Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 57,506 bioRxiv papers from 264,779 authors.
Most downloaded bioRxiv papers, since beginning of last month
56,052 results found. For more information, click each entry to expand.
991 downloads plant biology
Geometry and growth and division direction of individual cells are major contributors to plant organ shape and these processes are dependent on dynamics of microtubules (MT). Different MT structures, like the cortical microtubules, preprophase band and mitotic spindle, are characterized by diverse architectural dynamics (Hashimoto, 2015). While several MT binding proteins have been identified that have various effects on MT stability and architecture, they do not discriminate between the different MT structures. It is therefore likely that specific MT binding proteins exist that differentiate between MT structures in order to allow for the differences in architectural dynamics. Although evidence for the effect of specific cues, such as light and auxin, on MT dynamics has been shown in recent years (Lindeboom et al., 2013; Chen et al., 2014), it remains unknown how such cues are integrated and lead to specific effects. Here we provide evidence for how auxin and calcium signaling can be integrated to modulate MT dynamics, by means of IQD proteins. We show that the Arabidopsis IQD15-18 subclade of this family is regulated by auxin signaling, can bind calmodulins in a calcium-dependent manner and are evolutionarily conserved. Furthermore, AtIQD15-18 directly bind SPIRAL2 protein in vitro and in vivo and modulate its function, likely in a calmodulin-dependent way, thereby providing a missing link between two important regulatory pathways of MT dynamics.
991 downloads bioinformatics
Understanding the relationship between amino acid sequence and protein function is a long-standing problem in molecular biology with far-reaching scientific implications. Despite six decades of progress, state-of-the-art techniques cannot annotate 1/3 of microbial protein sequences, hampering our ability to exploit sequences collected from diverse organisms. In this paper, we explore an alternative methodology based on deep learning that learns the relationship between unaligned amino acid sequences and their functional annotations across all 17929 families of the Pfam database. Using the Pfam seed sequences we establish rigorous benchmark assessments that use both random and clustered data splits to control for potentially confounding sequence similarities between train and test sequences. Using Pfam full, we report convolutional networks that are significantly more accurate and computationally efficient than BLASTp, while learning sequence features such as structural disorder and transmembrane helices. Our model co-locates sequences from unseen families in embedding space, allowing sequences from novel families to be accurately annotated. These results suggest deep learning models will be a core component of future protein function prediction tools.
986 downloads neuroscience
Over the past twenty years, neuroscience research on reward-based learning has converged on a canonical model, under which the neurotransmitter dopamine 'stamps in' associations between situations, actions and rewards by modulating the strength of synaptic connections between neurons. However, a growing number of recent findings have placed this standard model under strain. In the present work, we draw on recent advances in artificial intelligence to introduce a new theory of reward-based learning. Here, the dopamine system trains another part of the brain, the prefrontal cortex, to operate as its own free-standing learning system. This new perspective accommodates the findings that motivated the standard model, but also deals gracefully with a wider range of observations, providing a fresh foundation for future research.
984 downloads neuroscience
Single neurons in visual cortex provide unreliable measurements of visual features due to their high trial-to-trial variability. It is not known if this "noise" extends its effects over large neural populations to impair the global encoding of sensory stimuli. We recorded simultaneously from ~20,000 neurons in mouse visual cortex and found that the neural population had discrimination thresholds of 0.3 degrees in an orientation decoding task. These thresholds are ~100 times smaller than those reported behaviorally in mice. The discrepancy between neural and behavioral discrimination could not be explained by the types of stimuli we used, by behavioral states or by the sequential nature of trial-by-trial perceptual learning tasks. These results imply that the limits of sensory perception in mice are not set by neural noise in sensory cortex, but by the limitations of downstream decoders.
972 downloads neuroscience
Ahmed S. Abdelfattah, Takashi Kawashima, Amrita Singh, Ondrej Novak, Hui Liu, Yichun Shuai, Yi-Chieh Huang, Jonathan B. Grimm, Ronak Patel, Johannes Friedrich, Brett D. Mensh, Liam Paninski, John J Macklin, Kaspar Podgorski, Bei-Jung Lin, Tsai-Wen Chen, Glenn C. Turner, Zhe Liu, Minoru Koyama, Karel Svoboda, Misha B Ahrens, Luke D. Lavis, Eric R Schreiter
Imaging changes in membrane potential using genetically encoded fluorescent voltage indicators (GEVIs) has great potential for monitoring neuronal activity with high spatial and temporal resolution. Brightness and photostability of fluorescent proteins and rhodopsins have limited the utility of existing GEVIs. We engineered a novel GEVI, Voltron, that utilizes bright and photostable synthetic dyes instead of protein-based fluorophores, extending the combined duration of imaging and number of neurons imaged simultaneously by more than tenfold relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously, over 15 minutes of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.
970 downloads developmental biology
Sabina Kanton, Michael James Boyle, Zhisong He, Malgorzata Santel, Anne Weigert, Fatima Sanchis Calleja, Leila Sidow, Jonas Fleck, Patricia Guijarro, Dingding Han, Zhengzong Qian, Michael Heide, Wieland Huttner, Philipp Khaitovich, Svante Pääbo, Barbara Treutlein, J. Gray Camp
The human brain has changed dramatically since humans diverged from our closest living relatives, chimpanzees and the other great apes. However, the genetic and developmental programs underlying this divergence are not fully understood. Here, we have analyzed stem cell-derived cerebral organoids using single-cell transcriptomics (scRNA-seq) and accessible chromatin profiling (scATAC-seq) to explore gene regulatory changes that are specific to humans. We first analyze cell composition and reconstruct differentiation trajectories over the entire course of human cerebral organoid development from pluripotency, through neuroectoderm and neuroepithelial stages, followed by divergence into neuronal fates within the dorsal and ventral forebrain, midbrain and hindbrain regions. We find that brain region composition varies in organoids from different iPSC lines, yet regional gene expression patterns are largely reproducible across individuals. We then analyze chimpanzee and macaque cerebral organoids and find that human neuronal development proceeds at a delayed pace relative to the other two primates. Through pseudotemporal alignment of differentiation paths, we identify human-specific gene expression resolved to distinct cell states along progenitor to neuron lineages in the cortex. We find that chromatin accessibility is dynamic during cortex development, and identify instances of accessibility divergence between human and chimpanzee that correlate with human-specific gene expression and genetic change. Finally, we map human-specific expression in adult prefrontal cortex using single-nucleus RNA-seq and find developmental differences that persist into adulthood, as well as cell state-specific changes that occur exclusively in the adult brain. Our data provide a temporal cell atlas of great ape forebrain development, and illuminate dynamic gene regulatory features that are unique to humans.
956 downloads neuroscience
Miniaturized fluorescence microscopes (miniscopes) have been instrumental to monitor neural activity during unrestrained behavior and their open-source versions have helped to distribute them at an affordable cost. Generally, the footprint and weight of open-source miniscopes is sacrificed for added functionality. Here, we present NINscope: a light-weight, small footprint open-source miniscope that incorporates a high-sensitivity image sensor, an inertial measurement unit (IMU), and an LED driver for an external optogenetic probe. We highlight the advantages of NINscope by performing the first simultaneous cellular resolution (dual scope) recordings from cerebellum and cerebral cortex in unrestrained mice, revealing that the activity of both regions generally precede the onset of behavioral acceleration. At the same time, we demonstrate the optogenetic stimulation capabilities of NINscope and show that cerebral cortical activity can be driven strongly by cerebellar stimulation. Finally, we combine optogenetic stimulation of cortex with imaging in the dorsal striatum and replicate previous studies that show action space is encoded by neurons in this subcortical region. In combination with cross-platform control software NINscope is a versatile addition to the expanding toolbox of open-source miniscopes and will aid multi-region circuit investigations during unrestrained behavior.
953 downloads biochemistry
Diverse RNAs and RNA-binding proteins form phase-separated, membraneless granules in cells under stress conditions. However, the role of the prevalent mRNA methylation, m6A, and its binding proteins in stress granule (SG) assembly remain unclear. Here, we show that m6A-modified mRNAs are enriched in SGs, and that m6A-binding YTHDF proteins are critical for SG formation. Depletion of YTHDF1/3 inhibits SG formation and recruitment of m6A-modified mRNAs to SGs. Both the N-terminal intrinsically disordered region and the C-terminal m6A-binding YTH domain of YTHDF proteins are crucial for SG formation. Super-resolution imaging further reveals that YTHDF proteins are in a super-saturated state, forming clusters that reside in the periphery of and at the junctions between SG core clusters, and promote SG phase separation by reducing the activation energy barrier and critical size for condensate formation. Our results reveal a new function and mechanistic insights of the m6A-binding YTHDF proteins in regulating phase separation.
952 downloads genetics
Katrina L. Grasby, Neda Jahanshad, Jodie N Painter, Lucía Colodro-Conde, Janita Bralten, Derrek P Hibar, Penelope A Lind, Fabrizio Pizzagalli, Christopher R.K. Ching, Mary AB McMahon, Natalia Shatokhina, Leo C.P. Zsembik, Ingrid Agartz, Saud Alhusaini, Marcio AA Almeida, Dag Alnæs, Inge K Amlien, Micael Andersson, Tyler Ard, Nicola J. Armstrong, Allison Ashley-Koch, Joshua R Atkins, Manon Bernard, Rachel M. Brouwer, Elizabeth EL Buimer, Robin Bülow, Christian Bürger, Dara M. Cannon, Mallar Chakravarty, Qiang Chen, Joshua W. Cheung, Baptiste Couvy-Duchesne, Anders M Dale, Shareefa Dalvie, Tânia K de Araujo, Greig I. de Zubicaray, Sonja MC de Zwarte, Anouk den Braber, Nhat Trung Doan, Katharina Dohm, Stefan Ehrlich, Hannah-Ruth Engelbrecht, Susanne Erk, Chun Chieh Fan, Iryna O. Fedko, Sonya F Foley, Judith M Ford, Masaki Fukunaga, Melanie E. Garrett, Tian Ge, Sudheer Giddaluru, Aaron L. Goldman, Melissa J Green, Nynke A. Groenewold, Dominik Grotegerd, Tiril P. Gurholt, Boris A. Gutman, Narelle K. Hansell, Mathew A Harris, Marc B Harrison, Courtney C. Haswell, Michael Hauser, Stefan Herms, Dirk J. Heslenfeld, New Fei Ho, David Hoehn, Per Hoffmann, Laurena Holleran, Martine Hoogman, Jouke-Jan Hottenga, Masashi Ikeda, Deborah Janowitz, Iris E Jansen, Tianye Jia, Christiane Jockwitz, Ryota Kanai, Sherif Karama, Dalia Kasperaviciute, Tobias Kaufmann, Sinead Kelly, Masataka Kikuchi, Marieke Klein, Michael Knapp, Annchen R Knodt, Bernd Krämer, Max Lam, Thomas M Lancaster, Phil H. Lee, Tristram A Lett, Lindsay B Lewis, Iscia Lopes-Cendes, Michelle Luciano, Fabio Macciardi, Andre F. Marquand, Samuel R Mathias, Tracy R Melzer, Yuri Milaneschi, Nazanin Mirza-Schreiber, Jose CV Moreira, Thomas W Mühleisen, Bertram Müller-Myhsok, Pablo Najt, Soichiro Nakahara, Kwangsik Nho, Loes M Olde Loohuis, Dimitri Papadopoulos Orfanos, John F Pearson, Toni L Pitcher, Benno Pütz, Yann Quidé, Anjanibhargavi Ragothaman, Faisal M. Rashid, William R Reay, Ronny Redlich, Céline S Reinbold, Jonathan Repple, Geneviève Richard, Brandalyn C Riedel, Shannon L. Risacher, Cristiane S Rocha, Nina Roth Mota, Lauren Salminen, Arvin Saremi, Andrew J. Saykin, Fenja Schlag, Lianne Schmaal, Peter R. Schofield, Rodrigo Secolin, Chin Yang Shapland, Li Shen, Jean Shin, Elena Shumskaya, Ida E Sønderby, Emma Sprooten, Lachlan T. Strike, Katherine E Tansey, Alexander Teumer, Anbupalam Thalamuthu, Sophia I. Thomopoulos, Diana Tordesillas-Gutiérrez, Jessica A. Turner, Anne Uhlmann, Costanza Ludovica Vallerga, Dennis van der Meer, Marjolein MJ van Donkelaar, Liza van Eijk, Theo G.M. van Erp, Neeltje E.M. van Haren, Daan Van Rooij, Marie-José van Tol, Jan H Veldink, Ellen Verhoef, Esther Walton, Mingyuan Wang, Yunpeng Wang, Joanna M Wardlaw, Wei Wen, Lars T. Westlye, Christopher D. Whelan, Stephanie H. Witt, Katharina Wittfeld, Christiane Wolf, Thomas Wolfers, Jing Qin Wu, Clarissa L. Yasuda, Dario Zaremba, Zuo Zhang, Alyssa H Zhu, Marcel P. Zwiers, Eric Artiges, Amelia A. Assareh, Rosa Ayesa-Arriola, Aysenil Belger, Christine L. Brandt, Gregory G Brown, Sven Cichon, Joanne E. Curran, Gareth E. Davies, Franziska Degenhardt, Michelle F Dennis, Bruno Dietsche, Srdjan Djurovic, Colin P. Doherty, Ryan Espiritu, Daniel Garijo, Yolanda Gil, Penny A Gowland, Robert C. Green, Alexander N Häusler, Walter Heindel, Beng-Choon Ho, Wolfgang U Hoffmann, Florian Holsboer, Georg Homuth, Norbert Hosten, Clifford R. Jack, MiHyun Jang, Andreas Jansen, Nathan A Kimbrel, Knut Kolskår, Sanne Koops, Axel Krug, Kelvin O. Lim, Jurjen J. Luykx, Daniel H Mathalon, Karen A. Mather, Venkata S. Mattay, Sarah Matthews, Jaqueline Mayoral Van Son, Sarah C McEwen, Ingrid Melle, Derek W Morris, Bryon A. Mueller, Matthias Nauck, Jan E. Nordvik, Markus M Nöthen, Daniel S O'Leary, Nils Opel, Marie-Laure Paillère Martinot, G B Pike, Adrian Preda, Erin B. Quinlan, Paul E Rasser, Varun Ratnakar, Simone Reppermund, Vidar M. Steen, Paul A Tooney, Fábio R Torres, Dick J. Veltman, James T Voyvodic, Robert Whelan, Tonya White, Hidenaga Yamamori, Hieab HH Adams, Joshua C Bis, Stéphanie Debette, Charles Decarli, Myriam Fornage, Vilmundur Gudnason, Edith Hofer, M. A Ikram, Lenore Launer, W T Longstreth, Oscar L. Lopez, Bernard Mazoyer, Thomas H Mosley, Gennady V Roshchupkin, Claudia L Satizabal, Reinhold Schmidt, Sudha Seshadri, Qiong Yang, The Alzheimer's Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, Mid-Atlantic MIRECC Workgroup, SYS Consortium, The Parkinson's Progression Markers Initiative, Marina KM Alvim, David Ames, Tim J Anderson, Ole A Andreassen, Alejandro Arias-Vasquez, Mark E Bastin, Bernhard T. Baune, John Blangero, Dorret I Boomsma, Henry Brodaty, Han G Brunner, Randy L. Buckner, Jan K Buitelaar, Juan R Bustillo, Wiepke Cahn, Murray J Cairns, Vince Calhoun, Vaughan j Carr, Xavier Caseras, Svenja Caspers, Gianpiero L. Cavalleri, Fernando Cendes, Aiden Corvin, Benedicto Crespo-Facorro, John C Dalrymple-Alford, Udo Dannlowski, Eco J.C. de Geus, Ian J Deary, Norman Delanty, Chantal Depondt, Sylvane Desrivières, Gary Donohoe, Thomas Espeseth, Guillén Fernández, Simon E. Fisher, Herta Flor, Andreas J. Forstner, Clyde Francks, Barbara Franke, David C Glahn, Randy L. Gollub, Hans J Grabe, Oliver Gruber, Asta K Håberg, Ahmad R Hariri, Catharina A. Hartman, Ryota Hashimoto, Andreas Heinz, Frans A Henskens, Manon H.J. Hillegers, Pieter J. Hoekstra, Avram J. Holmes, L E Hong, William D Hopkins, Hilleke E. Hulshoff Pol, Terry L Jernigan, Erik G Jönsson, René S. Kahn, Martin A Kennedy, Tilo TJ Kircher, Peter Kochunov, John BJ Kwok, Stephanie Le Hellard, Carmel M Loughland, Nicholas G Martin, Jean-Luc Martinot, Colm McDonald, Katie L. McMahon, Andreas Meyer-Lindenberg, Patricia T Michie, Rajendra A. Morey, Bryan Mowry, Lars Nyberg, Jaap Oosterlaan, Roel A. Ophoff, Christos Pantelis, Tomáŝ Paus, Zdenka Pausova, Brenda W.J.H. Penninx, Tinca JC Polderman, Danielle Posthuma, Marcella Rietschel, Joshua L. Roffman, Laura M Rowland, Perminder S. Sachdev, Philipp G Sämann, Ulrich Schall, Gunter Schumann, Rodney J. Scott, Kang Sim, Sanjay M. Sisodiya, Jordan W. Smoller, Iris E Sommer, Beate St Pourcain, Dan J. Stein, Arthur W Toga, Julian N. Trollor, Nic JA Van der Wee, Dennis van't Ent, Henry Völzke, Henrik Walter, Bernd Weber, Daniel R Weinberger, Margaret J Wright, Juan Zhou, Jason L Stein, Paul M Thompson, Sarah E Medland
The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P ≤ 5 x 10-8); 199 survived multiple testing correction (P ≤ 8.3 x 10-10; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression and ADHD. NOTE: K.L.G. and N.J. contributed to this work as co-first authors for this preprint. J.N.P., L.C.-C., J.B., D.P.H., P.A.L., F.P. contributed to this work as co-second authors for this preprint. J.L.S., P.M.T., S.E.M. contributed to this work as co-last authors for this preprint.
951 downloads immunology
Travis K Hughes, Marc H Wadsworth, Todd M Gierahn, Tran Do, David Weiss, Priscilla R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C Tsoi, Jose Ordovas-Montanes, Johann E Gudjonsson, Robert L Modlin, J Christopher Love, Alex K Shalek
The development of high-throughput single-cell RNA-sequencing (scRNA-Seq) methodologies has empowered the characterization of complex biological samples by dramatically increasing the number of constituent cells that can be examined concurrently. Nevertheless, these approaches typically recover substantially less information per-cell as compared to lower-throughput microtiter plate-based strategies. To uncover critical phenotypic differences among cells and effectively link scRNA-Seq observations to legacy datasets, reliable detection of phenotype-defining transcripts – such as transcription factors, affinity receptors, and signaling molecules – by these methods is essential. Here, we describe a substantially improved massively-parallel scRNA-Seq protocol we term Seq-Well S^3 (“Second-Strand Synthesis”) that increases the efficiency of transcript capture and gene detection by up to 10- and 5-fold, respectively, relative to previous iterations, surpassing best-in-class commercial analogs. We first characterized the performance of Seq-Well S^3 in cell lines and PBMCs, and then examined five different inflammatory skin diseases, illustrative of distinct types of inflammation, to explore the breadth of potential immune and parenchymal cell states. Our work presents an essential methodological advance as well as a valuable resource for studying the cellular and molecular features that inform human skin inflammation.
941 downloads neuroscience
Hod Dana, Yi Sun, Boaz Mohar, Brad Hulse, Jeremy P Hasseman, Getahun Tsegaye, Arthur Tsang, Allan Wong, Ronak Patel, John J Macklin, Yang Chen, Arthur Konnerth, Vivek Jayaraman, Loren L Looger, Eric R Schreiter, Karel Svoboda, Douglas S Kim
Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics, and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and tracking large populations of neurons using 2-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.
935 downloads bioengineering
Access to quantitative, robust, yet affordable diagnostic tools is necessary to reduce global infectious disease burden. Manual microscopy has served as a bedrock for diagnostics with wide adaptability, although at a cost of tedious labor and human errors. Automated robotic microscopes are poised to enable a new era of smart field microscopy but current platforms remain cost prohibitive and largely inflexible, especially for resource poor and field settings. Here we present Octopi, a low-cost ($250-$500) and reconfigurable autonomous microscopy platform capable of automated slide scanning and correlated bright-field and fluorescence imaging. Being highly modular, it also provides a framework for new disease-specific modules to be developed. We demonstrate the power of the platform by applying it to automated detection of malaria parasites in blood smears. Specifically, we discovered a spectral shift on the order of 10 nm for DAPI-stained Plasmodium falciparum malaria parasites. This shift allowed us to detect the parasites with a low magnification (equivalent to 10x) large field of view (2.56 mm^2) module. Combined with automated slide scanning, real time computer vision and machine learning-based classification, Octopi is able to screen more than 1.5 million red blood cells per minute for parasitemia quantification, with estimated diagnostic sensitivity and specificity exceeding 90% at parasitemia of 50/ul and 100% for parasitemia higher than 150/μl. With different modules, we further showed imaging of tissue slice and sputum sample on the platform. With roughly two orders of magnitude in cost reduction, Octopi opens up the possibility of a large robotic microscope network for improved disease diagnosis while providing an avenue for collective efforts for development of modular instruments.
926 downloads bioinformatics
Kevin R Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel Burkhardt, William Chen, Kristina Yim, Antonia van den Elzen, Matthew J Hirn, Ronald R. Coifman, Natalia B Ivanova, Guy Wolf, Smita Krishnaswamy
With the advent of high-throughput technologies measuring high-dimensional biological data, there is a pressing need for visualization tools that reveal the structure and emergent patterns of data in an intuitive form. We present PHATE, a visualization method that captures both local and global nonlinear structure in data by an information-geometric distance between datapoints. We perform extensive comparison between PHATE and other tools on a variety of artificial and biological datasets, and find that it consistently preserves a range of patterns in data including continual progressions, branches, and clusters. We define a manifold preservation metric DEMaP to show that PHATE produces quantitatively better denoised embeddings than existing visualization methods. We show that PHATE is able to gain unique insight from a newly generated scRNA-seq dataset of human germ layer differentiation. Here, PHATE reveals a dynamic picture of the main developmental branches in unparalleled detail, including the identification of three novel subpopulations. Finally, we show that PHATE is applicable to a wide variety of datatypes including mass cytometry, single-cell RNA-sequencing, Hi-C, and gut microbiome data, where it can generate interpretable insights into the underlying systems.
925 downloads bioinformatics
The recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a large variety of experimental and computational pipelines for which best practices have not been established, yet. Here, we use simulations based on five scRNA-seq library protocols in combination with nine realistic differential expression (DE) setups to systematically evaluate three mapping, four imputation, seven normalisation and four differential expression testing approaches resulting in ~ 3,000 pipelines, allowing us to also assess interactions among pipeline steps. We find that choices of normalisation and library preparation protocols have the biggest impact on scRNA-seq analyses. Specifically, we find that library preparation determines the ability to detect symmetric expression differences, while normalisation dominates pipeline performance in asymmetric DE-setups. Finally, we illustrate the importance of informed choices by showing that a good scRNA-seq pipeline can have the same impact on detecting a biological signal as quadrupling the sample size.
925 downloads bioinformatics
Karen H Miga, Sergey Koren, Arang Rhie, Mitchell R. Vollger, Ariel Gershman, Andrey Bzikadze, Shelise Brooks, Edmund Howe, David Porubsky, Glennis A. Logsdon, Valerie A Schneider, Tamara Potapova, Jonathan Wood, William Chow, Joel Armstrong, Jeanne Fredrickson, Evgenia Pak, Kristof Tigyi, Milinn Kremitzki, Christopher Markovic, Valerie Maduro, Amalia Dutra, Gerard G Bouffard, Alexander M Chang, Nancy F Hansen, Françoisen Thibaud-Nissen, Anthony D Schmitt, Jon-Matthew Belton, Siddarth Selvaraj, Megan Y. Dennis, Daniela C Soto, Ruta Sahasrabudhe, Gulhan Kaya, Josh Quick, Nicholas J Loman, Nadine Holmes, Matthew Loose, Urvashi Surti, Rosa ana Risques, Tina A. Graves Lindsay, Robert Fulton, Ira Hall, Benedict Paten, Kerstin Howe, Winston Timp, Alice Young, James C. Mullikin, Pavel A Pevzner, Jennifer E. Gerton, Beth A Sullivan, Evan E Eichler, Adam M Phillippy
After nearly two decades of improvements, the current human reference genome (GRCh38) is the most accurate and complete vertebrate genome ever produced. However, no one chromosome has been finished end to end, and hundreds of unresolved gaps persist ,. The remaining gaps include ribosomal rDNA arrays, large near-identical segmental duplications, and satellite DNA arrays. These regions harbor largely unexplored variation of unknown consequence, and their absence from the current reference genome can lead to experimental artifacts and hide true variants when re-sequencing additional human genomes. Here we present a de novo human genome assembly that surpasses the continuity of GRCh38 , along with the first gapless, telomere-to-telomere assembly of a human chromosome. This was enabled by high-coverage, ultra-long-read nanopore sequencing of the complete hydatidiform mole CHM13 genome, combined with complementary technologies for quality improvement and validation. Focusing our efforts on the human X chromosome , we reconstructed the ∼2.8 megabase centromeric satellite DNA array and closed all 29 remaining gaps in the current reference, including new sequence from the human pseudoautosomal regions and cancer-testis ampliconic gene families (CT-X and GAGE). This complete chromosome X, combined with the ultra-long nanopore data, also allowed us to map methylation patterns across complex tandem repeats and satellite arrays for the first time. These results demonstrate that finishing the human genome is now within reach and will enable ongoing efforts to complete the remaining human chromosomes. : #ref-1 : #ref-2 : #ref-3
921 downloads immunology
High throughput single-cell RNA sequencing (sc-RNAseq) has become a frequently used tool to assess immune cell function and heterogeneity. Recently, the combined measurement of RNA and protein expression by sequencing was developed, which is commonly known as CITE-Seq. Acquisition of protein expression data along with transcriptome data resolves some of the limitations inherent to only assessing transcript, but also nearly doubles the sequencing read depth required per single cell. Furthermore, there is still a paucity of analysis tools to visualize combined transcript-protein datasets. Here, we describe a novel targeted transcriptomics approach that combines analysis of over 400 genes with simultaneous measurement of over 40 proteins on more than 25,000 cells. This targeted approach requires only about 1/10 of the read depth compared to a whole transcriptome approach while retaining high sensitivity for low abundance transcripts. To analyze these multi-omic transcript-protein datasets, we adapted One-SENSE for intuitive visualization of the relationship of proteins and transcripts on a single-cell level.
919 downloads neuroscience
A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity, and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation. This representation captures many aspects of place cell responses that fall outside the traditional view of a cognitive map. Furthermore, we argue that entorhinal grid cells encode a low-dimensional basis set for the predictive representation, useful for suppressing noise in predictions and extracting multiscale structure for hierarchical planning.
906 downloads biophysics
Single-molecule localization microscopy (SMLM) promises to provide truly molecular scale images of biological specimens. However, mechanical instabilities in the instrument, readout errors and sample drift constitute significant challenges and severely limit both the useable data acquisition length and the localization accuracy of single molecule emitters. Here, we developed an actively stabilized total internal fluorescence (TIRF) microscope that performs 3D real-time drift corrections and achieves a stability of ≤1 nm. Self-alignment of the emission light path and corrections of readout errors of the camera automate channel alignment and ensure localization precisions of 1-4 nm in DNA origami structures and cells for different labels. We used Feedback SMLM to measure the separation distance of signaling receptors and phosphatases in T cells. Thus, an improved SMLM enables direct distance measurements between molecules in intact cells on the scale between 1-20 nm, potentially replacing Forster resonance energy transfer (FRET) to quantify molecular interactions. In summary, by overcoming the major bottlenecks in SMLM imaging, it is possible to generate molecular images with nanometer accuracy and conduct distance measurements on the biological relevant length scales.
902 downloads developmental biology
Small RhoGTPases and Myosin-II direct cell shape changes and movements during tissue morphogenesis. Their activities are tightly regulated in space and time to specify the desired pattern of contractility that supports tissue morphogenesis. This is expected to stem from polarized surface stimuli and from polarized signaling processing inside cells. We examined this general problem in the context of cell intercalation that drives extension of the Drosophila ectoderm. In the ectoderm, G protein coupled receptors (GPCRs) and their downstream heterotrimeric G proteins (Gα and Gβγ) activate Rho1 both medial-apically, where it exhibits pulsed dynamics, and at junctions, where its activity is planar polarized (Kerridge et al., 2016; Munjal et al., 2015). However, the mechanisms responsible for polarizing Rho1 activity are unclear. In particular, it is unknown how Rho1 activity is controlled at junctions. We report a division of labor in the mechanisms of Rho1 activation in that distinct guanine exchange factors (GEFs), that serve as activators of Rho1, operate in these distinct cellular compartments. RhoGEF2 acts uniquely to activate medial-apical Rho1. Although RhoGEF2 is recruited both medial-apically and at junctions by Gα12/13-GTP, also called Concertina (Cta) in Drosophila, its activity is restricted to the medial-apical compartment. Furthermore, we characterize a novel RhoGEF, p114RhoGEF/Wireless (Wrl), and report its requirement for cell intercalation in the extending ectoderm. p114RhoGEF/Wireless activates Rho1 specifically at junctions. Strikingly it is restricted to adherens junctions and is under Gβ13F/Gγ1 control. Gβ13F/Gγ1 activates junctional Rho1 and exerts quantitative control over planar polarization of Rho1. In particular, overexpression of Gβ13F/Gγ1 leads to hyper planar polarization of Rho1 and MyoII. Finally, we found that p114RhoGEF/Wireless is absent in the mesoderm, arguing for a tissue-specific control over junctional Rho1 activity. These results shed light on the mechanisms of polarization of Rho1 activity in different cellular compartments and reveal that distinct GEFs are sensitive tuning parameters of cell contractility in remodeling epithelia.
900 downloads microbiology
John P Pribis, Libertad García-Villada, Yin Zhai, Ohad Lewin-Epstein, Anthony Wang, Jingjing Liu, Jun Xia, Qian Mei, Devon M Fitzgerald, Julia Bos, Robert Austin, Christophe Herman, David Bates, Lilach Hadany, P.J. Hastings, Susan M Rosenberg
Antibiotics can induce mutations that cause antibiotic resistance. Yet, despite their importance, mechanisms of antibiotic-promoted mutagenesis remain elusive. We report that the fluoroquinolone antibiotic ciprofloxacin (cipro) induces mutations that cause drug resistance by triggering differentiation of a mutant-generating cell subpopulation, using reactive oxygen species (ROS) to signal the sigma-S (σS) general-stress response. Cipro-generated DNA breaks activate the SOS DNA-damage response and error-prone DNA polymerases in all cells. However, mutagenesis is restricted to a cell subpopulation in which electron transfer and SOS induce ROS, which activate the σS response, allowing mutagenesis during DNA-break repair. When sorted, this small σS-response-'on' subpopulation produces most antibiotic cross-resistant mutants. An FDA-approved drug prevents σS induction specifically inhibiting antibiotic-promoted mutagenesis. Furthermore, SOS-inhibited cell division, causing multi-chromosome cells, is required for mutagenesis. The data support a model in which within-cell chromosome cooperation together with development of a 'gambler' cell subpopulation promote resistance evolution without risking most cells.
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