laura , Aertbeliën Senne , Massawe Apia W. , Borremans Benny , Gryseels Sophie , Leirs Herwig 
Published: January 2017

AbstractIn Africa, indigenous multimammate mice (Mastomys natalensis) only appear to live commensally in houses when invasive black rats (Rattus rattus) are absent, yet little is known about the underlying mechanism. Avoidance through smell may cause the absence ofM. natalensisfrom areas occupied byR. rattus, but this hypothesis has not yet been tested. We conducted a Y-maze choice experiment where 15M. natalensiswere offered a choice between corridors containing conspecific scent,R. rattusscent, and a control scent. Residence time in theR. rattuscorridor was greater than that in the control corridor but equal to that in theM. natalensiscorridor, suggesting that multimammate mice do not actively avoid the scent of their invasive competitor.
Marchantialiverworts as aproxyto plants basal microbiomes
Authors: Alcaraz Luis D. , Peimbert Mariana , Dorantes-Acosta Ana E. , Bowman John L. , Arteaga-Vázquez Mario A. 
Published: January 2017

AbstractMicrobiomes influence plant development, establishment, nutrient acquisition, pathogen defense, and the myriad of roles that ultimately impacts plant health. Plants microbiome are shaped through interactions between the microbes (ranging from cooperative functions to chemical warfare) and a selection process entailed by the host plants that distinguishes between pathogens, commensals, symbionts and transient bacteria. The soil is a primary source for microbes colonizing plants, along with other environmental sources including rain and interactions with other organisms. In this work, we explore the microbiomes through massive sequencing of the 16S rRNA gene in the eldest terrestrial plants:Marchantialiverworts. We compared microbiomes fromM. polymorpha, andM. paleaceaplants collected in the wild and their soils, all together luckily in the same geographical location (sympatric) thus reducing geographic effects; and also from plants grown in vitro and established from gemmae obtained from the same population of wild plants. Qualitative and quantitative microbiome analysis allowed us to identify microbes conserved in both native and in vitroMarchantiaspecies. WhileM. polymorphanative plants microbiomes richness is reduced about M.paleacea, containing almost half of the Operative Taxonomic Units (OTUs) observed inM. paleacea, M. polymorphagrown in vitro exhibits larger OTUs. This diversity differences might be the result of impairment to recognize their microbial partners and being an open niche for opportunistic bacteria. The main OTUs inMarchantiamicrobiomes were assigned to the genera:Methylobacterium, Rhizobium, Paenibacillus, Lysobacter, Pirellula, Steroidobacter, andBryobacter. The assigned genera correspond to bacteria capable of plant-growth promotion, complex exudates degradation, nitrogen fixation, methylotrophs, and disease-suppressive bacteria, all hosted in the relatively simple anatomy of the plant that provides refuge on their surfaces, rhizoids, and multiple gas chambers that work as specialized niches for different bacterial groups.Marchantiais a promising model to study not only long-term relationships between plants and their microbes but also the transgenerational impact of microbiomes because ofMarchantialong 450 million years under climate change conditions testing microbiome configurations.
Joint estimation of relatedness coefficients and allele frequencies from ancient samples
Authors: Theunert Christoph , Racimo Fernando , Montgomery Slatkin 
Published: January 2017

AbstractWe develop and test a method to address whether DNA samples sequenced from a group of fossil hominin bone or teeth fragments originate from the same individual or from closely related individuals. Our method assumes low amounts of retrievable DNA, significant levels of sequencing error and contamination from one or more present-day humans. We develop and implement a maximum likelihood method that estimates levels of contamination, sequencing error rates and pairwise relatedness co-efficients in a set of individuals. We assume there is no reference panel for the ancient population to provide allele and haplotype frequencies. Our approach makes use of single nucleotide polymorphisms and does not make assumptions about the underlying demographic model. By artificially mating individual genomes from the 1000 Genomes Project, we determine the numbers of individuals at a given genomic coverage that are required to detect different levels of genetic relatedness with confidence.
De NovoPacBio long-read and phased avian genome assemblies correct and add to genes important in neuroscience research
Authors: Korlach Jonas , Gedman Gregory , Kingan Sarah B. , Chin Chen-Shan , Howard Jason , Cantin Lindsey , Jarvis Erich D. 
Published: January 2017

AbstractReference quality genomes are expected to provide a resource for studying gene structure and function. However, often genes of interest are not completely or accurately assembled, leading to unknown errors in analyses or additional cloning efforts for the correct sequences. A promising solution to this problem is long-read sequencing. Here we tested PacBio-based long-read sequencing and diploid assembly for potential improvements to the Sanger-based intermediate-read zebra finch reference and Illumina-based short-read Anna’s hummingbird reference, two vocal learning avian species widely studied in neuroscience and genomics. With DNA of the same individuals used to generate the reference genomes, we generated diploid assemblies with the FALCON-Unzip assembler, resulting in contigs with no gaps in the megabase range (N50s of 5.4 and 7.7 Mb, respectively), and representing 150-fold and 200-fold improvements over the current zebra finch and hummingbird references, respectively. These long-read assemblies corrected and resolved what we discovered to be misassemblies, including due to erroneous sequences flanking gaps, complex repeat structure errors in the references, base call errors in difficult to sequence regions, and inaccurate resolution of allelic differences between the two haplotypes. We analyzed protein-coding genes widely studied in neuroscience and specialized in vocal learning species, and found numerous assembly and sequence errors in the reference genes that the PacBio-based assemblies resolved completely, validated by single long genomic reads and transcriptome reads. These findings demonstrate, for the first time in non-human vocal learning species, the impact of higher quality, phased and gap-less assemblies for understanding gene structure and function.
Understanding sequence conservation with deep learning
Authors: Li Yi , Quang Daniel , Xie Xiaohui 
Published: January 2017

AbstractMotivationComparing the human genome to the genomes of closely related mammalian species has been a powerful tool for discovering functional elements in the human genome. Millions of conserved elements have been discovered. However, understanding the functional roles of these elements still remain a challenge, especially in noncoding regions. In particular, it is still unclear why these elements are evolutionarily conserved and what kind of functional elements are encoded within these sequences.ResultsWe present a deep learning framework, called DeepCons, to uncover potential functional elements within conserved sequences. DeepCons is a convolutional neural net (CNN) that receives a short segment of DNA sequence as input and outputs the probability of the sequence of being evolutionary conserved. DeepCons utilizes hundreds of convolution kernels to detect features within DNA sequences, and automatically learns these kernels after training the CNN model using 887,577 conserved elements and a similar number of nonconserved elements in the human genome. On a balanced test dataset, DeepCons can achieve an accuracy of 75% in determining whether a sequence element is conserved or not, and the area under the ROC curve of 0.83, based on information from the human genome alone. We further investigate the properties of the learned kernels. Some kernels are directly related to well-known regulatory motifs corresponding to transcription factors. Many kernels show positional biases relative to transcriptional start sites or transcription end sites. But most of discovered kernels do not correspond to any known functional element, suggesting that they might represent unknown categories of functional elements. We also utilize DeepCons to annotate how changes at each individual nucleotide might impact the conservation properties of the surrounding sequences.AvailabilityThe source code of DeepCons and all the learned convolution kernels in motif format is publicly available online athttps://github.com/uci-cbcl/DeepCons.Contactxhx@ics.uci.edu
LET-99-dependent spatial restriction of active force generators makes spindle’s position robust
Authors: Bouvrais H. , Chesneau L. , Pastezeur S. , Delattre M. , Pécréaux J. 
Published: January 2017

AbstractDuring the asymmetric division of theCaenorhabditis elegansnematode zygote, the polarity cues distribution and daughter cell fates depend on the correct positioning of the mitotic spindle, which results from both centering and cortical pulling forces. Revealed by anaphase spindle rocking, these pulling forces are regulated by the force generator dynamics, which are in turn consequent of mitotic progression. We found a novel, additional, regulation of these forces by the spindle position. It controls astral microtubule availability at the cortex, on which theactiveforce generators can pull. Importantly, this positional control relies on the polarity dependent LET-99 cortical band, which restricts or concentrates generators to a posterior crescent. After delaying anaphase onset, we detected this positional pulling force regulation inC. elegansas a precocious spindle rocking with respect to anaphase onset. We ascribed this control to the microtubule dynamics at the cortex. Indeed, in mapping the cortical contacts, we found a correlation between the centrosome–cortex distance and the microtubule contact density. In turn, it modulates pulling force generator activity. We modelled this control, predicting and experimentally validating that the posterior crescent extent controlled where the anaphase oscillations started, in addition to mitotic progression. We found in particular that the oscillation onset position resists changes in cellular geometry and moderate variations of active force generator count. Finally, we propose that spatially restricting force generator to a posterior crescent sets the spindle’s final position, reflecting polarity through the LET-99 dependent restriction of force generators to a posterior crescent. This regulation superimposes that of force generator processivity. This novel control confers a low dependence on microtubule and active force generator exact numbers or dynamics, provided that they exceed the threshold needed for posterior displacement. Interestingly, this robustness originates in cell mechanics rather than biochemical networks.
Antibiotic resistance genes in agriculture and urban influenced watersheds in southwestern British Columbia
Authors: Uyaguari-Díaz Miguel I. , Croxen Matthew A. , Luo Zhiyao , Cronin Kirby I. , Chan Michael , Baticados Waren N. , Nesbitt Matthew J. , Li Shaorong , Miller Kristi , Dooley Damion , Hsiao William , Isaac-Renton Judith L. , Tang Patrick , Prystajecky Natalie 
Published: February 2017

AbstractBackgroundThe dissemination of antibiotic resistance genes (ARGs) from anthropogenic activities into the environment poses an emerging public health threat. Water constitutes a major vehicle for transport of both biological material and chemical substances. The present study focused on putative antibiotic resistance and integrase genes present in the microbiome of agricultural, urban influenced and protected watersheds in southwestern British Columbia, Canada. A metagenomics approach and high throughput quantitative PCR (HT qPCR) were used to screen for elements of resistance including ARGs and integron-associated integrase genes (intI). Sequencing of bacterial genomic DNA was used to characterize the resistome of microbial communities present in watersheds over a one-year period.ResultsData mining using CARD and Integrall databases enabled the identification of putative antibiotic resistance genes present in watershed samples. Antibiotic resistance genes presence in samples from various watershed locations was low relative to the microbial population (<1 %). Analysis of the metagenomic sequences detected a total of 78 ARGs andintI1across all watershed locations. The relative abundance and richness of antibiotic resistance genes was found to be highest in agriculture impacted watersheds compared to protected and urban watersheds. Gene copy numbers (GCNs) from a subset of 21 different elements of antibiotic resistance were further estimated using HT qPCR. Most GCNs of ARGs were found to be variable over time. A downstream transport pattern was observed in the impacted watersheds (urban and agricultural) during dry months. Urban and agriculture impacted sites had a higher GCNs of ARGs compared to protected sites. Similar to other reports, this study found a strong association betweenintI1and ARGs (e.g.,sul1), an association which may be used as a proxy for anthropogenic activities. Chemical analysis of water samples for three major groups of antibiotics was negative. However, the high richness and GCNs of ARGs in impacted sites suggest effects of effluents on microbial communities are occurring even at low concentrations of antimicrobials in the water column.ConclusionAntibiotic resistance and integrase genes in a year-long metagenomic study showed that ARGs were driven mainly by environmental factors from anthropogenized sites in agriculture and urban watersheds. Environmental factors accounted for almost 40% of the variability observed in watershed locations.
High-throughput annotation of full-length long noncoding RNAs with Capture Long-Read Sequencing
Authors: Lagarde Julien , Uszczynska-Ratajczak Barbara , Carbonell Silvia , Pérez-Lluch SÍlvia , Abad Amaya , Davis Carrie , Gingeras Thomas R. , Frankish Adam , Harrow Jennifer , Guigo Roderic , Johnson Rory 
Published: February 2017

AbstractAccurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued–particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.Abbreviationsbpbase pairFLfull lengthntnucleotideROIread of insert,i.e.PacBio readSJsplice junctionSMRTsingle-molecule real-timeTMtranscript model
The mechanisms of regulatory focus
Authors: Zivnuska Suzanne , Kacmar K. Michele , Valle Matthew 
Published: February 2017

PurposeThe purpose of this paper is to explore the mechanisms underlying prevention-focus and promotion-focus, two distinct dimensions of regulatory focus undertaken to fulfill different goals. The authors explore distinct triggers (mindfulness and leader-member exchange (LMX)) and outcomes (role overload and burnout) of each.Design/methodology/approachThe model is grounded in regulatory focus theory (Higgins, 1997), and is tested with data collected at two times from 206 full-time workers.FindingsFindings revealed mindfulness was positively related to prevention- and promotion-focus, while LMX was positively related to only promotion-focus. Prevention-focus mediated the relationship between mindfulness and role overload and burnout, while promotion-focus mediated the relationship between both mindfulness and LMX and role overload, but not burnout.Originality/valueThis research expands the nomological network describing individual and dyadic antecedents to regulatory focus. It also explores the nature of the relationships between regulatory focus and career management consequences, and may allow us to offer useful advice for practicing managers trying to understand employee career trajectories.
Managing business networks for value creation in facilities and their external environments
Authors: Artto Karlos , Ahola Tuomas , Kyrö Riikka , Peltokorpi Antti 
Published: February 2017

Purpose
The purpose of this paper is to increase understanding of the logic of business network formation among the co-located and external actors of a facility.

Design/methodology/approach
The research adopts a theory-building approach through developing propositions inductively from the empirical case study on four purposefully sampled modern service station facilities. The focus is on analyzing how a facility and its inherent co-located actors represent an entity that forms a business network with external actors in the facility’s environment.

Findings
The findings propose that when co-located with a large number of actors, the facility and its actors represent an entity that is connected to a wide business network of multiple external actors. On the other hand, when co-located with a small number of actors, the facility becomes a part of the overall supply in the surrounding business environment with a differentiated offering for competitive advantage.

Practical implications
The research suggests that an appropriate co-locating strategy, for example, when planning the tenant mix of the facility, can contribute to creating a vivid business network in the external environment, which raises the facility to a role of a central entity in such a network.

Originality/value
The findings explaining how co-location affects the businesses within the facility and within a wider networked environment are novel to the scholarly knowledge on co-location. The research bridges the theories of co-location and business networks that have been treated as separate discourses in previous research.