bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptional analysis of sodium valproate in a serotonergic cell line reveals gene regulation through both HDAC inhibition-dependent and independent mechanisms
Authors: Sinha Priyanka , Cree Simone , Miller Allison L. , Pearson John F. , Kennedy Martin A.
Published: November 2019

Sodium valproate (VPA) is a histone deacetylase (HDAC) inhibitor, widely prescribed in the treatment of bipolar disorder, and yet the precise modes of therapeutic action for this drug are not fully understood. After exposure of the rat serotonergic cell line RN46A to VPA, RNA-sequencing (RNA-Seq) analysis showed widespread changes in gene expression. Analysis by multiple pipelines revealed as many as 230 genes were significantly upregulated and 72 genes were significantly downregulated. A subset of 23 differentially expressed genes was selected for validation using the nCounter®platform, and of these we obtained robust validation forADAM23, LSP1, MAOB, MMP13, PAK3, SERPINB2, SNAP91, WNT6, andZCCHC12. We investigated the effect of lithium on this subset and found four genes,CDKN1C, LSP1, SERPINB2andWNT6co-regulated by lithium and VPA. We also explored the effects of other HDAC inhibitors and the VPA analogue valpromide on the subset of 23 selected genes. Expression of eight of these genes,CDKN1C, MAOB, MMP13, NGFR, SHANK3, VGF, WNT6andZCCHC12, was modified by HDAC inhibition, whereas others did not appear to respond to several HDAC inhibitors tested. These results suggest VPA may regulate genes through both HDAC-dependent and independent mechanisms. Understanding the broader gene regulatory effects of VPA in this serotonergic cell model should provide insights into how this drug works and whether other HDACi compounds may have similar gene regulatory effects, as well as highlighting molecular processes that may underlie regulation of mood.
An integrative approach to investigate natural variation in the accumulation of aliphatic glucosinolates in Arabidopsis thaliana
Authors: Sharma Suraj , Popa Ovidiu , Kopriva Stanislav , Ebenhoeh Oliver
Published: November 2019

Glucosinolates are a fascinating class of specialised metabolites found in the plants of Brassicacea family. The variation in glucosinolate composition across different Arabidopsis ecotypes could be a result of allelic compositions at different biosynthetic loci. The contribution of methylthioalkylmalate synthase (MAM) genes to diversity of glucosinolate profiles across different Arabidopsis ecotypes has been confirmed by genetic analyses. Different MAM isoforms utilise different chain-elongated substrates for glucosinolate biosynthesis causing thus a variation in chain lengths across different Arabidopsis ecotypes. To further investigate the relationship between the genotype and the associated metabolic phenotype, we studied the diversity of genes and enzymes of glucosinolate biosynthesis. Using Shannon entropy as a measure we revealed that several genes of the pathway show a clear derivation from the expected behaviour, either accumulating non-synonymous SNPs or showing signs of purifying selection. We found that the genotype-phenotype relationship is much more complicated than inferred from the diversity of MAM synthases. We conclude therefore, that the ON/OFF feature of key QTLs is not enough to elucidate the diversity of glucosinolates across different Arabidopsis thaliana ecotypes and that glucosinolate profiles are determined also through the polymorphic residues along the coding regions of multiple metabolic genes.
Dynamic integration of forward planning and heuristic preferences during multiple goal pursuit
Authors: Ott Florian , Marković Dimitrije , Strobel Alexander , Kiebel Stefan J.
Published: November 2019

Selecting goals and successfully pursuing them in an uncertain and dynamic environment is an important aspect of human behaviour. In order to decide which goal to pursue at what point in time, one has to evaluate the consequences of one’s actions over future time steps by forward planning. However, when the goal is still temporally distant, detailed forward planning can be prohibitively costly. One way to select actions at minimal computational costs is to use heuristics. It is an open question how humans mix heuristics with forward planning to balance computational costs with goal reaching performance. To test a hypothesis about dynamic mixing of heuristics with forward planning, we used a novel stochastic sequential two-goal task. Comparing participants’ decisions with an optimal full planning agent, we found that at the early stages of goal-reaching sequences, in which both goals are temporally distant and planning complexity is high, on average 42% (SD = 19%) of participants’ choices deviated from the agent’s optimal choices. Only towards the end of the sequence, participant’s behaviour converged to near optimal performance. Subsequent model-based analyses showed that participants used heuristic preferences when the goal was temporally distant and switched to forward planning when the goal was close.

Author summary

When we pursue our goals, there is often a moment when we recognize that we did not make the progress that we hoped for. What should we do now? Persevere to achieve the original goal, or switch to another goal? Two features of real-world goal pursuit make these decisions particularly complex. First, goals can lie far into an unpredictable future and second, there are many potential goals to pursue. When potential goals are temporally distant, human decision makers cannot use an exhaustive planning strategy, rendering simpler rules of thumb more appropriate. An important question is how humans adjust the rule of thumb approach once they get closer to the goal. We addressed this question using a novel sequential two-goal task and analysed the choice data using a computational model which arbitrates between a rule of thumb and accurate planning. We found that participants’ decision making progressively improved as the goal came closer and that this improvement was most likely caused by participants starting to plan ahead.
Genome Repository of Oiled Systems (GROS): an interactive and searchable database that expands the catalogued diversity of crude oil-associated microbes
Authors: Karthikeyan Smruthi , Rodriguez-R Luis M. , Heritier-Robbins Patrick , Hatt Janet K. , Huettel Markus , Kostka Joel E. , Konstantinidis Konstantinos T.
Published: November 2019

Indigenous microbial communities ultimately control the fate of petroleum hydrocarbons (PHCs) that enters the natural environment through natural seeps or accidental oil spills, but the interactions among microbes and with their chemical environment during oil biodegradation are highly complex and poorly understood. Genome-resolved metagenomics have the potential to help in unraveling these complex interactions. However, the lack of a comprehensive database that integrates existing genomic/metagenomic data from oiled environments with physicochemical parameters known to regulate the fate of PHCs currently limits data analysis and interpretations. Here, we present a curated, comprehensive, and searchable database that documents microbial populations in oiled ecosystems on a global scale, along with underlying physicochemical data, geocoded via GIS to reveal geographic distribution patterns of the populations. Analysis of the ~2,000 metagenome-assembled genomes (MAGs) available in the database revealed strong ecological niche specialization within habitatse.g., specialization to coastal sediments vs. water-column vs. deep-sea sediments. Over 95% of the recovered MAGs represented novel and uncultured species underscoring the limited representation of cultured organisms from oil-contaminated and oil reservoir ecosystems. The majority of MAGs linked to oiled ecosystems are members of the rare biosphere in non-oiled samples, except for the Gulf of Mexico (GoM) which appears to be primed for oil biodegradation. GROS should facilitate future work toward a more predictive understanding of the microbial taxa and their activities that control the fate of oil spills as well as serve as a model approach for building similar resources for additional environmental processes and omic data of interest.
ERBB2 is a Key Mediator in Hearing Restoration in Noise-Deafened Young Adult Mice
Authors: Zhang Jingyuan , Na Daxiang , Beaulac Holly J. , Dilts Miriam , Henry Kenneth S. , Bullen Anwen , White Patricia M.
Published: November 2019

Noise-induced hearing loss (NIHL) affects over ten million adults in the United States, and has no biological treatment. We hypothesized that activation of signaling from ERBB2 receptors in cochlear supporting cells could mitigate cochlear damage. We adopted a new timeline for assessing mitigation that parallels hearing recovery from damage in avians. We drove expression of a constitutively active variant of ERBB2 (CA-ERBB2) in cochlear supporting cells three days after permanent noise damage in young adult mice. Between 100-200 supporting cells in the apical cochlea expressed a lineage marker, indicating competence to express CA-ERBB2. Hearing thresholds were assessed with auditory brainstem response tests, and hearing recovery was assessed over a ninety-day period. Mice harboring CA-ERBB2 capability had similar hearing thresholds to control littermates prior to noise exposure, immediately after, and 30-days after. Sixty and ninety days after noise exposure, CA-ERBB2+ mice demonstrated a partial but significant reversal of NIHL threshold shifts at one in five frequencies tested, which was in the region of CA-ERBB2 expression. We evaluated inner and outer hair cell (IHC and OHC) survival, synaptic preservation, stereociliary morphology, and IHC cytoskeletal alterations with histological techniques. Improved IHC and OHC survival were observed in the basal cochlea. No differences were seen in synaptic numbers or IHC cytoskeletal alterations, but more stereocilia may have been preserved. These data indicate, for the first time, that ERBB2 signaling in supporting cells can promote hair cell survival and partial functional recovery, and that permanent threshold shifts from noise may be partially reversed in mice.
A/T/N polygenic risk score for cognitive decline in old age
Authors: Moore Annah M. , Filshtein Teresa J. , Dumitrescu Logan , Harrati Amal , Elahi Fanny , Mormino Elizabeth C. , Deming Yuetiva , Kunkle Brian W. , Mungas Dan M. , Hedden Trey , Apostolova Liana G. , Saykin Andrew J. , Chasioti Danai , Lu Qiongshi , Dennis Jessica , Sealock Julia , Davis Lea K. , Fardo David W. , Buckley Rachel , Hohman Timothy J.
Published: November 2019

INTRODUCTION

We developed a novel polygenic risk score (PRS) based on the A/T/N (amyloid plaques (A), phosphorylated tau tangles (T), and neurodegeneration (N)) framework and compared a PRS based on clinical AD diagnosis to assess which was a better predictor of cognitive decline.

METHODS

We used summary statistics from genome wide association studies of cerebrospinal fluid amyloid-β (Aβ42) and phosphorylated-tau (ptau181), left hippocampal volume (LHIPV), and late-onset AD dementia to calculate PRS for 1181 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Individual PRS were averaged to generate a composite A/T/N PRS. We assessed the association of PRS with baseline and longitudinal cognitive composites of executive function and memory.

RESULTS

The A/T/N PRS showed superior predictive performance on AD biomarkers and executive function decline compared to the clinical AD PRS.

DISCUSSION

Results suggest that integration of genetic risk across AD biomarkers may improve prediction of disease progression.

Research in Context

Systematic Review

Authors reviewed relevant literature using PubMed and Google Scholar. Key studies that generated and validated polygenic risk scores (PRS) for clinical and pathologic AD were cited. PRS scores have been increasingly used in the literature but clinical utility continues to be questioned.

Interpretation

In the current research landscape concerning PRS clinical utility in the AD space, there is room for model improvement and our hypothesis was that a PRS with integrated risk for AD biomarkers could yield a better model for cognitive decline.

Future Directions

This study serves as proof-of-concept that encourages future study of integrated PRS across disease markers and utility in taking an A/T/N (amyloidosis, tauopathy and neurodegeneration) focused approach to genetic risk for cognitive decline and AD.
Co-Increasing Neuronal Noise and Beta Power in the Developing Brain
Authors: He Wei , Donoghue Thomas , Sowman Paul F , Seymour Robert A , Brock Jon , Crain Stephen , Voytek Bradley , Hillebrand Arjan
Published: November 2019

Accumulating evidence across species indicates that brain oscillations are superimposed upon an aperiodic 1/f- like power spectrum. Maturational changes in neuronal oscillations have not been assessed in tandem with this underlying aperiodic spectrum. The current study uncovers co-maturation of the aperiodic component alongside the periodic components (oscillations) in spontaneous magnetoencephalography (MEG) data. Beamformer-reconstructed MEG time-series allowed a direct comparison of power in the source domain between 24 children (8.0 ± 2.5 years, 17 males) and 24 adults (40.6 ± 17.4 years, 16 males). Our results suggest that the redistribution of oscillatory power from lower to higher frequencies that is observed in childhood does not hold once the age-related changes in the aperiodic signal are controlled for. When estimating both the periodic and aperiodic components, we found that power increases with age in the beta band only, and that the 1/fsignal is flattened in adults compared to children. These results suggest a pattern of co-maturing beta oscillatory power with the aperiodic 1/fsignal in typical childhood development.
DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
Authors: Kulmanov Maxat , Hoehndorf Robert
Published: November 2019

Motivation

Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted in a large number of genotype–phenotype association being available for humans and model organisms. Combined with recent advances in machine learning, it may now be possible to predict human phenotypes resulting from particular molecular aberrations.

Results

We developed DeepPheno, a neural network based hierarchical multi-class multi-label classification method for predicting the phenotypes resulting from complete loss-of-function in single genes. DeepPheno uses the functional annotations with gene products to predict the phenotypes resulting from a loss-of-function; additionally, we employ a two-step procedure in which we predict these functions first and then predict phenotypes. Prediction of phenotypes is ontology-based and we propose a novel ontology-based classifier suitable for very large hierarchical classification tasks. These methods allow us to predict phenotypes associated with any known protein-coding gene. We evaluate our approach using evaluation metrics established by the CAFA challenge and compare with top performing CAFA2 methods as well as several state of the art phenotype prediction approaches, demonstrating the improvement of DeepPheno over state of the art methods. Furthermore, we show that predictions generated by DeepPheno are applicable to predicting gene–disease associations based on comparing phenotypes, and that a large number of new predictions made by DeepPheno interact with a gene that is already associated with the predicted phenotype.

Availability

https://github.com/bio-ontology-research-group/deeppheno

Contact

robert.hoehndorf@kaust.edu.sa
BowSaw: inferring higher-order trait interactions associated with complex biological phenotypes
Authors: DiMucci Demetrius , Kon Mark , Segrè Daniel
Published: November 2019

Machine learning is helping the interpretation of biological complexity by enabling the inference and classification of cellular, organismal and ecological phenotypes based on large datasets, e.g. from genomic, transcriptomic and metagenomic analyses. A number of available algorithms can help search these datasets to uncover patterns associated with specific traits, including disease-related attributes. While, in many instances, treating an algorithm as a black box is sufficient, it is interesting to pursue an enhanced understanding of how system variables end up contributing to a specific output, as an avenue towards new mechanistic insight. Here we address this challenge through a suite of algorithms, named BowSaw, which takes advantage of the structure of a trained random forest algorithm to identify combinations of variables (“rules”) frequently used for classification. We first apply BowSaw to a simulated dataset, and show that the algorithm can accurately recover the sets of variables used to generate the phenotypes through complex Boolean rules, even under challenging noise levels. We next apply our method to data from the integrative Human Microbiome Project and find previously unreported high-order combinations of microbial taxa putatively associated with Crohn’s disease. By leveraging the structure of trees within a random forest, BowSaw provides a new way of using decision trees to generate testable biological hypotheses.
Temperature and nutrient gradients correspond with lineage-specific microdiversification in the ubiquitous and abundant Limnohabitans freshwater genus
Authors: Props Ruben , Denef Vincent J.
Published: November 2019

Most freshwater bacterial communities are characterized by a few dominant taxa, which are often ubiquitous across freshwater biomes worldwide. Our understanding of the genomic basis underlying this pattern is limited to a subset of taxa. Here, we investigated the genomic basis that enables Limnohabitans, a freshwater genus key in funneling carbon from primary producers to higher trophic levels, to achieve abundance and ubiquity. We reconstructed eight metagenome assembled genomes (MAGs) from this genus along broad environmental gradients existing in Lake Michigan, part of Earth’s largest surface freshwater system. De novo strain inference analysis resolved a total of 23 strains from these MAGs, which strongly partitioned into two habitat-specific clusters with co-occurring strains from different lineages. The largest number of strains belonged to the abundant LimB lineage, for which robust in situ strain-delineation had not previously been achieved. Our data show that temperature and nutrient levels may be two of the primary drivers of microdiversification within the Limnohabitans genus. Additionally, strains predominant in low and high phosphorus conditions had larger genomic divergence than strains abundant under different temperatures. Comparative genomics and gene expression analysis yielded evidence for the ability of LimB populations to exhibit cellular motility and chemotaxis, a phenotype not yet associated with cultured Limnohabitans strains. Our findings broaden historical marker gene-based surveys of Limnohabitans microdiversification, and provide in situ evidence of genome diversity and its functional implications across freshwater gradients.
Sounds are remapped across saccades
Authors: Szinte Martin , Aagten-Murphy David , Jonikaitis Donatas , Wollenberg Luca , Deubel Heiner
Published: November 2019

To achieve visual space constancy, our brain remaps eye-centered projections of visual objects across saccades. Here, we measured saccade trajectory curvature following the presentation of visual, auditory, and audiovisual distractors in a double-step saccade task to investigate if this stability mechanism also accounts for localized sounds. We found that saccade trajectories systematically curved away from the position at which either a light or a sound was presented, suggesting that both modalities are represented in eye-centered oculomotor centers. Importantly, the same effect was observed when the distractor preceded the execution of the first saccade. These results suggest that oculomotor centers keep track of visual, auditory and audiovisual objects by remapping their eye-centered representations across saccades. Furthermore, they argue for the existence of a supra-modal map which keeps track of multi-sensory object locations across our movements to create an impression of space constancy.
Identification of conserved gene regulatory networks that integrate environmental sensing and growth in the root cambium
Authors: Choe Goh , Van Hoang Nam , Zheng Yi , Aliaga Fandiño Ana Cecilia , Hur Jaeryung , Sung Inyoung , Ahn Hongryul , Kim Sun , Fei Zhangjun , Lee Ji-Young
Published: November 2019

Cambium drives lateral growth of stems and roots, contributing to diverse plant growth forms. Root crop is one outstanding example of the cambium-driven growth. To understand its molecular basis, we used radish to generate a compendium of root tissue- and stage-specific transcriptomes from two contrasting inbred lines in root growth. Expression patterns of key cambium regulators and hormone signaling components were validated. Clustering and GO enrichment analyses of radish datasets followed by comparative analysis against the newly established Arabidopsis early cambium data revealed evolutionary conserved stress-response transcription factors that might intimately control the cambium. Indeed, in vivo network made of selected stress-response and cambium regulators indicated ERF-1 as a potential key checkpoint of cambial activities, explaining how the cambium-driven growth is altered in response to environmental changes. Together, this study provides rich information about dynamic gene expression changes along the cambium-driven root growth with future engineering schemes for crop yields.
Actigraphy in brain-injured patients – A valid measurement for assessing circadian rhythms?
Authors: Angerer Monika , Schabus Manuel , Raml Marion , Pichler Gerald , Kunz Alexander B. , Scarpatetti Monika , Trinka Eugen , Blume Christine
Published: November 2019

Background

Actigraphy has received increasing attention in classifying rest-activity cycles. However, in patients with disorders of consciousness (DOC), actigraphy data may be considerably confounded by passive movements, such as nursing activities and therapies. Consequently, this study verified whether circadian rhythmicity is (still) visible in actigraphy data from patients with DOC after correcting for passive movements.

Methods

Wrist actigraphy was recorded over 7-8 consecutive days in patients with DOC (diagnosed with unresponsive wakefulness syndrome [UWS; n=19] and [exit] minimally conscious state [MCS/EMCS; n=11]). Presence and actions of clinical and research staff as well as visitors were indicated using a tablet in the patient’s room. Following removal and interpolation of passive movements, non-parametric rank-based tests were computed to identify differences between circadian parameters of uncorrected and corrected actigraphy data.

Results

Uncorrected actigraphy data overestimated the interdaily stability and intradaily variability of patients’ activity and underestimated the deviation from a circadian 24h rhythm. Only 5/30 (17%) patients deviated more than 1h from 24h in the uncorrected data, whereas this was the case for 17/30 (57%) patients in the corrected data. When contrasting diagnoses based on the corrected dataset, stronger circadian rhythms and higher activity levels were observed in MCS/EMCS as compared to UWS patients. Day-to-night differences in activity were evident for both patient groups.

Conclusion

Our findings indicate that uncorrected actigraphy data overestimates the circadian rhythmicity of patients’ activity, as nursing activities, therapies, and visits by relatives follow a circadian pattern itself. Therefore, we suggest correcting actigraphy data from patients with reduced mobility.
Size, not temperature, drives cyclopoid copepod predation of invasive mosquito larvae
Authors: Russell Marie C. , Qureshi Alima , Wilson Christopher G. , Cator Lauren J.
Published: November 2019

During range expansion, invasive species can experience new thermal regimes. Differences between the thermal performance of local and invasive species can alter species interactions, including predator-prey interactions. The Asian tiger mosquito,Aedes albopictus, is a known vector of several viral diseases of public health importance. It has successfully invaded many regions across the globe and currently threatens to invade regions of the UK where conditions would support seasonal activity. We assessed the functional response and predation efficiency (percentage of prey consumed) of the cyclopoid copepodsMacrocyclops albidusandMegacyclops viridisfrom South East England, UK against newly-hatched FrenchAe. albopictuslarvae across a relevant temperature range (15, 20, and 25°C). Predator-absent controls were included in all experiments to account for background prey mortality. We found that bothM. albidusandM. viridisdisplay type II functional response curves, and that both would therefore be suitable biocontrol agents in the event of anAe. albopictusinvasion in the UK. No significant effect of temperature on the predation interaction was detected by either type of analysis. However, the predation efficiency analysis did show differences due to predator species. The results suggest thatM. viridiswould be a superior predator against invasiveAe. albopictuslarvae due to the larger size of this copepod species, relative toM. albidus. Our work highlights the importance of size relationships in predicting interactions between invading prey and local predators.
Characterising shared space use networks using animal trapping data
Authors: Wanelik Klara M. , Farine Damien R.
Published: November 2019

Studying the social behaviour of small or cryptic species often relies on constructing networks from sparse point-based observations of individuals (e.g. live trapping data). Such an approach assumes that individuals that have been asynchronously detected in the same trapping location will also be more likely to have interacted. However, there is very little guidance on how much data are required for making robust co-trapping networks. In this study, we propose that co-trapping networks broadly assume that co-trapping captures shared space use (and, subsequently, likelihood of interacting), and that it may be more parsimonious to directly model shared space use. We first use empirical data to highlight that characteristics of how animals use space can help us to establish new ways to model the potential for individuals to co-occur. We then show that a method that explicitly models individuals’ home ranges and subsequent overlap in space among individuals (spatial overlap networks) requires fewer data for inferring observed networks that are correlated with the true shared space use network (relative to co-trapping networks constructed from space sharing events). Further, we show that shared space use networks based on estimating spatial overlap are also more powerful for detecting biological effects present in the true shared space use network. Finally, we discuss when it is appropriate to make inferences about social interactions from shared space use. Our study confirms the potential for using sparse trapping data from cryptic species to address a range of important questions in ecology and evolution.

Significance statement

Characterising animal social networks requires repeated (co-)observations of individuals. Collecting sufficient data to characterise the connections among individuals represents a major challenge when studying cryptic organisms—such as small rodents. This study draws from existing spatial mark-recapture data to inspire an approach that constructs networks by estimating space use overlap (representing the potential for interactions) from observations of individuals in the same location (e.g. a trap). We then use simulations to demonstrate that the method provides consistently higher correlations between inferred (or observed) networks and the true underlying network compared to current approaches, and requires fewer observations to reach higher correlations. We further demonstrate that these improvements translate to greater network accuracy and to more power for statistical hypothesis testing.
An information-theory approach to geometry for animal groups
Authors: Dahl Christoph D. , Ferrando Elodie , Zuberbühler Klaus
Published: November 2019

One of the hardest problems in studying animal behaviour is to quantify patterns of social interaction at the group level. Recent technological developments in global positioning system (GPS) devices have opened up new avenues for locating animals with unprecedented spatial and temporal resolution. Likewise, advances in computing power have enabled new levels of data analyses with complex mathematical models to address unresolved problems in animal behaviour, such as the nature of group geometry and the impact of group-level interactions on individuals. Here, we present an information theory-based tool for the analysis of group behaviour. We illustrate its affordances with GPS data collected from a freely interacting pack of 15 Siberian huskies (Canis lupus familiaris). We found that individual freedom in movement decisions was limited to about 4%, while a subject’s location could be predicted with 96% median accuracy by the locations of other group members, a pattern mediated by dominance, kin relations, sex, the relative time of the day and external events, such as feeding. We conclude that information theory-based approaches, coupled with state-of-the-art bio-logging technology, provide a powerful tool for future studies of animal social interactions beyond the dyadic level.
Environmental variables determining the distribution of an avian parasite: the case of thePhilornis torquanscomplex (Diptera: Muscidae) in South America
Authors: Cuervo Pablo F. , Percara Alejandro , Monje Lucas , Beldomenico Pablo M. , Quiroga Martín A.
Published: November 2019

Philornisflies are the major cause of myasis in altricial nestlings of neotropical birds. Its impact ranges from subtle to lethal, being of major concern in endangered bird species with geographically-restricted, fragmented and small-sized populations. In spite of its relevance for bird conservation, there is little information about the environmental dimensions determining their geographical range. We identified for the first time the macro-environmental variables constraining the abiotic niche of theP. torquanscomplex in South America, and provided a model map of its potential distribution based on environmental suitability. We used maximum entropy to model the ecological niche of theP. torquanscomplex, and to determine the contributing scenopoetic variables. We applied most of the recommendations to produce robust ecological niche models: accounting for sampling bias and spatial autocorrelation; using an accessible area for model calibration; testing multiple combinations of model parameters; using multiple statistical criteria; using a number of model replicates to determine consistency and uncertainty in geographical predictions. We identified the minimum temperature of the coldest month as the most relevant variable, associated with the largest decrease in habitat suitability in Brazil and northern South America. Furthermore, the mean temperature of the warmest quarter limited suitability mostly along the Andean range. In addition, humidity and moisture are influential factors in most of Argentina, northern Chile and coastal Peru. The geographical projection of the niche model suggests that environments in most of central-eastern Argentina, and in a broad area in central Chile, are suitable for the presence of theP. torquanscomplex. Besides of contributing to the knowledge of the ecology of the genus, this study is of relevance as a tool for bird conservation and represents a good reference for future work on the distribution of this parasite genus.
A mitochondria-targeted antioxidant affects the carotenoid-based plumage of red crossbills
Authors: Cantarero Alejandro , Mateo Rafael , Camarero Pablo , Alonso Daniel , Fernandez-Eslava Blanca , Alonso-Alvarez Carlos
Published: November 2019

The mechanisms involved in the production of red carotenoid-based ornaments in vertebrates are still poorly understood. Those colours generated by red carotenoids often depend on the enzymatic production (ketolation) of these pigments from dietary yellow carotenoids. Recently, it has been proposed that this conversion takes place at the inner mitochondrial membrane (IMM). This implies that carotenoid ketolation and cell respiration could share the same biochemical pathways. Such a link would favour the evolution of red ketocarotenoid-based ornaments as reliable indices of individual quality under a sexual selection scenario. We exposed captive male red crossbills (Loxia curvirostraLinnaeus) to two different synthetic antioxidants designed to penetrate into the IMM: a synthetic ubiquinone (mitoQ) and a superoxide dismutase mimetic (mitoTEMPO). MitoQ decreased the blood levels of substrate yellow carotenoids and tocopherol. This could be attributed to the characteristics of the mitoQ molecule, which can distort the IMM structure, increasing free radical (superoxide) production and, potentially, antioxidant consumption. Contrarily, mitoTEMPO-treated birds increased the plasma levels of the second most abundant red ketocarotenoid of red crossbills (i.e. canthaxanthin). MitoTEMPO also increased plumage redness and total ketocarotenoid concentration in feathers among those birds exhibiting a redder plumage at the beginning of the study, rising the plasma values of the main red pigment (3-hydroxyechinenone) in paler birds. The results as a whole support the involvement of the mitochondrial antioxidant machinery in carotenoid biotransformation. The fact that the initial plumage redness determined the effect of mitoTEMPO suggests that the mitochondrial-based mechanism is intimately linked to individual quality.

Summary statement

Antioxidants designed to penetrate the mitochondrial membrane increased avian plumage redness but depending on pre-existing colouration. This supports mitochondrial involvement in the evolution of carotenoid-based ornaments as reliable quality signals.
Phylogenetic and metabolic diversity have contrasting effects on the ecological functioning of bacterial communities
Authors: Xenophontos Constantinos , Taubert Martin , Harpole W. Stanley , Küsel Kirsten
Published: November 2019

Quantifying the relative contributions of microbial species to ecosystem functioning is challenging, because of the distinct mechanisms associated with microbial phylogenetic and metabolic diversity. We constructed bacterial communities with different diversity traits and employed exoenzyme activities (EEAs) and total available carbon (TAC) from substrates as proxies of bacterial functioning to test the independent effects of these two aspects of biodiversity. We expected that metabolic diversity, but not phylogenetic diversity would be associated with greater ecological function. Phylogenetically relatedness should intensify species interactions and coexistence, therefore amplifying the influence of metabolic diversity. We examined the effects of each diversity treatment using linear models, while controlling for the other, and found that phylogenetic diversity strongly influenced community functioning, positively and negatively. Metabolic diversity, however, exhibited negative or non-significant relationships with community functioning. When controlling for different substrates, EEAs increased along with phylogenetic diversity but decreased with metabolic diversity. The strength of diversity effects was related to substrate chemistry and the molecular mechanisms associated with each substrate’s degradation. EEAs of phylogenetically similar groups were strongly affected by within-genus interactions. These results highlight the unique flexibility of microbial metabolic functions that must be considered in further ecological theory development.
GeDex: A consensus Gene-disease Event Extraction System based on frequency patterns and supervised learning
Authors: Soto Larisa M. , Olayo-Alarcón Roberto , Velázquez-Ramírez David Alberto , Munguía-Reyes Adrián , Balderas-Martínez Yalbi Itzel , Méndez-Cruz Carlos-Francisco , Collado-Vides Julio
Published: November 2019

Motivation

The genetic mechanisms involved in human diseases are fundamental in biomedical research. Several databases with curated associations between genes and diseases have emerged in the last decades. Although, due to the demanding and time consuming nature of manual curation of literature, they still lack large amounts of information. Current automatic approaches extract associations by considering each abstract or sentence independently. This approach could potentially lead to contradictions between individual cases. Therefore, there is a current need for automatic strategies that can provide a literature consensus of gene-disease associations, and are not prone to making contradictory predictions.

Results

Here, we present GeDex, an effective and freely available automatic approach to extract consensus gene-disease associations from biomedical literature based on a predictive model trained with four simple features. As far as we know, it is the only system that reports a single consensus prediction from multiple sentences supporting the same association. We tested our approach on the curated fraction of DisGeNet (f-score 0.77) and validated it on a manually curated dataset, obtaining a competitive performance when compared to pre-existing methods (f-score 0.74). In addition, we effectively recovered associations from an article collection of chronic pulmonary diseases, and discovered that a large proportion is not reported in current databases. Our results demonstrate that GeDex, despite its simplicity, is a competitive tool that can successfully assist the curation of existing databases.

Availability

GeDex is available athttps://bitbucket.org/laigen/gedex/src/master/and can be used as a docker imagehttps://hub.docker.com/r/laigen/gedex

Contact

cmendezc@ccg.unam.mx

Supplementary information

Supplementary material are available atbioRxivonline.
annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions
Authors: Gaonkar Krutika S. , Marini Federico , Rathi Komal S. , Jain Payal , Zhu Yuankun , Chimicles Nicholas A. , Brown Miguel A. , Naqvi Ammar S. , Zhang Bo , Storm Phillip B. , Maris John M. , Raman Pichai , Resnick Adam C. , Strauch Konstantin , Taroni Jaclyn N. , Rokita Jo Lynne
Published: November 2019

Background

Gene fusion events are a significant source of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

Results

We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1,028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions.

Conclusions

annoFuse provides standardized filtering and annotation for gene fusion calls from STARFusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.
The astrocyte-enriched geneCG11000plays a crucial role in the development, locomotion and lifespan ofD. melanogaster
Authors: Najafi Hadi , Wong Kyle , Salkini Ammar , Miao Hongyu , Kim Woo Jae
Published: November 2019

The brain ofDrosophila melanogasteris a complex organ with various cell types, orchestrating the physiology and behaviors of the fly. While each cell type in theDrosophilabrain is known to express a unique set of genes, their complete genetic profile is still unknown. Advances in the RNA-sequencing techniques at single cell resolution facilitate identifying novel cell type-specific markers and/or examining the specificity of the available markers.

In this study, exploiting a single cell RNA sequencing data ofDrosophilaoptic lobe (which comprises two thirds of the brain with extensive cell type diversity), we first categorized cell types based on their known molecular markers, then the genes with enriched expression in astrocytes were identified. Consistent with previous findings, the known glial markersCG34335,Inx2andnrv2as well as the astrocytic genesCG9394,Eaat1,Gat,Gs2andCG1552exhibited enriched expression in the identified astrocyte cluster. Moreover, we identifiedCG11000as a gene with positive expression correlation with the astrocytic markerEaat1. The positive expression correlation betweenCG11000andEaat1genes was also observed in the single-cell RNA-sequencing data ofDrosophilamid-brain as well as in the bulk RNA-sequencing data ofDrosophilawhole brain during development.

Immunostaining of the brains dissected from adult flies showed overlapping fluorescence signals ofCG11000andEaat1expression, supporting co-expression of these genes in a set of single cells inDrosophilaoptic lobe. At the physiological level, RNAi-mediated suppression ofCG11000impeded th normal development of male flies without any effects on females. In adult flies,CG11000suppression affected the locomotion activity and lifespan ofD. melanogasterin an astrocyte-specific manner, suggesting pivotal role ofCG11000gene in astrocytes.
Cell cycle S-phase arrest drives cell extrusion
Authors: Dwivedi Vivek K. , Pardo-Pastor Carlos , Droste Rita , Denning Daniel P. , Rosenblatt Jody , Horvitz H. Robert
Published: November 2019

Cell extrusion is a process of cell elimination in which a cell is squeezed out from its tissue of origin. Extrusion occurs in organisms as diverse as sponges, nematodes, insects, fish and mammals. Defective extrusion is linked to many epithelial disorders, including cancer. Despite broad occurrence, cell-intrinsic triggers of extrusion conserved across phyla are generally unknown. We combined genome-wide genetic screens with live-imaging studies ofC. elegansembryos and mammalian epithelial cultures and found that S-phase arrest induced extrusion in both. Cells extruded fromC. elegansembryos exhibited S-phase arrest, and RNAi treatments that specifically prevent S-phase entry or arrest blocked cell extrusion. Pharmacological induction of S-phase arrest was sufficient to promote cell extrusion from a canine epithelial monolayer. Thus, we have discovered an evolutionarily conserved cell-cycle-dependent trigger of cell extrusion. We suggest that S-phase-arrest induced cell extrusion plays a key role in physiology and disease.
Blue/green light-responsive cyanobacteriochromes are cell shade sensors in red-light replete niches
Authors: Enomoto Gen , Ikeuchi Masahiko
Published: November 2019

Photoautotrophic cyanobacteria have developed sophisticated light response systems to capture and utilize the energy and information of incident light [1]. Cyanobacteria-specific photoreceptors cyanobacteriochromes (CBCRs) are distantly related to more widespread phytochromes. CBCRs show the most diverse spectral properties among the naturally occurring photoreceptors, typified by a unique and prevailing blue/green light-absorbing variant [2–6]. However, where the CBCR-mediated ‘colorful’ signaling systems function in nature has been elusive. We previously reported that the three CBCRs SesA/B/C synthesize/degrade a bacterial second messenger cyclic diguanylate (c-di-GMP) in response to blue/green light [6–8]. The cooperative action of SesA/B/C enables blue light-ON and green light-OFF regulation of the c-di-GMP-dependent cell aggregation of the thermophilic cyanobacteriumThermosynechococcus vulcanus[8, 9]. Here, we report that SesA/B/C can serve as a physiological sensor of cell density. Because cyanobacterial cells show lower transmittance of blue light than green light, higher cell density gives more green light-enriched irradiance to cells. The cell density-dependent suppression of cell aggregation under blue/green-mixed light and white light conditions support this idea. Such a sensing mechanism may provide information about the cell position in cyanobacterial mats in hot springs, the natural habitat ofThermosynechococcus. This cell position-dependent SesA/B/C-mediated regulation of cellular sessility (aggregation) might be ecophysiologically essential for the reorganization and growth of phototrophic mats. We also report that the green light-induced dispersion of cell aggregates requires red light-driven photosynthesis. Blue/green CBCRs might work as shade detectors in a different niche than red/far-red phytochromes, which may be why CBCRs have evolved in cyanobacteria.
Somalier: rapid relatedness estimation for cancer and germline studies using efficient genome sketches
Authors: Pedersen Brent S , Bhetariya Preeti J , Brown Joe , Marth Gabor , Jensen Randy L , Bronner Mary P , Underhill Hunter R , Quinlan Aaron R
Published: November 2019

When interpreting sequencing data from multiple spatial or longitudinal biopsies, detecting sample mix-ups is essential yet more difficult than in studies of germline variation. In most genomic studies of tumors, genetic variation is frequently detected through pairwise comparisons of the tumor and a matched normal tissue from the sample donor, and in many cases, only somatic variants are reported. The disjoint genotype information that results hinders the use of existing tools that detect sample swaps solely based on genotypes of germline variants. To address this problem, we have developedsomalier, which can operate directly on the alignments, so as not to require jointly-called germline variants. Instead,somalierextracts a smallsketchof informative genetic variation for each sample. Sketches from hundreds of biopsies and normal tissues can then be compared in under a second. This speed also makes it useful for checking relatedness in large cohorts of germline samples. Somalier produces both text output and an interactive visual report that facilitates the detection and correction of sample swaps using multiple relatedness metrics. We introduce the tool and demonstrate its utility on a cohort of five glioma samples each with a normal, tumor, and cell-free DNA sample. Applyingsomalierto high-coverage sequence data from the 1000 Genomes Project also identifies several related samples.Somaliercan be applied to diverse sequencing data types and genome builds, and is freely available for academic use atgithub.com/brentp/somalier.