How Uniprotkb Maps Genomes and Variants and Provides This Information
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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. -
(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. -
Annual Scientific Report 2013 on the Cover Structure 3Fof in the Protein Data Bank, Determined by Laponogov, I
EMBL-European Bioinformatics Institute Annual Scientific Report 2013 On the cover Structure 3fof in the Protein Data Bank, determined by Laponogov, I. et al. (2009) Structural insight into the quinolone-DNA cleavage complex of type IIA topoisomerases. Nature Structural & Molecular Biology 16, 667-669. © 2014 European Molecular Biology Laboratory This publication was produced by the External Relations team at the European Bioinformatics Institute (EMBL-EBI) A digital version of the brochure can be found at www.ebi.ac.uk/about/brochures For more information about EMBL-EBI please contact: [email protected] Contents Introduction & overview 3 Services 8 Genes, genomes and variation 8 Molecular atlas 12 Proteins and protein families 14 Molecular and cellular structures 18 Chemical biology 20 Molecular systems 22 Cross-domain tools and resources 24 Research 26 Support 32 ELIXIR 36 Facts and figures 38 Funding & resource allocation 38 Growth of core resources 40 Collaborations 42 Our staff in 2013 44 Scientific advisory committees 46 Major database collaborations 50 Publications 52 Organisation of EMBL-EBI leadership 61 2013 EMBL-EBI Annual Scientific Report 1 Foreword Welcome to EMBL-EBI’s 2013 Annual Scientific Report. Here we look back on our major achievements during the year, reflecting on the delivery of our world-class services, research, training, industry collaboration and European coordination of life-science data. The past year has been one full of exciting changes, both scientifically and organisationally. We unveiled a new website that helps users explore our resources more seamlessly, saw the publication of ground-breaking work in data storage and synthetic biology, joined the global alliance for global health, built important new relationships with our partners in industry and celebrated the launch of ELIXIR. -
1 Constructing the Scientific Population in the Human Genome Diversity and 1000 Genome Projects Joseph Vitti I. Introduction: P
Constructing the Scientific Population in the Human Genome Diversity and 1000 Genome Projects Joseph Vitti I. Introduction: Populations Coming into Focus In November 2012, some eleven years after the publication of the first draft sequence of a human genome, an article published in Nature reported a new ‘map’ of the human genome – created from not one, but 1,092 individuals. For many researchers, however, what was compelling was not the number of individuals sequenced, but rather the fourteen worldwide populations they represented. Comparisons that could be made within and among these populations represented new possibilities for the scientific study of human genetic variation. The paper – which has been cited over 400 times in the subsequent year – was the output of the first phase of the 1000 Genomes Project, one of several international research consortia launched with the intent of identifying and cataloguing such variation. With the project’s phase three data release, anticipated in early spring 2014, the sample size will rise to over 2500 individuals representing twenty-six populations. Each individual’s full sequence data is made publicly available online, and is also preserved through the establishment of immortal cell lines, from which DNA can be extracted and distributed. With these developments, population-based science has been made genomic, and scientific conceptions of human populations have begun to crystallize (see appendix). Such extensive biobanking and databasing of human populations is remarkable for a number of reasons, not least among them the socially charged terrain that such an enterprise inevitably must navigate. While the 1000 Genomes Project (1000G) has been relatively uncontroversial in its reception, predecessors such as the Human Genome Diversity Project (HGDP), first conceived in 1991, faced greater difficulty. -
NIH-GDS: Genomic Data Sharing
NIH-GDS: Genomic Data Sharing National Institutes of Health Data type Explain whether the research being considered for funding involves human data, non- human data, or both. Information to be included in this section: • Type of data being collected: human, non-human, or both human & non-human. • Type of genomic data to be shared: sequence, transcriptomic, epigenomic, and/or gene expression. • Level of the genomic data to be shared: Individual-level, aggregate-level, or both. • Relevant associated data to be shared: phenotype or exposure. • Information needed to interpret the data: study protocols, survey tools, data collection instruments, data dictionary, software (including version), codebook, pipeline metadata, etc. This information should be provided with unrestricted access for all data levels. Data repository Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access. For human genomic data, investigators are expected to register all studies in the database of Genotypes and Phenotypes (dbGaP) by the time data cleaning and quality control measures begin in addition to submitting the data to the relevant NIH-designated data repository (e.g., dbGaP, Gene Expression Omnibus (GEO), Sequence Read Archive (SRA), the Cancer Genomics Hub) after registration. Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan. Data in unrestricted-access repositories (e.g., The 1000 Genomes Project) are publicly available to anyone. -
Strategic Plan 2011-2016
Strategic Plan 2011-2016 Wellcome Trust Sanger Institute Strategic Plan 2011-2016 Mission The Wellcome Trust Sanger Institute uses genome sequences to advance understanding of the biology of humans and pathogens in order to improve human health. -i- Wellcome Trust Sanger Institute Strategic Plan 2011-2016 - ii - Wellcome Trust Sanger Institute Strategic Plan 2011-2016 CONTENTS Foreword ....................................................................................................................................1 Overview .....................................................................................................................................2 1. History and philosophy ............................................................................................................ 5 2. Organisation of the science ..................................................................................................... 5 3. Developments in the scientific portfolio ................................................................................... 7 4. Summary of the Scientific Programmes 2011 – 2016 .............................................................. 8 4.1 Cancer Genetics and Genomics ................................................................................ 8 4.2 Human Genetics ...................................................................................................... 10 4.3 Pathogen Variation .................................................................................................. 13 4.4 Malaria -
Browsing Genomes with Ensembl Annotation
Browsing genomes with EnsEMBL Annotation • During recent years release of large amounts of sequence data • Raw sequence data are not so useful on its own. They are most valuable when provided with comprehensive good quality annotation CCCAACAAGAATGTAAAATCTTTAAGTGCCTGTTTTCATACTTATTTGACCACCCTATCTCTAGAATCTTGCATGATG TCTAGCCCTAGTAGGATCAAAAAATACTTACAAAGCAACTGAATAGCTACATGAATAGATGGATGAATAAATGCATG GGTGGATGGATGGATTAATGAAATCATTTATATGACTTAAAGTTTGCAGAGGAGTATCATATTTGGAAGGCAGTAAG GAAGTCTGTGTAGTCGATGGTAAAGGCAATTGGGAAGTTTGTTAGGCACAATAGGTCAAAATTTGTTTTTGAAGTCC TGTTACTTCACGTTTCTTTGTTTCACTTTCTTAAAACAGGAAACTCTTTTCTATGATCATTCTTCCAGGGCCTGGCTCT TCATCTGCAACCCAGTAATATCCCTAATGTCAAAAAGCTACTGGTTTAATTCGTGCCATTTTCAAAGAGGACTACTGA ATTCTGATGTGGCTTCAAACATTTAGGTTAGGCATATCTAATGGAGAACTTGCAGCCACACTGACTTGTAGTGAAAT ATCTATTTTGAGCCTGCCCAGTGTTGCTTAAATTGTAGTTTTCCTTGCCAGCTATTCATACAAGAGATGTGAGAAGCA CCATAAAAGGCGTTGTGAGGAGTTGTGGGGGAGTGAGGGAGAGAAGAGGTTGAAAAGCTTATTAGCTGCTGTACGG TAAAAGTGAGCTCTTACGGGAATGGGAATGTAGTTTTAGCCCTCCAGGGATTCTATTTAGCCCGCCAGGAATTAACC TTGACTATAAATAGGCCATCAATGACCTTTCCAGAGAATGTTCAGAGACCTCAACTTTGTTTAGAGATCTTGTGTGGG TGGAACTTCCTGTTTGCACACAGAGCAGCATAAAGCCCAGTTGCTTTGGGAAGTGTTTGGGACCAGATGGATTGTAG GGAGTAGGGTACAATACAGTCTGTTCTCCTCCAGCTCCTTCTTTCTGCAACATGGGGAAGAACAAACTCCTTCATCC AAGTCTGGTTCTTCTCCTCTTGGTCCTCCTGCCCACAGACGCCTCAGTCTCTGGAAAACCGTGAGTTCCACACAGAG AGCGTGAAGCATGAACCTAGAGTCCTTCATTTATTGCAGATTTTTCTTTATATCATTCCTTTTTCTTTCCTATGATACT GTCATCTTCTTATCTCTAAGATTCCTTCCAGATTTTACAAATCTAGTTTACTCATTACTTGCTTACTTTTAATCATTCT TCCCCAACTCTCTGAAGCTCTAATATGCAAAGCCTTCCTAAGGGGTGTCAGAAATTTTTAGCTTTTTAAAAGAATAAA -
The Genomic Basis of Circadian and Circalunar Timing Adaptations in a Midge Tobias S
OPEN ARTICLE doi:10.1038/nature20151 The genomic basis of circadian and circalunar timing adaptations in a midge Tobias S. Kaiser1,2,3†, Birgit Poehn1,3, David Szkiba2, Marco Preussner4, Fritz J. Sedlazeck2†, Alexander Zrim2, Tobias Neumann1,2, Lam-Tung Nguyen2,5, Andrea J. Betancourt6, Thomas Hummel3,7, Heiko Vogel8, Silke Dorner1, Florian Heyd4, Arndt von Haeseler2,3,5 & Kristin Tessmar-Raible1,3 Organisms use endogenous clocks to anticipate regular environmental cycles, such as days and tides. Natural variants resulting in differently timed behaviour or physiology, known as chronotypes in humans, have not been well characterized at the molecular level. We sequenced the genome of Clunio marinus, a marine midge whose reproduction is timed by circadian and circalunar clocks. Midges from different locations show strain-specific genetic timing adaptations. We examined genetic variation in five C. marinus strains from different locations and mapped quantitative trait loci for circalunar and circadian chronotypes. The region most strongly associated with circadian chronotypes generates strain-specific differences in the abundance of calcium/calmodulin-dependent kinase II.1 (CaMKII.1) splice variants. As equivalent variants were shown to alter CaMKII activity in Drosophila melanogaster, and C. marinus (Cma)-CaMKII.1 increases the transcriptional activity of the dimer of the circadian proteins Cma-CLOCK and Cma-CYCLE, we suggest that modulation of alternative splicing is a mechanism for natural adaptation in circadian timing. Around the new or full moon, during a few specific hours surround- Our study aimed to identify the genetic basis of C. marinus adaptation ing low tide, millions of non-biting midges of the species C.