title: Adaptive learning through temporal dynamics of state representation

abstract:
People adjust their learning rate rationally according to local environmental statistics and calibrate such adjustments based on the broader statistical context. To date, no theory has captured the observed range of adaptive learning behaviors or the complexity of its neural correlates. Here, we attempt to do so using a neural network model that learns to map an internal context representation onto a behavioral response via supervised learning. The network shifts its internal context upon receiving supervised signals that are mismatched to its output, thereby changing the "state" to which feedback is associated. A key feature of the model is that such state transitions can either increase learning or decrease learning depending on the duration over which the new state is maintained. Sustained state transitions that occur after changepoints facilitate faster learning and mimic network reset phenomena observed in the brain during rapid learning. In contrast, state transitions after one-off outlier events are short-lived, thereby limiting the impact of outlying observations on future behavior. State transitions in our model provide the first mechanistic interpretation for bidirectional learning signals, such the p300, that relate to learning differentially according to the source of surprising events and may also shed light on discrepant observations regarding the relationship between transient pupil dilations and learning. Taken together, our results demonstrate that dynamic latent state representations can afford normative inference and provide a coherent framework for understanding neural signatures of adaptive learning across different statistical environments.

Significance StatementHow humans adjust their sensitivity to new information in a changing world has remained largely an open question. Bridging insights from normative accounts of adaptive learning and theories of latent state representation, here we propose a feed-forward neural network model that adjusts its learning rate online by controlling the speed of transitioning its internal state representations. Our model proposes a mechanistic framework for explaining learning under different statistical contexts, explains previously observed behavior and brain signals, and makes testable predictions for future experimental studies.


title: Predictive visual motion extrapolation emerges spontaneously and without supervision at each layer of a hierarchical neural network with spike-timing-dependent plasticity

abstract:
The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localisation of a moving object. One way this problem might be solved is extrapolation: using an objects past trajectory to predict its location in the present moment. Here, we investigate how a simulated in silico layered neural network might implement such extrapolation mechanisms, and how the necessary neural circuits might develop. We allowed an unsupervised hierarchical network of velocity-tuned neurons to learn its connectivity through spike-timing dependent plasticity. We show that the temporal contingencies between the different neural populations that are activated by an object as it moves causes the receptive fields of higher-level neurons to shift in the direction opposite to their preferred direction of motion. The result is that neural populations spontaneously start to represent moving objects as being further along their trajectory than where they were physically detected. Due to the inherent delays of neural transmission, this effectively compensates for (part of) those delays by bringing the represented position of a moving object closer to its instantaneous position in the world. Finally, we show that this model accurately predicts the pattern of perceptual mislocalisation that arises when human observers are required to localise a moving object relative to a flashed static object (the flash-lag effect).

Significance StatementOur ability to track and respond to rapidly changing visual stimuli, such as a fast moving tennis ball, indicates that the brain is capable of extrapolating the trajectory of a moving object in order to predict its current position, despite the delays that result from neural transmission. Here we show how the neural circuits underlying this ability can be learned through spike-timing dependent synaptic plasticity, and that these circuits emerge spontaneously and without supervision. This demonstrates how the neural transmission delays can, in part, be compensated to implement the extrapolation mechanisms required to predict where a moving object is at the present moment.

category: neuroscience


title: Control of aperture closure during reach-to-grasp movements in immersive haptic-free virtual reality

abstract: Virtual reality (VR) has garnered much interest as a training environment for motor skill acquisition, including for neurological rehabilitation of upper extremities. While the focus has been on gross upper limb motion, VR applications that involve reaching for, and interacting with, virtual objects are growing. The absence of true haptics in VR when it comes to hand-object interactions raises a fundamentally important question: can haptic-free immersive virtual environments (hf-VEs) support naturalistic coordination of reach-to-grasp movements? This issue has been grossly understudied, and yet is of significant importance in the development and application of VR across a number of sectors. In a previous study (Furmanek et al. 2019), we reported that reach-to-grasp movements are similarly coordinated in both the physical environment (PE) and hf-VE. The most noteworthy difference was that the closure phase--which begins at maximum aperture and lasts through the end of the movement--was longer in hf-VE than in PE, suggesting that different control laws might govern the initiation of closure between the two environments. To do so, we reanalyzed data from Furmanek et al. (2019), in which the participants reached to grasp three differently sized physical objects, and matching 3D virtual object renderings, placed at three different locations. Our analysis revealed two key findings pertaining to the initiation of closure in PE and hf-VE. First, the respective control laws governing the initiation of aperture closure in PE and hf-VE both included state estimates of transport velocity and acceleration, supporting a general unified control policy for implementing reach-to-grasp across physical and virtual environments. Second, aperture was less informative to the control law in hf-VE. We suggest that the latter was likely because transport velocity at closure onset and aperture at closure onset were less independent in hf-VE than in PE, ultimately resulting in aperture at closure onset having a weaker influence on the initiation of closure. In this way, the excess time and muscular effort needed to actively bring the fingers to a stop at the interface of a virtual object was factored into the control law governing the initiation of closure in hf-VE. Critically, this control law remained applicable, albeit with different weights in hf-VE, despite the absence of terminal haptic feedback and potential perceptual differences.


title: Effect of Handedness on Learned Controllers and Sensorimotor Noise During Trajectory-Tracking

abstract: In human-in-the-loop control systems, operators can learn to manually control dynamic machines with either hand using a combination of reactive (feedback) and predictive (feed-forward) control. This paper studies the effect of handedness on learned controllers and performance during a trajectory-tracking task. In an experiment with 18 participants, subjects perform an assay of unimanual trajectory-tracking and disturbance-rejection tasks through second-order machine dynamics, first with one hand then the other. To assess how hand preference (or dominance) affects learned controllers, we extend, validate, and apply a non-parametric modeling method to estimate the concurrent feedback and feedforward controllers. We find that performance improves because feedback adapts, regardless of the hand used. We do not detect statistically significant differences in performance or learned controllers between hands. Adaptation to reject disturbances arising exogenously (i.e. applied by the experimenter) and endogenously (i.e. generated by sensorimotor noise) explains observed performance improvements.


title: Memory for stimulus durations is not bound to spatial information

abstract: Different theories have been proposed to explain how the human brain derives an accurate sense of time. One specific class of theories, intrinsic clock theories, postulate that temporal information of a stimulus is represented much like other features such as color and location, bound together to form a coherent percept. Here we explored to what extent this holds for temporal information after it has been perceived and is held in working memory for subsequent comparison. We recorded EEG of participants who were asked to time stimuli at lateral positions of the screen followed by comparison stimuli presented in the center. Using well-established markers of working memory maintenance, we investigated whether the usage of temporal information evoked neural signatures that were indicative of the location where the stimuli had been presented, both during maintenance and during comparison. Behavior and neural measures including the contralateral delay activity, lateralized alpha suppression and decoding analyses through time all supported the same conclusion: the representation of location was strongly involved during perception of temporal information, but when temporal information was to be used for comparison it no longer showed a relation to spatial information. These results support a model where the initial perception of a stimulus involves intrinsic computations, but that this information is subsequently translated to a stimulus-independent format to be used to further guide behavior.


title: A dynamical system model for predicting gene expression from the epigenome

abstract: Gene regulation is an important fundamental biological process. The regulation of gene expression is managed through a variety of methods including epigentic processes (e.g., DNA methylation). Understanding the role of epigenetic changes in gene expression is a fundamental question of molecular biology. Predictions of gene expression values from epigenetic data have tremendous research and clinical potential. Despite active research, studies to date have focused on using statistical models to predict gene expression from methylation data. In contrast, dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN) which can also serve as a mechanistic hypothesis. Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. Software for dataset preparation, model parameter fitting and prediction generation, and reporting are available at https://github.com/kordk/stoch_epi_lib.

category: systems biology


title: Intestinal infection results in impaired lung innate immunity to secondary respiratory infection.

abstract:
BackgroundPneumonia and diarrhea are among the leading causes of death worldwide, and epidemiological studies have demonstrated that diarrhea is associated with an increased risk of subsequent pneumonia. Our aim was to determine the impact of intestinal infection on innate immune responses in the lung.

MethodsUsing a mouse model of intestinal infection by Salmonella enterica serovar Typhimurium (S. Typhimurium (ST)), we investigated how infection in the gut compartment can modulate immunity in the lungs and impact susceptibility to bacterial (Klebsiella pneumoniae (KP)) challenge.

ResultsWe found alterations in frequencies of innate immune cells in lungs of intestinally-infected mice compared to uninfected mice. On subsequent challenge with K. pneumoniae we found that mice with prior intestinal infection have higher lung bacterial burden and inflammation, increased neutrophil margination, and neutrophil extracellular traps (NETs), but lower overall numbers of neutrophils, compared to mice without prior intestinal infection. Total numbers of dendritic cells, innate-like T cells, and natural killer cells were not different between mice with and without prior intestinal infection.

ConclusionsTogether, these results suggest that intestinal infection impacts lung innate immune responses, most notably neutrophil characteristics, potentially resulting in increased susceptibility to secondary pneumonia.

Article summaryWe show, in a mouse model, that prior intestinal infection with Salmonella Typhimurium leads to increased susceptibility to respiratory Klebsiella pneumoniae infection, which is associated with altered neutrophil responses.

category: immunology


title: Noise-robust recognition of objects by humans and deep neural networks

abstract: Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs provide a viable model of human vision when tested with challenging noisy images of objects, sometimes presented at the very limits of visibility. We show that popular state-of-the-art DNNs perform in a qualitatively different manner than humans - they are unusually susceptible to spatially uncorrelated white noise and less impaired by spatially correlated noise. We implemented a noise-training procedure to determine whether noise-trained DNNs exhibit more robust responses that better match human behavioral and neural performance. We found that noise-trained DNNs provide a better qualitative match to human performance; moreover, they reliably predict human recognition thresholds on an image-by-image basis. Functional neuroimaging revealed that noise-trained DNNs provide a better correspondence to the pattern-specific neural representations found in both early visual areas and high-level object areas. A layer-specific analysis of the DNNs indicated that noise training led to broad-ranging modifications throughout the network, with greater benefits of noise robustness accruing in progressively higher layers. Our findings demonstrate that noise-trained DNNs provide a viable model to account for human behavioral and neural responses to objects in challenging noisy viewing conditions. Further, they suggest that robustness to noise may be acquired through a process of visual learning.


title: CSDE1 is a Post-Transcriptional Regulator of the LDL Receptor

abstract:
The low-density lipoprotein receptor (LDLR) controls cellular delivery of cholesterol and clears LDL from the bloodstream, protecting against atherosclerotic heart disease, the leading cause of death in the United States. We therefore sought to identify regulators of the LDLR beyond the targets of current clinical therapies and known causes of familial hypercholesterolemia. We show that Cold Shock Domain-Containing Protein E1 (CSDE1) enhances hepatic LDLR mRNA decay via its 3 untranslated region to regulate atherogenic lipoproteins in vivo. Using parallel phenotypic genome-wide CRISPR interference screens, we found 40 specific regulators of the LDLR left unidentified by observational human genetics. Among these, we show that CSDE1 regulates the LDLR at least as strongly as the mechanistically distinct pathways exploited by the best available clinical therapies: statins and PCSK9 inhibitors. Additionally, we show that hepatic gene silencing of Csde1 treats diet-induced dyslipidemia in mice better than that of Pcsk9. Our results reveal the therapeutic potential of manipulating a newly identified key factor in the post-transcriptional regulation of the LDLR mRNA for the prevention of cardiovascular disease. We anticipate that our approach of modelling a clinically relevant phenotype in a forward genetic screen, followed by mechanistic pharmacologic dissection and in vivo validation, will serve as a generalizable template for the identification of therapeutic targets in other human disease states.

One Sentence SummaryA genome-wide CRISPR screen identifies CSDE1 as a key regulator of hepatic LDLR mRNA decay in vivo, making it a promising target for heart disease.

Graphical Abstract

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category: genomics


title: A novel combination of Class-I fumarases and metabolites (α-ketoglutarate and fumarate) signal the DNA damage response in E. coli.

abstract:
Class-II fumarases (Fumarate Hydratase, FH) are dual targeted enzymes, occurring in the mitochondria and cytosol of all eukaryotes. They are essential components in the DNA damage response (DDR) and more specifically, protecting cells from DNA double strand breaks. Similarly, the Gram-positive Bacterium Bacillus subtilis Class-II fumarase, in addition to its role in the TCA cycle, also participates in the DDR. Escherichia coli, harbors three fumarase genes; Class-I fumA and fumB and Class-II fumC. Notably, Class-I fumarases, show no sequence similarity to Class-II fumarases and are of different evolutionary origin. Strikingly, here we show that E. coli fumarase functions are distributed between Class-I fumarases which participate in the DDR, and the Class-II fumarase which participates in respiration. In E. coli, we discover that the signaling molecule, alpha-ketoglutarate (-KG), has a novel function, complementing DNA damage sensitivity of fum null mutants. Excitingly, we identify the E. coli -KG dependent DNA repair enzyme AlkB, as the target of this interplay of metabolite signaling. In addition to -KG, fumarate (fumaric acid) is shown to affect DNA damage repair on two different levels, first by directly inhibiting the DNA damage repair enzyme AlkB demethylase activity, both in vitro and in vivo (countering -KG). The second is a more global effect on transcription, as fum null mutants exhibit a decrease in transcription of key DNA damage repair genes. Together these results show evolutionary adaptable metabolic signaling of the DDR, in which fumarases and different metabolites are recruited regardless of the evolutionary enzyme Class preforming the function.

Significance StatementClass-II fumarases have been shown to participate in cellular respiration and the DNA damage response. Here we show, for the first time, that in the model prokaryote, Escherichia coli, which harbors both Class-I and Class-II fumarases, it is the Class-I fumarases that participate in DNA damage repair by a mechanism which is different than those described for other fumarases. Strikingly, this mechanism employs a novel signaling molecule, alpha-ketoglutarate (-KG), and its target is the DNA damage repair enzyme AlkB. In addition, we show that fumarase precursor metabolites, fumarate and succinate, can inhibit the -KG-dependent DNA damage repair enzyme, AlkB, both in vitro and in vivo. This study provides a new perspective on the function and evolution of metabolic signaling.

category: microbiology


title: Illumina iSeq 100 and MiSeq exhibit similar performance in freshwater fish environmental DNA metabarcoding

abstract: Environmental DNA (eDNA) analysis is a method of detecting DNA from environmental samples and is used as a biomonitoring tool. In recent studies, Illumina MiSeq has been the most extensively used tool for eDNA metabarcoding. The Illumina iSeq 100 (hereafter, iSeq), one of the high-throughput sequencers (HTS), has a relatively simple workflow and is potentially more affordable than other HTS. However, its utility in eDNA metabarcoding has still not been investigated. In the present study, we applied fish eDNA metabarcoding to 40 water samples from river and lake ecosystems to assess the difference in species detectability and composition between iSeq and MiSeq. To check differences in sequence quality and errors, we also assessed differences in read changes between the two HTS. There were similar sequence qualities between iSeq and MiSeq. Significant difference was observed in the number of species between two HTS, but no difference was observed in species composition between the two HTS. Additionally, the species compositions in common with the conventional method were the same between the two HTS. According to the results, using the same amplicon library for sequencing, two HTS would exhibit a similar performance of fish species detection using eDNA metabarcoding.

category: ecology


title: Evolutionary mechanisms that determine which bacterial genes are carried on plasmids

abstract:
The evolutionary pressures that determine the location (chromosomal or plasmid-borne) of bacterial genes are not fully understood. We investigate these pressures through mathematical modelling in the context of antibiotic resistance, which is often found on plasmids. Our central finding is that gene location is under positive frequency-dependent selection: the higher the frequency of one form of resistance compared to the other, the higher its relative fitness. This can keep moderately beneficial genes on plasmids, despite occasional plasmid loss. For these genes, positive frequency-dependence leads to a priority effect: whichever form is acquired first - through either mutation or horizontal gene transfer - has time to increase in frequency and thus become difficult to displace. Higher rates of horizontal transfer of plasmid-borne than chromosomal genes therefore predict moderately beneficial genes will be found on plasmids. Gene flow between plasmid and chromosome allows chromosomal forms to arise, but positive frequencydependent selection prevents these from establishing. Further modelling shows this effect is particularly pronounced when genes are shared across a large number of species, suggesting antibiotic resistance genes are often found on plasmids because they are moderately beneficial across many species. We also revisit previous theoretical work - relating to the role of local adaptation in explaining gene location and to plasmid persistence - in light of our findings.

Impact StatementBacterial genes can either reside on the chromosome or on plasmids, extra-chromosomal genetic structures which can be transferred from cell to cell. The distribution of genes between plasmid and chromosome is not random: certain types of genes are particularly likely to be plasmid-associated. This includes a number of clinically important traits, such as antibiotic resistance and virulence factors. The evolutionary mechanisms that give rise to this pattern are not well understood. Plasmids are occasionally lost during cell replication and thus less reliably inherited than the chromosome, and genes are free to transition between plasmid and chromosome: so what keeps genes on plasmids? We address this question using a mathematical model. The key prediction from our model is that the relative fitness of chromosomal and plasmid-borne genes depends on their relative frequencies ( positive frequency-dependent selection). In other words, the fitness of a plasmid-borne gene will be higher in a population in which the chromosomal gene is rare (and vice-versa). This positive-frequency dependence can keep moderately beneficial genes on plasmids, despite occasional plasmid loss. This leads to a priority effect: whichever form of the gene (i.e. plasmid-borne or chromosomal) is acquired first has time to increase in frequency and thus become difficult to displace. Therefore, the relative rate of acquiring the gene on the plasmid vs the chromosome predicts where the gene will be found. Further modelling shows this effect is particularly pronounced when genes are beneficial across a large number of species. All together, the hypothesis that emerges from our work is that plasmid-borne genes are moderately beneficial; functional across a large number of species; and rarely acquired through chromosomal mutation. We suggest traits like antibiotic resistance are often found on plasmids because these genes commonly fulfill these criteria.

category: evolutionary biology


title: Ventral Pallidum GABA Neurons Mediate Motivation Underlying Risky Choice

abstract:
Pursuing rewards while avoiding danger is an essential function of any nervous system. Here, we examine a new mechanism helping rats negotiate the balance between risk and reward when making high-stakes decisions. Specifically, we focus on GABA neurons within an emerging mesolimbic circuit nexus--the ventral pallidum (VP). These neurons play a distinct role from other VP neurons in simple motivated behaviors in mice, but their roles in more complex motivated behaviors is unknown. Here, we interrogate the behavioral functions of VPGABA neurons in male and female transgenic GAD1:Cre rats (and wildtype littermates), using a reversible chemogenetic inhibition approach. Employing a behavioral assay of risky decision making, and of the food-seeking and shock-avoidance components of this task, we show that engaging inhibitory Gi/o signaling specifically in VPGABA neurons suppresses motivation to pursue highly salient palatable foods, and possibly also motivation to avoid being shocked. In contrast, inhibiting these neurons did not affect seeking of low-value food, free consumption of palatable food, or unconditioned affective responses to shock. Accordingly, when rats considered whether to pursue food despite potential for shock in a risky decision-making task, inhibiting VPGABA neurons caused them to more readily select a small but safe reward over a large but dangerous one--an effect not seen in the absence of shock threat. Together, results indicate that VPGABA neurons are critical for high-stakes adaptive responding that is necessary for survival, but which may also malfunction in psychiatric disorders.

Significance StatementIn a dynamic world, it is essential to implement appropriate behaviors under circumstances involving rewards, threats, or both. Here, we demonstrate a crucial role for VPGABA neurons in high-stakes motivated behavior of several types. We show that this VPGABA role in motivation impacts decision making, as inhibiting these neurons yields a conservative, risk-averse strategy not seen when the task is performed without threat of shock. These new roles for VPGABA neurons in behavior may inform future strategies for treating addiction, and other disorders of maladaptive decision making.


title: FDR control in GWAS with population structure

abstract: We present a comprehensive statistical framework to analyze data from genome-wide association studies of polygenic traits, producing distinct and interpretable discoveries while controlling the false discovery rate. This approach leverages sophisticated multivariate models, correcting for linkage disequilibrium, and accounts for population structure and relatedness, adapting to the characteristics of the samples at hand. A key element is the recognition that the observed genotypes can be considered as a random sample from an appropriate model, encapsulating our knowledge of genetic inheritance and human populations. This allows us to generate imperfect copies (knockoffs) of these variables which serve as ideal negative controls; knockoffs are indistinguishable from the original genotypes in distribution, and independent from the phenotype. In sharp contrast with state-of-the-art methods, the validity of our inference in no way depends on assumptions about the unknown relation between genotypes and phenotype. We develop and leverage a model for the genotypes that accounts for arbitrary and unknown population structure, which may be due to diverse ancestries or familial relatedness. We build a pipeline that is robust to the most prominent possible confounders, facilitating the discovery of causal variants. Validity and effectiveness are demonstrated by extensive simulations with real data, as well as by the analysis of several phenotypes in the UK Biobank. Finally, fast software is made available for researchers to apply the proposed methodology to Biobank-scale data sets.


title: Fitness benefits of providing services to others: Grooming predicts survival in a neotropical primate

abstract: Across multiple species of social mammals, a growing number of studies have found that that individual sociality is associated with survival. In long-lived species, like primates, lifespan is one of the main components of fitness. We used 18 years of data from the Lomas Barbudal Monkey project to quantify social integration in 11 capuchin (Cebus capucinus) groups and tested whether female survivorship was associated with females tendencies to interact with three types of partners: (1) all group members, (2) adult females, (3) adult males. We found strong evidence that females who engaged more with other females in affiliative interactions and foraged in close proximity experienced increased survivorship. We found some weak evidence that females might also benefit from engaging in more support in agonistic contexts with other females. These benefits were evident in models that account for the females rank and group size. Female interactions with all group members also increased survival, but the estimates of the effects were more uncertain. In interactions with adult males, only females who provided more grooming to males survived longer. The results presented here suggest that social integration may result in survival-related benefits. Females might enjoy these benefits through exchanging grooming for other currencies, such as coalitionary support or tolerance.

category: animal behavior and cognition


title: Social integration predicts survival in female white-faced capuchin monkeys


title: Seasonal climate variations promote bacterial α-diversity in soil

abstract: Ecological theory suggests that temporal environmental fluctuations can contribute greatly to diversity maintenance. Given bacterias short generation time and rapid responses to environmental change, seasonal climate fluctuations are very likely to play an important role in maintaining the extremely high -diversity of soil bacterial community, which has been unfortunately neglected in previous studies. Here, with in-depth analyses of two previously published soil bacterial datasets at global scale, we found that soil bacterial -diversity was positively correlated with both seasonal variations of temperature and precipitation. Furthermore, piecewise structural equation models showed that seasonal variations of temperature or precipitation directly promoted soil bacterial -diversity in each dataset. However, it is noteworthy that the importance of seasonal climate variations might be underestimated in the above analyses, due to the high level of environmental variations irrelevant to climate seasonality among sampling sites and the lack of sampling across seasons. Supplementary analyses of a previously published wheat cropland dataset with samples collected in both summer and winter across North China Plain was conducted. Similarly, we found that bacterial -diversity was positively correlated with seasonal climate variations, but much stronger, though the range of seasonal climate variations was much smaller compared to the two global datasets. Collectively, these findings implied that fluctuation-dependent mechanisms of diversity maintenance presumably operate in soil bacterial communities. Based on existing evidence, we speculated that the storage effect may be the main mechanism responsible for diversity maintenance in soil bacterial community, but rigorous experimental tests are needed in the future.


title: A quick and easy way to estimate entropy and mutual information for neuroscience

abstract: AO_SCPLOWBSTRACTC_SCPLOWCalculations of entropy of a signal or mutual information between two variables are valuable analytical tools in the field of neuroscience. They can be applied to all types of data, capture nonlinear interactions and are model independent. Yet the limited size and number of recordings one can collect in a series of experiments makes their calculation highly prone to sampling bias. Mathematical methods to overcome this so-called "sampling disaster" exist, but require significant expertise, great time and computational costs. As such, there is a need for a simple, unbiased and computationally efficient tool for estimating the level of entropy and mutual information. In this paper, we propose that application of entropy-encoding compression algorithms widely used in text and image compression fulfill these requirements. By simply saving the signal in PNG picture format and measuring the size of the file on the hard drive, we can estimate entropy changes through different conditions. Furthermore, with some simple modifications of the PNG file, we can also estimate the evolution of mutual information between a stimulus and the observed responses through different conditions. We first demonstrate the applicability of this method using white-noise-like signals. Then, while this method can be used in all kind of experimental conditions, we provide examples of its application in patch-clamp recordings, detection of place cells and histological data. Although this method does not give an absolute value of entropy or mutual information, it is mathematically correct, and its simplicity and broad use make it a powerful tool for their estimation through experiments.


title: Temperature Effect on Polymerase Fidelity

abstract: The discovery of extremophiles helped enable the development of groundbreaking technology such as polymerase chain reaction. Temperature variation is often an essential step of these technology platforms, but the effect of temperature on the error rate of polymerases from different origins is under-explored. Here, we applied high-throughput sequencing to profile the error rates of DNA polymerases from psychrophilic, mesophilic, and thermophilic origins with single-molecule resolution. We found that reaction temperature substantially increases substitution and deletion error rates of psychrophilic and mesophilic DNA polymerases. Our motif analysis shows that the substitution error profiles cluster according to phylogenetic similarity of polymerases, not reaction temperature, thus suggesting that reaction temperature increases global error rate of polymerases independent of sequence context. Intriguingly, we also found that the DNA polymerase I of a psychrophilic bacteria exhibits higher polymerization activity than its mesophilic ortholog across all temperature ranges, including down to -19{degrees}C which is well below the freezing temperature of water. Our results provide a useful reference for how reaction temperature, a crucial parameter of biochemistry, can affect DNA polymerase fidelity in organisms adapted to a wide range of thermal environments.

category: biochemistry


title: Characterization of extracellular vesicles and artificial nanoparticles with four orthogonal single-particle analysis platforms

abstract: We compared four orthogonal technologies for sizing, counting, and phenotyping of extracellular vesicles (EVs) and synthetic particles. The platforms were: single-particle interferometric reflectance imaging sensing (SP-IRIS) with fluorescence, nanoparticle tracking analysis (NTA) with fluorescence, microfluidic resistive pulse sensing (MRPS), and nanoflow cytometry measurement (NFCM). EVs from the human T lymphocyte line H9 (high CD81, low CD63) and the promonocytic line U937 (low CD81, high CD63) were separated from culture conditioned medium (CCM) by differential ultracentrifugation (dUC) or a combination of ultrafiltration (UF) and size exclusion chromatography (SEC) and characterized by transmission electron microscopy (TEM) and Western blot (WB). Mixtures of synthetic particles (silica and polystyrene spheres) with known sizes and/or concentrations were also tested. MRPS and NFCM returned similar particle counts, while NTA detected counts approximately one order of magnitude lower for EVs, but not for synthetic particles. SP-IRIS events could not be used to estimate particle concentrations. For sizing, SP-IRIS, MRPS, and NFCM returned similar size profiles, with smaller sizes predominating (per power law distribution), but with sensitivity typically dropping off below diameters of 60 nm. NTA detected a population of particles with a mode diameter greater than 100 nm. Additionally, SP-IRIS, MRPS, and NFCM were able to identify at least three of four distinct size populations in a mixture of silica or polystyrene nanoparticles. Finally, for tetraspanin phenotyping, the SP-IRIS platform in fluorescence mode was able to detect at least two markers on the same particle, while NFCM detected either CD81 or CD63. Based on the results of this study, we can draw conclusions about existing single-particle analysis capabilities that may be useful for EV biomarker development and mechanistic studies.

category: cell biology


title: Effect of sub-lethal prenatal endotoxemia on murine placental transport systems and lipid homeostasis

abstract: Infection alters the expression of transporters that mediate the placental exchange of xenobiotics, lipids and cytokines. We hypothesized that lipopolysaccharide (LPS) modifies the expression of placental transport systems and lipid homeostasis. LPS (150 g/kg; i.p.) treatments were administered for 4 h or 24 h, animals were euthanized at gestational days (GD) 15.5 or 18.5, and maternal blood, foetuses and placentae were collected. Increased rates of foetal demise were observed at GD15.5 following LPS treatment, whereas at GD18.5, high rates of early labour occurred and were associated with distinct proinflammatory responses. LPS did not alter ABC transporter mRNA expression but decreased Fabppm at GD15.5 (LPS-4 h) and increased Fat/Cd36 lipid transporter mRNA at GD18.5 (LPS-4 h). At the protein level, breast cancer-related protein (BCRP) and Abcg1 levels were decreased in the placental labyrinth zone (Lz) at GD15.5, whereas P-glycoprotein (P-gp) and Bcrp Lz-immunostaining was decreased at GD18.5. In the placental junctional zone (Jz), P-gp, Bcrp and Abcg1 levels were higher at GD18.5. Specific maternal plasma and placental changes in triacylglycerol, free fatty acid, cholesterol, cholesterol ester and monoacylglycerol levels were detected in a gestational age-dependent manner. In conclusion, LPS-induced foetal death and early labour were associated with altered placental ABC and lipid transporter expression and deranged maternal plasma and placental lipid homeostasis. These changes likely modify foetal xenobiotic exposure and placental lipid exchange in cases of bacterial infection.

category: physiology


title: Effect of sublethal prenatal endotoxaemia on murine placental transport systems and lipid homeostasis


title: Super-human cell death detection with biomarker-optimized neural networks

abstract: Cell death is an essential process in biology that must be accounted for in live microscopy experiments. Nevertheless, cell death is difficult to detect without perturbing experiments with stains, dyes or biosensors that can bias experimental outcomes, lead to inconsistent results, and reduce the number of processes that can be simultaneously labelled. These additional steps also make live microscopy difficult to scale for high-throughput screening because of the cost, labor, and analysis they entail. We address this fundamental limitation of live microscopy with biomarker-optimized convolutional neural networks (BO-CNN): computer vision models trained with a ground truth biosensor that detect live cells with superhuman, 96% accuracy more than 100 times faster than previous methods. Our models learn to identify important morphological characteristics associated with cell vitality without human input or additional perturbations, and to generalize to other imaging modalities and cell types for which they have no specialized training. We demonstrate that we can interpret decisions from BO-CNN models to gain biological insight into the patterns they use to achieve superhuman accuracy. The BO-CNN approach is broadly useful for live microscopy, and affords a powerful new paradigm for advancing the state of high-throughput imaging in a variety of contexts.


title: The evolution of trait correlations constrains phenotypic adaptation to high CO2 in a eukaryotic alga

abstract: Microbes form the base of food webs and drive biogeochemical cycling. Predicting the effects of microbial evolution on global elemental cycles remains a significant challenge due to the sheer number of interacting environmental and trait combinations. Here we present an approach for integrating multivariate trait data into a predictive model of trait evolution. We investigated the outcome of thousands of possible adaptive walks parameterized using empirical evolution data from the alga Chlamydomonas exposed to high CO2. We found that the direction of historical bias (existing trait correlations) influenced both the rate of adaptation and the evolved phenotypes (trait combinations). Critically, we use fitness landscapes derived directly from empirical trait values to capture known evolutionary phenomena. This work demonstrates that ecological models need to represent both changes in traits and changes in the correlation between traits in order to accurately capture phytoplankton evolution and predict future shifts in elemental cycling.


title: An acylsugar-deficient Nicotiana benthamiana strain for aphid and whitefly research

abstract: Nicotiana benthamiana is used extensively as a platform for transient gene expression and as a model system for studying plant-virus interactions. However, many tobacco-feeding generalist herbivores, including Myzus persicae (green peach aphid), Bemisia tabaci (whitefly), Macrosiphum euphorbiae (potato aphid), Heliothis virescens (tobacco budworm), Trichoplusia ni (cabbage looper), and Helicoverpa zea (corn earworm), grow poorly on N. benthamiana, limiting its utility for research on plant-insect interactions. Using CRISPR/Cas9, we generated knockout mutations in two N. benthamiana acylsugar acyltransferases, ASAT1 and ASAT2, which contribute to the biosynthesis of insect-deterrent acylsucroses. Whereas asat1 mutations reduced the abundance of two predominant acylsucroses, asat2 mutations caused almost complete depletion of foliar acylsucroses. The tested hemipteran and lepidopteran species survived, gained weight, and/or reproduced significantly better on asat2 mutant plants than on wildtype N. benthamiana. Furthermore, both asat1 and asat2 mutations reduced the water content and increased the temperature of leaves, indicating that foliar acylsucroses can protect against desiccation. Two experiments demonstrated the utility of the N. benthamiana asat2 mutant line for insect bioassays. Transmission of turnip mosaic virus by M. persicae was significantly improved by an asat2 mutation. Tobacco rattle virus constructs were used for virus-induced gene silencing of acetylcholinesterase, squalene synthase, toll-like receptor 7, and tubulin-specific chaperon D genes in B. tabaci, an experiment that would have been difficult with wild-type N. benthamiana due to high insect mortality. Additionally, the absence of acylsugars in asat2 mutant lines will simplify transient expression assays for the functional analysis of acylsugar biosynthesis genes from other Solanaceae.

category: plant biology


title: Recombinant SARS-CoV-2 genomes are currently circulating at low levels

abstract: Viral recombination can generate novel genotypes with unique phenotypic characteristics, including transmissibility and virulence. Although the capacity for recombination among betacoronaviruses is well documented, there is limited evidence of recombination between SARS-CoV-2 strains. By identifying the mutations that primarily determine SARS-CoV-2 clade structure, we developed a lightweight approach for detecting recombinant genomes. Among the over 537,000 genomes queried, we detect 1175 putative recombinants that contain multiple mutational markers from distinct clades. Additional phylogenetic analysis and the observed co-circulation of predicted parent clades in the geographic regions of exposure further support the feasibility of recombination in these detected cases. An analysis of these detected cases did not reveal any evidence for recombination hotspots in the SARS-CoV-2 genome. Although most recombinant genotypes were detected a limited number of times, at least two recombinants are now widely transmitted. Recombinant genomes were also found to contain substitutions of concern for elevated transmissibility and lower vaccine efficacy, including D614G, N501Y, E484K, and L452R. Adjusting for an unequal probability of detecting recombinants derived from different parent clades, and for geographic variation in clade abundance, we estimate that at most 5% of circulating viruses in the USA and UK are recombinant. While the phenotypic characterization of detected recombinants was beyond the scope of our analysis, the identification of transmitted recombinants involving substitutions of concern underscores the need to sustain efforts to monitor the emergence of new genotypes generated through recombination.


title: Phenotyping the preterm brain: characterising individual deviations from normative volumetric development in two large infant cohorts

abstract: The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.


title: Temperature-dependent effects of house fly proto-Y chromosomes on gene expression

abstract: Sex determination, the developmental process by which sexually dimorphic phenotypes are established, evolves fast. Species with polygenic sex determination, in which master regulatory genes are found on multiple different proto-sex chromosomes, are informative models to study the evolution of sex determination. House flies are such a model system, with male determining loci possible on all six chromosomes and a female-determiner on one of the chromosomes as well. The two most common male-determining proto-Y chromosomes form latitudinal clines on multiple continents, suggesting that temperature variation is an important selection pressure responsible for maintaining polygenic sex determination in this species. To identify candidate genes that may be under selection, we used RNA-seq to test for temperature-dependent effects of the proto-Y chromosomes on gene expression in adult house flies. We find no evidence for ecologically meaningful temperature-dependent expression of sex determining genes between male genotypes, but we were likely not sampling an appropriate developmental time-point to identify such effect. In contrast, we identified many other genes whose expression depends on the interaction between proto-Y chromosome genotype and temperature, including genes that encode proteins involved in reproduction, metabolism, lifespan, stress response, and immunity. Notably, genes with genotype-by-temperature interactions on expression are not enriched on the proto-sex chromosomes. Moreover, there is no evidence that temperature-dependent expression is driven by chromosome-wide expression divergence between the proto-Y and proto-X alleles. Therefore, if temperature-dependent gene expression is responsible for differences in phenotypes and fitness of proto-Y genotypes across house fly populations, these effects are driven by a small number of temperature-dependent alleles on the proto-Y chromosomes that may in turn affect the expression of genes on other chromosomes.


title: Common and distinct roles of frontal midline theta and occipital alpha oscillations in coding temporal intervals and spatial distances

abstract: Judging how far something is and how long it takes to get there are critical to memory and navigation. Yet, the neural codes for spatial and temporal information remain unclear, particularly the involvement of neural oscillations in maintaining such codes. To address these issues, we designed an immersive virtual reality environment containing teleporters that displace participants to a different location after entry. Upon exiting the teleporters, participants made judgements from two given options regarding either the distance they had travelled (spatial distance condition) or the duration they had spent inside the teleporters (temporal duration condition). We wirelessly recorded scalp EEG while participants navigated in the virtual environment by physically walking on an omnidirectional treadmill and traveling through teleporters. An exploratory analysis revealed significantly higher alpha and beta power for short distance versus long distance traversals, while the contrast also revealed significantly higher frontal midline delta-theta-alpha power, and global beta power increases for short versus long temporal duration teleportation. Analyses of occipital alpha instantaneous frequencies revealed their sensitivity for both spatial distances and temporal durations, suggesting a novel and common mechanism for both spatial and temporal coding. We further examined the resolution of distance and temporal coding by classifying discretized distance bins and 250ms time bins based on multivariate patterns of 2-30 Hz power spectra, finding evidence that oscillations code fine-scale time and distance information. Together, these findings support partially independent coding schemes for spatial and temporal information, suggesting that low-frequency oscillations play important roles in coding both space and time.


title: Automatic inference of demographic parameters using Generative Adversarial Networks

abstract: AO_SCPLOWBSTRACTC_SCPLOWPopulation genetics relies heavily on simulated data for validation, inference, and intuition. In particular, since the evolutionary "ground truth" for real data is always limited, simulated data is crucial for training supervised machine learning methods. Simulation software can accurately model evolutionary processes, but requires many hand-selected input parameters. As a result, simulated data often fails to mirror the properties of real genetic data, which limits the scope of methods that rely on it. Here, we develop a novel approach to estimating parameters in population genetic models that automatically adapts to data from any population. Our method, pg-gan, is based on a generative adversarial network that gradually learns to generate realistic synthetic data. We demonstrate that our method is able to recover input parameters in a simulated isolation-with-migration model. We then apply our method to human data from the 1000 Genomes Project, and show that we can accurately recapitulate the features of real data.


title: Songbirds can learn flexible contextual control over syllable sequencing

abstract: The flexible control of sequential behavior is a fundamental aspect of speech, enabling endless reordering of a limited set of learned vocal elements (syllables or words). Songbirds are phylogenetically distant from humans but share both the capacity for vocal learning and neural circuitry for vocal control that includes direct pallial-brainstem projections. Based on these similarities, we hypothesized that songbirds might likewise be able to learn flexible, moment by-moment control over vocalizations. Here, we demonstrate that Bengalese finches (Lonchura striata domestica), which sing variable syllable sequences, can learn to rapidly modify the probability of specific sequences (e.g.  ab-c versus  ab-d) in response to arbitrary visual cues. Moreover, once learned, this modulation of sequencing occurs immediately following changes in contextual cues and persists without external reinforcement. Our findings reveal a capacity in songbirds for learned contextual control over syllable sequencing that parallels human cognitive control over syllable sequencing in speech.


title: Dendrimer-targeted immunosuppression of microglia reactivity super-accelerates photoreceptor regeneration in the zebrafish retina

abstract: Muller glia (MG) function as injury-induced retinal stem cells in zebrafish but not mammals. Insights from zebrafish, however, have been used to stimulate limited regenerative responses from mammalian MG. Microglia/macrophages regulate MG stem cell activity in the chick, zebrafish and mouse. We previously showed that dexamethasone can accelerate retinal regeneration in zebrafish. Similarly, microglia ablation enhances regenerative outcomes in the mouse retina. Targeted immunomodulation may therefore enhance the regenerative potential of human MG. Nanoparticle-based immunomodulation is an emerging field with immense therapeutic potential. Here, we investigated how regeneration-enhancing dexamethasone treatments alter microglia behavior and how dendrimer-based targeting of dexamethasone to reactive microglia impact retinal regeneration kinetics. Intravital time-lapse imaging revealed specific dexamethasone-induced changes in microglia reactivity. Dendrimer-conjugated dexamethasone treatments resulted in: 1) decreased toxicity, 2) selective targeting of reactive microglia and, 3) "super-accelerated" retinal regeneration kinetics. These data support the use of dendrimer-based drug formulations for modulating microglia reactivity in degenerative disease contexts, especially as therapeutic strategies for promoting regenerative responses to neuronal cell loss.


title: Inhibition of SARS-CoV-2 polymerase by nucleotide analogs: a single moleculeperspective

abstract:
The nucleotide analog Remdesivir (RDV) is the only FDA-approved antiviral therapy to treat infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The physical basis for efficient utilization of RDV by SARS-CoV-2 polymerase is unknown. Here, we characterize the impact of RDV and other nucleotide analogs on RNA synthesis by the polymerase using a high-throughput, single-molecule, magnetic-tweezers platform. The location of the modification in the ribose or in the base dictates the catalytic pathway(s) used for its incorporation. We reveal that RDV incorporation does not terminate viral RNA synthesis, but leads the polymerase into deep backtrack, which may appear as termination in traditional ensemble assays. SARS-CoV-2 is able to evade the endogenously synthesized product of the viperin antiviral protein, ddhCTP, though the polymerase incorporates this nucleotide analog well. This experimental paradigm is essential to the discovery and development of therapeutics targeting viral polymerases.

TeaserWe revise Remdesivirs mechanism of action and reveal SARS-CoV-2 ability to evade interferon-induced antiviral ddhCTP

category: biophysics


title: MICROBIOTA-MEDIATED COMPETITION BETWEEN DROSOPHILA SPECIES

abstract: Species that share resources often avoid competition with context-dependent behaviors. This is the case for the invasive insect pest Drosophila suzukii, whose larval ecological niche overlaps with that of Drosophila melanogaster in ripe, but not rotten, fruit. We discovered D. suzukii females prevent costly interspecific larval competition by avoiding oviposition on substrates previously visited by D. melanogaster. More precisely, D. melanogaster association with gut bacteria of the genus Lactobacillus triggers D. suzukii avoidance. However, D. suzukii avoidance behavior is condition-dependent, and D. suzukii females that themselves carry D. melanogaster bacteria stop avoiding sites visited by D. melanogaster. The adaptive significance of avoiding cues from the competitors microbiota was revealed by experimentally reproducing in-fruit larval competition: reduced survival of D. suzukii larvae was dependent on the presence of gut bacteria in the competitor. This study unveils a new role for the symbiotic microbiota and plastic behaviors in mediating interspecific competition.


title: Spatially Explicit Modeling of Community Occupancy using Markov Random Field Models with Imperfect Observation: Mesocarnivores in Apostle Islands National Lakeshore

abstract: How species organize spatially is one of ecologys most motivating questions. Multiple theories have been advanced and various models developed to account for the environment, interactions among species, and spatial drivers. However, relative importance comparisons of explanatory phenomena generally are neglected in these analyses. We developed a spatially explicit community occupancy model based on Markov random fields that accounts for spatial auto-correlation and interspecific interactions in occupancy while also accounting for interspecific interaction in detection. Simulations demonstrated that the model can distinguish different mechanisms of environmental sorting, such as competition and spatial-autocorrelation. We applied our model to camera trap data from a fisher (Pekania pennanti)-marten (Martes americana) and coyote (Canis latrans)-fox (Vulpes vulpes) system in Apostle Island National Lakeshore (Wisconsin, USA). Model results indicated that the observed partitioning pattern between marten and fisher distributions could be explained best by a flipped mainland-island source-sink pattern rather than by competition. For the coyote-fox system, we determined that, in addition to a mainland-island source-sink pattern, there was a positive association between fox and coyote that deserved further study. Our model could be readily applied to other landscapes (island and non-island systems), enhancing our understanding of species coexistence patterns.


title: QTL mapping in an interspecific sorghum population uncovers candidate regulators of salinity tolerance

abstract: Salt stress impedes plant growth and disrupts normal metabolic processes, resulting in decreased biomass and increased leaf senescence. Therefore, the ability of a plant to maintain biomass when exposed to salinity stress is critical for the production of salt tolerant crops. To identify the genetic basis of salt tolerance in an agronomically important grain crop, we used a recombinant inbred line (RIL) population derived from an interspecific cross between domesticated Sorghum bicolor (inbred Tx7000) and a wild relative, Sorghum propinquum. A high-density genetic map was generated from 177 F3:5 RILs and covered the 10 Sorghum chromosomes with 1991 markers. The genetic map was used to identify 19 total QTL related to plant growth and overall health in optimal and saline conditions. Of these 19 QTL detected, 10 were specific to the salt stress response. The salt-responsive QTL contained numerous genes that have been previously shown to play a role in ionic tolerance, tissue tolerance, and osmotic tolerance, including many aquaporins.


title: Heterogenous susceptibility to R-pyocin killing in populations of Pseudomonas aeruginosa sourced from cystic fibrosis lungs

abstract:
Bacteriocins are proteinaceous antimicrobials produced by bacteria which are active against other strains of the same species. R-type pyocins are phage tail-like bacteriocins produced by Pseudomonas aeruginosa. Due to their anti-pseudomonal activity, R-pyocins have potential as therapeutics in infection. P. aeruginosa is a Gram-negative opportunistic pathogen and is particularly problematic for individuals with cystic fibrosis (CF). P. aeruginosa from CF lung infections develop increasing resistance to antibiotics, making new treatment approaches essential. P. aeruginosa populations become phenotypically and genotypically diverse during infection, however, little is known of the efficacy of R-pyocins against heterogeneous populations. R-pyocins vary by subtype (R1-R5), distinguished by binding to different residues on the lipopolysaccharide (LPS). Each type varies in killing spectrum, and each strain produces only one R-type. To evaluate the prevalence of different R-types, we screened P. aeruginosa strains from the International Pseudomonas Consortium Database (IPCD) and from our biobank of CF strains. We found that (i) R1-types were the most prevalent R-type among strains from respiratory sources; (ii) there is a large number of strains lacking R-pyocin genes, and (iii) isolates collected from the same patient have the same R-type. We then assessed the impact of intra-strain diversity on R-pyocin susceptibility and found a heterogenous response to R-pyocins within populations, likely due to differences in the LPS core. Our work reveals that heterogeneous populations of microbes exhibit variable susceptibility to R-pyocins and highlights that there is likely heterogeneity in response to other types of LPS-binding antimicrobials, including phage.

ImportanceR-pyocins have potential as alternative therapeutics against Pseudomonas aeruginosa in chronic infection, however little is known about the efficacy of R-pyocins in heterogeneous bacterial populations. P. aeruginosa is known to become resistant to multiple antibiotics, as well as evolve phenotypic and genotypic diversity over time; thus it is particularly difficult to eradicate in chronic cystic fibrosis (CF) lung infections. In this study, we found that P. aeruginosa populations from CF lungs maintain the same R-pyocin genotype but exhibit heterogeneity in susceptibility to R-pyocins from other strains. Our findings suggest there is likely heterogeneity in response to other types of LPS-binding antimicrobials, such as phage, highlighting the necessity of further studying the potential of LPS-binding antimicrobial particles as alternative therapies in chronic infections.


title: Sexual Reproduction in Bdelloid Rotifers

abstract: Bdelloid rotifers, common freshwater invertebrates of ancient origin and worldwide distribution have long been thought to be entirely asexual, being the principal exception to the view that in eukaryotes the loss of sex leads to early extinction. That bdelloids are facultatively sexual is shown by a study of allele sharing within a group of closely related bdelloids of the species Macrotrachella quadricornifera, making it likely that sexual reproduction is essential for long-term success in all eukaryotes.


title: Increased oscillatory power in a computational model of the olfactory bulb due to synaptic degeneration

abstract: Several neurodegenerative diseases impact the olfactory system, and in particular the olfactory bulb, early in disease progression. One mechanism by which damage occurs is via synaptic dysfunction. Here, we implement a computational model of the olfactory bulb and investigate the effect of weakened connection weights on network oscillatory behavior. Olfactory bulb network activity can be modeled by a system of equations that describes a set of coupled nonlinear oscillators. In this modeling framework, we propagate damage to synaptic weights using several strategies, varying from localized to global. Damage propagated in a dispersed or spreading manner leads to greater oscillatory power at moderate levels of damage. This increase arises from a higher average level of mitral cell activity due to a shift in the balance between excitation and inhibition. That this shift leads to greater oscillations critically depends on the nonlinearity of the activation function. Linearized analysis of the network dynamics predicts when this shift leads to loss of oscillatory activity. We thus demonstrate one potential mechanism involved in the increased gamma oscillations seen in some animal models of Alzheimers disease and highlight the potential that pathological olfactory bulb behavior presents as an early biomarker of disease.


title: Common synaptic phenotypes arising from diverse mutations in the human NMDA receptor subunit GluN2A

abstract: Dominant mutations in the human gene GRIN2A, encoding NMDA receptor (NMDAR) subunit GluN2A, make a significant and growing contribution to the catalogue of published single-gene epilepsies. Understanding the disease mechanism in these epilepsy patients is complicated by the surprising diversity of effects that the mutations have on NMDARs. We have examined the cell-autonomous effect of five GluN2A mutations, 3 loss-of-function and 2 gain-of-function, on evoked NMDAR-mediated synaptic currents (NMDA-EPSCs) in CA1 pyramidal neurons in cultured hippocampal slices. Despite the mutants differing in their functional incorporation at synapses, prolonged NMDA-EPSC current decays (with only marginal changes in charge transfer) were a common effect for both gain- and loss-of-function mutants. Modelling NMDA-EPSCs with mutant properties in a CA1 neuron revealed that the effect of GRIN2A mutations can lead to abnormal temporal integration and spine calcium dynamics during trains of concerted synaptic activity. Investigations beyond establishing the molecular defects of GluN2A mutants are much needed to understand their impact on synaptic transmission.


title: GwEEP - A comprehensive approach for genome-wide efficiency profiling of DNA modifying enzymes

abstract:
A precise understanding of DNA methylation dynamics on a genome wide scale is of great importance for the comprehensive investigation of a variety of biological processes such as reprogramming of somatic cells to iPSCs, cell differentiation and also cancer development. To date, a complex integration of multiple and distinct genome wide data sets is required to derive the global activity of DNA modifying enzymes. We present GwEEP - Genome-wide Epigenetic Efficiency Profiling as a versatile approach to infer dynamic efficiency changes of DNA modifying enzymes at base pair resolution on a genome wide scale. GwEEP relies on genome wide oxidative Hairpin Bisulfite sequencing (HPoxBS) data sets, which are translated by a sophisticated hidden Markov model into quantitative enzyme efficiencies with reported confidence around the estimates. GwEEP in its present form predicts de novo and maintenance methylation efficiencies of Dnmts, as well as the hydroxylation efficiency of Tets but its purposefully flexible design allows to capture further oxidation processes such as formylation and carboxylation given available data in the future. Applied to a well characterized ES cell model, GwEEP precisely predicts the complex epigenetic changes following a Serum-to-2i shift i.e., (i) instant reduction in maintenance efficiency (ii) gradually decreasing de novo methylation efficiency and (iii) increasing Tet efficiencies. In addition, a complementary analysis of Tet triple knock-out ES cells confirms the previous hypothesized mutual interference of Dnmts and Tets. GwEEP is applicable to a wide range of biological samples including cell lines, but also tissues and primary cell types.

MOTIVATIONDynamic changes of DNA methylation patterns are a common phenomenon in epigenetics. Although a stable DNA methylation profile is essential for cell identity, developmental processes require the rearrangement of 5-methylcytosine in the genome. Stable methylation patterns are the result of balanced Dnmts and Tets activities, while methylome transformation results from a coordinated change in Dnmt and Tet efficiencies. Such transformations occur on a global scale, for example during the reprogramming of maternal and paternal methylation patterns and the establishment of novel cell type specific methylomes during embryonic development in vivo, but also in vitro during (re)programming of induced pluripotent stem cells, as well as somatic cells. In addition, local (de)methylation events are key for gene regulation during cell differentiation. A detailed understanding of Dnmt and Tet cooperation is essential for understanding natural epigenetic adaptation as well as optimization of in vitro (re)programming protocols. For this purpose, we developed a pipeline for quantitative and precise estimation of Dnmt and Tet activity. Using only double strand methylation information, GwEEP infers accurate maintenance and de novo methylation efficiency of Dnmts, as well as hydroxylation efficiency of Tets at single base resolution. Thus, we believe GwEEP provides a powerful tool for the investigation of methylome rearrangements in various systems.


title: Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments

abstract: A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We first find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family-level. Pairs of more similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar-one organic acid). Second, a simple dominance rule emerges: sugars generally dominate organic acids. These findings may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict communities responses to dietary changes.


title: Confidence-controlled Hebbian learning efficiently extracts category membership from stimuli encoded in view of a categorization task

abstract: AO_SCPLOWBSTRACTC_SCPLOWIn experiments on perceptual decision-making, individuals learn a categorization task through trial-and-error protocols. We explore the capacity of a decision-making attractor network to learn a categorization task through reward-based, Hebbian type, modifications of the weights incoming from the stimulus encoding layer. For the latter, we assume a standard layer of a large number of stimulus specific neurons. Within the general framework of Hebbian learning, authors have hypothesized that the learning rate is modulated by the reward at each trial. Surprisingly, we find that, when the coding layer has been optimized in view of the categorization task, such reward-modulated Hebbian learning (RMHL) fails to extract efficiently the category membership. In a previous work we showed that the attractor neural networks nonlinear dynamics accounts for behavioral confidence in sequences of decision trials. Taking advantage of these findings, we propose that learning is controlled by confidence, as computed from the neural activity of the decision-making attractor network. Here we show that this confidence-controlled, reward-based, Hebbian learning efficiently extracts categorical information from the optimized coding layer. The proposed learning rule is local, and, in contrast to RMHL, does not require to store the average rewards obtained on previous trials. In addition, we find that the confidence-controlled learning rule achieves near optimal performance.


title: AtHDA15 attenuates COP1 via transcriptional quiescence, direct binding, and sub-compartmentalization during photomorphogenesis

abstract: Light is an essential environmental cue that determines the overall growth and development of plants. However, the molecular mechanisms underpinning the light signaling network are obscured by the epigenetic machinery where reversible acetylation and deacetylation play crucial roles in modulating light-regulated gene expression. In this paper, we demonstrate that HDA15 represses COP1, the master switch in the light signaling network, by deacetylation, protein interaction, and sub-compartmentalization. hda15 T-DNA mutant lines exhibited light hyposensitivity with significantly reduced HY5 and PIF3 transcript levels leading to long-hypocotyl phenotypes in the dark while its overexpression exhibited elevated HY5 transcripts and short hypocotyl phenotypes. In vivo and in vitro binding assays further show that HDA15 directly interacts with COP1 inside the nucleus modulating COP1s repressive activities. Crossing hda15-t27 with cop1-4 mutants resulted in short-hypocotyl and dwarfed phenotypes, reminiscent of cop1-4 mutants suggesting COP1 is epistatic to HDA15. Although light signals the nucleocytoplasmic shuttling of HDA15, the presence of COP1 triggers its nuclear localization. A working model is presented elucidating the concerted interplay between HDA15 and COP1 under light and dark conditions.


title: Cellular barcoding of protozoan pathogens reveals the within-host population dynamics of Toxoplasma gondii host colonization

abstract: Molecular barcoding techniques have emerged as powerful tools to understand microbial pathogenesis. However, barcoding strategies have not been extended to protozoan parasites, which have unique genomic structures and virulence strategies compared to viral and bacterial pathogens. Here, we present a versatile CRISPR-based method to barcode protozoa, which we successfully apply to Toxoplasma gondii and Trypanosoma brucei. The murine brain is an important transmission niche for T. gondii, and brain persistence is a clinically untreatable feature of infection. The blood-brain barrier is expected to physically restrict parasite colonization of this niche, resulting in a selection bottleneck. Using libraries of barcoded T. gondii we evaluate shifts in the population structure from acute to chronic infection of mice. Contrary to expectation, most barcodes were present in the brain one-month post-intraperitoneal infection in both inbred CBA/J and outbred Swiss mice. Although parasite cyst number and barcode diversity declined over time, barcodes that represented a minor fraction of the inoculum could become a dominant population in the brain by three months post-infection. Together, these data establish the first, robust molecular barcoding approach for protozoa and evidence that the blood-brain barrier does not represent a major bottleneck to colonization by T. gondii.


title: Memory Trace Imbalance in Reinforcement and Punishment Systems Can Reinforce Implicit Choices Leading to Obsessive-Compulsive Behavior

abstract: We may view most of our daily activities as rational action selections; however, we sometimes reinforce maladaptive behaviors despite having explicit environmental knowledge. In this study, we modeled obsessive-compulsive disorder (OCD) symptoms as implicitly learned maladaptive behaviors. Simulations in the reinforcement learning framework showed that agents implicitly learn to respond to intrusive thoughts when the memory trace signal for past actions decays differently for positive and negative prediction errors. Moreover, our model extends our understanding of therapeutic effects of behavioral therapy in OCD. Using empirical data, we confirmed that patients with OCD showed extremely imbalanced traces, which were normalized by serotonin enhancers. We found that healthy participants also varied in their obsessive-compulsive tendencies, consistent with the degree of imbalanced traces. These behavioral characteristics can be generalized to variations in the healthy population beyond the spectrum of clinical phenotypes.


title: Reliability assessment of temporal discounting measures in virtual reality environments

abstract: In recent years the emergence of high-performance virtual reality (VR) technology has opened up new possibilities for the examination of context effects in psychological studies. The opportunity to create ecologically valid stimulation in a highly controlled lab environment is especially relevant for studies of psychiatric disorders, where it can be problematic to confront participants with certain stimuli in real life. However, before VR can be confidently applied widely it is important to establish that commonly used behavioral tasks generate reliable data within a VR surrounding. One field of research that could benefit greatly from VR-applications are studies assessing the reactivity to addiction related cues (cue-reactivity) in participants suffering from gambling disorder. Here we tested the reliability of a commonly used temporal discounting task in a novel VR set-up designed for the concurrent assessment of behavioral and psychophysiological cue-reactivity in gambling disorder. On two days, thirty-four healthy non-gambling participants explored two rich and navigable VR-environments (neutral: cafe vs. gambling-related: casino and sports-betting facility), while their electrodermal activity was measured using remote sensors. In addition, participants completed the temporal discounting task implemented in each VR environment. On a third day, participants performed the task in a standard lab testing context. We then used comprehensive computational modeling using both standard softmax and drift diffusion model (DDM) choice rules to assess the reliability of discounting model parameters assessed in VR. Test-retest reliability estimates were good to excellent for the discount rate log(k), whereas they were poor to moderate for additional DDM parameters. Differences in model parameters between standard lab testing and VR, reflecting reactivity to the different environments, were mostly numerically small and of inconclusive directionality. Finally, while exposure to VR generally increased tonic skin conductance, this effect was not modulated by the neutral vs. gambling-related VR-environment. Taken together this proof-of- concept study in non-gambling participants demonstrates that temporal discounting measures obtained in VR are reliable, suggesting that VR is a promising tool for applications in computational psychiatry, including studies on cue-reactivity in addiction.


title: Egg size variation in a long-lived polyandrous shorebird in the context of senescence and breeding phenology

abstract:
Anisogamy is a central component of sex role evolution, however, the effect of female- female mating competition on egg size variation in polyandrous species is unclear. Moreover, egg size may also be shaped by age-dependent trade-offs between reproductive investments and somatic maintenance that are responsible for senescence. Here we investigate how mating behaviour and senescence are associated with egg size variation in female snowy plovers (Charadrius nivosus). Snowy plovers are long-lived shorebirds (longevity record: 20 years) that often produce several nests each year, with females either sequentially changing partners between breeding attempts or remaining monogamous between attempts. We examined how age, seasonality, body size, and mating behaviour relate to within- and between-female variation in egg volume using repeated measures collected over a 15-year period. We found no evidence of reproductive senescence in egg volume in snowy plover females. Rather, egg volume, polyandry, and re-nesting were strongly linked to breeding phenology: early breeding females had a higher likelihood of being polyandrous or replacing failed clutches, yet these individuals laid smaller eggs likely due to physiological limitations associated with the early season. Older individuals and local recruits secured the earliest breeding opportunities in the season suggesting that prior experience could give an edge in the female-female competition for mates. Larger females laid the largest eggs, as expected, but there was no relationship between body size and lay date - implying that size may not provide an advantage in female-female competition. Our findings highlight the existence of several direct and indirect constraints on female reproductive investment that likely shape individual variation in lifetime reproductive success. Future research investigating reproductive senescence of wild populations should consider mating system dynamics when examining variation in reproductive investment.

Impact SummaryThe divergent gamete sizes of males and females (anisogamy) is a key principle for sex role evolution, however, it remains unclear whether and how egg size variation is shaped by female-female competition in species with reversed sex roles. Furthermore, polygamy is typically associated with age such that egg size variation may also be shaped by age- dependent processes including senescence. Here, we use a 15-year longitudinal mark- recapture dataset of a wild subtropical population of snowy plovers (Charadrius nivosus) breeding in western Mexico to investigate how mating behaviour and senescence are associated with egg size variation. The snowy plover is a long-lived shorebird characterized by a flexible polyandrous mating system. This rare breeding behaviour represents a unique background for investigating senescence in light of individual variation in reproductive investment. We found no evidence of reproductive senescence in egg volume or polyandry. Instead, egg volume and polyandry were strongly linked to the seasonal timing of breeding: early nesting females had a higher likelihood of being polyandrous but laid smaller eggs. Early nesters also had a higher probability of laying a replacement clutch following breeding failure. Taken together, this suggests that females are driven to initiate laying as early as possible despite the cost this has on egg size of their early season clutches. Furthermore, older individuals and local recruits secured the earliest breeding opportunities in the season indicating that prior experience gave individuals an advantage in the competition for mates. Larger females laid the largest eggs, as expected, but there was no relationship between body size and lay date - implying that size is not an important factor in female-female competition. We conclude that individual female reproductive performance is regulated by flexible mating behaviour (i.e., monogamy or polyandry), age- and season-dependent effects, and prior local experience.


title: Individual human genomes frequently contain variants that have evolutionary couplings

abstract: Coevolution has been widely studied between species and has an important role in our understanding of biological function. For proteins there has recently been interest in the identification of positions within proteins that have coevolved including their use for modelling protein structure. Such studies focus on the identification of coevolving positions (or evolutionary couplings) within multiple sequence alignments of proteins from many species. Here, we exploit large human genome resources to investigate if it is possible to use genetic variation data from a single species, human, to identify positions within proteins that have coevolved. We combine the 1000 genome project genetic variation data with protein structural data to identify variant-variant interactions within individual human genomes. We find >4,000 combinations of variants that are located close in 3D protein structure and >1,200 in protein-protein interfaces. Many variant combinations include compensatory amino acid changes (e.g. maintaining charge/functional groups), thus supporting that these are coevolutionary events. Our study highlights that it is possible to identify coevolution within a single species. Given the important role that genetic variation plays in causing disease it is important for variant interpretation and precision medicine to consider the gestalt effects of variants rather than individual variants in isolation.

category: genetics


title: Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for sparse genomic measures and its application to tumor mutational burden

abstract: Deep learning has the ability to extract meaningful features from data given enough training examples. Large scale genomic data are well suited for this class of machine learning algorithms; however, for many of these data the labels are at the level of the sample instead of at the level of the individual genomic measures and features. To leverage the power of deep learning for these types of data we turn to a multiple instance learning framework, and present an easily extensible tool built with TensorFlow and Keras. We show how this tool can be applied to somatic variants (featurizing genomic position, sequence context, and read counts) on a range of artificial tasks (classification, regression, Cox regression). In addition, we confirm the model can achieve high performance on real-world problems, accurately classifying samples according to whether they contain a specific variant (hotspot or tumor suppressor), groups of variants (tumor clonality), or a type of variant (microsatellite instability). Our results suggest this framework will lead to improvements on sample-level tasks that require aggregation of a set of genomic measures.

category: bioinformatics


title: Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for sparse genomic measures


title: The Pancreatic Tumor Microenvironment Compensates for Loss of GOT2

abstract: The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDA) restricts vascularization and, consequently, access to blood-derived nutrients and oxygen, which impacts tumor growth. Intracellular redox imbalance is another restraint on cellular proliferation, yet it is unknown if the TME contributes to the maintenance of redox homeostasis in PDA cells. Here, we demonstrate that the loss of mitochondrial glutamate-oxaloacetate transaminase 2 (GOT2), a component in the malate-aspartate shuttle, disturbs redox homeostasis and halts proliferation of PDA cells in vitro. In contrast, GOT2 inhibition has no effect on in vivo tumor growth or tumorigenesis in an autochthonous model. We propose that this discrepancy is explained by heterocellular pyruvate exchange from the TME, including from cancer associated fibroblasts. More broadly, pyruvate similarly confers resistance to inhibitors of mitochondrial respiration. Genetic or pharmacologic inhibition of pyruvate uptake or metabolism abrogated pyruvate-mediated alleviation of reductive stress from NADH buildup. In sum, this work describes a potential resistance mechanism mediated by metabolic crosstalk within the pancreatic TME. These findings have important implications for metabolic treatment strategies since several mitochondrial inhibitors are currently in clinical trials for PDA and other cancers.

category: cancer biology


title: Prophylactic efficacy of riluzole against anxiety- and depressive-like behaviors in two rodent stress models

abstract:
BackgroundChronic stress-related illnesses, such as major depressive disorder and post-traumatic stress disorder share symptomatology, including anxiety, anhedonia, and helplessness. Across disorders, neurotoxic dysregulated glutamate (Glu) signaling may underlie symptom emergence. Current first-line antidepressant drugs, which do not directly target Glu signaling, fail to provide adequate benefit for many patients and are associated with high relapse rates. Riluzole modulates glutamatergic neurotransmission by increasing metabolic cycling and modulating signal transduction. Clinical studies exploring riluzoles efficacy in stress-related disorders have provided varied results. However, the utility of riluzole for treating specific symptom dimensions or as a prophylactic treatment has not been comprehensively assessed.

MethodsWe investigated whether chronic prophylactic riluzole ([~]12-15/kg/day p.o.) could prevent the emergence of behavioural deficits induced by unpredictable chronic mild stress (UCMS) in mice. We assessed: i) anxiety-like behaviour using the elevated-plus maze, open field test, and novelty-suppressed feeding, ii) mixed anxiety/anhedonia-like behaviour in the novelty-induced hypophagia test and, iii) anhedonia-like behaviour using the sucrose consumption test. Z-scoring summarized changes across tests measuring similar dimensions. In a separate learned helplessness (LH) cohort, we investigated whether chronic prophylactic riluzole treatment could block the development of helplessness-like behaviour.

ResultsUCMS induced an elevation in anxiety-, anhedonia-like behaviour, and overall behavioural emotionality that was blocked by prophylactic riluzole. In the LH cohort, prophylactic riluzole blocked the development of helplessness-like behaviour.

ConclusionThis study supports the utility of riluzole as a prophylactic medication for preventing anhedonia, anxiety, and helplessness symptoms associated with stress-related disorders.

category: pharmacology and toxicology


title: Septins and a formin have distinct functions in anaphase chiral cortical rotation in the C. eleganszygote.

abstract: Many cells and tissues exhibit chirality that stems from the chirality of proteins and polymers. In the C. elegans zygote actomyosin contractility drives chiral rotation of the entire cortex circumferentially around the division plane during anaphase. How contractility is translated to cell-scale chirality, and what dictates handedness, are unknown. Septins are candidate contributors to cell-scale chirality because they anchor and crosslink the actomyosin cytoskeleton. We report that septins are required for anaphase cortical rotation. In contrast, the formin CYK-1, which we found to be enriched in the posterior in early anaphase, is not required for cortical rotation, but contributes to its chirality. Simultaneous loss of septin and CYK-1 function led to abnormal and often reversed cortical rotation. Our results suggest that anaphase contractility leads to chiral rotation by releasing torsional stress generated during formin-based polymerization, which is polarized along the cell anterior-posterior axis, and which accumulates due to actomyosin network connectivity. Our findings shed light on the molecular and physical bases for cellular chirality in the C. elegans zygote. We also identify conditions in which chiral rotation fails but animals are developmentally viable, opening avenues for future work on the relationship between early embryonic cellular chirality and animal body plan.


title: Contemporary and historical selection in Tasmanian devils (Sarcophilus harrisii) support novel, polygenic response to transmissible cancer

abstract: Tasmanian devils (Sarcophilus harrisii) are evolving in response to a unique transmissible cancer, devil facial tumour disease (DFTD), first described in 1996. Persistence of wild populations and the recent emergence of a second independently evolved transmissible cancer suggest that transmissible cancers may be a recurrent feature in devils. Here we compared signatures of selection across temporal scales to determine whether genes or gene pathways under contemporary selection (6-8 generations) have also been subject to historical selection (65-85 million years), and test for recurrent selection in devils. First, we used a targeted sequencing approach, RAD-capture, to identify genomic regions subject to rapid evolution in approximately 2,500 devils in six populations as DFTD spread across the species range. We documented genome-wide contemporary evolution, including 186 candidate genes related to cell cycling and immune response. Then we used a molecular evolution approach to identify historical positive selection in devils compared to other marsupials and found evidence of selection in 1,773 genes. However, we found limited overlap across time scales, with historical selection detected in only 16 contemporary candidate genes, and no overlap in enriched functional gene sets. Our results are consistent with a novel, multi-locus evolutionary response of devils to DFTD. Our results can inform management actions to conserve adaptive potential of devils by identifying high priority targets for genetic monitoring and maintenance of functional diversity in managed populations.


title: Raven: a de novo genome assembler for long reads

abstract: We present new methods for the improvement of de novo genome assembly from erroneous long-reads incorporated into a straightforward tool called Raven (https://github.com/lbcb-sci/raven). Raven maintains similar performance for various genomes and has accuracy on par with other assemblers which support third-generation sequencing data. It is one of the fastest options while having the lowest memory consumption on the majority of benchmarked datasets.


title: Ig-VAE: Generative Modeling of Immunoglobulin Proteins by Direct 3D Coordinate Generation

abstract: AO_SCPLOWBSTRACTC_SCPLOWWhile deep learning models have seen increasing applications in protein science, few have been implemented for protein backbone generation--an important task in structure-based problems such as active site and interface design. We present a new approach to building class-specific backbones, using a variational auto-encoder to directly generate the 3D coordinates of immunoglobulins. Our model is torsion- and distance-aware, learns a high-resolution embedding of the dataset, and generates novel, high-quality structures compatible with existing design tools. We show that the Ig-VAE can be used to create a computational model of a SARS-CoV2-RBD binder via latent space sampling. We further demonstrate that the models generative prior is a powerful tool for guiding computational protein design, motivating a new paradigm under which backbone design is solved as constrained optimization problem in the latent space of a generative model.


title: Regulatory signatures of drought response in stress resilient Sorghum bicolor

abstract: The effects of drought stress can be devastating to crop production worldwide. A grand challenge facing agriculture is development of crop varieties with improved drought resilience through breeding or biotechnology. To accelerate this, a mechanistic understanding is needed of the regulatory networks underlying drought response in crop genomes and the genetic elements that modulate them. Here, we explore the regulatory landscape of sorghum [Sorghum bicolor (L.) Moench] in response to controlled-environment drought stress. Sorghum is a C4 cereal crop with innate drought resilience. To define molecular signatures of drought response, we mapped genome-wide chromatin accessibility using an Assay for Transposase Accessible Chromatin by sequencing and analyzed parallel transcriptional profiles in drought-stressed sorghum shoot and root tissues. Drought-responsive changes in accessibility were largely in proximal promoters of differentially expressed genes and also in distal regions. Data were integrated to infer gene network connections and cis-regulatory modules underlying drought response and the transcription factors that control them. Inspection of pan-genomic data and phenotyping across sorghum diversity revealed variation in genomic signatures that associated with water use efficiency. Our analyses provide drought-inducible regulatory modules in sorghum that can be leveraged for fine-tuning responses to stress, mining for advantageous alleles, and translating across species.


title: Comparison of polygenic risk scores for heart disease highlights obstacles to overcome for clinical use

abstract: Polygenic risk scores, or PRS, are a tool to estimate individuals liabilities to a disease or trait measurement based solely on genetic information. One commonly discussed potential use is in the clinic to identify people who are at greater risk of developing a disease. In this paper, we investigate the suitability of three large PRS for coronary artery disease (CAD) for clinical use. In the UK Biobank, the cohort which was used in the creation of each score, we calculated the association between CAD, the scores, and population structure for the white British subset. After adjustment for geographic and socioeconomic factors, CAD was not associated with population structure; however all three scores were confounded by genetic ancestry, raising questions about how these biases would impact clinical application. Furthermore, we investigated the differences in risk stratification using four different UK Biobank assessment centers as separate cohorts and tested how missing genetic data affected risk stratification through simulation and comparisons to scores calculated in French Canadians. We show that missing data impact classification for extreme individuals for high- and low-risk, and quantiles of risk is sensitive to individual-level genotype missingness. Distributions of scores varied between assessment centers, revealing that thresholding based on quantiles can be problematic for consistency across centers and populations. We highlight three criteria that a genetic risk score must fulfill in order to be used to stratify patients in the clinic: 1) it must be robust to population structure 2) scores must provide absolute thresholds for risk levels, and 3) there must be an approach to compensate for missing genetic data. Finally, we propose potential avenues of improvements for determining individuals genetic liability to a complex trait such as CAD.