title: Between-subject prediction reveals a shared representational geometry in the rodent hippocampus

abstract: The rodent hippocampus constructs statistically independent representations across environments ("global remapping") and assigns individual neuron firing fields to locations within an environment in an apparently random fashion, processes thought to contribute to the role of the hippocampus in episodic memory. This random mapping implies that it should be challenging to predict hippocampal encoding of a given experience in one subject based on the encoding of that same experience in another subject. Contrary to this prediction, we find that by constructing a common representational space across rats in which neural activity is aligned using geometric operations (rotation, reflection, and translation; "hyperalignment"), we can predict data of "right" trials (R) on a T-maze in a target rat based on 1) the "left" trials (L) of the target rat, and 2) the relationship between L and R trials from a different source rat. These cross-subject predictions relied on ensemble activity patterns including both firing rate and field location, and outperformed a number of control mappings, such as those based on permuted data that broke the relationship between L and R activity for individual neurons, and those based solely on within-subject prediction. This work constitutes proof-of-principle for successful cross-subject prediction of ensemble activity patterns in the hippocampus, and provides new insights in understanding how different experiences are structured, enabling further work identifying what aspects of experience encoding are shared vs. unique to an individual.


title: Energetics of stochastic BCM type synaptic plasticity and storing of accurate information

abstract: Excitatory synaptic signaling in cortical circuits is thought to be metabolically expensive. Two fundamental brain functions, learning and memory, are associated with long-term synaptic plasticity, but we know very little about energetics of these slow biophysical processes. This study investigates the energy requirement of information storing in plastic synapses for an extended version of BCM plasticity with a decay term, stochastic noise, and nonlinear dependence of neurons firing rate on synaptic current (adaptation). It is shown that synaptic weights in this model exhibit bistability. In order to analyze the system analytically, it is reduced to a simple dynamic mean-field for a population averaged plastic synaptic current. Next, using the concepts of nonequilibrium thermodynamics, we derive the energy rate (entropy production rate) for plastic synapses and a corresponding Fisher information for coding presynaptic input. That energy, which is of chemical origin, is primarily used for battling fluctuations in the synaptic weights and presynaptic firing rates, and it increases steeply with synaptic weights, and more uniformly though nonlinearly with presynaptic firing. At the onset of synaptic bistability, Fisher information and memory lifetime both increase sharply, by a few orders of magnitude, but the plasticity energy rate changes only mildly. This implies that a huge gain in the precision of stored information does not have to cost large amounts of metabolic energy, which suggests that synaptic information is not directly limited by energy consumption. Interestingly, for very weak synaptic noise, such a limit on synaptic coding accuracy is imposed instead by a derivative of the plasticity energy rate with respect to the mean presynaptic firing, and this relationship has a general character that is independent of the plasticity type. An estimate for primate neocortex reveals that a relativemetabolic cost of BCM type synaptic plasticity, as a fraction of neuronal cost related to fast synaptic transmission and spiking, can vary from negligible to substantial, depending on the synaptic noise level and presynaptic firing.

category: neuroscience


title: Extreme hot weather has stronger impacts on avian reproduction in forests than in cities

abstract:
Climate change and urbanization are among the most salient human-induced changes affecting Earths biota. Extreme weather events can have high biological impacts and are becoming more frequent recently. In cities, the urban heat island can amplify the intensity and frequency of hot weather events. However, the joint effects of heat events and urban microclimate on wildlife are unclear, as urban populations may either suffer more from increased heat stress or become adapted to warmer temperatures. Here we test whether the effects of hot weather on reproductive success of great tits (Parus major) are exacerbated or dampened in urban environments compared to forest habitats. By studying two urban and two forest populations over six years, we show that 14-16 days-old nestlings have smaller body mass and tarsus length, and suffer increased mortality when they experience a higher number of hot days during the nestling period. The negative effects of hot weather on body mass and survival are significantly stronger in forests than in urban areas, where these effects are dampened or even reversed. These results suggest that urban birds are less vulnerable to extreme hot weather conditions than their non-urban conspecifics, possibly by adaptively evolving or flexibly adjusting nestling physiology to tolerate heat stress, and/or by adjusting parental behavior in response to heat. This finding highlights that endothermic vertebrates may be able to adapt to heat stress, which may help their populations cope with the joint challenges of climate change and urbanization.

Significance statementExtreme weather events are becoming more frequent due to climate change and can have substantial effects on reproduction and survival of wild animals. Urban heat island can amplify the frequency of extreme hot weather events, making it potentially more harmful for city-dwelling organisms. Alternatively, urban populations living in warmer environments may adapt to better tolerate heat. We investigated these alternatives by comparing nestling development and survival between urban and forest great tit (Parus major) populations. We found that urban populations are less vulnerable to heat: nestling body mass and survival decreased rapidly with the increasing number of hot days in forests, while these effects were dampened in urban broods. Thus, urban populations may become adapted to better tolerate heat events.

category: ecology


title: The Landscape of Precision Cancer Combination Therapy: A Single-Cell Perspective

abstract: The availability of single-cell transcriptomics data opens new opportunities for rational design of combination cancer treatments. Mining such data, we employed combinatorial optimization techniques to explore the landscape of optimal combination therapies in solid tumors including brain, head and neck, melanoma, lung, breast and colon cancers. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. As a baseline case, we studied the killing of at least 80% of the tumor cells while sparing more than 90% of the non-tumor cells in each patient, as a putative regimen. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient. However, the number of distinct targets that one would need to assemble to treat all patients in a cohort accordingly would be around 10 in most cases. Further requiring that the target genes be also lowly expressed in healthy tissues uncovers qualitatively similar trends. However, as one asks for more stringent and selective killing beyond the baseline regimen we focused on, we find that the number of targets needed rises rapidly. Emerging individual promising receptor targets include PTPRZ1, which is frequently found in the optimal combinations for brain and head and neck cancers, and EGFR, a recurring target in multiple tumor types. In sum, this systematic single-cell based characterization of the landscape of combinatorial receptor-mediated cancer treatments establishes first of their kind estimates on the number of targets needed, identifying promising ones for future development.

category: bioinformatics


title: The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective


title: eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

abstract: An increasing number of gene expression quantitative trait locus (eQTL) studies have made summary statistics publicly available, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and colocalisation. However, differences between these datasets, in their variants tested, allele codings, and in the transcriptional features quantified, are a barrier to their widespread use. Consequently, target genes for most GWAS signals have still not been identified. Here, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl/), a resource which contains quality controlled, uniformly recomputed QTLs from 21 eQTL studies. We find that for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies, enabling the integrative analysis of these data. Although most cis-eQTLs were shared between most bulk tissues, the analysis of purified cell types identified a greater diversity of cell-type-specific eQTLs, a subset of which also manifested as novel disease colocalisations. Our summary statistics can be downloaded by FTP, accessed via a REST API, and visualised on the Ensembl genome browser. New datasets will continuously be added to the eQTL Catalogue, enabling the systematic interpretation of human GWAS associations across many cell types and tissues.

category: genomics


title: The histone variant macroH2A1.1 regulates RNA Polymerase II paused genes within defined chromatin interaction landscapes.

abstract: The histone variant macroH2A1.1 (mH2A1.1) plays a role in cancer development and metastasis-related processes. To determine the underlying molecular mechanisms, we mapped genome-wide localization of endogenous mH2A1.1 in the human breast cancer cell MDA-MB 231. We demonstrate that mH2A1.1 specifically binds to active promoters and enhancers in addition to facultative heterochromatin. Selective knock-down of mH2A1.1 deregulates expression of hundreds of highly active genes. Depending on the chromatin landscape, mH2A1.1 acts through two distinct molecular mechanisms. The first is to limit excessive transcription in a predefined environment and relies on domain recruitment of mH2A1.1 at the promoter and gene body. The second mechanism is specific to RNA Pol II (Pol II) paused genes. It requires recruitment of mH2A1.1 restricted to the TSS of these genes. Moreover, we show that these processes occur in a predefined local 3D genome organization and are largely independent of enhancer-promoter looping. Among the genes activated by mH2A1.1, genes regulating mammary tumor cell migration are mostly dependent on Pol II release for their expression level, unlike other categories of mH2A1.1-regulated genes. We thus identified an intriguing new mode of transcriptional regulation by mH2A1.1 and propose that mH2A1.1 serves as a transcriptional modulator with a potential role in assisting the conversion of promoter-locked RNA polymerase II into a productive and elongated Pol II.


title: Learning to Integrate an Artificial Sensory Device: Early Bayesian Integration and Conscious Perception

abstract: The present study examines how artificial tactile stimulation from a novel non-invasive sensory device is learned and integrated with information from another sensory system. Participants were trained to identify the direction of visual dot motion stimuli with a low, medium, and high signal-to-noise ratio. In bimodal trials, this visual direction information was paired with reliable symbolic tactile information. Over several training blocks, discrimination performance in unimodal tactile test trials and subjects confidence in their decision improved, indicating that participants were able to associate the visual and tactile information consciously and thus learned the meaning of the symbolic tactile cues. Formal analysis of the results in bimodal trials showed that both modalities are being integrated already in the early learning phases. Our modeling results revealed that this integration is consistent with a Bayesian model, which is an optimal integration of sensory information. Furthermore, we showed that a confidence-based Bayesian integration explains the observed behavioral data better than the classical variance-based Bayesian integration. Thus, the present study demonstrates that humans can consciously learn and integrate an artificial sensory device that delivers symbolic tactile information. This finding connects the field of multisensory integration research to the development of sensory substitution systems.


title: Dynamic landscape of protein occupancy across the Escherichia coli chromosome

abstract: Free-living bacteria adapt to environmental change by reprogramming gene expression through precise interactions of hundreds of DNA-binding proteins. A predictive understanding of bacterial physiology requires us to globally monitor all such protein-DNA interactions across a range of environmental and genetic perturbations. Here, we show that such global observations are possible using an optimized version of in vivo protein occupancy display technology (IPOD-HR), and present a pilot application to E. coli. We observe that the E. coli protein-DNA interactome organizes into two distinct prototypic features: (1) highly dynamic condition-dependent transcription factor occupancy, and (2) robust kilobase scale occupancy by nucleoid factors, forming silencing domains analogous to eukaryotic heterochromatin. We show that occupancy dynamics across a range of conditions can rapidly reveal the global transcriptional regulatory organization of a bacterium. Beyond discovery of previously hidden regulatory logic, we show that these observations can be utilized to computationally determine sequence-specificity models for the majority of active transcription factors. Our study demonstrates that global observations of protein occupancy combined with statistical inference can rapidly and systematically reveal the transcriptional regulatory and structural features of a bacterial genome. This capacity is particularly crucial for non-model bacteria which are not amenable to routine genetic manipulation.

category: systems biology


title: Insights into Cross-species Evolution of Novel Human Coronavirus SARS-CoV-2 and Defining Immune Determinants for Vaccine Development

abstract: Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in the city of Wuhan, China during December 2019, has now spread to various countries across the globe triggering a heightened containment effort. This human pathogen is a member of betacoronavirus genus carrying 30 kilobase of single positive-sense RNA genome. Understanding the evolution, zoonotic transmission, and source of this novel virus would help accelerating containment and prevention efforts. The present study reported detailed analysis of SARS-CoV-2 genome evolution and potential candidate peptides for vaccine development. This new coronavirus genotype might have been evolved from a bat-coronavirus by accumulating non-synonymous mutations, indels, and recombination events. Structural proteins Spike (S), and Membrane (M) had extensive mutational changes, whereas Envelope (E) and Nucleocapsid (N) proteins were very conserved suggesting differential selection pressures exerted on SARS-CoV-2 during evolution. Interestingly, SARS-CoV-2 Spike protein contains a 39 nucleotide sequence insertion relative to SARS-like bat-SL-CoVZC45/2017. Furthermore, we identified eight high binding affinity (HBA) CD4 T-cell epitopes in the S, E, M and N proteins, which can be commonly recognized by HLA-DR alleles of Asia and Asia-Pacific Region population. These immunodominant epitopes can be incorporated in universal subunit SARS-CoV-2 vaccine. Diverse HLA types and variations in the epitope binding affinity may contribute to the wide range of immunopathological outcomes of circulating virus in humans. Our findings emphasize the requirement for continuous surveillance of SARS-CoV-2 strains in live animal markets to better understand the viral adaptation to human host and to develop practical solutions to prevent the emergence of novel pathogenic SARS-CoV-2 strains.

category: microbiology


title: Interpretable detection of novel human viruses from genome sequencing data

abstract: Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. Further, we develop a suite of interpretability tools and show that it can be applied also to other models beyond the host prediction task. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect regions of interest in novel agents, for example the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020. All methods presented here are implemented as easy-to-install packages enabling analysis of NGS datasets without requiring any deep learning skills, but also allowing advanced users to easily train and explain new models for genomics.


title: Loss and recovery of transcriptional plasticity after long-term adaptation to global change conditions in a marine copepod

abstract: Adaptive evolution from standing genetic variation and physiological plasticity will fuel resilience in the geologically unprecedented warming and acidification of the earths oceans. For marine animals, however, we have much to learn about the mechanisms, interactions, and costs of adaptation. Here, using 20 generations of experimental evolution followed by three generations of reciprocal transplantation, we investigate the relationship between adaptation and plasticity in the marine copepod, Acartia tonsa, in future greenhouse conditions (high temperature, high CO2). We find highly parallel genetic adaptation to greenhouse conditions in genes related to stress response, gene expression regulation, actin regulation, developmental processes, and energy production. However, reciprocal transplantation showed that genetic adaptation resulted in a loss of transcriptional plasticity, reduced fecundity, and reduced population growth when greenhouse animals were returned to ambient conditions or reared in low food conditions, suggestive of genetic assimilation after 20 generations of adaptation. Despite the loss of plasticity at F21, after three successive transplant generations, greenhouse-adapted animals were able to match the ambient-adaptive transcriptional profile. Concurrent changes in allele frequencies and erosion of nucleotide diversity suggest that this recovery occurred via adaptation back to ancestral conditions. These results demonstrate the power of experimental evolution from natural populations to reveal the mechanisms, timescales of responses, consequences, and reversibility of complex, physiological adaptation. While plasticity facilitated initial survival in global change conditions, it eroded after 20 generations as populations genetically adapted, limiting resilience to new stressors and previously benign environments.

category: evolutionary biology


title: CopyMix: Mixture Model Based Single-Cell Clustering and Copy Number Profiling using Variational Inference

abstract: Single-cell sequencing technologies are becoming increasingly more established, in particular, in the study of tumor heterogeneity. Investigating tumor heterogeneity is imperative to better understand how tumors evolve since each cell subpopulation harbors a unique set of genomic features that yields a unique phenotype, an issue that is bound to have clinical relevance. Clustering of cells based on copy number data, obtained from single-cell DNA sequencing, provides an opportunity to assess different tumor cell subpopulations. Accordingly, computational methods have emerged for single-cell copy number profiling as well as clustering; however, these two tasks have up to now been handled sequentially, and, included various ad-hoc preprocessing steps; hence, prone to introduce clustering artifacts. We propose CopyMix, a mixture model-based method using Variational Inference, to simultaneously cluster cells and infer a single copy number profile for each cluster, revealing the underlying copy number variation pattern for each cluster. CopyMix is evaluated using simulated data as well as published biological data from ovarian cancer. The results reveal high clustering performance and low errors in copy number profiling. These favorable results indicate a considerable potential to obtain clinical impact by using CopyMix in studies of cancer tumor heterogeneity.


title: Arginine-vasopressin mediates counter-regulatory glucagon release and is diminished in type 1 diabetes

abstract: Insulin-induced hypoglycemia is a major barrier to the treatment of type-1 diabetes (T1D). Accordingly, it is important that we understand the mechanisms regulating the circulating levels of glucagon - the bodys principal blood glucose-elevating hormone which is secreted from alpha-cells of the pancreatic islets. Varying glucose over the range of concentrations that occur physiologically between the fed and fuel-deprived states (from 8 to 4 mM) has no significant effect on glucagon secretion in isolated islets (in vitro) and yet associates with dramatic changes in plasma glucagon in vivo. The identity of the systemic factor(s) that stimulates glucagon secretion remains unknown. Here, we show that arginine-vasopressin (AVP), secreted from the posterior pituitary, stimulates glucagon secretion. Glucagon-secreting alpha-cells express high levels of the vasopressin 1b receptor gene (Avpr1b). Activation of AVP neurons in vivo increased circulating copeptin (the C-terminal segment of the AVP precursor peptide, a stable surrogate marker of AVP) and increased blood glucose; effects blocked by pharmacological antagonism of either the glucagon receptor or vasopressin 1b receptor. AVP also mediates the stimulatory effects of hypoglycemia produced by exogenous insulin and 2-deoxy-D-glucose on glucagon secretion. We show that the A1/C1 neurons of the medulla oblongata drive AVP neuron activation in response to insulin-induced hypoglycemia. Exogenous injection of AVP in vivo increased cytoplasmic Ca2+ in alpha-cells (implanted into the anterior chamber of the eye) and glucagon release. Hypoglycemia also increases circulating levels of AVP in humans and this hormone stimulates glucagon secretion from isolated human islets. In patients with T1D, hypoglycemia failed to increase both plasma copeptin and glucagon levels. These findings suggest that AVP is a physiological systemic regulator of glucagon secretion and that this mechanism becomes impaired in T1D.

category: cell biology


title: Fitting drift-diffusion decision models to trial-by-trial data

abstract: Drift-diffusion models or DDMs are becoming a standard in the field of computational neuroscience. They extend models from signal detection theory by proposing a simple mechanistic explanation for the observed relationship between decision outcomes and reaction times (RT). In brief, they assume that decisions are triggered once the accumulated evidence in favor of a particular alternative option has reached a predefined threshold. Fitting a DDM to empirical data then allows one to interpret observed group or condition differences in terms of a change in the underlying model parameters. However, current approaches only yield reliable parameter estimates in specific situations (c.f. fixed drift rates vs drift rates varying over trials). In addition, they become computationally unfeasible when more general DDM variants are considered (e.g., with collapsing bounds). In this note, we propose a fast and efficient approach to parameter estimation that relies on fitting a "self-consistency" equation that RT fulfill under the DDM. This effectively bypasses the computational bottleneck of standard DDM parameter estimation approaches, at the cost of estimating the trial-specific neural noise variables that perturb the underlying evidence accumulation process. For the purpose of behavioral data analysis, these act as nuisance variables and render the model "overcomplete", which is finessed using a variational Bayesian system identification scheme. But for the purpose of neural data analysis, estimates of neural noise perturbation terms are a desirable (and unique) feature of the approach. Using numerical simulations, we show that this "overcomplete" approach matches the performance of current parameter estimation approaches for simple DDM variants, and outperforms them for more complex DDM variants. Finally, we demonstrate the added-value of the approach, when applied to a recent value-based decision making experiment.

category: animal behavior and cognition


title: Semantic and Prosodic Threat Processing in Trait Anxiety.

abstract: The present study attempts to identify how trait anxiety, measured as worry-level, affects the processing of threatening speech. Two experiments using dichotic listening tasks were implemented; where participants had to identify sentences that convey threat through three different information channels: prosody-only, semantic-only and both semantic and prosody (congruent threat). We expected different ear advantages (left or right) depending on task demands, information type, and worry level. We used a full Bayesian approach for statistical modelling and analysis. Results indicate that when participants made delayed responses (Experiment 1), reaction times barely increased as a function of worry level, but under time pressure (Experiment 2) worry level induced clear decreases in reaction times. We explain these results in terms of multistep models of anxiety and language, concluding that present results mainly indicate effects threat aversion-related over-attention to threat, and that we do not provide enough evidence for supporting the integration of anxiety and language multiphasic models.


title: Understanding population structure in an evolutionary context: population-specific FST and pairwise FST

abstract: Populations are shaped by their history. It is crucial to interpret population structure in an evolutionary context. Pairwise FST measures population structure, whereas population-specific FST measures deviation from the ancestral population. To understand the current population structure and a populations history of range expansion, we propose a representation method that overlays population-specific FST estimates on a sampling location map, and on an unrooted neighbor-joining tree and a multi-dimensional scaling plot inferred from a pairwise FST distance matrix. We examined the usefulness of our procedure using simulations that mimicked population colonization from an ancestral population and by analyzing published human, Atlantic cod, and wild poplar data. Our results demonstrated that population-specific FST values identify the source population and trace the evolutionary history of its derived populations. Conversely, pairwise FST values represent the current population structure. By integrating the results of both estimators, we obtained a new picture of the population structure that incorporates evolutionary history. The generalized least squares of genome-wide population-specific FST indicated that the wild poplar population expanded its distribution to the north, where daylight hours are long in summer, to seashores with abundant rainfall, and to the south with dry summers. Genomic data highlight the power of the bias-corrected moment estimators of FST, whether global, pairwise, or population-specific, that provide unbiased estimates of FST. All FST moment estimators described in this paper have reasonable process times and are useful in population genomics studies. The R codes for our method and simulations are available in the Supplemental Material.


title: Sharing mating opportunities by coalition males in stump-tailed macaques: elucidation of ecological mechanism by diversion of PvS model

abstract: In multi-male multi-female groups of animals, male reproductive success is often skewed toward top-ranking males. Coalition formation by middle- to low-rankers can be seen as a collaborative effort to modify the distribution of reproductive success within the group, so that they gain more than they would do otherwise. It has been pointed out, on the other hand, that a coalition of top-ranking males could hardly be profitable in the sense that they would gain little additional benefit from making collaborative effort. Here we report our novel observation of facultative sharing of mating opportunities among males in a wild population of stump-tailed macaques (Macaca arctoides) as a possible case of coalition-like behavior in which dominant males jointly guard females from mating with subordinate males and actively share mating opportunities within the allies. First, we report our novel observation of facultative sharing of mating opportunities in male stump-tailed macaques, where two or more males remain in close proximity to and copulate with a female in turn without contesting or sneaking. Second, considering the kind of coalition formation in which dominant males collaboratively exclude subordinates from mating competition and thereby strengthen the reproductive skew that already exists, we specify, by means of mathematical modeling, the condition for this kind of coalition formation to be selectively favored. Finally, we derive predictions about the occurrence of the coalition-like behavior depending on ecological and demographic factors, and test them empirically using data from the five groups of stump-tailed macaques in our study population.


title: Mate sharing in male stump-tailed macaques as a possible case of coalition-like behavior to modify the group-wise fitness distribution


title: GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data

abstract:
MotivationGenome Architecture Mapping (GAM) was recently introduced as a digestion- and ligation-free method to detect chromatin conformation. Orthogonal to existing approaches based on chromatin conformation capture (3C), GAMs ability to capture both inter- and intra-chromosomal contacts from low amounts of input data makes it particularly well suited for allele-specific analyses in a clinical setting. Allele-specific analyses are powerful tools to investigate the effects of genetic variants on many cellular phenotypes including chromatin conformation, but require the haplotypes of the individuals under study to be known a-priori. So far however, no algorithm exists for haplotype reconstruction and phasing of genetic variants from GAM data, hindering the allele-specific analysis of chromatin contact points in non-model organisms or individuals with unknown haplotypes.

ResultsWe present GAMIBHEAR, a tool for accurate haplotype reconstruction from GAM data. GAMIBHEAR aggregates allelic co-observation frequencies from GAM data and employs a GAM-specific probabilistic model of haplotype capture to optimise phasing accuracy. Using a hybrid mouse embryonic stem cell line with known haplotype structure as a benchmark dataset, we assess correctness and completeness of the reconstructed haplotypes, and demonstrate the power of GAMIBHEAR to infer accurate genome-wide haplotypes from GAM data.

AvailabilityGAMIBHEAR is available as an R package under the open source GPL-2 license at https://bitbucket.org/schwarzlab/gamibhear

Maintainer: julia.markowski@mdc-berlin.de


title: Further perceptions of probability: in defence of trial-by-trial estimation models

abstract: Many events we experience are binary and probabilistic, such as the weather (rain or no rain) and the outcome of medical tests (negative or positive). Extensive research in the behavioural sciences has addressed peoples ability to learn stationary probabilities (i.e., probabilities that stay constant over time) of such events, but only recently have there been attempts to model the cognitive processes whereby people learn - and track - non-stationary probabilities. The old debate on whether learning occurs trial-by-trial or by occasional shifts between discrete hypotheses has been revived in this context. Trial-by-trial estimation models - such as the delta-rule model - have been successful in describing human learning in various contexts. It has been argued, however, that behaviour on non-stationary probability learning tasks is incompatible with trial-by-trial learning and can only be explained by models in which learning proceeds through hypothesis testing. Here, we show that this conclusion was premature. By combining two well-supported concepts from cognitive modelling - delta-rule learning and drift diffusion evidence accumulation - we reproduce all behavioural phenomena that were previously used to reject trial-by-trial learning models. Moreover, a quantitative model comparison shows that this model accounts for the data better than a model based on hypothesis testing. In the spirit of cumulative science, our results demonstrate that a combination of two well-established theories of trial-by-trial learning and evidence accumulation is sufficient to explain human learning of non-stationary probabilities.


title: The context dependent effects of host competence, competition, and the pathogen transmission mode on disease prevalence

abstract: Biodiversity in communities is changing globally, including the gain and loss of host species in host-pathogen communities. Increased host diversity can cause infection prevalence in a focal host to increase (amplification) or decrease (dilution). However, it is unclear what general rules govern the context dependent effects, in part because theories for pathogens with different transmission modes have developed largely independently. Using a two-host model, we explore how the pathogen transmission mode and characteristics of a second host (disease competence and competitive ability) influence disease prevalence in a focal host. Our work shows how the theories for pathogens with environmental transmission, density-dependent direct transmission, and frequency-dependent direct transmission can be unified. Our work also identifies general rules about how host and pathogen characteristics affect amplification/dilution. For example, higher competence hosts promote amplification, unless they are strong interspecific competitors; strong interspecific competitors promote dilution, unless they are large sources of new infections; and dilution occurs under frequency-dependent direct transmission more than density-dependent direct transmission, unless interspecific host competition is sufficiently strong. Our work helps explain how the characteristics of the pathogen and a second host affect disease prevalence in a focal host.


title: A Self-Attention Model for Inferring Cooperativity between Regulatory Features

abstract: Deep learning has demonstrated its predictive power in modeling complex biological phenomena such as gene expression. The value of these models hinges not only on their accuracy, but also on the ability to extract biologically relevant information from the trained models. While there has been much recent work on developing feature attribution methods that discover the most important features for a given sequence, inferring cooperativity between regulatory elements, which is the hallmark of phenomena such as gene expression, remains an open problem. We present SATORI, a Self-ATtentiOn based model to detect Regulatory element Interactions. Our approach combines convolutional layers with a self-attention mechanism that helps us capture a global view of the landscape of interactions between regulatory elements in a sequence. A comprehensive evaluation demonstrates the ability of SATORI to identify numerous statistically significant TF-TF interactions, many of which have been previously reported. Our method is able to detect higher numbers of experimentally verified TF-TF interactions than existing methods, and has the advantage of not requiring a computationally expensive post-processing step. Finally, SATORI can be used for detection of any type of feature interaction in models that use a similar attention mechanism, and is not limited to the detection of TF-TF interactions.


title: Non-negative Independent Factor Analysis disentangles discrete and continuous sources of variation in scRNA-seq data

abstract:
MotivationSingle-cell RNA-seq analysis has emerged as a powerful tool for understanding inter-cellular heterogeneity. Due to the inherent noise of the data, computational techniques often rely on dimensionality reduction (DR) as both a pre-processing step and an analysis tool. Ideally, dimensionality reduction should preserve the biological information while discarding the noise. However if the dimensionality reduction is to be used directly to gain biological insight it must also be interpretable - that is the individual dimensions of the reduction should correspond to specific biological variables such as cell-type identity or pathway activity. Maximizing biological interpretability necessitates making assumption about the data structures and the choice of the model is critical.

ResultsWe present a new probabilistic single-cell factor analysis model, Non-negative Independent Factor Analysis (NIFA), that incorporates different interpretability inducing assumptions into a single modeling framework. The key advantage of our NIFA model is that it simultaneously models uni- and multi-modal latent factors, and thus isolates discrete cell-type identity and continuous pathway activity into separate components. We apply our approach to a range of datasets where cell-type identity is known, and we show that NIFA-derived factors outperform results from ICA, PCA, NMF and scCoGAPS (an NMF method designed for single-cell data) in terms of disentangling biological sources of variation. Studying an immunotherapy dataset in detail, we show that NIFA is able to reproduce and refine previous findings in a single analysis framework and enables the discovery of new clinically relevant cell states.

AvailabilityNFIA is a R package which is freely available at GitHub (https://github.com/wgmao/NIFA).

Contactmchikina@pitt.edu

Supplementary informationSupplementary data are available at Bioinformatics online.


title: Aquatic microbial community is partially functionally redundant: insights from an in situ reciprocal transplant experiment

abstract: Microbial communities are considered to be functionally redundant, but few studies have tested this hypothesis empirically. In this study, we performed an in situ reciprocal transplant experiment on the surface and bottom waters of two lakes with disparate trophic states and tracked changes in their microbial community and functional attributes for 6 weeks using high-throughput sequencing and functional approaches. The communities from both lakes were resistant to changes in composition after the reciprocal transplant, but their functions tended to become similar to the incubating lakes functional profiles. A significant linear positive relationship was observed between the microbial community and functional attributes, though with varying scales of similarity, suggesting partial functional redundancy. Furthermore, the entropy-based L-divergence measure quantified the scale of partial functional redundancy in the lakes surface and bottom waters. This study establishes and quantifies the scale of partial functional redundancy in the freshwater ecosystem through empirical investigation.


title: CLOCK-induced upregulated HMGB1 resulting in circadian rhythms disruption of inflammatory microglia contributes to non-dipper hypertension in stressed rats

abstract: The authors have withdrawn their manuscript as they have discovered some potential inconsistencies in their results after further experimentation. Therefore, the authors do not wish this work to be cited as reference for the project.

category: physiology


title: Godanti Bhasma (anhydrous CaSO4) induces massive cytoplasmic vacuolation and cell survival response through stimulation of LC3 Associated Phagocytosis (LAP)

abstract:
Bhasmas are Ayurvedic herbo-mineral formulations that have been used since ancient times for therapeutic benefits. Godanti Bhasma (GB) is an anhydrous calcium sulfate preparation processed by heating of gypsum powder with herbal extracts. Thermo-transformation of gypsum into the anhydrous GB was confirmed by Raman and FT-IR spectroscopy. GB particle showed size range of 0.5-5 {micro}m and neutral surface charge. Exposure to mammalian cells with GB particles showed massive vacuolation in their cytoplasm. Interestingly, no vacuolation was observed with parent gypsum particle. The result indicated that the cytoplasmic vacuolation by GB was due to its unique physicochemical property obtained during the thermo-transformation of gypsum. Using lysosomal inhibitors Bafilomycin A1 (BFA1) and Chloroquine (CQ), the process of vacuole formation was suppressed indicating GB induced vacuolation require acidic environment. The GB induced vacuolation was also found to follow dose and time dependent manner. Vacuolation often accompany with the sign of cell death whereas, in our study, massive vacuolation by GB did not induce any cell death. Moreover, GB treated cells survive with massive vacuolar process, which was reversed following post-treatment with vacuole inhibitors in GB treated cells, suggesting normal vacuolar function is essential for cell survival. Treatment of cells with GB was also found to induce translocation of LC3 protein from the nucleus to vacuolar membrane, indicating LC3 associated phagocytosis (LAP) is involved in the vacuolar process. Interestingly, the LAP function was found to be reversed in the cells treated with vacuole inhibitors. Our results provide a mechanistic correlation with GB induced vacuolation and associated LAP function, essential for cell survival.

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title: Macrophage Scavenger Receptor 1 mediates lipid-induced inflammation in non-alcoholic fatty liver disease

abstract:
Obesity-associated inflammation is a key player in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, the exact mechanisms remain incompletely understood. Here we demonstrate that macrophage scavenger receptor 1 (MSR1, CD204) expression is associated with the occurrence of hepatic lipid-laden foamy macrophages and correlates with the degree of steatosis and steatohepatitis in a cohort of 170 NAFLD patients. Mice lacking Msr1 are protected against high fat-cholesterol diet (HFD)-induced metabolic disorder, showing fewer hepatic lipid-laden foamy macrophages, less hepatic inflammation, improved dyslipidemia and glucose tolerance, while showing a change in hepatic lipid metabolism. We show that MSR1 induces a pro-inflammatory response via the JNK signaling pathway upon triggering by saturated fatty acids. In vitro blockade of the receptor prevented the accumulation of lipids in primary macrophages which inhibited the switch towards a pro-inflammatory phenotype and the release of cytokines such as TNFa. Targeting MSR1 using monoclonal antibody therapy in an obesity-associated NAFLD mouse model and ex vivo human liver slices resulted in the prevention of foamy macrophage formation and liver inflammation. Moreover, we identified that rs41505344, a polymorphism in the upstream transcriptional region of MSR1, was associated with altered serum triglycerides and aspartate transaminase levels in a cohort of over 400,000 patients. Taken together, our data suggest a critical role for MSR1 in lipid homeostasis and a potential therapeutic target for the treatment of NAFLD.

One Sentence SummaryThe immunometabolic role of MSR1 in human NAFLD.

category: immunology


title: Functional Role of Second Heart Field-derived Cells in Aortic Integrity in Mice

abstract:
BackgroundThe ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies.

MethodsAscending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry assisted proteomics, and molecular features of SHF-derived cells were determined by single cell transcriptomic analyses. Genetic deletion of either low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-{beta} receptor 2 (Tgfbr2) in SHF- derived cells was conducted to examine the impact of SHF-derived cells on vascular integrity.

ResultsPathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas following AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion, prior to overt pathology, evoked downregulation of SMC proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single cell transcriptomics results identified plasminogen activator inhibitor 1 (PAI1) as the most increased protein in SHF-derived SMCs and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies.

ConclusionSHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and TGF-{beta} signaling associated with increases of aortic PAI1.

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org.highwire.dtl.DTLVardef@185e3d9org.highwire.dtl.DTLVardef@131d702org.highwire.dtl.DTLVardef@11afa42org.highwire.dtl.DTLVardef@242786_HPS_FORMAT_FIGEXP  M_FIG C_FIG Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABS- SHF-derived SMCs and fibroblasts associate with AngII-induced aortic pathologies.
- AngII induces a distinct fibroblast sub-cluster that is less abundant for mRNAs related to major extracellular components and TGF{beta} ligands and receptors, but more abundant for proliferative genes.
- TGFBR2 deletion in SHF-derived cells are embryonic lethal with significant dilatation of the outflow tract in mice.
- SHF-specific deletion of LRP1 leads to aortic pathologies in mice, supporting the importance of SHF-derived cells in maintaining ascending aortic wall integrity.

What are the clinical implications?- Heterogeneity of the embryonic origins of SMCs and fibroblasts contributes to complex mechanisms of vasculopathy formation, which should be considered when investigating the pathogenesis of thoracic aortopathies.

category: pathology


title: Second Heart Field-derived Cells Contribute to Angiotensin II-mediated Ascending Aortopathies


title: Optimal anticipatory control as a theory of motor preparation: a thalamo-cortical circuit model

abstract: Across a range of motor and cognitive tasks, cortical activity can be accurately described by low-dimensional dynamics unfolding from specific initial conditions on every trial. These "preparatory states" largely determine the subsequent evolution of both neural activity and behaviour, and their importance raises questions regarding how they are -- or ought to be -- set. Here, we formulate motor preparation as optimal anticipatory control of future movements, and show that the solution requires a form of internal feedback control of cortical circuit dynamics. In contrast to a simple feedforward strategy, feedback control enables fast movement preparation and orthogonality between preparatory and movement activity, a distinctive feature of peri-movement activity in reaching monkeys. We propose a circuit model in which optimal preparatory control is implemented as a thalamo-cortical loop gated by the basal ganglia.


title: Impact of immediate cryopreservation on the establishment of patient derived xenografts from head and neck cancer patients.

abstract:
BackgroundPatient-derived xenografts established from human cancers are important tools for investigating novel anti-cancer therapies. Establishing PDXs requires a significant investment and many PDXs may be used infrequently due to their similarity to existing models, their growth rate, or the lack of relevant mutations. We performed this study to determine whether we could efficiently establish PDXs after cryopreservation to allow molecular profiling to be completed prior to implanting the human cancer.

MethodsFresh tumor was split with half used to establish a PDX immediately and half cryopreserved for later implantation. Resulting tumors were assessed histologically and tumors established from fresh or cryopreserved tissues compared as to the growth rate, extent of tumor necrosis, mitotic activity, keratinization, and grade. All PDXs were subjected to short tandem repeat testing to confirm identity and assess similarity between methods.

ResultsTumor growth was seen in 70% of implanted cases. No growth in either condition was seen in 30% of tumors. One developed a SCC from the immediate implant but a lymphoproliferative mass without SCC from the cryopreserved specimen. No difference in growth rate was seen. No difference between histologic parameters was seen between the two approaches.

ConclusionsFresh human cancer tissue can be immediately cryopreserved and later thawed and implanted to establish PDXs. This resource saving approach allows for tumor profiling prior to implantation into animals thus maximizing the probability that the tumor will be utilized for future research.

category: cancer biology


title: The hidden cost of receiving favors: A theory of indebtedness

abstract: Receiving help or a favor from another person can sometimes have a hidden cost. In this study, we explore these hidden costs by developing and validating a theoretical model of indebtedness across three studies that combine a large-scale online questionnaire, interpersonal games, computational modeling, and neuroimaging. Our model captures how individuals perceive the altruistic and strategic intentions of the benefactor. These perceptions produce distinct feelings of guilt and obligation that together comprise indebtedness and motivate reciprocity. Perceived altruistic intentions convey care and concern and are associated with activity in the insula, dorsolateral prefrontal cortex and ventromedial prefrontal cortex, while perceived strategic intentions convey expectations of future reciprocity and are associated with activation in the temporal parietal junction and dorsomedial prefrontal cortex. We further develop a neural utility model of indebtedness using multivariate patterns of brain activity that captures the tradeoff between these feelings and reliably predicts reciprocity behavior.


title: The parasite Schistocephalus solidus secretes proteins with putative host manipulation functions

abstract:
BackgroundManipulative parasites are thought to liberate molecules in their external environment acting as manipulation factors with biological functions implicated in their hosts physiological and behavioural alterations. These manipulation factors are part of a complex mixture called the secretome. While the secretomes of various parasites have been described, there is very little data for a putative manipulative parasite. It is necessary to study the molecular interaction between a manipulative parasite and its host to better understand how such alterations evolve.

MethodsHere, we used proteomics to characterize the secretome of a model cestode with a complex life cycle based on trophic transmission. We studied Schistocephalus solidus during the life stage in which behavioural changes take place in its obligatory intermediate fish host, the threespine stickleback (Gasterosteus aculeatus). We produced a novel genome sequence and assembly of S. solidus to improve protein coding gene prediction and annotation for this parasite. We then described the whole worms proteome and its secretome during fish host infection using LC-MS/MS.

ResultsA total of 2 290 proteins were detected in the proteome of S. solidus, and 30 additional proteins were detected specifically in the secretome. We found that the secretome contains proteases, proteins with neural and immune functions, as well as proteins involved in cell communication. We detected Receptor-type tyrosine-protein phosphatases, which were reported in other parasitic systems to be manipulation factors. We also detected 12 S. solidus-specific proteins in the secretome that may play important roles in host-parasite interactions.

ConclusionsOur results suggest that S. solidus liberates molecules with putative host manipulation functions in the host and that many of them are species specific.


title: Hnrnpul1 loss of function affects skeletal and limb development

abstract: Mutations in RNA binding proteins can lead to pleiotropic phenotypes including craniofacial, skeletal, limb and neurological symptoms. Heterogeneous Nuclear Ribonucleoproteins (hnRNPs) are involved in nucleic acid binding, transcription and splicing through direct binding to DNA and RNA, or through interaction with other proteins in the spliceosome. We show a developmental role for Hnrnpul1 in zebrafish, resulting in reduced craniofacial tendon length, severe adult-onset scoliosis and reduced fin size. We demonstrate a role of Hnrnpul1 in alternative splicing and transcriptional regulation using RNA sequencing. Given its cross-species conservation and role in splicing it would not be surprising if it had a role in human development but the developmental role of this gene in humans has not been explored. Whole exome sequencing detected a frameshift variant in HNRNPUL1 in two siblings with congenital limb malformations which remain variants of unknown significance. Zebrafish Hnrnpul1 mutants suggest an important developmental role of hnRNPUL1 and provide motivation for exploring potential conservation of ancient regulatory circuits involving hnRNPUL1 in human development.

category: developmental biology


title: Association of CDH11 with ASD revealed by matched-gene co-expression analysis and mouse behavioral studies

abstract: A large number of putative risk genes of autism spectrum disorder (ASD) have been reported. The functions of most of these susceptibility genes in developing brains remain unknown, and a causal relationship between their variations and autism traits has not been established. The aim of this study is to predict putative risk genes at the whole-genome level based on the analysis of gene co-expression with a group of high confidence ASD risk genes (hcASDs). Results showed that three gene features, including gene size, mRNA abundance, and guanine-cytosine content, affect genome-wide co-expression profiles of hcASDs. To circumvent the interference of these gene features on gene co-expression analysis (GCA), we developed a method to determine whether a gene is significantly co-expressed with hcASDs by statistically comparing the co-expression profile of this gene with hcASDs to that of this gene with permuted gene sets of feature-matched genes. This method is referred to as "matched-gene co-expression analysis" (MGCA). With MGCA, we demonstrated the convergence in developmental expression profiles of hcASDs and improved the efficacy of risk gene prediction. Results of analysis of two recently reported ASD candidate genes, CDH11 and CDH9, suggested the involvement of CDH11, but not CDH9, in ASD. Consistent with this prediction, behavioral studies showed that Cdh11-null mice, but not Cdh9-null mice, have multiple autism-like behavioral alterations. This study highlighted the power of MGCA in revealing ASD-associated genes and the potential role of CDH11 in ASD.


title: EMBER: Multi-label prediction of kinase-substrate phosphorylation events through deep learning

abstract:
Kinase-catalyzed phosphorylation of proteins forms the back-bone of signal transduction within the cell, enabling the coordination of numerous processes such as the cell cycle, apoptosis, and differentiation. While on the order of 105 phosphorylation events have been described, we know the specific kinase performing these functions for less than 5% of cases. The ability to predict which kinases initiate specific individual phosphorylation events has the potential to greatly enhance the design of downstream experimental studies, while simultaneously creating a preliminary map of the broader phosphorylation network that controls cellular signaling. To this end, we describe EMBER, a deep learning method that integrates kinase-phylogeny information and motif-dissimilarity information into a multi-label classification model for the prediction of kinase-motif phosphorylation events. Unlike previous deep learning methods that perform single-label classification, we restate the task of kinase-motif phosphorylation prediction as a multi-label problem, allowing us to train a single unified model rather than a separate model for each of the 134 kinase families. We utilize a Siamese network to generate novel vector representations, or an embedding, of motif sequences, and we compare our novel embedding to a previously proposed peptide embedding. Our motif vector representations are used, along with one-hot encoded motif sequences, as input to a classification network while also leveraging kinase phylogenetic relationships into our model via a kinase phylogeny-weighted loss function. Results suggest that this approach holds significant promise for improving our map of phosphorylation relations that underlie kinome signaling.

Availabilityhttps://github.com/gomezlab/EMBER


title: Bidirectional synaptic plasticity rapidly modifies hippocampal representations

abstract: Learning requires neural adaptations thought to be mediated by activity-dependent synaptic plasticity. A relatively non-standard form of synaptic plasticity driven by dendritic plateau potentials has been reported to underlie place field formation in hippocampal CA1 neurons. Here we found that this behavioral timescale synaptic plasticity (BTSP) can also reshape existing place fields via bidirectional synaptic weight changes that depend on the temporal proximity of plateau potentials to pre-existing place fields. When evoked near an existing place field, plateau potentials induced less synaptic potentiation and more depression, suggesting BTSP might depend inversely on postsynaptic activation. However, manipulations of place cell membrane potential and computational modeling indicated that this anti-correlation actually results from a dependence on current synaptic weight such that weak inputs potentiate and strong inputs depress. A network model implementing this bidirectional synaptic learning rule suggested that BTSP enables population activity, rather than pairwise neuronal correlations, to drive neural adaptations to experience.


title: When to depart from a stopover site? Time-since-arrival matters more than current weather conditions

abstract: On the journey to wintering sites, migratory birds usually alternate between flights and stopovers where they rest and refuel. Migration strategies are assumed to differ according to season: a time-minimization pre-breeding migration strategy towards breeding locations, and an energy-minimization post-breeding migration strategy to wintering ones. The duration of flights and stopovers determines the energy requirements and the total duration of the journey. Since migrating birds actually spend most of the time at stopovers, selection to minimize the amount of energy or time spent on migration is very likely to operate on the effectiveness of stopover rest and refueling. Here we address the relative contribution of factors to departure decisions from stopover sites during the post-breeding migration in a long-distance migratory songbird. When capture probability is low it is impossible to assess the variation in body condition over the entire duration of the stopover. To get around this, we use Time Since Arrival (TSA) as a proxy for the changes in the state of individuals during the stopover. We propose that TSA is an integrative proxy for resting, feeding and fattening efficiency. We develop a capture-recapture model to address the relationship between departure probability, estimated TSA, and weather conditions. Using a 20-year dataset from sedge warblers, we show that TSA has a larger effect on departure probability than weather conditions. Low humidity and an increase in atmospheric pressure in the days preceding departure are associated with higher departure probability, but these effects are smaller than that of TSA.


title: Depletion of nuclear pore protein NUP210 suppresses metastasis through heterochromatin-mediated disruption of tumor cell mechanical response

abstract: Mechanical signals from the extracellular microenvironment have been implicated in tumor and metastatic progression. Here, we identified nucleoporin NUP210 as a metastasis susceptibility gene for human estrogen receptor positive (ER+) breast cancer and a cellular mechanosensor. Nup210 depletion suppresses lung metastasis in mouse models of breast cancer. Mechanistically, NUP210 interacts with LINC complex protein SUN2 which connects the nucleus to the cytoskeleton. In addition, the NUP210/SUN2 complex interacts with chromatin via the short isoform of BRD4 and histone H3.1/H3.2 at the nuclear periphery. In Nup210 knockout cells, mechanosensitive genes accumulate H3K27me3 heterochromatin modification, mediated by the polycomb repressive complex 2 and differentially reposition within the nucleus. Transcriptional repression in Nup210 knockout cells results in defective mechanotransduction and focal adhesion necessary for their metastatic capacity. Our study provides a new insight into the role of nuclear pore protein in cellular mechanosensation and metastasis.


title: Random access DNA memory in a scalable, archival file storage system

abstract: DNA is an ultra-high-density storage medium that could meet exponentially growing worldwide demand for archival data storage if DNA synthesis costs declined sufficiently and random access of files within exabyte-to-yottabyte-scale DNA data pools were feasible. To overcome the second barrier, here we encapsulate data-encoding DNA file sequences within impervious silica capsules that are surface-labeled with single-stranded DNA barcodes. Barcodes are chosen to represent file metadata, enabling efficient and direct selection of sets of files with Boolean logic. We demonstrate random access of image files from an image database using fluorescence sorting with selection sensitivity of 1 in 106 files, which thereby enables 1 in 106N per N optical channels. Our strategy thereby offers retrieval of random file subsets from exabyte and larger-scale long-term DNA file storage databases, offering a scalable solution for random-access of archival files in massive molecular datasets.

category: bioengineering


title: Highly replicated evolution of parapatric ecotypes

abstract: Parallel evolution of ecotypes occurs when selection independently drives the evolution of similar traits across similar environments. The multiple origin of ecotypes is often inferred on the basis of a phylogeny which clusters populations according to geographic location and not by the environment they occupy. However, the use of phylogenies to infer parallel evolution in closely related populations is problematic because gene flow and incomplete lineage sorting can uncouple the genetic structure at neutral markers from the colonization history of populations. Here, we demonstrate multiple origins within ecotypes of an Australian wildflower, Senecio lautus. We observed strong genetic structure as well as phylogenetic clustering by geography and show that this is unlikely due to gene flow between parapatric ecotypes, which is surprisingly low. We further confirm this analytically by demonstrating that phylogenetic distortion due to gene flow often requires higher levels of migration than those observed in S. lautus. Our results imply that selection can repeatedly create similar phenotypes despite the perceived homogenizing effects of gene flow.


title: Phenotypic and genotypic parallel evolution in parapatric ecotypes of Senecio

abstract: The independent and repeated adaptation of populations to similar environments often results in the evolution of similar forms. This phenomenon creates a strong correlation between phenotype and environment and is referred to as parallel evolution. However, we are still largely unaware of the dynamics of parallel evolution, as well as the interplay between phenotype and genotype within natural systems. Here, we examined phenotypic and genotypic parallel evolution in multiple parapatric Dune-Headland coastal ecotypes of an Australian wildflower, Senecio lautus. We observed a clear trait-environment association within the system, with all replicate populations having evolved along the same phenotypic evolutionary trajectory. Similar phenotypes have arisen via mutational changes occurring in different genes, although many share the same biological functions. Our results shed light on how replicated adaptation manifests at the phenotypic and genotypic levels within populations, and highlights S. lautus as one of the most striking cases of phenotypic parallel evolution in nature.


title: Shape matters: the relationship between cell geometry and diversity in phytoplankton

abstract: Size and shape profoundly influence an organisms ecophysiological performance and evolutionary fitness, suggesting a link between morphology and diversity. However, not much is known about how body shape is related to taxonomic richness, especially in microbes. Here we analyse global datasets of unicellular marine phytoplankton, a major group of primary producers with an exceptional diversity of cell sizes and shapes and, additionally, heterotrophic protists. Using two measures of cell shape elongation, we quantify taxonomic diversity as a function of cell size and shape. We find that cells of intermediate volume have the greatest shape variation, from oblate to extremely elongated forms, while small and large cells are mostly compact (e.g., spherical or cubic). Taxonomic diversity is strongly related to cell elongation and cell volume, together explaining up to 92% of total variance. Taxonomic diversity decays exponentially with cell elongation and displays a log-normal dependence on cell volume, peaking for intermediate-volume cells with compact shapes. These previously unreported broad patterns in phytoplankton diversity reveal selective pressures and ecophysiological constraints on the geometry of phytoplankton cells which may improve our understanding of marine ecology and the evolutionary rules of life.


title: Dynamic control of visually-guided locomotion through cortico-subthalamic projections

abstract: Goal-directed locomotion requires control signals that propagate from higher-order areas to regulate spinal mechanisms. The cortico-subthalamic hyperdirect pathway offers a short route for cortical information to reach locomotor centers in the brainstem. We developed a task where head-fixed mice run to a visual landmark then stop and wait to collect reward, and examined the role of secondary motor cortex (M2) projections to the subthalamic nucleus (STN) in controlling locomotion. Our modeled behavioral strategy indicates a switching point in behavior or a sudden change from running to stopping, suggesting a critical neuronal control signal at stop locations. Optogenetic activation of M2 axons in STN leads the animal to stop prematurely. By imaging M2 neurons projecting to STN, we find neurons that are active at the onset of stops when executed at the landmark but not when executed spontaneously elsewhere. Our results suggest that the M2-STN pathway can be recruited during visually-guided locomotion to rapidly and precisely control the mesencephalic locomotor region (MLR) through the basal ganglia. By capturing the physiological dynamics through a feedback control model and analyzing neuronal signals in M2, MLR and STN, we find that the cortico-subthalamic projections potentially control MLR activity by differentiating an M2 error signal to ensure fast input-output dynamics.


title: Persistent increases of PKMζ in memory-activated neurons trace LTP maintenance during spatial long-term memory storage

abstract: PKM{zeta} is an autonomously active PKC isoform crucial for the maintenance of synaptic long-term potentiation (LTP) and long-term memory. Unlike other protein kinases that are transiently stimulated by second messengers, PKM{zeta} is persistently activated through sustained increases in kinase protein expression. Therefore, visualizing increases in PKM{zeta} expression during long-term memory storage might reveal the sites of its persistent action and thus the location of memory-associated LTP maintenance in the brain. Using quantitative immunohistochemistry validated by the lack of staining in PKM{zeta}-null mice, we examined the amount and distribution of PKM{zeta} in subregions of the hippocampal formation of wild-type mice during LTP maintenance and spatial long-term memory storage. During LTP maintenance in hippocampal slices, PKM{zeta} increases in the pyramidal cell body and stimulated dendritic layers of CA1 for at least 2 h. During spatial memory storage, PKM{zeta} increases in CA1 pyramidal cells for at least 1 month, paralleling the persistence of the memory. The subset of CA1 pyramidal cells that are tagged by immediate early gene Arc-driven transcription of fluorescent proteins, whose expression increases during initial memory formation, also expresses the persistent increase of PKM{zeta} during memory storage. In the memory-tagged cells, the increased PKM{zeta} expression persists in dendritic compartments within stratum radiatum for 1 month, indicating the long-term storage of information in the CA3-to-CA1 pathway during remote spatial memory. We conclude that persistent increases in PKM{zeta} trace the molecular mechanism of LTP maintenance and thus the sites of information storage within brain circuitry during long-term memory.


title: Multi-scale planning helps resolve global conservation needs with regional priorities

abstract: Area-based conservation through reserves or other measures is vital for preserving biodiversity and its functions for future generations1-5, but its effective implementation suffers from a lack of both spatial detail necessary for management practices6 and transparency around national responsibilities that might underpin cross-national support mechanisms7. Here we implement a conservation prioritization2,8 framework that accounts for spatial data limitations yet offers actionable guidance at a 1km resolution. Our multi-scale linear optimization approach delineates globally the areas required to meet area-based conservation targets for all ~32 000 described terrestrial vertebrate species, while offering flexibility in decision management to meet different local conservation objectives. Roughly 30.4% of land is sufficient to meet conservation targets for all species, of which 60.1% is either already protected9 or has minimal human modification10. However, the remaining 39.9% of human-modified areas need to be managed or restored in some form to ensure the long-term survival for over half of species. This burden of area-based conservation is distributed very unevenly among countries, and, without a process that explicitly addresses geopolitical inequity, meeting species conservation targets would require disproportionately large commitments from poorer countries (i.e., lower GNI). Our analysis provides baseline information for a potential intergovernmental and stakeholder contribution mechanism in service of a globally shared goal of sustaining biodiversity. Future updates and extensions to this global priority map have the potential to guide local and national advocacy and actions with a data-driven approach to support global conservation outcomes.


title: Dynamic, adaptive sampling during nanopore sequencing using Bayesian experimental design

abstract:
One particularly promising feature of nanopore sequencing is the ability to reject reads, enabling real-time selection of molecules without complex sample preparation. This is based on the idea of deciding whether a molecule warrants full sequencing depending on reading a small initial part. Previously, such decisions have been based on a priori determination of which regions of the genome were considered of interest. Instead, here we consider more general and complex strategies that incorporate already-observed data in order to optimize the rejection strategy and maximise information gain from the sequencing process. For example, in the presence of coverage bias redistributing data from areas of high to areas of low coverage would be desirable.

We present BOSS-RUNS, a mathematical and algorithmic framework to calculate the expected benefit of new reads and generate dynamically updated decision strategies for nanopore sequencing. During sequencing, in real time, we quantify the current uncertainty at each site of one or multiple reference genomes, and for each novel DNA fragment being sequenced we decide whether the potential decrease in uncertainty at the sites it will most likely cover warrants reading it in its entirety. This dynamic, adaptive sampling allows real-time focus of sequencing efforts onto areas of highest benefit.

We demonstrate the effectiveness of BOSS-RUNS by mitigating coverage bias across and within the species of a microbial community. Additionally, we show that our approach leads to improved variant calling due to its ability to sample more data at the most relevant genomic positions.


title: Rational arbitration between statistics and rules in human sequence processing

abstract: Detecting and learning temporal regularities is essential to accurately predict the future. A long-standing debate in cognitive science concerns the existence of a dissociation, in humans, between two systems, one for handling statistical regularities governing the probabilities of individual items and their transitions, and another for handling deterministic rules. Here, to address this issue, we used finger tracking to continuously monitor the online build-up of evidence, confidence, false alarms and changes-of-mind during sequence processing. All these aspects of behaviour conformed tightly to a hierarchical Bayesian inference model with distinct hypothesis spaces for statistics and rules, yet linked by a single probabilistic currency. Alternative models based either on a single statistical mechanism or on two non-commensurable systems were rejected. Our results indicate that a hierarchical Bayesian inference mechanism, capable of operating over distinct hypothesis spaces for statistics and rules, underlies the human capability for sequence processing.


title: Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

abstract: Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28 - 85% for vectors, 44 - 88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.


title: Depletion of glycosaminoglycans decreases contact stiffness of single collagen I fibrils in aqueous solution

abstract:
Fibrillar collagen-integrin interactions in the extracellular matrix (ECM) regulate a multitude of cellular processes and cell signalling. Collagen I fibrils serve as the molecular scaffolding for connective tissues throughout the human body and are the most abundant protein building blocks in the ECM. The ECM environment is diverse, made up of several ECM proteins, enzymes, and proteoglycans. The contents of the ECM environment are modulated by disease and aging and may influence these critical collagen-integrin interactions. In particular, glycosaminoglycans (GAGs), anionic polysaccharides that decorate proteoglycans, become depleted in the ECM with natural aging and their mis-regulation has been linked to cancers and other diseases. The impact of GAG concentration in the ECM environment on collagen interactions is not well understood. Here, we integrate protein adhesion assays with liquid high resolution atomic force microscopy (AFM) to assess the affects of GAG depletion on the interaction of collagen I fibrils with the integrin 2I domain. Adhesion assays demonstrate that 2I preferentially binds to GAG-depleted collagen I fibrils. By amplitude modulated AFM in air and in solution, we find that GAG-depleted collagen I fibrils retain structural features of the native fibrils, including their characteristic D-banding pattern, a key structural motif. AFM fast force mapping in solution shows that GAG depletion reduces the stiffness of individual fibrils, lowering the indentation modulus by half compared to native fibrils. Together these results shed new light on how GAGs influence collagen I fibril- integrin interactions and may aid in strategies to treat diseases that result from GAG misregulation.

Statement for broader audienceAging and disease result in mis-regulation of glycosaminoglycan (GAG) levels in the extracellular matrix (ECM), which may affect fibrillar collagen interactions that are vital for cellular processes. Here, we characterize the impact of GAG depletion on collagen-integrin 2I domain interactions and collagen fibril topography and stiffness. We show that GAG depletion increases collagen-2I binding and reduces stiffness in comparison to native fibrils. These results may inform on strategies for treating GAG mis-regulation.

category: biophysics


title: Probing the effect of glycosaminoglycan depletion on integrin interactions with collagen I fibrils in the native ECM environment.


title: Mechanisms underlying the cooperation between loss of epithelial polarity and Notch signaling during neoplastic growth in Drosophila

abstract: Aggressive neoplastic growth can be initiated by a limited number of genetic alterations, such as the well-established cooperation between loss of cell architecture and hyperactive signaling pathways. However, our understanding of how these different alterations interact and influence each other remains very incomplete. Using Drosophila paradigms of imaginal wing disc epithelial growth, we have monitored the changes in Notch pathway activity according to the polarity status of cells (scrib mutant). We show that the scrib mutation impacts the direct transcriptional output of the Notch pathway, without altering the global distribution of Su(H), the Notch dedicated transcription factor. The Notch-dependent neoplasms require however, the action of a group of transcription factors, similar to those previously identified for Ras/scrib neoplasm (namely AP-1, Stat92E, Ftz-F1, and bZIP factors), further suggesting the importance of this transcription factor network during neoplastic growth. Finally our work highlights some Notch/scrib specificities, in particular the role of the PAR domain containing bZIP transcription factor and Notch direct target Pdp1 for neoplastic growth.


title: Sparse latent factor regression models for genome-wide and epigenome-wide association studies

abstract: Association of phenotypes or exposures with genomic and epigenomic data faces important statistical challenges. One of these challenges is to account for variation due to unobserved confounding factors, such as individual ancestry or cell-type composition in tissues. This issue can be addressed with penalized latent factor regression models, where penalties are introduced to cope with high dimension in the data. If a relatively small proportion of genomic or epigenomic markers correlate with the variable of interest, sparsity penalties may help to capture the relevant associations, but the improvement over non-sparse approaches has not been fully evaluated yet. Here, we present least-squares algorithms that jointly estimate effect sizes and confounding factors in sparse latent factor regression models. In simulated data, sparse latent factor regression models generally achieved higher statistical performance than other sparse methods, including the least absolute shrinkage and selection operator (LASSO) and a Bayesian sparse linear mixed model (BSLMM). In generative model simulations, statistical performance was slightly lower (while being comparable) to non-sparse methods, but in simulations based on empirical data, sparse latent factor regression models were more robust to departure from the model than the non-sparse approaches. We applied sparse latent factor regression models to a genome-wide association study of a flowering trait for the plant Arabidopsis thaliana and to an epigenome-wide association study of smoking status in pregnant women. For both applications, sparse latent factor regression models facilitated the estimation of non-null effect sizes while overcoming multiple testing issues. The results were not only consistent with previous discoveries, but they also pinpointed new genes with functional annotations relevant to each application.


title: Post-copulatory sexual selection is associated with sperm aggregate quality in Peromyscus mice

abstract: In some species, sperm form coordinated groups that are hypothesized to improve their swimming performance in competitive contexts or to navigate through the viscous fluids of the female reproductive tract. Here we investigate sperm aggregation across closely-related species of Peromyscus mice that naturally vary by mating system to test the predictions that sperm aggregates (1) are faster than solitary sperm in species that females mate multiply to aid cells in sperm competition, and (2) outperform solitary sperm cells in viscous environments. We find significant variation in the size of sperm aggregates, which negatively associates with relative testis mass, a proxy for sperm competition risk, suggesting that post-copulatory sexual selection has a stabilizing effect on sperm group size. Moreover, our results show that sperm aggregates are faster than solitary sperm in some, but not all, species, and this can vary by fluid viscosity. Of the two species that produce the largest and most frequent groups, we find that sperm aggregates from the promiscuous P. maniculatus are faster than solitary sperm in every experimentally viscous environment but aggregation provides no such kinematic advantage under these same conditions for the monogamous P. polionotus. The reduced performance of P. polionotus aggregates is associated with less efficient aggregate geometry and the inclusion of immotile or morphological abnormal sperm. Our cross-species comparison yields insight into the evolution of sperm social behaviors, provides evidence of extensive variation in the Peromyscus lineage, and reveals that differences in sperm aggregate quality associate with post-copulatory sexual selection.


title: Reference-free reconstruction and quantification of transcriptomes from Nanopore long-read sequencing

abstract: Nanopore sequencing enables the efficient and unbiased measurement of transcriptomes from any sample. However, current methods for transcript identification and quantification rely of mapping reads to a reference genome, which precludes the study of species with a partial or missing reference or the identification of disease-specific transcripts not readily identifiable from a reference. Here we present RATTLE, a tool to perform reference-free reconstruction and quantification of transcripts using only Nanopore reads. Using simulated data and experimental data from isoform spike-ins, human tissues, and cell lines, we show that RATTLE accurately determines transcript sequences and their abundances, and shows good scalability with the number of transcripts. RATTLE provides unprecedented access to transcriptomes from any sample and species without relying on a reference or additional technologies.


title: RATTLE: Reference-free reconstruction and quantification of transcriptomes from Nanopore sequencing


title: SlKIX8 and SlKIX9 are negative regulators of leaf and fruit growth in tomato

abstract:
Plant organ size and shape are major agronomic traits that depend on cell division and expansion, which are both regulated by complex gene networks. In several eudicot species belonging to the rosid clade, organ growth is controlled by a repressor complex consisting of PEAPOD (PPD) and KINASE-INDUCIBLE DOMAIN INTERACTING (KIX) proteins. The role of these proteins in asterids, which together with the rosids constitute most of the core eudicot species, is still unknown. We used CRISPR-Cas9 genome editing to target SlKIX8 and SlKIX9 in the asterid model species tomato (Solanum lycopersicum) and analyzed loss-of-function phenotypes. We found that loss of function of SlKIX8 and SlKIX9 led to the production of enlarged, dome-shaped leaves and that these leaves exhibited increased expression of putative SlPPD target genes. Unexpectedly, kix8 kix9 mutants carried enlarged fruits with increased pericarp thickness due to cell expansion. At the molecular level, protein interaction assays indicated that SlKIX8 and SlKIX9 act as adaptors between the SlPPD and SlTOPLESS co-repressor proteins. Our results show that KIX8 and KIX9 are regulators of organ growth in asterids and can provide strategies to improve important traits in produce such as thickness of the fruit flesh.

One sentence summaryTwo transcriptional repressors negatively regulate organ growth in tomato with loss-of-function lines producing enlarged fruits due to an appearance of more expanded cells in the fruit flesh.

category: plant biology


title: Mapping microglia and astrocytes activation in vivo using diffusion MRI

abstract: Glia, and particularly microglia, are increasingly implicated in the pathophysiology of psychiatric and neurodegenerative disorders. However, to date the only methods for imaging these cells in vivo involve either invasive procedures (e.g. multi-photon imaging in rodents) or TSPO-PET radiotracers, which afford low resolution and specificity, since TSPO expresses across multiple cell types. Here, we present a non-invasive diffusion-weighted MRI method to image changes in glia morphometry in vivo. Using two rat models of neuroinflammation, with and without neurodegeneration, we demonstrate that diffusion-weighted MRI carries the fingerprint of microglia and astrocytes activation, and that specific signatures from each population can be quantified non-invasively. We demonstrate that the method can further detect glia proliferation, and provide a quantitative account of neuroinflammation regardless of the existence of a concomitant neuronal loss. We prove the translational value of the approach showing significant correlations between MRI and histological microglia markers measured across different brain regions in humans. This framework holds the potential to transform basic and clinical research by providing a tool to clarify the role of inflammation in health and disease across the lifespan.

category: neuroscience


title: A cryptic pocket in Ebola VP35 allosterically controls RNA binding

abstract: Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola viral protein 35 (VP35). VP35 plays multiple essential roles in Ebolas replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these successes, we expect our pipeline is equally applicable to other proteins.

category: biochemistry


title: Pathogen community composition and co-infection patterns in a wild community of rodents

abstract: Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors that may influence their distribution in the wild. Here, we describe the occurrence and distribution patterns of a range of endemic and zoonotic pathogens circulating among rodent communities in northern France. The community sample consisted of 713 rodents, including 11 host species from diverse habitats. Rodents were screened for virus exposure (hantaviruses, cowpox virus, Lymphocytic choriomeningitis virus, Tick-borne encephalitis virus) using antibody assays. Bacterial communities were characterized using 16S rRNA amplicon sequencing of splenic samples. Multiple correspondence (MCA), regression and association screening (SCN) analyses were used to determine the degree to which extrinsic factors contributed to pathogen community structure, and to identify patterns of associations between pathogens within hosts. We found a rich diversity of bacterial genera, with 36 known or suspected to be pathogenic. We revealed that host species is the most important determinant of pathogen community composition, and that hosts that share habitats can have very different pathogen communities. Pathogen diversity and co-infection rates also vary among host species. Aggregation of pathogens responsible for zoonotic diseases suggests that some rodent species may be more important for transmission risk than others. Moreover, we detected positive associations between several pathogens, including Bartonella, Mycoplasma species, Cowpox virus (CPXV) and hantaviruses, and these patterns were generally specific to particular host species. Altogether, our results suggest that host and pathogen specificity is the most important driver of pathogen community structure, and that interspecific pathogen-pathogen associations also depend on host species.

category: ecology


title: Parallel mechanisms of visual memory formation across distinct regions of the honey bee brain

abstract: Visual learning is vital to the behavioral ecology of the Western honey bee (Apis mellifera). Honey bee workers forage for floral resources, a behavior that requires the learning and long-term memory of visual landmarks, but how these memories are mapped to the brain remains poorly understood. To address this gap in our understanding, we collected bees that successfully learned visual associations in a conditioned aversion paradigm and compared gene expression correlates of memory formation in the mushroom bodies, a higher-order sensory integration center classically thought to contribute to learning, as well as the optic lobes, the primary visual neuropil responsible for sensory transduction of visual information. We quantitated expression of CREB and CaMKii, two classical genetic markers of learning and fen-1, a gene specifically associated with punishment learning in vertebrates. As expected, we report substantial involvement of the mushroom bodies for all three markers but additionally demonstrate an unexpected involvement of the optic lobes across a similar time course. Our findings imply the molecular involvement of a sensory neuropil during visual associative learning parallel to a higher-order brain region, furthering our understanding of how a tiny brain processes environmental signals.


title: SpliceViNCI: Visualizing the splicing of non-canonical introns through recurrent neural networks

abstract: Most of the current computational models for splice junction prediction are based on the identification of canonical splice junctions. However, it is observed that the junctions lacking the consensus dimers GT and AG also undergo splicing. Identification of such splice junctions, called the non-canonical splice junctions, is also essentially important for a comprehensive understanding of the splicing phenomenon. This work focuses on the identification of non-canonical splice junctions through the application of a bidirectional long short-term memory (BLSTM) network. Furthermore, we apply a back-propagation based (integrated gradient) and a perturbation based (occlusion) visualization techniques to extract the non-canonical splicing features learned by the model. The features obtained are validated with the existing knowledge from the literature. Integrated gradient extracts features that comprise contiguous nucleotides, whereas occlusion extracts features that are individual nucleotides distributed across the sequence.

category: bioinformatics


title: Spatiotemporal control of cell cycle acceleration during axolotl spinal cord regeneration

abstract: Axolotls are uniquely able to resolve spinal cord injuries, but little is known about the mechanisms underlying spinal cord regeneration. We previously found that tail amputation leads to reactivation of a developmental-like program in spinal cord ependymal cells (Rodrigo Albors et al., 2015), characterized by a high-proliferation zone emerging 4 days post-amputation (Rost et al., 2016). What underlies this spatiotemporal pattern of cell proliferation, however, remained unknown. Here, we use modelling, tightly linked to experimental data, to demonstrate that this regenerative response is consistent with a signal that recruits ependymal cells during 85 hours after amputation within ~830{square}m of the injury. We adapted FUCCI technology to axolotls (AxFUCCI) to visualize cell cycles in vivo. AxFUCCI axolotls confirmed the predicted appearance time and size of the injury-induced recruitment zone and revealed cell cycle synchrony between ependymal cells. Our modeling and imaging move us closer to understanding bona fide spinal cord regeneration.

category: systems biology


title: Mobile Element Insertions and Associated Structural Variants in Longitudinal Breast Cancer Samples

abstract: While mobile elements are largely inactive in healthy somatic tissues, increased activity has been found in cancer tissues, with significant variation among different cancer types. In addition to insertion events, mobile elements have also been found to mediate many structural variation events in the genome. Here, to better understand the timing and impact of mobile element insertions and structural variants involving existing mobile elements in cancer, we examined their activity in longitudinal samples of four metastatic breast cancer patients. With whole-genome sequencing data from multiple timepoints through tumor progression, we used mobile element detection software followed by visual confirmation of the insertions. We identified 11 mobile element insertions or structural variants involving existing elements and found that the majority of these occurred early in tumor progression. Two of the identified insertions were SVA elements, which have rarely been found in previous cancer studies. Most of the variants appear to impact intergenic regions; however, we identified a translocation interrupting MAP2K4 involving Alu elements and a deletion in YTHDF2 involving mobile elements that likely inactivate reported tumor suppressor genes. The high variant allele fraction of the MAP2K4 translocation, the loss of the other copy of MAP2K4, the recurrent loss-of-function mutations found in this gene in other human cancers, and the important function of MAP2K4 indicate that this translocation is potentially a driver mutation. Overall, using a unique longitudinal dataset, we find that most variants are likely passenger mutations in the four patients we examined, but some variants impact tumor progression.

category: genomics