Curriculum Vitae Judith Anne Blake, Ph.D
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
GCAT|Panel, a Comprehensive Structural Variant Haplotype Map of the Iberian Population from High-Coverage Whole-Genome Sequencing
bioRxiv preprint doi: https://doi.org/10.1101/2021.07.20.453041; this version posted July 21, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing Jordi Valls-Margarit1,#, Iván Galván-Femenía2,3,#, Daniel Matías-Sánchez1,#, Natalia Blay2, Montserrat Puiggròs1, Anna Carreras2, Cecilia Salvoro1, Beatriz Cortés2, Ramon Amela1, Xavier Farre2, Jon Lerga- Jaso4, Marta Puig4, Jose Francisco Sánchez-Herrero5, Victor Moreno6,7,8,9, Manuel Perucho10,11, Lauro Sumoy5, Lluís Armengol12, Olivier Delaneau13,14, Mario Cáceres4,15, Rafael de Cid2,*,† & David Torrents1,15,* 1. Life sciences dept, Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain. 2. Genomes for Life-GCAT lab Group, Institute for Health Science Research Germans Trias i Pujol (IGTP), Badalona, 08916, Spain. 3. Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028, Barcelona, Spain (current affiliation). 4. Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, 08193, Spain. 5. High Content Genomics and Bioinformatics Unit, Institute for Health Science Research Germans Trias i Pujol (IGTP), 08916, Badalona, Spain. 6. Catalan Institute of Oncology, Hospitalet del Llobregat, 08908, Spain. 7. Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet del Llobregat, 08908, Spain. 8. CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, 28029, Spain. 9. Universitat de Barcelona (UB), Barcelona, 08007, Spain. -
Creating the Gene Ontology Resource: Design and Implementation
Resource Creating the Gene Ontology Resource: Design and Implementation The Gene Ontology Consortium2 The exponential growth in the volume of accessible biological information has generated a confusion of voices surrounding the annotation of molecular information about genes and their products. The Gene Ontology (GO) project seeks to provide a set of structured vocabularies for specific biological domains that can be used to describe gene products in any organism. This work includes building three extensive ontologies to describe molecular function, biological process, and cellular component, and providing a community database resource that supports the use of these ontologies. The GO Consortium was initiated by scientists associated with three model organism databases: SGD, the Saccharomyces Genome database; FlyBase, the Drosophila genome database; and MGD/GXD, the Mouse Genome Informatics databases. Additional model organism database groups are joining the project. Each of these model organism information systems is annotating genes and gene products using GO vocabulary terms and incorporating these annotations into their respective model organism databases. Each database contributes its annotation files to a shared GO data resource accessible to the public at http://www.geneontology.org/. The GO site can be used by the community both to recover the GO vocabularies and to access the annotated gene product data sets from the model organism databases. The GO Consortium supports the development of the GO database resource and provides tools enabling curators and researchers to query and manipulate the vocabularies. We believe that the shared development of this molecular annotation resource will contribute to the unification of biological information. As the amount of biological information has grown, it has examining microarray expression data, sequencing genotypes become increasingly important to describe and classify bio- from a population, or identifying all glycolytic enzymes is logical objects in meaningful ways. -
To Find Information About Arabidopsis Genes Leonore Reiser1, Shabari
UNIT 1.11 Using The Arabidopsis Information Resource (TAIR) to Find Information About Arabidopsis Genes Leonore Reiser1, Shabari Subramaniam1, Donghui Li1, and Eva Huala1 1Phoenix Bioinformatics, Redwood City, CA USA ABSTRACT The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive Web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene function, orthologs gene expression, mutant phenotypes, biological materials such as clones and seed stocks, genetic markers, genetic and physical maps, genome organization, images of mutant plants, protein sub-cellular localizations, publications, and the research community. The various data types are extensively interconnected and can be accessed through a variety of Web-based search and display tools. This unit primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes and genome, Additionally we describe how members of the community can share data using TAIR’s Online Annotation Submission Tool (TOAST), in order to make their published research more accessible and visible. Keywords: Arabidopsis ● databases ● bioinformatics ● data mining ● genomics INTRODUCTION The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive Web resource for the biology of Arabidopsis thaliana (Huala et al., 2001; Garcia-Hernandez et al., 2002; Rhee et al., 2003; Weems et al., 2004; Swarbreck et al., 2008, Lamesch, et al., 2010, Berardini et al., 2016). The TAIR database contains information about genes, proteins, gene expression, mutant phenotypes, germplasms, clones, genetic markers, genetic and physical maps, genome organization, publications, and the research community. In addition, seed and DNA stocks from the Arabidopsis Biological Resource Center (ABRC; Scholl et al., 2003) are integrated with genomic data, and can be ordered through TAIR. -
Long-Read Cdna Sequencing Identifies Functional Pseudogenes in the Human Transcriptome Robin-Lee Troskie1, Yohaann Jafrani1, Tim R
Troskie et al. Genome Biology (2021) 22:146 https://doi.org/10.1186/s13059-021-02369-0 SHORT REPORT Open Access Long-read cDNA sequencing identifies functional pseudogenes in the human transcriptome Robin-Lee Troskie1, Yohaann Jafrani1, Tim R. Mercer2, Adam D. Ewing1*, Geoffrey J. Faulkner1,3* and Seth W. Cheetham1* * Correspondence: adam.ewing@ mater.uq.edu.au; faulknergj@gmail. Abstract com; [email protected]. au Pseudogenes are gene copies presumed to mainly be functionless relics of evolution 1Mater Research Institute-University due to acquired deleterious mutations or transcriptional silencing. Using deep full- of Queensland, TRI Building, QLD length PacBio cDNA sequencing of normal human tissues and cancer cell lines, we 4102 Woolloongabba, Australia Full list of author information is identify here hundreds of novel transcribed pseudogenes expressed in tissue-specific available at the end of the article patterns. Some pseudogene transcripts have intact open reading frames and are translated in cultured cells, representing unannotated protein-coding genes. To assess the biological impact of noncoding pseudogenes, we CRISPR-Cas9 delete the nucleus-enriched pseudogene PDCL3P4 and observe hundreds of perturbed genes. This study highlights pseudogenes as a complex and dynamic component of the human transcriptional landscape. Keywords: Pseudogene, PacBio, Long-read, lncRNA, CRISPR Background Pseudogenes are gene copies which are thought to be defective due to frame- disrupting mutations or transcriptional silencing [1, 2]. Most human pseudogenes (72%) are derived from retrotransposition of processed mRNAs, mediated by proteins encoded by the LINE-1 retrotransposon [3, 4]. Due to the loss of parental cis-regula- tory elements, processed pseudogenes were initially presumed to be transcriptionally silent [1] and were excluded from genome-wide functional screens and most transcrip- tome analyses [2]. -
Use and Misuse of the Gene Ontology Annotations
Nature Reviews Genetics | AOP, published online 13 May 2008; doi:10.1038/nrg2363 REVIEWS Use and misuse of the gene ontology annotations Seung Yon Rhee*, Valerie Wood‡, Kara Dolinski§ and Sorin Draghici|| Abstract | The Gene Ontology (GO) project is a collaboration among model organism databases to describe gene products from all organisms using a consistent and computable language. GO produces sets of explicitly defined, structured vocabularies that describe biological processes, molecular functions and cellular components of gene products in both a computer- and human-readable manner. Here we describe key aspects of GO, which, when overlooked, can cause erroneous results, and address how these pitfalls can be avoided. The accumulation of data produced by genome-scale FIG. 1b). These characteristics of the GO structure enable research requires explicitly defined vocabularies to powerful grouping, searching and analysis of genes. describe the biological attributes of genes in order to allow integration, retrieval and computation of the Fundamental aspects of GO annotations data1. Arguably, the most successful example of system- A GO annotation associates a gene with terms in the atic description of biology is the Gene Ontology (GO) ontologies and is generated either by a curator or project2. GO is widely used in biological databases, automatically through predictive methods. Genes are annotation projects and computational analyses (there associated with as many terms as appropriate as well as are 2,960 citations for GO in version 3.0 of the ISI Web of with the most specific terms available to reflect what is Knowledge) for annotating newly sequenced genomes3, currently known about a gene. -
GCAT (NM 014291) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG204870 GCAT (NM_014291) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: GCAT (NM_014291) Human Tagged ORF Clone Tag: TurboGFP Symbol: GCAT Synonyms: KBL Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RG204870 representing NM_014291 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGTGGCCTGGGAACGCCTGGCGCGCCGCACTCTTCTGGGTGCCCCGCGGCCGCCGCGCACAGTCAGCGC TGGCCCAGCTGCGTGGCATTCTGGAGGGGGAGCTGGAAGGCATCTGCGGAGCTGGCACTTGGAAGAGTGA GCGGGTCATCACGTCCCGTCAGGGGCCGCACATCCGCGTGGACGGCGTCTCCGGAGGAATCCTTAACTTC TGTGCCAACAACTACCTGGGCCTGAGCAGCCACCCTGAGGTGATCCAGGCAGGTCTGCAGGCTCTGGAGG AGTTTGGAGCTGGCCTCAGCTCTGTCCGCTTTATCTGTGGAACCCAGAGCATCCACAAGAATCTAGAAGC AAAAATAGCCCGCTTCCACCAGCGGGAGGATGCCATCCTCTATCCCAGCTGTTATGACGCCAACGCCGGC CTCTTTGAGGCCCTGCTGACCCCAGAGGACGCAGTCCTGTCGGACGAGCTGAACCATGCCTCCATCATCG ACGGCATCCGGCTGTGCAAGGCCCACAAGTACCGCTATCGCCACCTGGACATGGCCGACCTAGAAGCCAA GCTGCAGGAGGCCCAGAAGCATCGGCTGCGCCTGGTGGCCACTGATGGGGCCTTTTCCATGGATGGCGAC ATCGCACCCCTGCAGGAGATCTGCTGCCTCGCCTCTAGATATGGTGCCCTGGTCTTCATGGATGAATGCC ATGCCACTGGCTTCCTGGGGCCCACAGGACGGGGCACAGATGAGCTGCTGGGTGTGATGGACCAGGTCAC CATCATCAACTCCACCCTGGGGAAGGCCCTGGGTGGAGCATCAGGGGGCTACACGACAGGGCCTGGGCCC CTGGTGTCCCTGCTGCGGCAGCGCGCCCGGCCATACCTCTTCTCCAACAGTCTGCCACCTGCTGTCGTTG -
The Impact of Databases on Model Organism Biology Sabina Leonelli
Re-Thinking Organisms: The Impact of Databases on Model Organism Biology Sabina Leonelli (corresponding author) ESRC Centre for Genomics in Society, University of Exeter Byrne House, St Germans Road, EX4 4PJ Exeter, UK. Tel: 0044 1392 269137 Fax: 0044 1392 269135 Email: [email protected] Rachel A. Ankeny School of History and Politics, University of Adelaide 423 Napier, Adelaide 5005 SA, AUSTRALIA. Tel: 0061 8 8303 5570 Fax: 0061 8 8303 3443 Email: [email protected] ‘Databases for model organisms promote data integration through the development and implementation of nomenclature standards, controlled vocabularies and ontologies, that allow data from different organisms to be compared and contrasted’ (Carole Bult 2002, 163) Abstract Community databases have become crucial to the collection, ordering and retrieval of data gathered on model organisms, as well as to the ways in which these data are interpreted and used across a range of research contexts. This paper analyses the impact of community databases on research practices in model organism biology by focusing on the history and current use of four community databases: FlyBase, Mouse Genome Informatics, WormBase and The Arabidopsis Information Resource. We discuss the standards used by the curators of these databases for what counts as reliable evidence, acceptable terminology, appropriate experimental set-ups and adequate materials (e.g., specimens). On the one hand, these choices are informed by the collaborative research ethos characterising most model organism communities. On the other hand, the deployment of these standards in databases reinforces this ethos and gives it concrete and precise instantiations by shaping the skills, practices, values and background knowledge required of the database users. -
Epigenetic Regulation of the Nuclear-Coded GCAT and SHMT2
www.nature.com/scientificreports OPEN Epigenetic regulation of the nuclear-coded GCAT and SHMT2 genes confers human Received: 29 October 2014 Accepted: 14 April 2015 age-associated mitochondrial Published: 22 May 2015 respiration defects Osamu Hashizume1,*, Sakiko Ohnishi1,*, Takayuki Mito1,*, Akinori Shimizu1, Kaori Ishikawa1, Kazuto Nakada1,2, Manabu Soda3, Hiroyuki Mano3, Sumie Togayachi4, Hiroyuki Miyoshi4,5, Keisuke Okita6 & Jun-Ichi Hayashi1,2,7 Age-associated accumulation of somatic mutations in mitochondrial DNA (mtDNA) has been proposed to be responsible for the age-associated mitochondrial respiration defects found in elderly human subjects. We carried out reprogramming of human fibroblast lines derived from elderly subjects by generating their induced pluripotent stem cells (iPSCs), and examined another possibility, namely that these aging phenotypes are controlled not by mutations but by epigenetic regulation. Here, we show that reprogramming of elderly fibroblasts restores age-associated mitochondrial respiration defects, indicating that these aging phenotypes are reversible and are similar to differentiation phenotypes in that both are controlled by epigenetic regulation, not by mutations in either the nuclear or the mitochondrial genome. Microarray screening revealed that epigenetic downregulation of the nuclear-coded GCAT gene, which is involved in glycine production in mitochondria, is partly responsible for these aging phenotypes. Treatment of elderly fibroblasts with glycine effectively prevented the expression of these -
The Mouse Genome Database: Integration of and Access to Knowledge About the Laboratory Mouse Judith A
D810–D817 Nucleic Acids Research, 2014, Vol. 42, Database issue Published online 26 November 2013 doi:10.1093/nar/gkt1225 The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse Judith A. Blake*, Carol J. Bult, Janan T. Eppig, James A. Kadin and Joel E. Richardson The Mouse Genome Database Groupy Bioinformatics and Computational Biology, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA Received October 1, 2013; Revised November 4, 2013; Accepted November 5, 2013 ABSTRACT genes and as a comprehensive data integration site and repository for mouse genetic, genomic and phenotypic The Mouse Genome Database (MGD) (http://www. data derived from primary literature as well as from informatics.jax.org) is the community model major data providers (1,2). organism database resource for the laboratory The central mission of the MGD is to support the trans- mouse, a premier animal model for the study of lation of information from experimental mouse models to genetic and genomic systems relevant to human uncover the genetic basis of human diseases. As a highly biology and disease. MGD maintains a comprehen- curated and comprehensive model organism database, sive catalog of genes, functional RNAs and other MGD provides web and programmatic access to a genome features as well as heritable phenotypes complete catalog of mouse genes and genome features and quantitative trait loci. The genome feature including genomic sequence and variant information. catalog is generated by the integration of computa- MGD curates and maintains the comprehensive listing of functional annotations for mouse genes using Gene tional and manual genome annotations generated Ontology (GO) terms and contributes to the development by NCBI, Ensembl and Vega/HAVANA. -
Linkage and Association Analysis of Obesity Traits Reveals Novel Loci and Interactions with Dietary N-3 Fatty Acids in an Alaska Native (Yup’Ik) Population
METABOLISM CLINICAL AND EXPERIMENTAL XX (2015) XXX– XXX Available online at www.sciencedirect.com Metabolism www.metabolismjournal.com Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup’ik) population Laura Kelly Vaughan a, Howard W. Wiener b, Stella Aslibekyan b, David B. Allison c, Peter J. Havel d, Kimber L. Stanhope d, Diane M. O’Brien e, Scarlett E. Hopkins e, Dominick J. Lemas f, Bert B. Boyer e,⁎, Hemant K. Tiwari c a Department of Biology, King University, 1350 King College Rd, Bristol, TN 37620, USA b Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA c Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL 35294, USA d Departments of Nutrition and Molecular Biosciences, University of California at Davis, 1 Shields Ave, Davis, CA 95616, USA e USACenter for Alaska Native Health Research, Institute of Arctic Biology, 311 Irving I Building, University of Alaska Fairbanks, Fairbanks, AK 99775, USA f Department of Pediatrics, Section of Neonatology, University of Colorado Anschutz Medical Campus, 13123 East 16th Ave, Aurora, CO 80045, USA ARTICLE INFO ABSTRACT Article history: Objective. To identify novel genetic markers of obesity-related traits and to identify gene- Received 16 June 2014 diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup’ik people. Accepted 28 February 2015 Material and methods. We measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. -
Gene and Alternative Splicing Annotation with AIR
Downloaded from genome.cshlp.org on May 8, 2012 - Published by Cold Spring Harbor Laboratory Press Gene and alternative splicing annotation with AIR Liliana Florea, Valentina Di Francesco, Jason Miller, et al. Genome Res. 2005 15: 54-66 Access the most recent version at doi:10.1101/gr.2889405 Supplemental http://genome.cshlp.org/content/suppl/2004/12/08/15.1.54.DC1.html Material References This article cites 49 articles, 34 of which can be accessed free at: http://genome.cshlp.org/content/15/1/54.full.html#ref-list-1 Article cited in: http://genome.cshlp.org/content/15/1/54.full.html#related-urls Creative This article is distributed exclusively by Cold Spring Harbor Laboratory Press Commons for the first six months after the full-issue publication date (see License http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/. Email alerting Receive free email alerts when new articles cite this article - sign up in the box at the service top right corner of the article or click here To subscribe to Genome Research go to: http://genome.cshlp.org/subscriptions © 2005, Published by Cold Spring Harbor Laboratory Press Downloaded from genome.cshlp.org on May 8, 2012 - Published by Cold Spring Harbor Laboratory Press Methods Gene and alternative splicing annotation with AIR Liliana Florea,1,4,5 Valentina Di Francesco,2 Jason Miller,1 Russell Turner,1 Alison Yao,2 Michael Harris,2 Brian Walenz,1 Clark Mobarry,1 Gennady V. -
Spring 2003 Final3
NCBI News National Center for Biotechnology Information National Library of Medicine National Institutes of Health Department of Health and Human Services Spring 2003 [ A Field Guide to GenBank® and NCBI Resources: First Version of Human NCBI’s Scientific Outreach and Training Program Genome Reference Sequence Debuts on Biological sequence and structure use of NCBI databases and tools. DNA’s 50th information are now used in nearly The course, called “A Field Guide every field of biological research. A to GenBank and NCBI Resources”, working knowledge of these resources is designed especially for biologists April 14, 2003 marked the and standard computational biology who work at the bench or in the field 50th anniversary of the tools are an essential part of every but use sequence and structure data description of the structure biologist’s toolkit. However, keeping in their research. All researchers, of DNA and also saw the up with these databases and tools can educators and students who work release of the first version of be challenging in this period of rapidly with biological sequence and structure the 3 billion base pair refer- changing bioinformatics resources. data should find this to be a useful ence sequence of the human introduction and survey of the genome. Annotations to the In order to help researchers keep available NCBI tools and databases. raw sequence made public on April 14 abreast of enhancements and the Because of the rapid expansion of were released on April 29 when the increasing diversity of NCBI molecu- the resources, even experienced NCBI reference genome, NCBI build 33, lar biology resources, the NCBI users will likely learn something new appeared in the NCBI Map Viewer.