Annual Scientific Report 2013 on the Cover Structure 3Fof in the Protein Data Bank, Determined by Laponogov, I
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Ensembl Genomes: Extending Ensembl Across the Taxonomic Space P
Published online 1 November 2009 Nucleic Acids Research, 2010, Vol. 38, Database issue D563–D569 doi:10.1093/nar/gkp871 Ensembl Genomes: Extending Ensembl across the taxonomic space P. J. Kersey*, D. Lawson, E. Birney, P. S. Derwent, M. Haimel, J. Herrero, S. Keenan, A. Kerhornou, G. Koscielny, A. Ka¨ ha¨ ri, R. J. Kinsella, E. Kulesha, U. Maheswari, K. Megy, M. Nuhn, G. Proctor, D. Staines, F. Valentin, A. J. Vilella and A. Yates EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK Received August 14, 2009; Revised September 28, 2009; Accepted September 29, 2009 ABSTRACT nucleotide archives; numerous other genomes exist in states of partial assembly and annotation; thousands of Ensembl Genomes (http://www.ensemblgenomes viral genomes sequences have also been generated. .org) is a new portal offering integrated access to Moreover, the increasing use of high-throughput genome-scale data from non-vertebrate species sequencing technologies is rapidly reducing the cost of of scientific interest, developed using the Ensembl genome sequencing, leading to an accelerating rate of genome annotation and visualisation platform. data production. This not only makes it likely that in Ensembl Genomes consists of five sub-portals (for the near future, the genomes of all species of scientific bacteria, protists, fungi, plants and invertebrate interest will be sequenced; but also the genomes of many metazoa) designed to complement the availability individuals, with the possibility of providing accurate and of vertebrate genomes in Ensembl. Many of the sophisticated annotation through the similarly low-cost databases supporting the portal have been built in application of functional assays. -
Abstracts Genome 10K & Genome Science 29 Aug - 1 Sept 2017 Norwich Research Park, Norwich, Uk
Genome 10K c ABSTRACTS GENOME 10K & GENOME SCIENCE 29 AUG - 1 SEPT 2017 NORWICH RESEARCH PARK, NORWICH, UK Genome 10K c 48 KEYNOTE SPEAKERS ............................................................................................................................... 1 Dr Adam Phillippy: Towards the gapless assembly of complete vertebrate genomes .................... 1 Prof Kathy Belov: Saving the Tasmanian devil from extinction ......................................................... 1 Prof Peter Holland: Homeobox genes and animal evolution: from duplication to divergence ........ 2 Dr Hilary Burton: Genomics in healthcare: the challenges of complexity .......................................... 2 INVITED SPEAKERS ................................................................................................................................. 3 Vertebrate Genomics ........................................................................................................................... 3 Alex Cagan: Comparative genomics of animal domestication .......................................................... 3 Plant Genomics .................................................................................................................................... 4 Ksenia Krasileva: Evolution of plant Immune receptors ..................................................................... 4 Andrea Harper: Using Associative Transcriptomics to predict tolerance to ash dieback disease in European ash trees ............................................................................................................ -
Rare Variant Contribution to Human Disease in 281,104 UK Biobank Exomes W 1,19 1,19 2,19 2 2 Quanli Wang , Ryan S
https://doi.org/10.1038/s41586-021-03855-y Accelerated Article Preview Rare variant contribution to human disease W in 281,104 UK Biobank exomes E VI Received: 3 November 2020 Quanli Wang, Ryan S. Dhindsa, Keren Carss, Andrew R. Harper, Abhishek N ag, I oa nn a Tachmazidou, Dimitrios Vitsios, Sri V. V. Deevi, Alex Mackay, EDaniel Muthas, Accepted: 28 July 2021 Michael Hühn, Sue Monkley, Henric O ls so n , S eb astian Wasilewski, Katherine R. Smith, Accelerated Article Preview Published Ruth March, Adam Platt, Carolina Haefliger & Slavé PetrovskiR online 10 August 2021 P Cite this article as: Wang, Q. et al. Rare variant This is a PDF fle of a peer-reviewed paper that has been accepted for publication. contribution to human disease in 281,104 UK Biobank exomes. Nature https:// Although unedited, the content has been subjectedE to preliminary formatting. Nature doi.org/10.1038/s41586-021-03855-y (2021). is providing this early version of the typeset paper as a service to our authors and Open access readers. The text and fgures will undergoL copyediting and a proof review before the paper is published in its fnal form. Please note that during the production process errors may be discovered which Ccould afect the content, and all legal disclaimers apply. TI R A D E T A R E L E C C A Nature | www.nature.com Article Rare variant contribution to human disease in 281,104 UK Biobank exomes W 1,19 1,19 2,19 2 2 https://doi.org/10.1038/s41586-021-03855-y Quanli Wang , Ryan S. -
The ELIXIR Core Data Resources: Fundamental Infrastructure for The
Supplementary Data: The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences The “Supporting Material” referred to within this Supplementary Data can be found in the Supporting.Material.CDR.infrastructure file, DOI: 10.5281/zenodo.2625247 (https://zenodo.org/record/2625247). Figure 1. Scale of the Core Data Resources Table S1. Data from which Figure 1 is derived: Year 2013 2014 2015 2016 2017 Data entries 765881651 997794559 1726529931 1853429002 2715599247 Monthly user/IP addresses 1700660 2109586 2413724 2502617 2867265 FTEs 270 292.65 295.65 289.7 311.2 Figure 1 includes data from the following Core Data Resources: ArrayExpress, BRENDA, CATH, ChEBI, ChEMBL, EGA, ENA, Ensembl, Ensembl Genomes, EuropePMC, HPA, IntAct /MINT , InterPro, PDBe, PRIDE, SILVA, STRING, UniProt ● Note that Ensembl’s compute infrastructure physically relocated in 2016, so “Users/IP address” data are not available for that year. In this case, the 2015 numbers were rolled forward to 2016. ● Note that STRING makes only minor releases in 2014 and 2016, in that the interactions are re-computed, but the number of “Data entries” remains unchanged. The major releases that change the number of “Data entries” happened in 2013 and 2015. So, for “Data entries” , the number for 2013 was rolled forward to 2014, and the number for 2015 was rolled forward to 2016. The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences 1 Figure 2: Usage of Core Data Resources in research The following steps were taken: 1. API calls were run on open access full text articles in Europe PMC to identify articles that mention Core Data Resource by name or include specific data record accession numbers. -
PLK-1 Promotes the Merger of the Parental Genome Into A
RESEARCH ARTICLE PLK-1 promotes the merger of the parental genome into a single nucleus by triggering lamina disassembly Griselda Velez-Aguilera1, Sylvia Nkombo Nkoula1, Batool Ossareh-Nazari1, Jana Link2, Dimitra Paouneskou2, Lucie Van Hove1, Nicolas Joly1, Nicolas Tavernier1, Jean-Marc Verbavatz3, Verena Jantsch2, Lionel Pintard1* 1Programme Equipe Labe´llise´e Ligue Contre le Cancer - Team Cell Cycle & Development - Universite´ de Paris, CNRS, Institut Jacques Monod, Paris, France; 2Department of Chromosome Biology, Max Perutz Laboratories, University of Vienna, Vienna Biocenter, Vienna, Austria; 3Universite´ de Paris, CNRS, Institut Jacques Monod, Paris, France Abstract Life of sexually reproducing organisms starts with the fusion of the haploid egg and sperm gametes to form the genome of a new diploid organism. Using the newly fertilized Caenorhabditis elegans zygote, we show that the mitotic Polo-like kinase PLK-1 phosphorylates the lamin LMN-1 to promote timely lamina disassembly and subsequent merging of the parental genomes into a single nucleus after mitosis. Expression of non-phosphorylatable versions of LMN- 1, which affect lamina depolymerization during mitosis, is sufficient to prevent the mixing of the parental chromosomes into a single nucleus in daughter cells. Finally, we recapitulate lamina depolymerization by PLK-1 in vitro demonstrating that LMN-1 is a direct PLK-1 target. Our findings indicate that the timely removal of lamin is essential for the merging of parental chromosomes at the beginning of life in C. elegans and possibly also in humans, where a defect in this process might be fatal for embryo development. *For correspondence: [email protected] Introduction Competing interests: The After fertilization, the haploid gametes of the egg and sperm have to come together to form the authors declare that no genome of a new diploid organism. -
Deep Profiling of Protease Substrate Specificity Enabled by Dual Random and Scanned Human Proteome Substrate Phage Libraries
Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries Jie Zhoua, Shantao Lib, Kevin K. Leunga, Brian O’Donovanc, James Y. Zoub,d, Joseph L. DeRisic,d, and James A. Wellsa,d,e,1 aDepartment of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158; bDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305; cDepartment of Biochemistry and Biophysics, University of California, San Francisco, CA 94158; dChan Zuckerberg Biohub, San Francisco, CA 94158; and eDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158 Edited by Benjamin F. Cravatt, Scripps Research Institute, La Jolla, CA, and approved August 19, 2020 (received for review May 11, 2020) Proteolysis is a major posttranslational regulator of biology inside lysate and miss low abundance proteins and those simply not and outside of cells. Broad identification of optimal cleavage sites expressed in cell lines tested that typically express only half their and natural substrates of proteases is critical for drug discovery genomes (13). and to understand protease biology. Here, we present a method To potentially screen a larger and more diverse sequence that employs two genetically encoded substrate phage display space, investigators have developed genetically encoded substrate libraries coupled with next generation sequencing (SPD-NGS) that phage (14, 15) or yeast display libraries (16, 17). Degenerate DNA allows up to 10,000-fold deeper sequence coverage of the typical six- sequences (up to 107) encoding random peptides were fused to a to eight-residue protease cleavage sites compared to state-of-the-art phage or yeast coat protein gene for a catch-and-release strategy synthetic peptide libraries or proteomics. -
Open Targets Genetics
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.16.299271; this version posted September 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 Open Targets Genetics: An open approach to systematically prioritize causal variants 2 and genes at all published GWAS trait-associated loci 3 4 Edward Mountjoy1,2, Ellen M. Schmidt1,2, Miguel Carmona2,3, Gareth Peat2,3, Alfredo Miranda2,3, 5 Luca Fumis2,3, James Hayhurst2,3, Annalisa Buniello2,3, Jeremy Schwartzentruber1,2,3, Mohd 6 Anisul Karim1,2, Daniel Wright1,2, Andrew Hercules2,3, Eliseo Papa4, Eric Fauman5, Jeffrey C. 7 Barrett1,2, John A. Todd6, David Ochoa2,3, Ian Dunham1,2,3, Maya Ghoussaini1,2,*. 8 9 1. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 10 1SA, UK 11 2. Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 12 3. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), 13 Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK 14 4. Systems Biology, Biogen, Cambridge, MA, 02142, United States 15 5. Integrative Biology, Internal Medicine Research Unit, Pfizer Worldwide Research, 16 Development and Medical, Cambridge, MA 02139, United States 17 6. Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford 18 Biomedical Research Centre, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, 19 UK 20 * Corresponding author 21 22 23 24 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.16.299271; this version posted September 17, 2020. -
Methods in and Applications of the Sequencing of Short Non-Coding Rnas" (2013)
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Methods in and Applications of the Sequencing of Short Non- Coding RNAs Paul Ryvkin University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Ryvkin, Paul, "Methods in and Applications of the Sequencing of Short Non-Coding RNAs" (2013). Publicly Accessible Penn Dissertations. 922. https://repository.upenn.edu/edissertations/922 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/922 For more information, please contact [email protected]. Methods in and Applications of the Sequencing of Short Non-Coding RNAs Abstract Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields angingr from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non- coding RNAs, as well as a study in which they are applied to Alzheimer's Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications ot RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. -
(DDD) Project: What a Genomic Approach Can Achieve
The Deciphering Development Disorders (DDD) project: What a genomic approach can achieve RCP ADVANCED MEDICINE, LONDON FEB 5TH 2018 HELEN FIRTH DM FRCP DCH, SANGER INSTITUTE 3,000,000,000 bases in each human genome Disease & developmental Health & development disorders Fascinating facts about your genome! –~20,000 protein-coding genes –~30% of genes have a known role in disease or developmental disorders –~10,000 protein altering variants –~100 protein truncating variants –~70 de novo mutations (~1-2 coding ie. In exons of genes) Rare Disease affects 1 in 17 people •Prior to DDD, diagnostic success in patients with rare paediatric disease was poor •Not possible to diagnose many patients with current methodology in routine use– maximum benefit in this group •DDD recruited patients with severe/extreme clinical features present from early childhood with high expectation of genetic basis •Recruitment was primarily of trios (ie The Doctor Sir Luke Fildes (1887) child and both parents) ~ 90% Making a genomic diagnosis of a rare disease improves care •Accurate diagnosis is the cornerstone of good medical practice – informing management, treatment, prognosis and prevention •Enables risk to other family members to be determined enabling predictive testing with potential for surveillance and therapy in some disorders February 28th 2018 •Reduces sense of isolation, enabling better access to support and information •Curtails the diagnostic odyssey •Not just a descriptive label; identifies the fundamental cause of disease A genomic diagnosis can be a gateway to better treatment •Not just a descriptive label; identifies the fundamental cause of disease •Biallelic mutations in the CFTR gene cause Cystic Fibrosis • CFTR protein is an epithelial ion channel regulating absorption/ secretion of salt and water in the lung, sweat glands, pancreas & GI tract. -
Different Evolutionary Patterns of Snps Between Domains and Unassigned Regions in Human Protein‑Coding Sequences
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector Mol Genet Genomics (2016) 291:1127–1136 DOI 10.1007/s00438-016-1170-7 ORIGINAL ARTICLE Different evolutionary patterns of SNPs between domains and unassigned regions in human protein‑coding sequences Erli Pang1 · Xiaomei Wu2 · Kui Lin1 Received: 14 September 2015 / Accepted: 18 January 2016 / Published online: 30 January 2016 © The Author(s) 2016. This article is published with open access at Springerlink.com Abstract Protein evolution plays an important role in Furthermore, the selective strength on domains is signifi- the evolution of each genome. Because of their functional cantly greater than that on unassigned regions. In addition, nature, in general, most of their parts or sites are differently among all of the human protein sequences, there are 117 constrained selectively, particularly by purifying selection. PfamA domains in which no SNPs are found. Our results Most previous studies on protein evolution considered indi- highlight an important aspect of protein domains and may vidual proteins in their entirety or compared protein-coding contribute to our understanding of protein evolution. sequences with non-coding sequences. Less attention has been paid to the evolution of different parts within each pro- Keywords Human genome · Protein-coding sequence · tein of a given genome. To this end, based on PfamA anno- Protein domain · SNPs · Natural selection tation of all human proteins, each protein sequence can be split into two parts: domains or unassigned regions. Using this rationale, single nucleotide polymorphisms (SNPs) in Introduction protein-coding sequences from the 1000 Genomes Project were mapped according to two classifications: SNPs occur- Studying protein evolution is crucial for understanding ring within protein domains and those within unassigned the evolution of speciation and adaptation, senescence and regions. -
Comparing Tools for Non-Coding RNA Multiple Sequence Alignment Based On
Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press ES Wright 1 1 TITLE 2 RNAconTest: Comparing tools for non-coding RNA multiple sequence alignment based on 3 structural consistency 4 Running title: RNAconTest: benchmarking comparative RNA programs 5 Author: Erik S. Wright1,* 6 1 Department of Biomedical Informatics, University of Pittsburgh (Pittsburgh, PA) 7 * Corresponding author: Erik S. Wright ([email protected]) 8 Keywords: Multiple sequence alignment, Secondary structure prediction, Benchmark, non- 9 coding RNA, Consensus secondary structure 10 Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press ES Wright 2 11 ABSTRACT 12 The importance of non-coding RNA sequences has become increasingly clear over the past 13 decade. New RNA families are often detected and analyzed using comparative methods based on 14 multiple sequence alignments. Accordingly, a number of programs have been developed for 15 aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for 16 these tasks remain unclear because existing benchmarks contain too few sequences belonging to 17 only a small number of RNA families. RNAconTest (RNA consistency test) is a new 18 benchmarking approach relying on the observation that secondary structure is often conserved 19 across highly divergent RNA sequences from the same family. RNAconTest scores multiple 20 sequence alignments based on the level of consistency among known secondary structures 21 belonging to reference sequences in their output alignment. Similarly, consensus secondary 22 structure predictions are scored according to their agreement with one or more known structures 23 in a family. -
The HUPO Proteomics Standards Initiative Meeting: Towards Common Standards for Exchanging Proteomics Data Hinxton, Cambridge, UK, 19–20 October 2002
Comparative and Functional Genomics Comp Funct Genom 2003; 4: 16–19. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.232 Feature Meeting Review: The HUPO Proteomics Standards Initiative meeting: towards common standards for exchanging proteomics data Hinxton, Cambridge, UK, 19–20 October 2002 Sandra Orchard, Paul Kersey, Henning Hermjakob* and Rolf Apweiler EMBL Outstation–European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK *Correspondence to: Abstract Henning Hermjakob, EMBL Outstation–European The Proteomics Standards Initiative (PSI) aims to define community standards Bioinformatics Institute, for data representation in proteomics and to facilitate data comparison, exchange Wellcome Trust Genome and verification. Initially the fields of protein–protein interactions (PPI) and mass Campus, Hinxton, Cambridge, spectroscopy have been targeted and the inaugural meeting of the PSI addressed the UK. questions of data storage and exchange in both of these areas. The PPI group rapidly E-mail: reached consensus as to the minimum requirements for a data exchange model; an [email protected] XML draft is now being produced. The mass spectroscopy group have achieved major advances in the definition of a required data model and working groups are currently taking these discussions further. A further meeting is planned in January 2003 to Received: 14 November 2002 advance both these projects. Copyright 2003 John Wiley & Sons, Ltd. Accepted: 14 November 2002 Keywords: proteomics; spectroscopy; protein–protein interactions Introduction process, before splitting into two working parties to address the issues facing their respective fields. The Proteomics Standards Initiative was estab- lished following a meeting in April 2002, jointly organized by HUPO and NAS, at which the urgent Protein–protein interactions (PPI) group need for standardization of proteomics data was recognized.