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Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 52,871 bioRxiv papers from 244,990 authors.

Most tweeted bioRxiv papers, last 24 hours

347 results found. For more information, click each entry to expand.

61: Estimation of the force of infection and infectious period of skin sores in remote Australian communities using interval-censored data
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Posted to bioRxiv 21 Jun 2019

Estimation of the force of infection and infectious period of skin sores in remote Australian communities using interval-censored data
6 tweets epidemiology

Michael Lydeamore, Patricia T Campbell, David J. Price, Yue Wu, Adrian J Marcato, Will Cuningham, Jonathan R. Carapetis, Ross M Andrews, Malcolm I McDonald, Jodie McVernon, Steven Y. C. Tong, James M McCaw

Prevalence of impetigo (skin sores) remains high in remote Australian Aboriginal communities, Fiji, and other areas of socio-economic disadvantage. Skin sore infections, driven primarily in these settings by Group A Streptococcus (GAS) contribute substantially to the disease burden in these areas. Despite this, estimates for the force of infection, infectious period and basic reproductive ratio - all necessary for the construction of dynamic transmission models - have not been obtained. By utilising three datasets each containing longitudinal infection information on individuals, we estimate each of these epidemiologically important parameters. With an eye to future study design, we also quantify the optimal sampling intervals for obtaining information about these parameters. We verify the estimation method through a simulation estimation study, and test each dataset to ensure suitability to the estimation method. We find that the force of infection differs by population prevalence, and the infectious period is estimated to be between 12 and 20 days. We also find that optimal sampling interval depends on setting, with an optimal sampling interval between 9 and 11 days in a high prevalence setting, and 21 and 27 days for a lower prevalence setting. These estimates unlock future model-based investigations on the transmission dynamics of GAS and skin sores.

62: Amyloid pathology disrupts gliotransmitter release in astrocytes
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Posted to bioRxiv 22 Jun 2019

Amyloid pathology disrupts gliotransmitter release in astrocytes
6 tweets neuroscience

Anup G Pillai, Suhita Nadkarni

Accumulation of amyloid-β peptide (Aβ), a hallmark of Alzheimer's disease (AD), is associated with synchronous hyperactivity and dysregulated Ca2+ signaling in hippocampal astrocytes. However, the consequences of altered Ca2+ signaling on the temporal dynamics of Ca2+ and gliotransmitter release events at astrocytic microdomains are not known. We have developed a detailed biophysical model of microdomain signaling at a single astrocytic process that accurately describes key temporal features of Ca2+ events and Ca2+-mediated kiss-and-run and full fusion exocytosis. Using this model, we ask how aberrant plasma-membrane Ca2+ pumps and mGluR activity, molecular hallmarks of Aβ toxicity that are also critically involved in Ca2+ signaling, modify astrocytic feedback at a tripartite synapse. We show that AD related molecular pathologies increase the rate and synchrony of Ca2+ and exocytotic events triggered by neuronal activity. Moreover, temporal precision between Ca2+ and release events, a mechanism indispensable for rapid modulation of synaptic transmission by astrocytes, is lost in AD astrocytic processes. Our results provide important evidence on the link between AD-related molecular pathology, dysregulated calcium signaling and gliotransmitter release at an astrocytic process.

63: XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples
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Posted to bioRxiv 21 Jun 2019

XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples
5 tweets bioinformatics

Stefano Cheloni, Roman Hillje, Lucilla Luzi, Pier Giuseppe Pelicci, Elena Gatti

Single-cell sequencing technologies provide unprecedented opportunities to deconvolve the genomic, transcriptomic or epigenomic heterogeneity of complex biological systems. Its application in samples from xenografts of patient-derived biopsies (PDX), however, is limited by the presence in the analysed samples of a mixture of cells arising from the host and the graft. We have developed XenoCell, the first stand-alone pre-processing tool that performs fast and reliable classification of host and graft cellular barcodes. We show its application on a single cell dataset composed by human and mouse cells.

64: The common message of constraint-based optimization approaches: overflow metabolism is caused by two growth-limiting constraints
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Posted to bioRxiv 21 Jun 2019

The common message of constraint-based optimization approaches: overflow metabolism is caused by two growth-limiting constraints
5 tweets systems biology

Daan Hugo de Groot, Julia Lischke, Riccardo Muolo, Robert Planque, Frank J. Bruggeman, Bas Teusink

In each environment, living cells can express different metabolic pathways that support growth. The criteria that determine which pathways are selected remain unclear. One recurrent selection is overflow metabolism: the seemingly wasteful, simultaneous usage of an efficient and an inefficient pathway, shown for example in E. coli, S. cerevisiae and cancer cells. Many different models, based on different assumptions, can reproduce this observation. Therefore, they provide no conclusive evidence which mechanism is causing overflow metabolism. We compare the mathematical structure of these models. Although ranging from Flux Balance Analyses to self-fabricating Metabolism and Expression models, we could rewrite all models into one standard form. We conclude that all models predict overflow metabolism when two, model-specific, growth-limiting constraints are hit. This is consistent with recent theory. Thus, identifying these two constraints is essential for understanding overflow metabolism. We list all the imposed constraints by these models, so that they can hopefully be tested in future experiments.

65: H3K9me2 orchestrates inheritance of spatial positioning of peripheral heterochromatin through mitosis
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Posted to bioRxiv 21 Jun 2019

H3K9me2 orchestrates inheritance of spatial positioning of peripheral heterochromatin through mitosis
5 tweets cell biology

Andrey Poleshko, Cheryl L Smith, Son C. Nguyen, Priya Sivaramakrishnan, John Isaac Murray, Melike Lakadamyali, Eric F. Joyce, Raj Jain, Jonathan A Epstein

Cell-type-specific 3D organization of the genome is unrecognizable during mitosis. It remains unclear how essential positional information is transmitted through cell division such that a daughter cell recapitulates the spatial genome organization of the parent. Lamina-associated domains (LADs) are regions of repressive heterochromatin positioned at the nuclear periphery that vary by cell type and contribute to cell-specific gene expression. Here we show that histone 3 lysine 9 dimethylation (H3K9me2) specifically marks peripheral heterochromatin and is retained through mitosis when phosphorylation of histone 3 serine 10 shields the H3K9me2 mark allowing for dissociation from the nuclear lamina. The H3K9me2 modification of peripheral heterochromatin ensures that positional information is safeguarded through cell division such that individual LADs are re-established at the nuclear periphery in daughter nuclei. Thus, H3K9me2 acts as a 3D architectural mitotic guidepost. Our data establish a mechanism for epigenetic memory and inheritance of spatial organization of the genome.

66: SynQuant: An Automatic Tool to Quantify Synapses from Microscopy Images
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Posted to bioRxiv 02 Feb 2019

SynQuant: An Automatic Tool to Quantify Synapses from Microscopy Images
5 tweets neuroscience

Yizhi Wang, Congchao Wang, Petter Ranefall, Gerard Broussard, Yinxue Wang, Guilai Shi, Boyu Lyu, Yue Wang, Lin Tian, Guoqiang Yu

Motivation: Synapses are essential to neural signal transmission. Therefore, quantification of synapses and related neurites from images is vital to gain insights into the underlying pathways of brain functionality and diseases. Despite the wide availability of synaptic punctum imaging data, several issues are impeding satisfactory quantification of these structures by current tools. First, the antibodies used for labeling synapses are not perfectly specific to synapses. These antibodies may exist in neurites or other cell compartments. Second, the brightness for different neurites and synaptic puncta is heterogeneous due to the variation of antibody concentration and synapse-intrinsic differences. Third, images often have low signal to noise ratio due to constraints of experiment facilities and availability of sensitive antibodies. These issues make the detection of synapses challenging and necessitates developing a new tool to easily and accurately quantify synapses. Results: We present an automatic probability-principled synapse detection algorithm and integrate it into our synapse quantification tool SynQuant. Derived from the theory of order statistics, our method controls the false discovery rate and improves the power of detecting synapses. SynQuant is unsupervised, works for both 2D and 3D data, and can handle multiple staining channels. Through extensive experiments on one synthetic and three real data sets with ground truth annotation or manual labeling, SynQuant was demonstrated to outperform peer specialized synapse detection tools as well as generic spot detection methods, including 4 unsupervised and 11 variants of 3 supervised methods. Availability: Java source code, Fiji plug-in, and test data available at https://github.com/yu-lab-vt/SynQuant.

67: Nonlinear Interaction Decomposition (NID): A Method for Separation of Cross-Frequency Coupled Sources in Human Brain
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Posted to bioRxiv 23 Jun 2019

Nonlinear Interaction Decomposition (NID): A Method for Separation of Cross-Frequency Coupled Sources in Human Brain
5 tweets neuroscience

Mina Jamshidi Idaji, Klaus-Robert Mueller, Guido Nolte, Burkhard Maess, Arno Villringer, Vadim V Nikulin

Cross-frequency coupling (CFC) is a phenomenon through which spatially and spectrally distributed information can be integrated in the brain. There is, however, a lack of methods decomposing brain electrophysiological data into interacting components. Here, we propose a novel framework for detecting such interactions in Magneto- and Electroencephalography (MEG/EEG), which we refer to as Nonlinear Interaction Decomposition (NID). In contrast to all previous methods for separation of cross-frequency (CF) sources in the brain, we propose that the extraction of nonlinearly interacting oscillations can be based on the statistical properties of their linear mixtures. The main idea of NID is that nonlinearly coupled brain oscillations can be mixed in such a way that the resulting linear mixture has a non-Gaussian distribution. We evaluate this argument analytically for amplitude-modulated narrow-band oscillations which are either phase-phase or amplitude-amplitude CF coupled. We validated NID extensively with simulated EEG obtained with realistic head modeling. The method extracted nonlinearly interacting components reliably even at SNRs as small as −15 (dB). Additionally, we applied NID to the resting-state EEG of 81 subjects to characterize CF phase-phase coupling between alpha and beta oscillations. The extracted sources were located in temporal, parietal and frontal areas, demonstrating the existence of diverse local and distant nonlinear interactions in resting-state EEG data.

68: Principles of self-organization and load adaptation by the actin cytoskeleton during clathrin-mediated endocytosis
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Posted to bioRxiv 21 Jun 2019

Principles of self-organization and load adaptation by the actin cytoskeleton during clathrin-mediated endocytosis
5 tweets cell biology

Matthew Akamatsu, Ritvik Vasan, Daniel Serwas, Michael Ferrin, Padmini Rangamani, David G. Drubin

Force generation due to actin assembly is a fundamental aspect of membrane sculpting for many essential processes. In this work, we use a multiscale computational model constrained by experimental measurements to show that a minimal branched actin network is sufficient to internalize endocytic pits against physiological membrane tension. A parameter sweep identified the number of Arp2/3 complexes as particularly important for robust internalization, which prompted the development of a molecule-counting method in live mammalian cells. Using this method, we found that ~200 Arp2/3 complexes assemble at sites of clathrin-mediated endocytosis in human cells. Our simulations also revealed that actin networks self-organize in a radial branched array with barbed filament ends oriented to grow toward the base of the pit, and that the distribution of linker proteins around the endocytic pit is critical for this organization. Surprisingly, our model predicted that long actin filaments bend from their attachment sites in the coat to the base of the pit and store elastic energy that can be harnessed to drive endocytosis. This prediction was validated using cryo-electron tomography on cells, which revealed the presence of bent actin filaments along the endocytic site. Furthermore, we predict that under elevated membrane tension, the self-organized actin network directs more growing filaments toward the base of the pit, increasing actin nucleation and bending for increased force production. Thus, our study reveals that spatially constrained actin filament assembly utilizes an adaptive mechanism that enables endocytosis under varying physical constraints.

69: Seasonal stability and dynamics of DNA methylation in plants in a natural environment
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Posted to bioRxiv 29 Mar 2019

Seasonal stability and dynamics of DNA methylation in plants in a natural environment
5 tweets plant biology

Tasuku Ito, Haruki Nishio, Yoshiaki Tarutani, Naoko Emura, Mie N Honjo, Atsushi Toyoda, Asao Fujiyama, Tetsuji Kakutani, Hiroshi Kudoh

Organisms survive in naturally fluctuating environments by responding to long-term signals, such as seasonality, by filtering out short-term noise. DNA methylation has been considered a stable epigenetic mark but has also been reported to change in response to experimental manipulations of biotic and abiotic factors. However, it is unclear how they behave in natural environments. Here, we analyzed seasonal patterns of genome-wide DNA methylation at a single-base resolution using a single clone from a natural population of the perennial Arabidopsis halleri. The genome-wide pattern of DNA methylation was primarily stable, and most of the repetitive regions were methylated across the year. Although the proportion was small, we detected seasonally methylated cytosines (SeMCs) in the genome. SeMCs in the different contexts showed distinct seasonal patterns of methylation. SeMCs in CHH context were detected predominantly at repetitive sequences in intergenic regions. Additionally, we found that CHH methylation within AhgFLC locus showed a seasonal pattern that was negatively associated with changes in gene expression. Gene-body CG methylation (gbM) itself was generally stable across seasons, but the levels of gbM were positively associated with seasonal stability of RNA expression of the genes. These results suggest the existence of two distinct aspects of DNA methylation in natural environments: sources of epigenetic variation and epigenetic marks for stable gene expression.

70: Higher fitness yeast genotypes are less robust to deleterious mutations
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Posted to bioRxiv 20 Jun 2019

Higher fitness yeast genotypes are less robust to deleterious mutations
5 tweets evolutionary biology

Milo S. Johnson, Alena Martsul, Sergey Kryazhimskiy, Michael M Desai

Natural selection drives populations towards higher fitness, but second-order selection for adaptability and mutational robustness can also influence the dynamics of adaptation. In many microbial systems, diminishing returns epistasis contributes to a tendency for more-fit genotypes to be less adaptable, but no analogous patterns for robustness are known. To understand how robustness varies across genotypes, we measure the fitness effects of hundreds of individual insertion mutations in a panel of yeast strains. We find that more-fit strains are less robust: they have distributions of fitness effects (DFEs) with lower mean and higher variance. These shifts in the DFE arise because many mutations have more strongly deleterious effects in faster-growing strains. This negative correlation between fitness and robustness implies that second-order selection for robustness will tend to conflict with first-order selection for fitness.

71: Complete single neuron reconstruction reveals morphological diversity in molecularly defined claustral and cortical neuron types
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Posted to bioRxiv 20 Jun 2019

Complete single neuron reconstruction reveals morphological diversity in molecularly defined claustral and cortical neuron types
5 tweets neuroscience

Yun Wang, Peng Xie, Hui Gong, Zhi Zhou, Xiuli Kuang, Yimin Wang, An-an Li, Yaoyao Li, Lijuan Liu, Matthew B Veldman, Tanya L Daigle, Karla E Hirokawa, Lei Qu, Phil Lesnar, Shengdian Jiang, Yang Yu, Wayne Wakeman, Shaoqun Zeng, Xiangning Li, Jing Yuan, Thuc Nghi Nguyen, Rachael Larsen, Sara Kedebe, Yuanyuan Song, Lulu Yin, Sujun Zhao, Aaron Feiner, Elise Shen, Chris Hill, Quanxin Wang, Stephanie Mok, Susan M Sunkin, Z. Josh Huang, Luke Esposito, Zizhen Yao, Michael J Hawrylycz, Bosiljka Tasic, Lydia Ng, Staci A. Sorensen, X. William Yang, Julie A Harris, Christof Koch, Qingming Luo, Hanchuan Peng, Hongkui Zeng

Ever since the seminal findings of Ramon y Cajal, dendritic and axonal morphology has been recognized as a defining feature of neuronal types and their connectivity. Yet our knowledge about the diversity of neuronal morphology, in particular its distant axonal projections, is still extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale in mice, we established a pipeline that encompasses five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling of a wide range of neuronal types across the mouse brain in an efficient way by combining transgenic or viral Cre delivery with novel transgenic reporter lines, and generated a large set of high-resolution whole-brain fluorescent imaging datasets containing thousands of reconstructable neurons using the fluorescence micro-optical sectioning tomography (fMOST) system. We developed a set of software tools based on the visualization and analysis suite, Vaa3D, for large-volume image data processing and computation-assisted morphological reconstruction. In a proof-of-principle case, we reconstructed full morphologies of 96 neurons from the claustrum and cortex that belong to a single transcriptomically-defined neuronal subclass. We developed a data-driven clustering approach to classify them into multiple morphological and projection types, suggesting that these neurons work in a targeted and coordinated manner to process cortical information. Imaging data and the new computational reconstruction tools are publicly available to enable community-based efforts towards large-scale full morphology reconstruction of neurons throughout the entire mouse brain.

72: Passenger Hotspot Mutations in Cancer
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Posted to bioRxiv 19 Jun 2019

Passenger Hotspot Mutations in Cancer
5 tweets genomics

Julian M Hess, Andre Bernards, Jaegil Kim, Mendy Miller, Amaro Taylor-Weiner, Nicholas J Haradhvala, Michael S Lawrence, Gad Getz

Hotspots, or mutations that recur at the same genomic site across multiple tumors, have been conventionally interpreted as strong universal evidence of somatic positive selection, unequivocally pinpointing genes driving tumorigenesis. Here, we demonstrate that this convention is falsely premised on an inaccurate statistical model of background mutagenesis. Many hotspots are in fact passenger events, recurring at sites that are simply inherently more mutable rather than under positive selection, which current background models do not account for. We thus detail a log-normal-Poisson (LNP) background model that accounts for variation in site-specific mutability in a manner consistent with models of mutagenesis, use this model to show that the tendency to generate passenger hotspots pervades all common mutational processes, and apply it to a ~10,000 patient cohort from The Cancer Genome Atlas to nominate driver hotspots with far fewer false positives compared to conventional methods. As the biomedical community faces critical decisions in prioritizing putative driver mutations for deep experimental characterization to assess therapeutic potential, we offer our findings as a guide to avoid wasting valuable scientific resources on passenger hotspots.

73: FOXO mediates organismal hypoxia tolerance by regulating NF-κB in Drosophila
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Posted to bioRxiv 22 Jun 2019

FOXO mediates organismal hypoxia tolerance by regulating NF-κB in Drosophila
5 tweets cell biology

Elizabeth C Barretto, Danielle M Polan, Amy N Beevor-Potts, Byoungchun Lee, Savraj S Grewal

Exposure of tissues and organs to low oxygen (hypoxia) occurs in both physiological and pathological conditions in animals. Under these conditions, organisms have to adapt their physiology to ensure proper functioning and survival. Here we define a role for the transcription factor FOXO as a mediator of hypoxia tolerance in Drosophila. We find that upon hypoxia exposure, FOXO transcriptional activity is rapidly induced in both larvae and adults. Moreover, we see that foxo mutant animals show misregulated glucose metabolism in low oxygen and subsequently exhibit reduced hypoxia survival. We identify the innate immune transcription factor, NF-KappaB/Relish, as a key FOXO target in the control of hypoxia tolerance. We find that expression of Relish and its target genes are increase in a FOXO-dependent manner in hypoxia, and that relish mutant animals show reduced survival in hypoxia. Together, these data indicate that FOXO is a hypoxia inducible factor that mediates tolerance to low oxygen by inducing immune-like responses.

74: A Human Liver Cell Atlas: Revealing Cell Type Heterogeneity and Adult Liver Progenitors by Single-Cell RNA-sequencing
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Posted to bioRxiv 24 May 2019

A Human Liver Cell Atlas: Revealing Cell Type Heterogeneity and Adult Liver Progenitors by Single-Cell RNA-sequencing
5 tweets genomics

Nadim Aizarani, Antonio Saviano, Sagar, Laurent Mailly, Sarah Durand, Patrick Pessaux, Thomas F Baumert, Dominic Grün

The human liver is an essential multifunctional organ, and liver diseases are rising with limited treatment options. However, the cellular complexity and heterogeneity of the liver remain poorly understood. Here, we performed single-cell RNA-sequencing of ~5,000 cells from normal liver tissue of 6 human donors to construct the first human liver cell atlas. Our analysis revealed previously unknown sub-types among endothelial cells, Kupffer cells, and hepatocytes with transcriptome-wide zonation of these populations. We show that the EPCAM+ population is highly heterogeneous and consists of hepatocyte progenitors, cholangiocytes and a MUC6+ stem cell population with a specific potential to form liver organoids. As proof-of-principle, we applied our atlas to unravel phenotypic changes in cells from hepatocellular carcinoma tissue and to investigate cellular phenotypes of human hepatocytes and liver endothelial cells engrafted into a humanized FAH-/- mouse liver. Our human liver cell atlas provides a powerful and innovative resource enabling the discovery of previously unknown cell types in the normal and diseased liver.

75: Comprehensive ecosystem-specific 16S rRNA gene databases with automated taxonomy assignment (AutoTax) provide species-level resolution in microbial ecology
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Posted to bioRxiv 18 Jun 2019

Comprehensive ecosystem-specific 16S rRNA gene databases with automated taxonomy assignment (AutoTax) provide species-level resolution in microbial ecology
5 tweets microbiology

Morten Simonsen Dueholm, Kasper S. Skytte Andersen, Francesca Petriglieri, Simon Jon McIlroy, Marta Nierychlo, Jette Fisher Petersen, Jannie Munk Kristensen, Erika Yashiro, Soeren Michael Karst, Mads Albertsen, Per Halkjaer Nielsen

High-throughput 16S rRNA gene amplicon sequencing is an indispensable method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases, and by the lack of a systematic and comprehensive taxonomic classification for most environmental bacteria. Here we combine high-quality and high-throughput full-length 16S rRNA gene sequencing with a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) to create robust, near-complete 16S rRNA gene databases for complex environmental ecosystems. To demonstrate the benefit of the approach, we created an ecosystem-specific database for wastewater treatment systems and anaerobic digesters. The novel approach allows consistent species-level classification of 16S rRNA amplicons sequence variants and the design of highly specific oligonucleotide probes for fluorescence in situ hybridization, which can reveal in situ properties of microbes at unprecedented taxonomic resolution.

76: A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates
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Posted to bioRxiv 11 Oct 2018

A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates
4 tweets evolutionary biology

Joelle Barido-Sottani, Timothy G Vaughan, Tanja Stadler

Heterogeneous populations can lead to important differences in birth and death rates across a phylogeny. Taking this heterogeneity into account is thus critical to obtain accurate estimates of the underlying population dynamics. We present a new multi-state birth-death model (MSBD) that can estimate lineage-specific birth and death rates. For species phylogenies, this corresponds to estimating lineage-dependent speciation and extinction rates. Contrary to existing models, we do not require a prior hypothesis on a trait driving the rate differences and we allow the same rates to be present in different parts of the phylogeny. Using simulated datasets, we show that the MSBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtained by MSBD and by the existing software BAMM. The MSBD model is implemented as a package in the Bayesian inference software BEAST2, which allows joint inference of the phylogeny and the model parameters.

77: Modeling the Human Segmentation Clock with Pluripotent Stem Cells
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Posted to bioRxiv 27 Feb 2019

Modeling the Human Segmentation Clock with Pluripotent Stem Cells
4 tweets developmental biology

Mitsuhiro Matsuda, Yoshihiro Yamanaka, Maya Uemura, Mitsujiro Osawa, Megumu K. Saito, Ayako Nagahashi, Megumi Nishio, Long Guo, Shiro Ikegawa, Satoko Sakurai, Shunsuke Kihara, Michiko Nakamura, Tomoko Matsumoto, Hiroyuki Yoshitomi, Makoto Ikeya, Takuya Yamamoto, Knut Woltjen, Miki Ebisuya, Junya Toguchida, Cantas Alev

Pluripotent stem cells (PSCs) have increasingly been used to model different aspects of embryogenesis and organ formation. Despite recent advances in the in vitro induction of major mesodermal lineages and mesoderm-derived cell types experimental model systems that can recapitulate more complex biological features of human mesoderm development and patterning are largely missing. Here, we utilized induced pluripotent stem cells (iPSCs) for the stepwise in vitro induction of presomitic mesoderm (PSM) and its derivatives to model distinct aspects of human somitogenesis. We focused initially on modeling the human segmentation clock, a major biological concept believed to underlie the rhythmic and controlled emergence of somites, which give rise to the segmental pattern of the vertebrate axial skeleton. We succeeded to observe oscillatory expression of core segmentation clock genes, including HES7 and DKK1, and identified novel oscillatory genes in human iPSC-derived PSM. We furthermore determined the period of the human segmentation clock to be around five hours and showed the presence of dynamic traveling wave-like gene expression within in vitro induced human PSM. Utilizing CRISPR/Cas9-based genome editing technology, we then targeted genes, for which mutations in patients with abnormal axial skeletal development such as spondylocostal dysostosis (SCD) (HES7, LFNG and DLL3) or spondylothoracic dysostosis (STD) (MESP2) have been reported. Subsequent analysis of patient-like iPSC knock-out lines as well as patient-derived iPSCs together with their genetically corrected isogenic controls revealed gene-specific alterations in oscillation, synchronization or differentiation properties, validating the overall utility of our model system, to recapitulate not only key features of human somitogenesis but also to provide novel insights into diseases associated with the formation and patterning of the human axial skeleton.

78: Redox-mediated Kick-Start of Mitochondrial Energy Metabolism drives Resource-efficient Seed Germination
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Posted to bioRxiv 20 Jun 2019

Redox-mediated Kick-Start of Mitochondrial Energy Metabolism drives Resource-efficient Seed Germination
4 tweets plant biology

Thomas Nietzel, Joerg Mostertz, Cristina Ruberti, Stephan Wagner, Anna Moseler, Philippe Fuchs, Stefanie J Müller-Schüssele, Abdelilah Benamar, Gernot Poschet, Michael Buettner, Guillaume Nee, Ian Max Moller, Christopher Horst Lillig, David Macherel, Iris Finkemeier, Markus Wirtz, Rüdiger Hell, Andreas J Meyer, Falko Hochgraefe, Markus Schwarzländer

Seeds preserve a far developed plant embryo in a quiescent state. Seed metabolism relies on stored resources and is re-activated to drive germination when the external conditions are favorable. Since the switchover from quiescence to re-activation provides a remarkable case of a cell physiological transition we investigated the earliest events in energy and redox metabolism of Arabidopsis seeds at imbibition. By developing fluorescent protein biosensing in intact seeds, we observed ATP accumulation and oxygen uptake within minutes, indicating rapid activation of mitochondrial respiration, which coincided with a sharp transition from an oxidizing to a more reducing thiol redox environment in the mitochondrial matrix. To identify individual operational protein thiol switches, we captured the fast release of metabolic quiescence in organello and devised quantitative iodoacetyl tandem mass tag-based (iodoTMT) thiol redox proteomics. The redox state across all Cys-peptides was shifted towards reduction from 27.1 % to 13.0 %. A large number of Cys-peptides (412) were redox-switched, representing central pathways of mitochondrial energy metabolism, including the respiratory chain and each enzymatic step of the tricarboxylic acid cycle (TCA). Active site Cys-peptides of glutathione reductase 2, NADPH-thioredoxin reductase a/b and thioredoxin-o1 showed the strongest responses. Germination of seeds lacking those redox proteins was associated with markedly enhanced respiration and deregulated TCA cycle dynamics suggesting decreased resource efficiency of energy metabolism. Germination in aged seeds was strongly impaired. We identify a global operation of thiol redox switches that is required for optimal usage of energy stores by the mitochondria to drive efficient germination.

79: CLIJ: Enabling GPU-accelerated image processing in Fiji
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Posted to bioRxiv 09 Jun 2019

CLIJ: Enabling GPU-accelerated image processing in Fiji
4 tweets bioinformatics

Robert Haase, Loic Royer, Peter Steinbach, Deborah Schmidt, Alexandr Dibrov, Uwe Schmidt, Martin Weigert, Nicola Maghelli, Pavel Tomancak, Florian Jug, Eugene W. Myers

Graphics processing units (GPU) allow image processing at unprecedented speed. We present CLIJ, a Fiji plugin enabling end-users with entry level experience in programming to benefit from GPU-accelerated image processing. Freely programmable workflows can sped up image processing in Fiji by factor 10 and more using high-end GPU hardware and on affordable mobile computers with built-in GPUs.

80: PaKman: Scalable Assembly of Large Genomes on Distributed Memory Machines
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Posted to bioRxiv 17 Jan 2019

PaKman: Scalable Assembly of Large Genomes on Distributed Memory Machines
4 tweets bioinformatics

Priyanka Ghosh, Sriram Krishnamoorthy, Ananth Kalyanaraman

De novo genome assembly is a fundamental problem in the field of bioinformatics, that aims to assemble the DNA sequence of an unknown genome from numerous short DNA fragments (aka reads) obtained from it. With the advent of high-throughput sequencing technologies, billions of reads can be generated in a matter of hours, necessitating efficient parallelization of the assembly process. While multiple parallel solutions have been proposed in the past, conducting a large-scale assembly at scale remains a challenging problem because of the inherent complexities associated with data movement, and irregular access footprints of memory and I/O operations. In this paper, we present a novel algorithm, called PaKman, to address the problem of performing large-scale genome assemblies on a distributed memory parallel computer. Our approach focuses on improving performance through a combination of novel data structures and algorithmic strategies for reducing the communication and I/O footprint during the assembly process. PaKman presents a solution for the two most time-consuming phases in the full genome assembly pipeline, namely, k-mer counting and contig generation.A key aspect of our algorithm is its graph data structure, which comprises fat nodes (or what we call "macro-nodes") that reduce the communication burden during contig generation. We present an extensive performance and qualitative evaluation of our algorithm, including comparisons to other state-of-the-art parallel assemblers. Our results demonstrate the ability to achieve near-linear speedups on up to 8K cores (tested); outperform state-of-the-art distributed memory and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly. For instance, PaKman is able to generate a high-quality set of assembled contigs for complex genomes such as the human and wheat genomes in a matter of minutes on 8K cores.

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