bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and in silico comparison of transposable elements of Solanum tuberosum subsp. andigena from two localities of Peru
Authors: Carmen Sifuentes Sheyla , Cornejo Villanueva Victor 
Published: August 2021

ABSTRACTThe potato is one of the main crops in Peru, being one of the pillars in the country’s economy. It also has a cultural importance, being a basic element of Peruvian gastronomy and an emblematic crop of the Peruvian highlands, where small farmers over time have been able to conserve and cultivate 6048 native varieties. In Peru, around 300,000 hectares of potatoes are planted annually, and in 2019 Peru remained the main potato producer in Latin America, registering an annual production of 5.3 million tons. Therefore, it is necessary to study and characterize the genome of this very important tuber for the country. Although there are many potato genomic studies in the world and in Peru; these have been based on the search for genes of importance, genetic diversity, etc. and little has been deeply studied about the transposable elements (ETs) that are part of its genome. It is known that in many eukaryotes, transposable elements are powerful drivers of genome evolution, and they occupy a considerable part in plant genomes, so with these studies, more could be understood about how these ETs have intervened in the evolution of the potato in Peru; thus, how these mechanisms would help in the future to the survival of the species in scenarios of climate change, among others. This study proposes the identification and comparison of the transposable elements of the only 2 complete genomes of potatoes grown in Peru, found in the NCBI database, one from the department of Puno and the other from Cusco. There are various approaches to search for ETs in genomes, but for a complete and reliable annotation, it has been shown that the best strategy is the adoption of combined approaches, in this study, we will use 2 approaches, one based on homology, with the program RepeatMasker, and the other de novo, with the RepeatModeler2 program.
Quantifying RNA Synthesis at Rate-Limiting Steps of Transcription Using Nascent RNA-Sequencing Data
Authors: Rabenius Adelina , Chandrakumaran Sajitha , Sistonen Lea , Vihervaara Anniina 
Published: August 2021

SummaryNascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide data-analytical steps to 1) identify transcribed regulatory elements de novo genome-wide, 2) quantify engaged transcription complexes at enhancers, promoter-proximal regions, divergent transcripts, gene bodies and termination windows, and 3) measure distribution of transcription machineries and regulatory proteins across functional genomic regions. This protocol follows RNA synthesis and genome-regulation in mammals, as demonstrated in human K562 erythroleukemia cells.For complete details on the use and execution of this protocol, please refer to Vihervaara, et al., 2021.Graphical Abstract
No broad decline of breeding monarch butterflies in North America: implications for conservation efforts
Authors: Davis Andrew K. , Crossley Michael S. , Moran Matthew D. , Glassberg Jeffrey , Snyder William E. 
Published: August 2021

AbstractMany insects are in clear decline, with monarch butterflies (Danaus plexippus) drawing particular attention as a flagship species. Falling numbers of overwintering monarchs are well documented, but there has been debate regarding population trends of summer breeding populations. Here, we compile a series of long-term monarch monitoring datasets, some which are analyzed here for the first time, that reveal highly variable responses across the migratory geographic range, but no broad net decline in numbers of breeding monarchs. We also did not find evidence that sampling biased towards natural sites was masking declines at disturbed sites. Overall, our results suggest a robust resiliency in summer populations that thus far has allowed recovery from losses during the winter. Thus, monarchs may not require as much breeding habitat restoration as once thought, and focus should be on conserving the fall and spring migration.
Natural killer cell division regulates FcεRIγ expression downstream of mTOR activity
Authors: Shemesh Avishai , Calabrese Daniel R. , Arakawa-Hoyt Janice , Greenland John R. , Lanier Lewis L. 
Published: August 2021

AbstractThe expansion of human FcεRIγ-/low(FcRγ-/low) natural killer (NK) cells accrues during viral infections; however, the molecular mechanisms regulating FcRγ expression is not well defined and can have implication for host protection and NK cell immunotherapy. Our analysis of NK cell subsets in lung transplant patients during rapamycin treatment revealed significantly lower FcRγ levels in the NK cell population. Moreover, lower FcRγ levels in healthy donors were associated with low mTORC1/C2 activity and low T-bet expression. Cell division suppression by rapamycin or TGFβ suppressed FcRγ upregulation during IL-2 receptor stimulation, whereas promoting NK cell division by co-inhibiting FOXO1 activity restored FcRγ upregulation. These results suggest that the human FcRγ-/lowNK cell phenotype is associated with cell division suppression and reduced mTOR activity.
A new approach to integrate phylogenetic structure and partner availability to study biotic specialization in ecological networks
Authors: Pardo-De la Hoz Carlos J. , Medeiros Ian D. , Gibert Jean P. , Chagnon Pierre-Luc , Magain Nicolas , Miadlikowska Jolanta , Lutzoni François 
Published: August 2021

SummaryBiotic specialization holds information about the assembly, evolution and stability of biological communities. Phylogenetic diversity metrics have been used to quantify biotic specialization, but their current implementations do not adequately account for the availability of the interacting partners. Also, the overdispersed pattern of phylogenetic specialization has been misinterpreted as an attribute of generalists. We developed an approach that resolves these issues by accounting for partner availability to quantify the phylogenetic structure of specialization (i.e., clustered, overdispersed, or random) in ecological networks. We showed that our approach avoids biases of previous methods. We also implemented it on empirical networks of host–parasite, avian seed-dispersal, lichenized fungi– cyanobacteria and coral–dinoflagellate interactions. We found a large proportion of taxa that interact with phylogenetically random partners, in some cases to a larger extent than detected with an existing method that does not account for partner availability. We also found many taxa that interact with phylogenetically clustered partners, while taxa with overdispersed partners were rare. Our results highlight the important role of randomness in shaping interaction networks, even in highly intimate symbioses, and provide a much-needed quantitative framework to assess the role that evolutionary history and symbiotic specialization play in shaping patterns of biodiversity.
Mites alight! Sunflower crop area and pollen supplementation enhance honey bee resistance to Varroa destructor
Authors: Palmer-Young Evan C , Malfi Rosemary , Zhou Yujun , Joyce Bryanna , Whitehead Hannah , Van Wyk Jennifer I , Baylis Kathy , Grubbs Kyle , Lopez Dawn , Evans Jay D , Irwin Rebecca E , Adler Lynn S 
Published: August 2021

ABSTRACTAnthropogenic landscape changes can affect parasite epidemiology in wild and agricultural animals. Honey bees are agricultural animals whose services are threatened by loss of floral resources and by parasites, most notably the invasive mite Varroa destructor. Existing mite control strategies rely heavily on chemical treatments that can adversely affect bees. Alternative, pesticide-free control methods are urgently needed to maintain effective pollination services. Many flowering plants provide nectar and pollen that enhance resistance to parasites in animals. Enrichment of landscapes with antiparasitic floral resources could therefore provide a sustainable means of parasite control in pollinators.Floral rewards of Asteraceae plants have been shown to reduce parasitic infection in diverse bee species, including honey and bumble bees. Here, we tested the effects of sunflower (Helianthus annuus) cropland and pollen supplementation on honey bee resistance to macro- and microparasites. Our results show that each doubling of sunflower crop area is associated with a 28% reduction in mite infestation intensity. Late-summer supplementation of colonies with sunflower pollen reduced mite infestation by 2.75-fold relative to an artificial pollen. Our findings suggest the potential for sunflower plantings or pollen supplements to counteract a main driver of honey bee losses worldwide.
Near-Zero Phase-Lag Hyperscanning in a Novel Wireless EEG System
Authors: Chuang Chun-Hsiang , Lu Shao-Wei , Chao Yi-Ping , Peng Po-Hsun , Hsu Hao-Che , Jung Tzyy-Ping 
Published: August 2021

AbstractHyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with wireless electroencephalography (EEG) is increasingly popular owing to its mobility and ability to decipher social interactions in natural settings at the millisecond scale. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposed a clock-synchronized method using a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional RF channels to keep the counter of their receiving dongles updated, guaranteeing that binding event markers received by the dongle with the EEG time series have the correct timestamp. The results of two simulation experiments and one video gaming experiment revealed that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase-lag and negligible amplitude difference between signals. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.
Assembling an illustrated family-level tree of life for exploration in mobile devices
Authors: Del Risco Andrés A. , Chacón Diego A. , Ángel Lucia , García David A. 
Published: August 2021

ABSTRACTSince the concept of the tree of life was introduced by Darwin about a century and a half ago, a considerable fraction of the scientific community has focused its efforts on its reconstruction, with remarkable progress during the last two decades with the advent of DNA sequences. However, the assemblage of a comprehensive tree of life for its exploration has been a difficult task to achieve due to two main obstacles: i) information is scattered into a plethora of individual sources and ii) practical visualization tools for exceptionally large trees are lacking. To overcome both challenges, we aimed to synthetize a family-level tree of life by compiling over 1400 published phylogenetic studies, ensuring that the source trees represent the best phylogenetic hypotheses to date based on a set of objective criteria. Moreover, we dated the synthetic tree by employing over 550 secondary-calibration points, using publicly available sequences for more than 5000 taxa, and by incorporating age ranges from the fossil record for over 2800 taxa. Additionally, we developed a mobile app (Tree of Life) for smartphones in order to facilitate the visualization and interactive exploration of the resulting tree. Interactive features include an easy exploration by zooming and panning gestures of touch screens, collapsing branches, visualizing specific clades as subtrees, a search engine, a timescale to determine extinction and divergence dates, and quick links to Wikipedia. Small illustrations of organisms are displayed at the tips of the branches, to better visualize the morphological diversity of life on earth. Our assembled Tree of Life currently includes over 7000 taxonomic families (about half of the total family-level diversity) and its content will be gradually expanded through regular updates to cover all life on earth at family-level.
Evaluating the efficacy of a consumer-centric method for ecological sampling: Using bonobo (Pan paniscus) feeding patterns as an instrument for tropical forest characterization
Authors: Wessling Erin G. , Samuni Liran , Mundry Roger , Pascual Miguel Adan , Lucchesi Stefano , Kambale Bienfait , Surbeck Martin 
Published: August 2021

AbstractCharacteristics of food availability and distribution are a key component of a species ecology. Objective measurement of food resources, such as vegetation plot sampling, do not consider aspects of selection by the consumer and therefore may produce imprecise measures of availability. Further, in most animal ecology research, traditional ecological surveying often is time-intensive and supplementary to ongoing behavioral observation. We propose a method to integrate ecological sampling of an animal’s environment into existing behavioral data collection systems by using the consumer as the surveyor. Here, we introduce the consumer-centric method (CCM) of assessing resource availability for its ability to measure food resource abundance, distribution, and dispersion. This method catalogues feeding locations observed during behavioral observation and uses aggregated data to characterize these ecological metrics.We evaluated the CCM relative to traditional vegetation plot surveying using accumulated feeding locations across three years visited by a tropical frugivore, the bonobo (Pan paniscus), and compared it with data derived from over 200 vegetation plots across their 50km2+ home range.We demonstrate that food species abundance estimates derived from the CCM are comparable to those derived from traditional vegetation plot sampling after approximately 600 observation days or 60 spatially explicit feeding locations. The agreement between the methods further improved when accounting for aspects of consumer selectivity in objective vegetation plot sampling (e.g., size minima). Estimates of density from CCM correlated with plot-derived estimates and were relatively insensitive to home range inclusion and other species characteristics, but were sensitive to sampling frequency (e.g., consumption frequency). Agreement between the methods in relative distribution of resources performed better across species than expected by chance, although measures of dispersion correlated poorly.We demonstrate that while providing a robust measure to quantify local food availability, the CCM has an advantage over traditional sampling methods as it incorporates sampling biases relevant to the consumer. Therefore, as this method can be incorporated into existing observational data collection and does not require additional ecological surveying, it serves as a promising method for behavioral ecological data collection for animal species who re-use space and consume immobile food items.
A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells
Authors: Unosson Måns , Brancaccio Marco , Hastings Michael , Johansen Adam M. , Finkenstädt Bärbel 
Published: August 2021

AbstractWe propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatiotemporal gene expression in intact networks of cells. The model describes the oscillating time evolution of molecular mRNA counts through a negative transcriptional-translational feedback loop encoded in a chemical Langevin equation with a probabilistic delay distribution. The model is extended spatially by means of a multiplicative random effects model with a first order Markov random field prior distribution. Our methodology effectively separates intrinsic molecular noise, measurement noise, and extrinsic noise and phenotypic variation driving cell heterogeneity, while being amenable to parameter identification and inference. Based on the single-cell model we propose a novel computational stability analysis that allows us to infer two key characteristics, namely the robustness of the oscillations, i.e. whether the reaction network exhibits sustained or damped oscillations, and the profile of the regulation, i.e. whether the inhibition occurs over time in a more distributed versus a more direct manner, which affects the cells’ ability to phase-shift to new schedules. We show how insight into the spatio-temporal characteristics of the circadian feedback loop in the suprachiasmatic nucleus (SCN) can be gained by applying the methodology to bioluminescence-reported expression of the circadian core clock geneCry1across mouse SCN tissue. We find that while (almost) all SCN neurons exhibit robust cell-autonomous oscillations, the parameters that are associated with the regulatory transcription profile give rise to a spatial division of the tissue between the central region whose oscillations are resilient to perturbation in the sense that they maintain a high degree of synchronicity, and the dorsal region which appears to phase shift in a more diversified way as a response to large perturbations and thus could be more amenable to entrainment.
Canine oral melanoma genomic and transcriptomic study defines two molecular subgroups with different therapeutical targets
Authors: Prouteau Anais , Mottier Stephanie , Primot Aline , Cadieu Edouard , Bachelot Laura , Botherel Nadine , Cabillic Florian , Houel Armel , Cornevin Laurence , Kergal Camille , Corre Sebastien , Abadie Jerome , Hitte Christophe , Gilot David , Lindblad-Toh Kerstin , Andre Catherine , Derrien Thomas , Hedan Benoit 
Published: August 2021

AbstractMucosal melanoma (MM) is a rare and aggressive clinical cancer that occurs mostly in the head, neck, and anogenital regions. Despite recent advances in genetics and the development of revolutionary treatments, such as immunotherapy, the prognosis for MM remains poor. Canine MM shares several clinical, histological, and genetic features with its human counterpart, offering a relevant spontaneous and immunocompetent model to decipher the genetic bases and explore treatment options for human MM. We performed an integrative genomic and transcriptomic analysis of 32 canine MM samples, which allowed us to identify two molecular subgroups differing in microenvironment and structural variant (SV) content. The overexpression of genes related to the microenvironment and T-cell response was associated with tumors harboring a lower content of structural variants, whereas the overexpression of pigmentation-related pathways and oncogenes such as TERT were associated with a high SV burden. To detail the SVs, especially those with focal amplifications, whole-genome sequencing was performed on four canine MM cell lines. We showed that focal amplifications characterized complex chromosomal rearrangements targeting oncogenes such as MDM2 or CDK4 and a recurrently amplified region on canine chromosome 30, comprising the genes TRPM7, GABPB1, USP8, and SPPL2A, were candidate oncogenes for MM. We showed that the copy numbers of these genes were significantly correlated with their expression levels. Finally, we demonstrated that the genes TRPM7, GABPB1, and SPPL2A play a role in cell proliferation; thus, these may be considered new candidate oncogenes for human MM. Our findings suggest the existence of two MM molecular subgroups that may benefit from dedicated therapies, such as immune checkpoint inhibitors or targeted therapies. These results illustrate the relevance of dog models for deciphering genetic mechanisms in spontaneous MM, along with the potential to screen for efficient targeted therapies for rare and aggressive cancers in humans.
RPnet: A Reverse Projection Based Neural Network for Coarse-graining Metastable Conformational States for Protein Dynamics
Authors: Gu Hanlin , Wang Wei , Cao Siqin , Unarta Ilona Christy , Yao Yuan , Sheong Fu Kit , Huang Xuhui 
Published: August 2021

ABSTRACTMarkov State Model (MSM) is a powerful tool for modeling the long timescale dynamics based on numerous short molecular dynamics (MD) simulation trajectories, which makes it a useful tool for elucidating the conformational changes of biological macromolecules. By partitioning the phase space into discretized states and estimate the probabilities of inter-state transitions based on short MD trajectories, one can construct a kinetic network model that could be used to extrapolate long time kinetics if the Markovian condition is met. However, meeting the Markovian condition often requires hundreds or even thousands of states (microstates), which greatly hinders the comprehension of conformational dynamics of complex biomolecules. Kinetic lumping algorithms can coarse grain numerous microstates into a handful of metastable states (macrostates), which would greatly facilitate the elucidation of biological mechanisms. In this work, we have developed a reverse projection based neural network (RPnet) method to lump microstates into macrostates, by making use of a physics-based loss function based on the projection operator framework of conformational dynamics. By recognizing that microstate and macrostate transition modes can be related through a projection process, we have developed a reverse projection scheme to directly compare the microstate and macrostate dynamics. Based on this reverse projection scheme, we designed a loss function that allows effectively assess the quality of a given kinetic lumping. We then make use of a neural network to efficiently minimize this loss function to obtain an optimized set of macrostates. We have demonstrated the power of our RPnet in analyzing the dynamics of a numerical 2D potential, alanine dipeptide, and the clamp opening of an RNA polymerase. In all these systems, we have illustrated that our method could yield comparable or better results than competing methods in terms of state partitioning and reproduction of slow dynamics. We expect that our RPnet holds promise in analyzing conformational dynamics of biological macromolecules.