bluuebunny/crossref_metadata_2025_split huggingface dataset:
Migration through a major Andean ecogeographic disruption as a driver of genotypic and phenotypic diversity in a wild tomato species
Authors: Landis Jacob B. , Miller Christopher M. , Broz Amanda K. , Bennett Alexandra A. , Carrasquilla-Garcia Noelia , Cook Douglas R. , Last Robert L. , Bedinger Patricia A. , Moghe Gaurav D. 
Published: September 2020

AbstractThe large number of species on our planet arises from the phenotypic variation and reproductive isolation occurring at the population level. In this study, we sought to understand the origins of such population-level variation in defensive acylsugar chemistry and mating systems inSolanum habrochaites– a wild tomato species found in diverse Andean habitats in Ecuador and Peru. Using Restriction-Associated-Digestion Sequencing (RAD-seq) of 50S. habrochaitesaccessions, we identified eight population clusters generated via isolation and hybridization dynamics of 4-6 ancestral populations. Estimation of heterozygosity, fixation index, isolation by distance, and migration probabilities, allowed identification of multiple barriers to gene flow leading to the establishment of extant populations. One major barrier is the Amotape-Huancabamba Zone (AHZ) – a geographical feature in the Andes with high endemism, where the mountainous range breaks up into isolated microhabitats. The AHZ was associated with emergence of alleles for novel reproductive and acylsugar phenotypes. These alleles led to the evolution of self-compatibility in the northern populations, where alleles for novel defense-related enzyme variants were also found to be fixed. We identified geographical distance as a major force causing population differentiation in the central/southern part of the range, whereS. habrochaiteswas also inferred to have originated. Findings presented here highlight the role of the diverse ecogeography of Peru and Ecuador in generating new, reproductively isolated populations, and enhance our understanding of the microevolutionary processes that lay a path to speciation.
Automatic Traits Extraction and Fitting for Field High-throughput Phenotyping Systems
Authors: Guo Xingche , Qiu Yumou , Nettleton Dan , Yeh Cheng-Ting , Zheng Zihao , Hey Stefan , Schnable Patrick S. 
Published: September 2020

ABSTRACTHigh-throughput phenotyping is a modern technology to measure plant traits efficiently and in large scale by imaging systems over the whole growth season. Those images provide rich data for statistical analysis of plant phenotypes. We propose a pipeline to extract and analyze the plant traits for field phenotyping systems. The proposed pipeline include the following main steps: plant segmentation from field images, automatic calculation of plant traits from the segmented images, and functional curve fitting for the extracted traits. To deal with the challenging problem of plant segmentation for field images, we propose a novel approach on image pixel classification by transform domain neural network models, which utilizes plant pixels from greenhouse images to train a segmentation model for field images. Our results show the proposed procedure is able to accurately extract plant heights and is more stable than results from Amazon Turks, who manually measure plant heights from original images.
ARL15 modulates magnesium homeostasis through N-glycosylation of CNNMs
Authors: Zolotarov Yevgen , Ma Chao , González-Recio Irene , Hardy Serge , Franken Gijs , Uetani Noriko , Latta Femke , Kostantin Elie , Boulais Jonathan , Thibault Marie-Pier , Côté Jean-François , Moreno Irene Díaz , Quintana Antonio Díaz , Hoenderop Joost G.J. , Martínez-Cruz Luis Alfonso , Tremblay Michel L. , de Baaij Jeroen H.F. 
Published: September 2020

ABSTRACTCyclin M (CNNM1-4) proteins maintain cellular and body magnesium (Mg2+) homeostasis. Using various biochemical approaches, we have identified members of the CNNM family as direct interacting partners of ADP-ribosylation factor-like protein 15 (ARL15), a small GTP-binding protein. ARL15 interacts with CNNMs at their carboxyl-terminal conserved cystathionine-β-synthase (CBS) domains. In silico modeling of the interaction using the reported structures of both CNNM2 and ARL15 supports that the small GTPase specifically binds the CBS1 domain. Immunocytochemical experiments demonstrate that CNNM2 and ARL15 co-localize in the kidney, with both proteins showing subcellular localization in the Golgi-apparatus. Most importantly, we found that ARL15 is required for forming complex N-glycosylation of CNNMs. Overexpression of ARL15 promotes complex N-glycosylation of CNNM3. Mg2+ uptake experiments with a stable isotope demonstrate that there is a significant increase of 25Mg2+ uptake upon knockdown of ARL15 in multiple kidney cancer cell lines. Altogether, our results establish ARL15 as a novel negative regulator of Mg2+ transport by promoting the complex N-glycosylation of CNNMs.
Allele-specific gene regulation by KDM6A
Authors: Ma Wenxiu , Fang He , Pease Nicolas , Filippova Galina N. , Disteche Christine M. , Berletch Joel B. 
Published: September 2020

SUMMARYKDM6A demethylates the repressive histone mark H3K27me3 and thus plays an important role in developmental gene regulation. KDM6A expression is female-biased due to escape from X inactivation, suggesting that this protein may play a role in sex differences. Here, we report that maternal and paternal alleles of a subset of mouse genes are differentially regulated by KDM6A. Knockouts ofKdm6ain male and female embryonic stem cells derived from F1 hybrid mice from reciprocal interspecific crosses resulted in preferential downregulation of maternal alleles of a number of genes implicated in development. Moreover, the majority of these genes exhibited a maternal allele expression bias, which was observed in both reciprocal crosses. Promoters of genes downregulated on maternal but not paternal alleles demonstrated a loss of chromatin accessibility, while the expected increase in H3K27me3 levels occurred only at promoters of genes downregulated on paternal but not maternal alleles. These results illustrate parent-of-origin mechanisms of gene regulation by KDM6A, consistent with histone demethylation-dependent and -independent activities.
American mammals susceptibility to dengue according to geographical, environmental and phylogenetic distances
Authors: Robles-Fernández Ángel L. , Santiago-Alarcon Diego , Lira-Noriega Andrés 
Published: September 2020

ABSTRACTMany human emergent and re-emergent diseases have a sylvatic cycle. Yet, little effort has been put into discovering and modeling the wild mammal reservoirs of dengue (DENV), particularly in the Americas. Here, we show a species-level susceptibility prediction to dengue of wild mammals in the Americas as a function of the three most important biodiversity dimensions (ecological, geographical, and phylogenetic spaces), using machine learning protocols. Model predictions showed that different species of bats would be highly susceptible to DENV infections, where susceptibility mostly depended on phylogenetic relationships among hosts and their environmental requirement. Mammal species predicted as highly susceptible coincide with sets of species that have been reported infected in field studies, but it also suggests other species that have not been previously considered or that have been captured in low numbers. Also, the environment (i.e., the distance between the species’ optima in bioclimatic dimensions) in combination with geographic and phylogenetic distance is highly relevant in predicting susceptibility to DENV in wild mammals. Our results agree with previous modeling efforts indicating that temperature is an important factor determining DENV transmission, and provide novel insights regarding other relevant factors and the importance of considering wild reservoirs. This modeling framework will aid in the identification of potential DENV reservoirs for future surveillance efforts.
Assembly of a double-stranded RNA synthesizing complex: RNA-DEPENDENT RNA POLYMERASE 2 docks with NUCLEAR RNA POLYMERASE IV at the clamp domain
Authors: Mishra Vibhor , Singh Jasleen , Fukudome Akihito , Wang Feng , Zhang Yixiang , Takagi Yuichiro , Trinidad Jonathan C , Pikaard Craig S 
Published: September 2020

AbstractIn plants, transcription of selfish genetic elements such as transposons and DNA viruses is suppressed by RNA-directed DNA methylation. This process is guided by 24 nt short-interfering RNAs (siRNAs) whose double-stranded precursors are synthesized by DNA-dependent NUCLEAR RNA POLYMERASE IV (Pol IV) and RNA-DEPENDENT RNA POLYMERASE 2 (RDR2). Pol IV and RDR2 co-immunoprecipitate, and their activities are tightly coupled, yet the basis for their association is unknown. Here, we show that RDR2 stably associates with Pol IV’s largest catalytic subunit, NRPD1 at three sites, all within the clamp module. The clamp is a ubiquitous feature of DNA-dependent RNA polymerases that opens to allow DNA template entry and closes to encase the DNA-RNA hybrid adjacent to the RNA exit channel. The clamp also provides binding sites for polymerase-specific subunits or regulatory proteins, thus RDR2 binding to the Pol IV clamp is consistent with this theme. Within RDR2, the site of interaction with NRPD1 is very near the catalytic center. The locations of the NRPD1-RDR2 contact sites suggest a model in which transcripts emanating from Pol IV’s RNA exit channel align with the template cleft of RDR2, facilitating rapid conversion of terminated Pol IV transcripts into double-stranded RNAs.Significance StatementShort interfering RNAs (siRNAs) play important roles in gene regulation by inhibiting mRNA translation into proteins or by guiding chromatin modifications that inhibit gene transcription. In plants, transcriptional gene silencing is guided by siRNAs derived from double-stranded (ds) RNAs generated by coupling the activities of DNA-dependent NUCLEAR RNA POLYMERASE IV and RNA-DEPENDENT RNA POLYMERASE 2. We show that the physical basis for Pol IV-RDR2 coupling is RDR2 binding to the clamp domain of Pol IV’s largest subunit. The positions of the protein docking sites suggest that nascent Pol IV transcripts are generated in close proximity to RDR2’s catalytic site, enabling rapid conversion of Pol IV transcripts into dsRNAs.
Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations
Authors: Samantray Suman , Yin Feng , Kav Batuhan , Strodel Birgit 
Published: September 2020

AbstractThe progress towards understanding the molecular basis of Alzheimers’s disease is strongly connected to elucidating the early aggregation events of the amyloid-β(Aβ) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of Aβinto oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as Aβwere developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the Aβ16−22peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-dispoverestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results are obtained with CHARMM36m and especially its version with increased protein–water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it.
Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network
Authors: David Rakesh , Menezes Rhys-Joshua D. , De Klerk Jan , Castleden Ian R. , Hooper Cornelia M. , Carneiro Gustavo , Gilliham Matthew 
Published: September 2020

AbstractWith the advent of increased diversity and scale of molecular data, there has been a growing appreciation for the applications of machine learning and statistical methodologies to gain new biological insights. An important step in achieving this aim is the Relation Extraction process which specifies if an interaction exists between two or more biological entities in a published study. Here, we employed natural-language processing (CBOW) and deep Recurrent Neural Network (bi-directional LSTM) to predict relations between biological entities that describe protein subcellular localisation in plants. We applied our system to 1700 publishedArabidopsisprotein subcellular studies from the SUBA manually curated dataset. The system was able to extract relevant text and the classifier predicted interactions between protein name, subcellular localisation and experimental methodology. It obtained a final precision, recall rate, accuracy and F1 scores of 0.951, 0.828, 0.893 and 0.884 respectively. The classifier was subsequently tested on a similar problem in crop species (CropPAL) and demonstrated a comparable accuracy measure (0.897). Consequently, our approach can be used to extract protein functional features from unstructured text in the literature with high accuracy. The developed system will improve dissemination or protein functional data to the scientific community and unlock the potential of big data text analytics for generating new hypotheses from diverse datasets.
Disease Network Delineates the Disease Progression Profile of Cardiovascular Diseases
Authors: Tang Zefang , Yu Yiqin , Ng Kenney , Sow Daby , Hu Jianying , Mei Jing 
Published: September 2020

AbstractAs Electronic Health Records (EHR) data accumulated explosively in recent years, the tremendous amount of patient clinical data provided opportunities to discover real world evidence. In this study, a graphical disease network, named progressive cardiovascular disease network (progCDN), was built based on EHR data from 14.3 million patients1to delineate the progression profiles of cardiovascular diseases (CVD). The network depicted the dominant diseases in CVD development, such as the heart failure and coronary arteriosclerosis. Novel progression relationships were also discovered, such as the progression path from long QT syndrome to major depression. In addition, three age-group progCDNs identified a series of age-associated disease progression paths and important successor diseases with age bias. Furthermore, we extracted a list of salient features to build a series of disease risk models based on the progression pairs in the disease network. The progCDN network can be further used to validate or explore novel disease relationships in real world data. Features with sufficient abundance and high correlation can be widely applied to train disease risk models when using EHR data.
A detailed mathematical theory of thalamic and cortical microcircuits based on inference in a generative vision model
Authors: George Dileep , Lázaro-Gredilla Miguel , Lehrach Wolfgang , Dedieu Antoine , Zhou Guangyao 
Published: September 2020

AbstractUnderstanding the information processing roles of cortical circuits is an outstanding problem in neuroscience and artificial intelligence. Theory-driven efforts will be required to tease apart the functional logic of cortical circuits from the vast amounts of experimental data on cortical connectivity and physiology. Although the theoretical setting of Bayesian inference has been suggested as a framework for understanding cortical computation, making precise and falsifiable biological mappings need models that tackle the challenge of real world tasks. Based on a recent generative model, Recursive Cortical Networks, that demonstrated excellent performance on visual task benchmarks, we derive a family of anatomically instantiated and functional cortical circuit models. Efficient inference and generalization guided the representational choices in the original computational model. The cortical circuit model is derived by systematically comparing the computational requirements of this model with known anatomical constraints. The derived model suggests precise functional roles for the feed-forward, feedback, and lateral connections observed in different laminae and columns, assigns a computational role for the path through the thalamus, predicts the interactions between blobs and inter-blobs, and offers an algorithmic explanation for the innate inter-laminar connectivity between clonal neurons within a cortical column. The model also explains several visual phenomena, including the subjective contour effect, and neon-color spreading effect, with circuit-level precision. Our work paves a new path forward in understanding the logic of cortical and thalamic circuits.
T cell competition profoundly reduces the effect of initial precursor frequency on the generation of CD4 T cell memory
Authors: Smith Adrian L. , de St. Groth Barbara Fazekas 
Published: September 2020

SummaryProtective immune responses are accompanied by increases in the frequency of high affinity T cells, which contribute to subsequent immunological memory. There is evidence that the fold-change in T cell number during the immune response is inversely related to initial precursor frequency, but the size of this effect remains poorly defined. Indeed, in many reports precursor frequency has been considered as directly proportional to the magnitude of the response. We have determined the effect of initial precursor frequency over the course of an in vivo antigen-specific response, in an experimental setting in which the other variables, TCR affinity and antigen dose, are kept constant. A major effect of precursor frequency was apparent in both the expansion and contraction phases; low initial precursor frequency in the physiological range was associated with greater initial expansion in T cell numbers, and also with preferential retention of memory cells. The effect was seen continuously across a 1000-fold naïve cell frequency range, leading to memory cell frequencies that differed by only 3-fold. These results are consistent with the existence of ongoing competition for antigen throughout the course of the immune response and explain the paradoxical ability of populations of genetically diverse individuals to make appropriate protective immune responses despite the large differences in initial repertoire that result from semi-random thymic TCR repertoire generation and selection.
The effects of seasonal anoxia on the microbial community structure in demosponges in a marine lake (Lough Hyne, Ireland)
Authors: Schuster Astrid , Strehlow Brian William , Eckford-Soper Lisa , McAllen Rob , Canfield Donald Eugene 
Published: September 2020

AbstractClimate change is expanding marine oxygen minimum zones (OMZs), while anthropogenic nutrient input depletes oxygen concentrations locally. The effects of deoxygenation on animals are generally detrimental; however, some sponges (Porifera) exhibit hypoxic and anoxic tolerance through currently unknown mechanisms. Sponges harbor highly specific microbiomes, which can include microbes with anaerobic capabilities. Sponge-microbe symbioses must also have persisted through multiple anoxic/hypoxic periods throughout Earth history. Since sponges lack key components of the hypoxia-inducible factor (HIF) pathway responsible for hypoxic responses in other animals, it was hypothesized that sponge tolerance to deoxygenation may be facilitated by its microbiome. To test this hypothesis, we determined the microbial composition of sponge species tolerating seasonal anoxia and hypoxiain situin a semi-enclosed marine lake, using 16S rRNA amplicon sequencing. We discovered a high degree of cryptic diversity among sponge species tolerating seasonal deoxygenation, including at least nine encrusting species of the orders Axinellida and Poecilosclerida. Despite significant changes in microbial community structure in the water, sponge microbiomes were species specific and remarkably stable under varied oxygen conditions, though some symbiont sharing occurred under anoxia. At least three symbiont combinations, all including large populations ofThaumarchaeota, corresponded with deoxygenation tolerance, and some combinations were shared between distantly related hosts. We propose hypothetical host-symbiont interactions following deoxygenation that could confer deoxygenation tolerance.ImportanceThe oceans have an uncertain future due to anthropogenic stressors and an uncertain past that is becoming clearer with advances in biogeochemistry. Both past and future oceans were, or will be, deoxygenated compared to present conditions. Studying how sponges and their associated microbes tolerate deoxygenation provides insights into future marine ecosystems. Moreover, sponges form the earliest branch of the animal evolutionary tree and they likely resemble some of the first animals. We determined the effects of variable environmental oxygen concentrations on the microbial communities of several demosponge species during seasonal anoxia in the field. Our results indicate that anoxic tolerance in some sponges may depend on their symbionts, but anoxic tolerance was not universal in sponges. Therefore, some sponge species could likely outcompete benthic organisms like corals in future, reduced-oxygen ecosystems. Our results support the molecular evidence that sponges and other animals have a Neoproterozoic origin, and that animal evolution was not limited by low-oxygen conditions.