bluuebunny/crossref_metadata_2025 huggingface dataset:
Fezf2transient expression via modRNA with concurrent SIRT1 inhibition enhances differentiation of cortical subcerebral / corticospinal neuron identity from mES cells
Authors: Sadegh Cameron , Ebina Wataru , Arvanites Anthony C. , Davidow Lance S. , Rubin Lee L. , Macklis Jeffrey D.
Published: August 2020

During late embryonic development of the cerebral cortex, the major class of cortical output neurons termed subcerebral projection neurons (SCPN; including the predominant population of corticospinal neurons, CSN) and the class of interhemispheric callosal projection neurons (CPN) initially express overlapping molecular controls that later undergo subtype-specific refinements. Such molecular refinements are largely absent in heterogeneous, maturation-stalled, neocortical-like neurons (termed “cortical” here) spontaneously generated by established embryonic stem cell (ES) and induced pluripotent stem cell (iPSC) differentiation. Building on recently identified central molecular controls over SCPN development, we used a combination of synthetic modified mRNA (modRNA) forFezf2, the central transcription factor controlling SCPN specification, and small molecule screening to investigate whether distinct chromatin modifiers might complementFezf2functions to promote SCPN-specific differentiation by mouse ES (mES)-derived cortical-like neurons. We find that the inhibition of a specific histone deacetylase, Sirtuin 1 (SIRT1), enhances refinement of SCPN subtype molecular identity by both mES-derived cortical-like neurons and primary dissociated E12.5 mouse cortical neurons.In vivo, we identify that SIRT1 is specifically expressed by CPN, but not SCPN, during late embryonic and postnatal differentiation. Together, these data indicate that SIRT1 has neuronal subtype-specific expression in the mouse cortexin vivo, and its inhibition enhances subtype-specific differentiation of highly clinically relevant SCPN / CSN cortical neuronsin vitro.
A Wnt-specific astacin proteinase controls head formation inHydra
Authors: Ziegler Berenice , Yiallouros Irene , Trageser Benjamin , Kumar Sumit , Mercker Moritz , Kling Svenja , Fath Maike , Warnken Uwe , Schnölzer Martina , Holstein Thomas W. , Hartl Markus , Marciniak-Czochra Anna , Stetefeld Jörg , Stöcker Walter , Özbek Suat
Published: August 2020

TheHydrahead organizer acts as a signaling center that initiates and maintains the primary body axis in steady state polyps and during budding or regeneration. Wnt/beta-Catenin signaling functions as a primary cue controlling this process, but how Wnt ligand activity is locally restricted at the protein level is poorly understood.

Here we report the identification of an astacin family proteinase as a Wnt processing factor.Hydraastacin-7 (HAS-7) is expressed from gland cells as an apical-distal gradient in the body column, peaking close beneath the tentacle zone.HAS-7siRNA knockdown abrogates HyWnt3 proteolysis in the head tissue and induces a robust double axis phenotype, which is rescued by simultaneousHyWnt3knockdown. Accordingly, double axes are also observed in conditions of increased Wnt levels as in transgenic actin::HyWnt3 and HyDkk1/2/4 siRNA treated animals.HyWnt3-induced double axes inXenopusembryos could be rescued by co-injection ofHAS-7mRNA. Mathematical modelling combined with experimental promotor analysis indicate an indirect regulation ofHAS-7by beta-Catenin, expanding the classical Turing-type activator-inhibitor model.

Our data suggest a negative regulatory function of Wnt processing astacin proteinases in the global patterning of the oral-aboral axis inHydra.
Metaviromic identification of genetic hotspots of coronavirus pathogenicity using machine learning
Authors: Park Jonathan J. , Chen Sidi
Published: August 2020

The COVID-19 pandemic caused by SARS-CoV-2 has become a major threat across the globe. Here, we developed machine learning approaches to identify key pathogenic regions in coronavirus genomes. We trained and evaluated 7,562,625 models on 3,665 genomes including SARS-CoV-2, MERS-CoV, SARS-CoV and other coronaviruses of human and animal origins to return quantitative and biologically interpretable signatures at nucleotide and amino acid resolutions. We identified hotspots across the SARS-CoV-2 genome including previously unappreciated features in spike, RdRp and other proteins. Finally, we integrated pathogenicity genomic profiles with B cell and T cell epitope predictions for enrichment of sequence targets to help guide vaccine development. These results provide a systematic map of predicted pathogenicity in SARS-CoV-2 that incorporates sequence, structural and immunological features, providing an unbiased collection of genetic elements for functional studies. This metavirome-based framework can also be applied for rapid characterization of new coronavirus strains or emerging pathogenic viruses.
Forage stoichiometry predicts the home range size of a small terrestrial herbivore
Authors: Rizzuto Matteo , Leroux Shawn J. , Vander Wal Eric , Richmond Isabella C. , Heckford Travis R. , Balluffi-Fry Juliana , Wiersma Yolanda F.
Published: August 2020

Consumers make space use decisions based on resource quality. Most studies that investigate the influence of resource quality on the spatial ecology of consumers use diverse proxies for quality including measures based on habitat classification, forage species diversity and abundance, and nutritional indicators, e.g., protein. Ecological stoichiometry measures resource quality in terms of elemental ratios, e.g., carbon (C):nitrogen (N) ratio, but rarely have these currencies been used to study consumer space use decisions. Yet, elemental ratios provide a uniquely quantitative way to assess resource quality. Consequently, ecological stoichiometry allows for investigation of how consumers respond to spatial heterogeneity in resource quality by changing their space use, e.g. their home range size, and how this may influence ecosystem dynamics and trophic interactions. Here, we test whether the home range size of a keystone boreal herbivore, the snowshoe hare (Lepus americanus), varies with differences in the C:N, C:phosphorus (P), and N:P ratios of two preferred forage species, lowland blueberry (Vaccinium angustifolium) and red maple (Acer rubrum). We consider forage resources with higher C content relative to N and P to be lower quality than resources with lower relative C content. We use a novel approach, combining elemental distribution models with herbivore home range size estimates to test our hypothesis that hare home range size will be smaller in areas with access to high, homogeneous resource quality compared to areas with access to low, heterogeneous resource quality during summer months. Our results support our prediction for lowland blueberry, but not for red maple. Herbivore home range size decreased with increasing blueberry foliage quality, but also with decreasing spatial heterogeneity in blueberry foliage quality, i.e. N or P content. Herbivores in the boreal forest face strong nutritional constraints due to the paucity of N and P. Access to areas of high, homogeneous resource quality is paramount to meeting their dietary requirements with low effort. In turn, this may influence community (e.g., trophic interactions) and ecosystem (e.g., nutrient cycling) processes. Paradoxically, our study shows that taking a reductionist approach of viewing resources through a biochemical lens can lead to holistic insights of consumer spatial ecology.
Functional shifts of soil microbial communities associated withAlliaria petiolatainvasion
Authors: Duchesneau Katherine , Golemiec Anneke , Colautti Robert I. , Antunes Pedro M.
Published: August 2020

Soil feedback is thought to be an important contributor to the success of invasive plants. Despite evidence that invasive plants change soil microbial diversity, the functional roles of microbes impacted by invasion are still unclear. This knowledge is a critical component of our understanding of ecological mechanisms of plant invasion. Mounting evidence suggestsAlliaria petiolatacan suppress arbuscular mycorrhizal fungi (AMF) to disrupt native plant communities in controlled laboratory and greenhouse experiments, though it is less clear if allelochemicals persist under natural field conditions. Alternatively, invasive plants may accumulate pathogens that are more harmful to competitors as predicted by the Enemy of my Enemy Hypothesis (EEH). We examined changes in functional groups of soil bacteria and fungi associated with ten naturally occurring populations ofA. petiolatausing amplicon sequences (16S and ITS rRNA). To relate soil microbial communities to impacts on co-occurring plants, we measured root infections and AMF colonization. We found no changes in the diversity and abundance of AMF in plants co-occurring withA. petiolata, suggesting that mycorrhizal suppression in the field may not be as critical to the invasion ofA. petiolataas implied by more controlled experiments. Instead, we found changes in pathogen community composition and marginal evidence of increase in root lesions of plants growing withA. petiolata, lending support to the EEH. In addition to these impacts on plant health, changes in ectomycorrhiza, and other nutrient cycling microbes may be important forces underlying the invasion ofA. petiolataand its impact on ecosystem function.
Suv39h-catalysed H3K9me3 is critical for euchromatic genome organisation and the maintenance of gene transcription
Authors: Keenan Christine R. , Coughlan Hannah D. , Iannarella Nadia , Johanson Timothy M. , Chan Wing Fuk , Garnham Alexandra L. , Smyth Gordon K. , Allan Rhys S.
Published: August 2020

H3K9me3-dependent heterochromatin is critical for the silencing of repeat-rich pericentromeric regions and also has key roles in repressing lineage-inappropriate protein-coding genes in differentiation and development. Here, we investigate the molecular consequences of heterochromatin loss in cells deficient in both Suv39h1 and Suv39h2 (Suv39DKO), the major mammalian histone methyltransferase enzymes that catalyse heterochromatic H3K9me3 deposition. Unexpectedly, we reveal a predominant repression of protein-coding genes in Suv39DKO cells, with these differentially expressed genes principally in euchromatic (DNaseI-accessible, H3K27ac-marked) rather than heterochromatic (H3K9me3-marked) regions. Examination of the 3D nucleome reveals that transcriptomic dysregulation occurs in euchromatic regions close to the nuclear periphery in 3-dimensional space. Moreover, this transcriptomic dysregulation is highly correlated with altered 3-dimensional genome organization in Suv39DKO cells. Together, our results suggest that the nuclear lamina-tethering of Suv39-dependent H3K9me3 domains provides an essential scaffold to support euchromatic genome organisation and the maintenance of gene transcription for healthy cellular function.
circHiC: circular visualization of Hi-C data and integration of genomic data
Authors: Junier Ivan , Varoquaux Nelle
Published: August 2020

Genome wide contact frequencies obtained using Hi-C-like experiments have raised novel challenges in terms of visualization and rationalization of chromosome structuring phenomena. In bacteria, display of Hi-C data should be congruent with the circularity of chromosomes. However, standard representations under the form of square matrices or horizontal bands are not adapted to periodic conditions as those imposed by (most) bacterial chromosomes. Here, we fill this gap and propose a Python library, built upon the widely used Matplotlib library, to display Hi-C data in circular strips, together with the possibility to overlay genomic data. The proposed tools are light and fast, aiming to facilitate the exploration and understanding of bacterial chromosome structuring data. The library further includes the possibility to handle linear chromosomes, providing a fresh way to display and explore eukaryotic data.

Availability and implementation

The package runs under Python 3 and is freely available at https://github.com/TrEE-TIMC/circHiC. The documentation can be found at https://tree-timc.github.io/circhic/; images obtained in different organisms are provided in the gallery section and are accompanied with codes.

Contact

ivan.junier@univ-grenoble-alpes.fr, nelle.varoquaux@univ-grenoble-alpes.fr
Differing effects of size and lifestyle on bone structure in mammals
Authors: Amson Eli , Bibi Faysal
Published: August 2020

The skeleton is involved in most aspects of vertebrate life history. Previous macroevolutionary analyses have shown that structural, historical, and functional factors influence the gross morphology of bone. The inner structure of bone has, however, received comparatively little attention. Here we address this gap in our understanding of vertebrate evolution by quantifying bone structure in appendicular and axial elements (humerus and mid-lumbar vertebra) across therian mammals (placentals + marsupials). Our sampling captures all transitions to aerial, fully aquatic, and subterranean lifestyles in extant mammal clades. We found that mammalian inner bone structure is highly disparate. We show that vertebral structure mostly correlates with body size, but not lifestyle, while the opposite is true for humeral structure. The latter also shows a high degree of convergence among the clades that have acquired specialised lifestyles. Our results suggest that radically different extrinsic constraints can apply to bone structure in different skeletal elements.
IP3R activity increases frequency of RyR-mediated sparks by elevating dyadic Ca2+
Authors: Chung Joshua , Tilūnaitė Agnė , Ladd David , Hunt Hilary , Soeller Christian , Crampin Edmund J. , Johnston Stuart , Roderick H. Llewelyn , Rajagopal Vijay
Published: August 2020

Calcium (Ca2+) plays a critical role in the excitation contraction coupling (ECC) process that governs the contraction of cardiomyocytes during each heartbeat. While ryanodine receptors (RyRs) are the primary Ca2+channels responsible for mediating cell-wide Ca2+transients during ECC, Ca2+release via inositol 1,4,5-trisphosphate (IP3) receptors (IP3Rs) have been reported to elicit ECC-modulating effects. Recent studies suggest that the proximal localization of IP3Rs at dyads grants their ability to modify the occurrence of Ca2+sparks (elementary Ca2+release events that constitute ECC-associated Ca2+transients) which may underlie the modulatory effects on ECC. Here, we aim to uncover the mechanism by which IP3Rs affect Ca2+spark dynamics. To this end, we developed a mathematical model of the dyad that incorporates IP3Rs to reveal their impact on local Ca2+handling and corresponding Ca2+spark formation. Consistent with published experimental data, our model predicts that the propensity for Ca2+spark formation increases with IP3R activity. Our simulations support the hypothesis that IP3R activity elevates Ca2+within the dyad, sensitizing proximal RyRs for future release. However, this lowers Ca2+in the JSR available for release and thus results in Ca2+sparks with the same duration but lower amplitudes.
Why did the animal turn? Time-varying step selection analysis for inference between observed turning points in high frequency data
Authors: Munden Rhys , Börger Luca , Wilson Rory P. , Redcliffe James , Brown Rowan , Garel Mathieu , Potts Jonathan R.
Published: August 2020

Step selection analysis (SSA) is a fundamental technique for uncovering the drivers of animal movement decisions. Its typical use has been to view an animal as “selecting” each measured location, given its current (and possibly previous) locations. Although an animal is unlikely to make decisions precisely at the times its locations are measured, if data are gathered at a relatively low frequency (every few minutes or hours) this is often the best that can be done. Nowadays, though, tracking data is increasingly gathered at very high frequencies, often ≥1Hz, so it may be possible to exploit these data to perform more behaviourally-meaningful step selection analysis.

Here, we present a technique to do this. We first use an existing algorithm to determine the turning-points in an animal’s movement path. We define a “step” to be a straight-line movement between successive turning-points. We then construct a generalised version of integrated SSA (iSSA), calledtime-varying iSSA(tiSSA), which deals with the fact that turning-points are usually irregularly spaced in time. We demonstrate the efficacy of tiSSA by application to data on both simulated animals and free-ranging goats (Capra aegagrus hircus), comparing our results to those of regular iSSA with locations that are separated by a constant time-interval.

Using (regular) iSSA with constant time-steps can give results that are misleading compared to using tiSSA with the actual turns made by the animals. Furthermore, tiSSA can be used to infer covariates that are dependent on the time between turns, which is not possible with regular iSSA. As an example, we show that our study animals tend to spend less time between successive turns when the ground is rockier and/or the temperature is hotter.

By constructing a step selection technique that works between observed turning-points of animals, we enable step selection to be used on high-frequency movement data, which are becoming increasingly prevalent in modern biologging studies. Furthermore, since turning-points can be viewed as decisions, our method places step selection analysis on a more behaviourally-meaningful footing compared to previous techniques.
A lateralised design for the interaction of visual memories and heading representations in navigating ants
Authors: Wystrach Antoine , Le Moël Florent , Clement Leo , Schwarz Sebastian
Published: August 2020

The navigational skills of ants, bees and wasps represent one of the most baffling examples of the powers of minuscule brains. Insects store long-term memories of the visual scenes they experience1, and they use compass cues to build a robust representation of directions2,3. We know reasonably well how long-term memories are formed, in a brain area called the Mushroom Bodies (MB)4–8, as well as how heading representations are formed in another brain area called the Central Complex (CX)9–12. However, how such memories and heading representations interact to produce powerful navigational behaviours remains unclear7,13,14. Here we combine behavioural experiments with computational modelling that is strictly based on connectomic data to provide a new perspective on how navigation might be orchestrated in these insects. Our results reveal a lateralised design, where signals about whether to turn left or right are segregated in the left and right hemispheres, respectively. Furthermore, we show that guidance is a two-stage process: the recognition of visual memories – presumably in the MBs – does not directly drive the motor command, but instead updates a “desired heading” – presumably in the CX – which in turn is used to control guidance using celestial compass information. Overall, this circuit enables ants to recognise views independently of their body orientation, and combines terrestrial and celestial cues in a way that produces exceptionally robust navigation.
A Patient-based Model to Investigate the Effect of Micro-structure Scars on the Optogenetic Defibrillation Success: A Computational Modelling Approach
Authors: Zafarghandi Elham Zakeri , Bahrami Fariba
Published: August 2020

This study investigates the role of the microstructure of real scars in the success of optogenetic defibrillation. To reduce the computational cost of high-order models (like Ten Tusscher Model, TTM) for a single cell as well as to take advantage of their ability to generate a more realistic output, we developed a low-order model of optogenetic cardiac tissue based on the modified Alieve-Panfilov single-cell model and estimated its parameters using a TTM. Two-dimensional electrophysiological cardiac tissue models were produced including different scar shapes that were extracted from Late Gadolinium-Enhanced (LGE) magnetic resonance imaging data set of 10 patients with non-ischemic dilated cardiomyopathy. The scar shapes were classified based on four criteria: transmurality, relative area, scar entropy, and interface length. Scar with the highest 25% of the relative area showed 25% of successful cases, this ratio is 27%, and 25% for a scar with the most top 25% of entropy, and transmurality, respectively. In comparison, the proportions are 61.54%, 44.44%, and 61.76%, for the lowest 25% of the area, entropy, and transmurality. We also investigated the efficacy of various methods for light-sensitive cells’ distribution within the cardiac tissue with scar. Four types of distributions were defined. Defibrillation within tissues with 0.1 light-sensitive out of all cells was 15 to 25% more successful than their counterparts with 0.05 light-sensitive cells. Lastly, we examined the effect of an earlier stimulation on the success probability of defibrillation. Our results indicated that inducing 0.5 msec earlier resulted in a roughly 15% rise in successful cases.
Maternal high fat diet alters lactation-specific miRNA expression and programs the DNA methylome in the amygdala of female offspring
Authors: Abuaish Sameera , Wijenayake Sanoji , de Vega Wilfred C. , Lum Christine M.W. , Sasaki Aya , McGowan Patrick O.
Published: August 2020

Adverse maternal diets high in saturated fats are associated with impaired neurodevelopment and epigenetic modifications in offspring. Maternal milk, the primary source of early life nutrition in mammals, contains lactation-specific microRNAs (miRNAs). Lactation-specific miRNAs have been found in various offspring tissues in early life, including the brain. We examined the effects of maternal high saturated fat diet (mHFD) on lactation-specific miRNAs that inhibit DNA methyltransferases (DNMTs), enzymes that catalyze DNA methylation modifications, in the amygdala of female offspring during early life and adulthood. Offspring exposed to mHFD showed reduced miR-148/152 and miR-21 transcripts in stomach milk and amygdala in the first week of life. This was associated with increased DNMT1 expression, DNMT activity, and global DNA methylation in the amygdala. In addition, persistent DNA methylation modifications from early life to adulthood were observed in pathways involved in neurodevelopment as well as genes regulating the DNMT machinery and protein function in mHFD offspring. The findings indicate a novel link between exogenous, lactation-specific miRNAs and developmental programming of the neural DNA methylome in offspring.
A Statistical Framework for QTL Hotspot Detection
Authors: Wu Po-Ya , Yang Man-Hsia , Kao Chen-Hung
Published: August 2020

Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These detection methods attempt to address some of the concerns, including the correlation structure among traits, the magnitude of LOD scores within a hotspot and computational cost, that arise during the process of QTL hotspot detection. In this article, we describe a statistical framework that can handle both types of data as well as address all the concerns at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computation cost, and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,αprofile, are introduced into the framework. The trait grouping attempts to group the closely linked or pleiotropic traits together to take care of the true linkages and cope with the underestimation of hotspot thresholds due to non-genetic correlations (arising from ignoring the correlation structure among traits), so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,αprofile is designed to outline the LOD-score pattern of a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD score distributions. Real examples, numerical analysis and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.
Inhibitory control and the structural parcellation of the right inferior frontal gyrus
Authors: Boen Rune , Raud Liisa , Huster Rene J.
Published: August 2020

The right inferior frontal gyrus (rIFG) has most strongly, although not exclusively, been associated with response inhibition, not least based on covariations of behavioral performance measures and local grey matter characteristics. However, the white matter microstructure of the rIFG as well as its connectivity has been less in focus, especially when it comes to the consideration of potential subdivisions within this area. The present study reconstructed the structural connections of the three main subregions of the rIFG (i.e. pars opercularis, pars triangularis and pars orbitalis) using diffusion tensor imaging, and further assessed their associations with behavioral measures of inhibitory control. The results revealed a marked heterogeneity of the three subregions with respect to the pattern and extent of their connections, with the pars orbitalis showing the most widespread inter-regional connectivity, while the pars opercularis showed the least amount of connections. When relating behavioral performance measures of a stop signal task to brain structure, the data indicated a differential association of dorsal and ventral opercular connectivity with the go reaction time and the stopping accuracy, respectively.
Microbiota in milk from healthy and mastitis cows varies greatly in diversity, species richness and composition, as revealed by PacBio sequencing
Authors: Ma Teng , Shen Lingling , Wen Qiannan , lv Ruirui , Hou Qiangchuan , Kwok Lai Yu , Sun Zhihong , Zhang Heping
Published: August 2020

Mastitis is the most economically important disease of dairy cows. This study used PacBio single-molecule real-time sequencing technology to sequence the full-length of the l6S rRNA from the microbiota in 27 milk samples (18 from mastitis and 9 from healthy cows; the cows were at different stages of lactation). We observed that healthy or late stage milk microbiota had significantly higher microbial diversity and richness. The community composition of the microbiota from different groups also varied greatly. In milk from healthy cows the microbiota was predominantly comprised ofLactococcus lactis, Acinetobacter johnsoniiandBacteroides dorei, while from mastitis cows it was predominantly comprised ofBacillus cereus, Clostridium cadaverisandStreptococcus suis. The prevalence ofLa. lactisandB. cereusin milk from healthy and mastitis cows was confirmed by digital droplets PCR. Differences in milk microbiota composition could suggest an important role for these microbes in protecting the host from mastitis. Based on the milk microbiota profiles, the Udder Health Index was constructed to predict the risk of bovine mastitis. Application of this predictive model could aid early identification and prevention of mastitis in dairy cows, though the model requires further optimisation using a larger dataset.
Effective variant filtering and expected candidate variant yield in studies of rare human disease
Authors: Pedersen Brent S. , Brown Joe M. , Dashnow Harriet , Wallace Amelia D. , Velinder Matt , Tvrdik Tatiana , Mao Rong , Best D. Hunter , Bayrak-Toydemir Pinar , Quinlan Aaron R.
Published: August 2020

In studies of families with rare disease, it is common to screen forde novomutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we derive effective guidelines for variant filtering and report the expected number of candidates forde novodominant and recessive modes of inheritance. The filters are applied to common attributes, including genotype quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield approximately 10 candidate SNP and INDEL variants per exome, and 19 per genome. For whole genomes, this includes an average of threede novo, ten compound-heterozygotes, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. Theslivarsoftware we developed to establish and rapidly apply these filters to VCF files is available athttps://github.com/brentp/slivarunder an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.
glmGamPoi: Fitting Gamma-Poisson Generalized Linear Models on Single Cell Count Data
Authors: Ahlmann-Eltze Constantin , Huber Wolfgang
Published: August 2020

Motivation

The Gamma-Poisson distribution is a theoretically and empirically motivated model for the sampling variability of single cell RNA-sequencing counts (Grünet al., 2014; Towneset al., 2019; Svensson, 2020; Silvermanet al., 2018; Hafemeister and Satija, 2019) and an essential building block for analysis approaches including differential expression analysis (Robinsonet al., 2010; McCarthyet al., 2012; Anders and Huber, 2010; Loveet al., 2014), principal component analysis (Towneset al., 2019) and factor analysis (Rissoet al., 2018). Existing implementations for inferring its parameters from data often struggle with the size of single cell datasets, which typically comprise thousands or millions of cells; at the same time, they do not take full advantage of the fact that zero and other small numbers are frequent in the data. These limitations have hampered uptake of the model, leaving room for statistically inferior approaches such as logarithm(-like) transformation.

Results

We present a newRpackage for fitting the Gamma-Poisson distribution to data with the characteristics of modern single cell datasets more quickly and more accurately than existing methods. The software can work with data on disk without having to load them into RAM simultaneously.

Availability

The packageglmGamPoiis available from Bioconductor (since release 3.11) for Windows, macOS, and Linux, and source code is available on GitHub under a GPL-3 license. The scripts to reproduce the results of this paper are available on GitHub as well.

Contact

constantin.ahlmann@embl.de
Scarless engineering of theDrosophilagenome near any site-specific integration site
Authors: Feng Siqian , Lu Shan , Grueber Wesley B. , Mann Richard S.
Published: August 2020

We describe a simple and efficient technique that allows scarless engineering ofDrosophilagenomic sequences near any landing site containing an inverted attP cassette, such as aMiMICinsertion. This 2-step method combines phiC31 integrase mediated site-specific integration and homing nuclease-mediated resolution of local duplications, efficiently converting the original landing site allele to modified alleles that only have the desired change(s). Dominant markers incorporated into this method allow correct individual flies to be efficiently identified at each step. In principle, single attP sites and FRT sites are also valid landing sites. Given the large and increasing number of landing site lines available in the fly community, this method provides an easy and fast way to efficiently edit the majority of theDrosophilagenome in a scarless manner. This technique should also be applicable to other species.
Transient non-specific DNA binding dominates the target search of bacterial DNA-binding proteins
Authors: Stracy Mathew , Schweizer Jakob , Sherratt David J , Kapanidis Achillefs N , Uphoff Stephan , Lesterlin Christian
Published: August 2020

Despite their diverse biochemical characteristics and functions, all DNA-binding proteins share the ability to accurately locate their target sites among the vast excess of non-target DNA. Towards identifying universal mechanisms of the target search, we used single-molecule tracking of 11 diverse DNA-binding proteins in living Escherichia coli. The mobility of these proteins during the target search was dictated by DNA interactions, rather than by their molecular weights. By generating cells devoid of all chromosomal DNA, we discovered that the nucleoid does not pose a physical barrier for protein diffusion, but significantly slows the motion of DNA-binding proteins through frequent short-lived DNA interactions. The representative DNA-binding proteins (irrespective of their size, concentration, or function) spend the majority (58-99%) of their search time bound to DNA and occupy as much as ∼30% of the chromosomal DNA at any time. Chromosome-crowding likely has important implications for the function of all DNA-binding proteins.
Genetic testing of dogs predicts problem behaviors in clinical and nonclinical samples
Authors: Zapata Isain , Lilly M. Leanne , Herron Meghan E. , Serpell James A. , Alvarez Carlos E.
Published: August 2020

Very little is known about the etiology of personality and psychiatric disorders. Because the core neurobiology of many such traits is evolutionarily conserved, dogs present a powerful model. We previously reported genome scans of breed averages of ten traits related to fear, anxiety, aggression and social behavior in multiple cohorts of pedigree dogs. As a second phase of that discovery, here we tested the ability of markers at 13 of those loci to predict canine behavior in a community sample of 397 pedigree and mixed-breed dogs with individual-level genotype and phenotype data. We found support for all markers and loci. By including 122 dogs with veterinary behavioral diagnoses in our cohort, we were able to identify eight loci associated with those diagnoses. Logistic regression models showed subsets of those loci could predict behavioral diagnoses. We corroborated our previous findings that small body size is associated with many problem behaviors and large body size is associated with increased trainability. Children in the home were associated with anxiety traits; illness and other animals in the home with coprophagia; working-dog status with increased energy and separation-related problems; and competitive dogs with increased aggression directed at familiar dogs, but reduced fear directed at humans and unfamiliar dogs. Compared to other dogs, Pit Bull-type dogs were not defined by a set of our markers and were not more aggressive; but they were strongly associated with pulling on the leash. Using severity-threshold models, Pit Bull-type dogs showed reduced risk of owner-directed aggression (75thquantile) and increased risk of dog-directed fear (95thquantile). Our findings have broad utility, including for clinical and breeding purposes, but we caution that thorough understanding is necessary for their interpretation and use.
Profiling variable-number tandem repeat variation across populations using repeat-pangenome graphs
Authors: Lu Tsung-Yu ,   The Human Genome Structural Variation Consortium, Chaisson Mark
Published: August 2020

Variable number tandem repeat sequences (VNTR) are composed of consecutive repeats of short segments of DNA with hypervariable repeat count and composition. They include protein coding sequences and associations with clinical disorders. It has been difficult to incorporate VNTR analysis in disease studies that use short-read sequencing because the traditional approach of mapping to the human reference is less effective for repetitive and divergent sequences. We solve VNTR mapping for short reads with a repeat-pangenome graph (RPGG), a data structure that encodes both the population diversity and repeat structure of VNTR loci from multiple haplotype-resolved assemblies. We developed software to build a RPGG, and use the RPGG to estimate VNTR composition with short reads. We used this to discover VNTRs with length stratified by continental population, and novel expression quantitative trait loci, indicating that RPGG analysis of VNTRs will be critical for future studies of diversity and disease.
The RNA-binding protein Puf5 buffers mRNA levels against chromatin-mediated changes in nascent transcription
Authors: Kochan David Z. , Mawer Julia S. P. , Tishinov Kiril , Parekh Swati , Massen Jennifer , Graef Martin , Spang Anne , Tessarz Peter
Published: August 2020

Gene expression is a dynamic process regulated at all stages, starting with opening of chromatin, transcription, and continuing with mRNA export, translation and, finally, degradation. While there are feedback mechanisms within the system, it is not clear whether these extend to crosstalk between chromatin architecture and mRNA decay. Here, we show that changes in nascent transcription, mediated by mutating H3K56 to alanine, are post-transcriptionally buffered by the Pumilio protein Puf5, which stabilizes transcripts in a context-dependent manner. Depleting Puf5 in an H3K56A background leads to synthetic lethality. This genetic interaction can be explained by a decrease in translation due to downregulation of its direct mRNA targets, largely consisting of ribosomal protein genes. Importantly, we show that this post-transcriptional buffering is not only linked to H3K56A, but may be a more widespread phenomenon that also buffers against an increase in nascent RNA transcription in order to maintain physiological mRNA levels and cellular homeostasis.
Identifying potential hosts of short-branch Microsporidia
Authors: Doliwa Annemie , Dunthorn Micah , Rassoshanska Erika , Mahé Frédéric , Bass David , Ritter Camila Duarte
Published: August 2020

Microsporidia are obligate parasites that are closely related to Fungi. While the widely-known “long-branch” Microsporidia infect mostly animals, the hosts of “short-branch” Microsporidia are only partially characterized or not known at all. Here, we used network analyses from Neotropical rainforest soil metabarcoding data, to infer co-occurrences between environmental lineages of short-branch microsporidians and their potential hosts. We found significant co-occurrences with several taxa, especially with Apicomplexa, Cercozoa, Fungi, as well as some Metazoa. Our results are the first step to identify potential hosts of the environmental lineages of short-branch microsporidians, which can be targeted in future molecular and microscopic studies.
Bacterial Vipp1 and PspA are members of the ancient ESCRT-III membrane-remodelling superfamily
Authors: Liu Jiwei , Tassinari Matteo , Souza Diorge P , Naskar Souvik , Noel Jeffrey K. , Bohuszewicz Olga , Buck Martin , Williams Tom A. , Baum Buzz , Low Harry H
Published: August 2020

Membrane remodelling and repair are essential for all cells. Proteins that perform these functions include Vipp1/IM30 in photosynthetic plastids, PspA in bacteria, CdvB in TACK archaea and ESCRT-III in eukaryotes. Here, we show that these protein families are homologous and share a common evolutionary origin. Using cryo-electron microscopy we present structures for Vipp1 rings over a range of symmetries. Each ring is built from rungs that stack and spontaneously self-organise to form domes. Rungs are assembled from a polymer that is strikingly similar in structure to ESCRT-III. A tilt between rungs generates the dome-shaped curvature with constricted open ends and an inner membrane-binding lumen. Overall, our results reveal conserved mechanistic principles that underlie Vipp1, PspA and ESCRT-III dependent membrane remodelling across all domains of life.

One sentence summary

Evolutionary and structural analyses of Vipp1/IM30 rings reveal ESCRT-III-like polymers that remodel membranes in bacteria.
Assessment of Neurovascular Coupling & Cortical Spreading Depression in Mixed Models of Atherosclerosis & Alzheimer’s Disease
Authors: Shabir Osman , Pendry Ben , Lee Llywelyn , Eyre Beth , Sharp Paul , Rebollar Monica A , Howarth Clare , Heath Paul R , Wharton Stephen B , Francis Sheila E , Berwick Jason
Published: August 2020

Neurovascular coupling is a critical brain mechanism whereby changes to blood flow accompany localised neural activity. The breakdown of neurovascular coupling is linked to the development and progression of several neurological conditions including dementia. In this study, we examined cortical haemodynamics in preparations that modelled Alzheimer’s disease (J20-AD) and atherosclerosis (PCSK9-ATH) between 9-12m of age. We report novel findings with atherosclerosis where neurovascular decline is characterised by significantly reduced blood volume, levels of oxyhaemoglobin & deoxyhaemoglobin, in addition to global neuroinflammation. In the comorbid mixed model (J20-PCSK9-MIX), we report a 3x fold increase in hippocampal amyloid-beta plaques. A key finding was that cortical spreading depression (CSD) due to electrode insertion into the brain was worse in the diseased animals and led to a prolonged period of hypoxia. These findings suggest that systemic atherosclerosis can be detrimental to neurovascular health and that having cardiovascular comorbidities can exacerbate pre-existing Alzheimer’s-related amyloid-plaques.
iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning
Authors: Rychel Kevin , Decker Katherine , Sastry Anand V , Phaneuf Patrick V , Poudel Saugat , Palsson Bernhard O
Published: August 2020

Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (E. coli, S. aureus, andB. subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.
Structural and biochemical mechanisms of NLRP1 inhibition by DPP9
Authors: Huang Menghang , Zhang Xiaoxiao , Ann Toh Gee , Gong Qin , Wang Jia , Han Zhifu , Wu Bin , Zhong Franklin , Chai Jijie
Published: August 2020

The nucleotide-binding domain (NBD) and leucine-rich repeat (LRR)-containing receptors (NLRs) mediate innate immunity by forming inflammasomes. Activation of the NLR protein NLRP1 requires auto-cleavage within its FIIND domain1–7. In resting cells, the dipeptidyl peptidase DPP9 interacts with NLRP1-FIIND and together with a related enzyme DPP8, suppresses spontaneous NLRP1 activation8,9. The mechanisms of DPP8/9-mediated NLRP1 inhibition, however, remain elusive. Here we provide structural and biochemical evidence demonstrating that rat NLRP1 (rNLRP1) interacts with rDPP9 in a stepwise manner to form a 2:1 complex. An auto-inhibited rNLRP1 molecule first interacts with rDPP9 via its ZU5 domain. This 1:1 rNLRP1-rDPP9 complex then captures the UPA domain of a second rNLRP1 molecule via a UPA-interacting site on DPP9 and dimeric UPA-UPA interactions with the first rNLRP1. The 2:1 rNLRP1-rDPP9 complex prevents NLRP1 UPA-mediated higher order oligomerization and maintains NLRP1 in the auto-inhibited state. Structure-guided biochemical and functional assays show that both NLRP1-binding and its enzymatic activity are required for DPP9 to suppress NLRP1, supporting guard-type activation of the NLR. Together, our data reveal the mechanism of DPP9-mediated inhibition of NLRP1 and shed light on activation of the NLRP1 inflammasome.
Changes in Cell Size and Shape During 50,000 Generations of Experimental Evolution withEscherichia coli
Authors: Grant Nkrumah A. , Magid Ali Abdel , Franklin Joshua , Dufour Yann , Lenski Richard E.
Published: August 2020

Bacteria adopt a wide variety of sizes and shapes, with many species exhibiting stereotypical morphologies. How morphology changes, and over what timescales, is less clear. Previous work examining cell morphology in an experiment withEscherichia colishowed that populations evolved larger cells and, in some cases, cells that were less rod-like. That experiment has now run for over two more decades. Meanwhile, genome sequence data are available for these populations, and new computational methods enable high-throughput microscopic analyses. Here, we measured stationary-phase cell volumes for the ancestor and 12 populations at 2,000, 10,000, and 50,000 generations, including measurements during exponential growth at the last timepoint. We measured the distribution of cell volumes for each sample using a Coulter counter and microscopy, the latter of which also provided data on cell shape. Our data confirm the trend toward larger cells, while also revealing substantial variation in size and shape across replicate populations. Most populations first evolved wider cells, but later reverted to the ancestral length-to-width ratio. All but one population evolved mutations in rod-shape maintenance genes. We also observed many ghost-like cells in the only population that evolved the novel ability to grow on citrate, supporting the hypothesis that this lineage struggles with maintaining balanced growth. Lastly, we show that cell size and fitness remain correlated across 50,000 generations. Our results suggest larger cells are beneficial in the experimental environment, while the reversion toward ancestral length-to-width ratios suggests partial compensation for the less favorable surface area-to-volume ratios of the evolved cells.

Importance

Bacteria exhibit great morphological diversity, yet we have only a limited understanding of how their cell sizes and shapes evolve, and of how these features affect organismal fitness. This knowledge gap reflects, in part, the paucity of the fossil record for bacteria. Here, we revive and analyze samples extending over 50,000 generations from 12 populations of experimentally evolvingEscherichia colito investigate the relation between cell size, shape, and fitness. Using this “frozen fossil record” we show that all 12 populations evolved larger cells concomitant with increased fitness, with substantial heterogeneity in cell size and shape across the replicate lines. Our work demonstrates that cell morphology can readily evolve and diversify, even among populations living in identical environments.