Integrating Natural History Collections and Comparative Genomics to Study Royalsocietypublishing.Org/Journal/Rstb the Genetic Architecture of Convergent Evolution
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CENTRE for POPULATION GENOMICS Strategic Plan 2021-2022 CENTRE for POPULATION GENOMICS Strategic Plan 2021-2022
CENTRE FOR POPULATION GENOMICS Strategic Plan 2021-2022 CENTRE FOR POPULATION GENOMICS Strategic Plan 2021-2022 • Plan-on-a-page page 3 • Vision page 4 • Purpose page 5 • Goals page 6 • Objectives page 7 • Goal 1 detail page 8 - 10 • Goal 2 detail page 11 - 13 • Goal 3 detail page 14 - 16 • Goal 4 detail page 17 - 19 • Principles page 20 • Operating model page 21 - 25 • Operational plan page 26 • Monitoring & evaluation plan page 27 – 28 • Team values page 29 CENTRE FOR POPULATION GENOMICS Strategic Plan-on-a-page 2021-2022 Vision: A world in which genomic information enables comprehensive disease prediction, accurate diagnosis and effective therapeutics for all people Purpose: To establish respectful partnerships with diverse communities, collect and analyse genomic data at transformative scale and drive genomic discovery and equitable genomic medicine in Australia Goals: Community Computational Genomic Scientific & medical partnerships infrastructure datasets knowledge Principles: Respect Diversity Openness Scalability Connectedness 3 CENTRE FOR POPULATION GENOMICS Strategic Plan 2021-2022 Vision: A world in which genomic information enables comprehensive disease prediction, accurate diagnosis and effective therapeutics for all people • The next decade will see a transformation of medicine and biology, driven in part by an explosion in our understanding of the connections between human genetic variation and individuals’ traits. This knowledge will allow the dissection of the biological basis of human traits, improve the prediction and diagnosis of disease, and accelerate the discovery and validation of new therapeutic targets. Key to these discoveries will be population genomics: the generation and analysis of massive-scale data sets of human genetic variation, combined with information on health and clinical outcomes. -
Herpetofaunal Survey of the Ongeluksnek (Malekgalonyane) Nature Reserve in the Foothills of the Drakensberg, Eastern Cape Province, South Africa
Herpetology Notes, volume 13: 717-730 (2020) (published online on 25 August 2020) Herpetofaunal survey of the Ongeluksnek (Malekgalonyane) Nature Reserve in the foothills of the Drakensberg, Eastern Cape Province, South Africa Werner Conradie1,2,* Brian Reeves3, Sandile Mdoko3, Lwandiso Pamla3, and Oyama Gxabhu3 Abstract. The results of a herpetofaunal survey of Ongeluksnek Nature Reserve, Eastern Cape Province, South Africa are presented here. Combination of visual encounter survey methods and standard Y-shape trap arrays were used to conduct the survey. A total of 26 species (eight amphibians and 18 reptiles) were recorded, representing 29 quarter-degree grid cell records, of which 62% represented the first records for these units. Furthermore, we document the presence of three species of snakes (Crotaphopeltis hotamboeia, Hemachatus haemachatus and Homoroselaps lacteus) for the first time for the whole degree square of 3028 (approx. 100 km2). This study highlights the need to survey poorly known regions to enable us to understand and document the full distributional extent of species. We also discuss the impact of uncontrolled fires on the absence of grassland specialised species during our survey. Keywords. Amphibia, Reptilia, karroid, conservation, biodiversity, fire Introduction has been done in the southern and western regions (e.g. Branch and Braack, 1987), while the northern and The herpetofaunal richness of South Africa is central areas associated with the former homelands of considered to be amongst the highest in the world the Ciskei and Transkei remained poorly surveyed. In (Branch, 1998; Bates et al., 2014; Du Preez and recent years a series of rapid biodiversity studies has Carruthers, 2017; Tolley et al., 2019). -
13 Genomics and Bioinformatics
Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 799 13 GENOMICS AND BIOINFORMATICS Spencer Muse, PhD Chapter Contents 13.1 Introduction 13.1.1 The Central Dogma: DNA to RNA to Protein 13.2 Core Laboratory Technologies 13.2.1 Gene Sequencing 13.2.2 Whole Genome Sequencing 13.2.3 Gene Expression 13.2.4 Polymorphisms 13.3 Core Bioinformatics Technologies 13.3.1 Genomics Databases 13.3.2 Sequence Alignment 13.3.3 Database Searching 13.3.4 Hidden Markov Models 13.3.5 Gene Prediction 13.3.6 Functional Annotation 13.3.7 Identifying Differentially Expressed Genes 13.3.8 Clustering Genes with Shared Expression Patterns 13.4 Conclusion Exercises Suggested Reading At the conclusion of this chapter, the reader will be able to: & Discuss the basic principles of molecular biology regarding genome science. & Describe the major types of data involved in genome projects, including technologies for collecting them. 799 Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 800 800 CHAPTER 13 GENOMICS AND BIOINFORMATICS & Describe practical applications and uses of genomic data. & Understand the major topics in the field of bioinformatics and DNA sequence analysis. & Use key bioinformatics databases and web resources. 13.1 INTRODUCTION In April 2003, sequencing of all three billion nucleotides in the human genome was declared complete. This landmark of modern science brought with it high hopes for the understanding and treatment of human genetic disorders. There is plenty of evidence to suggest that the hopes will become reality—1631 human genetic diseases are now associated with known DNA sequences, compared to the less than 100 that were known at the initiation of the Human Genome Project (HGP) in 1990. -
Freshwater Fishes
WESTERN CAPE PROVINCE state oF BIODIVERSITY 2007 TABLE OF CONTENTS Chapter 1 Introduction 2 Chapter 2 Methods 17 Chapter 3 Freshwater fishes 18 Chapter 4 Amphibians 36 Chapter 5 Reptiles 55 Chapter 6 Mammals 75 Chapter 7 Avifauna 89 Chapter 8 Flora & Vegetation 112 Chapter 9 Land and Protected Areas 139 Chapter 10 Status of River Health 159 Cover page photographs by Andrew Turner (CapeNature), Roger Bills (SAIAB) & Wicus Leeuwner. ISBN 978-0-620-39289-1 SCIENTIFIC SERVICES 2 Western Cape Province State of Biodiversity 2007 CHAPTER 1 INTRODUCTION Andrew Turner [email protected] 1 “We live at a historic moment, a time in which the world’s biological diversity is being rapidly destroyed. The present geological period has more species than any other, yet the current rate of extinction of species is greater now than at any time in the past. Ecosystems and communities are being degraded and destroyed, and species are being driven to extinction. The species that persist are losing genetic variation as the number of individuals in populations shrinks, unique populations and subspecies are destroyed, and remaining populations become increasingly isolated from one another. The cause of this loss of biological diversity at all levels is the range of human activity that alters and destroys natural habitats to suit human needs.” (Primack, 2002). CapeNature launched its State of Biodiversity Programme (SoBP) to assess and monitor the state of biodiversity in the Western Cape in 1999. This programme delivered its first report in 2002 and these reports are updated every five years. The current report (2007) reports on the changes to the state of vertebrate biodiversity and land under conservation usage. -
Genomics and Its Impact on Science and Society: the Human Genome Project and Beyond
DOE/SC-0083 Genomics and Its Impact on Science and Society The Human Genome Project and Beyond U.S. Department of Energy Genome Research Programs: genomics.energy.gov A Primer ells are the fundamental working units of every living system. All the instructions Cneeded to direct their activities are contained within the chemical DNA (deoxyribonucleic acid). DNA from all organisms is made up of the same chemical and physical components. The DNA sequence is the particular side-by-side arrangement of bases along the DNA strand (e.g., ATTCCGGA). This order spells out the exact instruc- tions required to create a particular organism with protein complex its own unique traits. The genome is an organism’s complete set of DNA. Genomes vary widely in size: The smallest known genome for a free-living organism (a bac- terium) contains about 600,000 DNA base pairs, while human and mouse genomes have some From Genes to Proteins 3 billion (see p. 3). Except for mature red blood cells, all human cells contain a complete genome. Although genes get a lot of attention, the proteins DNA in each human cell is packaged into 46 chro- perform most life functions and even comprise the mosomes arranged into 23 pairs. Each chromosome is majority of cellular structures. Proteins are large, complex a physically separate molecule of DNA that ranges in molecules made up of chains of small chemical com- length from about 50 million to 250 million base pairs. pounds called amino acids. Chemical properties that A few types of major chromosomal abnormalities, distinguish the 20 different amino acids cause the including missing or extra copies or gross breaks and protein chains to fold up into specific three-dimensional rejoinings (translocations), can be detected by micro- structures that define their particular functions in the cell. -
Genetic Effects on Microsatellite Diversity in Wild Emmer Wheat (Triticum Dicoccoides) at the Yehudiyya Microsite, Israel
Heredity (2003) 90, 150–156 & 2003 Nature Publishing Group All rights reserved 0018-067X/03 $25.00 www.nature.com/hdy Genetic effects on microsatellite diversity in wild emmer wheat (Triticum dicoccoides) at the Yehudiyya microsite, Israel Y-C Li1,3, T Fahima1,MSRo¨der2, VM Kirzhner1, A Beiles1, AB Korol1 and E Nevo1 1Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel; 2Institute for Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany This study investigated allele size constraints and clustering, diversity. Genome B appeared to have a larger average and genetic effects on microsatellite (simple sequence repeat number (ARN), but lower variance in repeat number 2 repeat, SSR) diversity at 28 loci comprising seven types of (sARN), and smaller number of alleles per locus than genome tandem repeated dinucleotide motifs in a natural population A. SSRs with compound motifs showed larger ARN than of wild emmer wheat, Triticum dicoccoides, from a shade vs those with perfect motifs. The effects of replication slippage sun microsite in Yehudiyya, northeast of the Sea of Galilee, and recombinational effects (eg, unequal crossing over) on Israel. It was found that allele distribution at SSR loci is SSR diversity varied with SSR motifs. Ecological stresses clustered and constrained with lower or higher boundary. (sun vs shade) may affect mutational mechanisms, influen- This may imply that SSR have functional significance and cing the level of SSR diversity by both processes. natural constraints. -
Gene Prediction and Genome Annotation
A Crash Course in Gene and Genome Annotation Lieven Sterck, Bioinformatics & Systems Biology VIB-UGent [email protected] ProCoGen Dissemination Workshop, Riga, 5 nov 2013 “Conifer sequencing: basic concepts in conifer genomics” “This Project is financially supported by the European Commission under the 7th Framework Programme” Genome annotation: finding the biological relevant features on a raw genomic sequence (in a high throughput manner) ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Thx to: BSB - annotation team • Lieven Sterck (Ectocarpus, higher plants, conifers, … ) • Yao-cheng Lin (Fungi, conifers, …) • Stephane Rombauts (green alga, mites, …) • Bram Verhelst (green algae) • Pierre Rouzé • Yves Van de Peer ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Annotation experience • Plant genomes : A.thaliana & relatives (e.g. A.lyrata), Poplar, Physcomitrella patens, Medicago, Tomato, Vitis, Apple, Eucalyptus, Zostera, Spruce, Oak, Orchids … • Fungal genomes: Laccaria bicolor, Melampsora laricis- populina, Heterobasidion, other basidiomycetes, Glomus intraradices, Pichia pastoris, Geotrichum Candidum, Candida ... • Algal genomes: Ostreococcus spp, Micromonas, Bathycoccus, Phaeodactylum (and other diatoms), E.hux, Ectocarpus, Amoebophrya … • Animal genomes: Tetranychus urticae, Brevipalpus spp (mites), ... ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Why genome annotation? • Raw sequence data is not useful for most biologists • To be meaningful to them it has to be converted into biological significant knowledge -
Small Variants Frequently Asked Questions (FAQ) Updated September 2011
Small Variants Frequently Asked Questions (FAQ) Updated September 2011 Summary Information for each Genome .......................................................................................................... 3 How does Complete Genomics map reads and call variations? ........................................................................... 3 How do I assess the quality of a genome produced by Complete Genomics?................................................ 4 What is the difference between “Gross mapping yield” and “Both arms mapped yield” in the summary file? ............................................................................................................................................................................. 5 What are the definitions for Fully Called, Partially Called, Half-Called and No-Called?............................ 5 In the summary-[ASM-ID].tsv file, how is the number of homozygous SNPs calculated? ......................... 5 In the summary-[ASM-ID].tsv file, how is the number of heterozygous SNPs calculated? ....................... 5 In the summary-[ASM-ID].tsv file, how is the total number of SNPs calculated? .......................................... 5 In the summary-[ASM-ID].tsv file, what regions of the genome are included in the “exome”? .............. 6 In the summary-[ASM-ID].tsv file, how is the number of SNPs in the exome calculated? ......................... 6 In the summary-[ASM-ID].tsv file, how are variations in potentially redundant regions of the genome counted? ..................................................................................................................................................................... -
Advances in Genomics for Drug Development
G C A T T A C G G C A T genes Review Advances in Genomics for Drug Development Roberto Spreafico , Leah B. Soriaga, Johannes Grosse, Herbert W. Virgin and Amalio Telenti * Vir Biotechnology, Inc., San Francisco, CA 94158, USA; Rspreafi[email protected] (R.S.); [email protected] (L.B.S.); [email protected] (J.G.); [email protected] (H.W.V.) * Correspondence: [email protected] Received: 24 July 2020; Accepted: 13 August 2020; Published: 15 August 2020 Abstract: Drug development (target identification, advancing drug leads to candidates for preclinical and clinical studies) can be facilitated by genetic and genomic knowledge. Here, we review the contribution of population genomics to target identification, the value of bulk and single cell gene expression analysis for understanding the biological relevance of a drug target, and genome-wide CRISPR editing for the prioritization of drug targets. In genomics, we discuss the different scope of genome-wide association studies using genotyping arrays, versus exome and whole genome sequencing. In transcriptomics, we discuss the information from drug perturbation and the selection of biomarkers. For CRISPR screens, we discuss target discovery, mechanism of action and the concept of gene to drug mapping. Harnessing genetic support increases the probability of drug developability and approval. Keywords: druggability; loss-of-function; CRISPR 1. Introduction For over 20 years, genomics has been used as a tool for accelerating drug development. Various conceptual approaches and techniques assist target identification, target prioritization and tractability, as well as the prediction of outcomes from pharmacological perturbations. These basic premises are now supported by a rapid expansion of population genomics initiatives (sequencing or genotyping of hundreds of thousands of individuals), in-depth understanding of disease and drug perturbation at the tissue and single-cell level as measured by transcriptome analysis, and by the capacity to screen for loss of function or activation of genes, genome-wide, using CRISPR technologies. -
The Evolution and Genomic Basis of Beetle Diversity
The evolution and genomic basis of beetle diversity Duane D. McKennaa,b,1,2, Seunggwan Shina,b,2, Dirk Ahrensc, Michael Balked, Cristian Beza-Bezaa,b, Dave J. Clarkea,b, Alexander Donathe, Hermes E. Escalonae,f,g, Frank Friedrichh, Harald Letschi, Shanlin Liuj, David Maddisonk, Christoph Mayere, Bernhard Misofe, Peyton J. Murina, Oliver Niehuisg, Ralph S. Petersc, Lars Podsiadlowskie, l m l,n o f l Hans Pohl , Erin D. Scully , Evgeny V. Yan , Xin Zhou , Adam Slipinski , and Rolf G. Beutel aDepartment of Biological Sciences, University of Memphis, Memphis, TN 38152; bCenter for Biodiversity Research, University of Memphis, Memphis, TN 38152; cCenter for Taxonomy and Evolutionary Research, Arthropoda Department, Zoologisches Forschungsmuseum Alexander Koenig, 53113 Bonn, Germany; dBavarian State Collection of Zoology, Bavarian Natural History Collections, 81247 Munich, Germany; eCenter for Molecular Biodiversity Research, Zoological Research Museum Alexander Koenig, 53113 Bonn, Germany; fAustralian National Insect Collection, Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT 2601, Australia; gDepartment of Evolutionary Biology and Ecology, Institute for Biology I (Zoology), University of Freiburg, 79104 Freiburg, Germany; hInstitute of Zoology, University of Hamburg, D-20146 Hamburg, Germany; iDepartment of Botany and Biodiversity Research, University of Wien, Wien 1030, Austria; jChina National GeneBank, BGI-Shenzhen, 518083 Guangdong, People’s Republic of China; kDepartment of Integrative Biology, Oregon State -
Whole-Genome Analysis of Polymorphism and Divergence in Drosophila Simulans David J
Washington University School of Medicine Digital Commons@Becker Open Access Publications 2007 Population genomics: Whole-genome analysis of polymorphism and divergence in Drosophila simulans David J. Begun University of California - Davis Alisha K. Holloway University of California - Davis Kristian Stevens University of California - Davis LaDeana W. Hillier Washington University School of Medicine in St. Louis Yu-Ping Poh University of California - Davis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Part of the Medicine and Health Sciences Commons Recommended Citation Begun, David J.; Holloway, Alisha K.; Stevens, Kristian; Hillier, LaDeana W.; Poh, Yu-Ping; Hahn, Matthew W.; Nista, Phillip M.; Jones, Corbin D.; Kern, Andrew D.; Dewey, Colin N.; Pachter, Lior; Myers, Eugene; and Langley, Charles H., ,"Population genomics: Whole-genome analysis of polymorphism and divergence in Drosophila simulans." PLoS Biology.,. e310. (2007). https://digitalcommons.wustl.edu/open_access_pubs/877 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors David J. Begun, Alisha K. Holloway, Kristian Stevens, LaDeana W. Hillier, Yu-Ping Poh, Matthew W. Hahn, Phillip M. Nista, Corbin D. Jones, Andrew D. Kern, Colin N. Dewey, Lior Pachter, Eugene Myers, and Charles H. Langley This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/877 PLoS BIOLOGY Population Genomics: Whole-Genome Analysis of Polymorphism and Divergence in Drosophila simulans David J. -
Population and Comparative Genomics Inform Our Understanding of Bacterial Species Diversity in the Soil
Chapter 11 Population and Comparative Genomics Inform Our Understanding of Bacterial Species Diversity in the Soil Margaret A. Riley 11.1 Introduction The diversity of soil bacteria is simply staggering. According to Torsvik and colleagues (Torsvik et al. 1990; Torsvik and Ovreas 2002), species diversity in soil samples is so high that our most powerful methods of estimation provide only the crudest measure of its magnitude. Nonetheless, many such estimates exist, and they suggest that a single gram of soil may contain over 10 billion microbial cells and more than 1,800 bacterial species (Torsvik and Ovreas 2002; Gans et al. 2005; Zhang et al. 2008). An equally compelling estimate is provided by Dykhuizen (Dykhuizen and Dean 2004), who examined levels of genetic diversity in soil bacteria and predicted that 30 g of forest soil contains over half a million species! As our methods of empirically estimating bacterial diversity improve, so to do our methods of mathematically refining these numbers. For example, some analyti- cal methods now take into account the fact that there are very few common soil species and untold numbers of rare species (Youssef and Elshahed 2009; Schloss and Handelsman 2006). These refinements push our estimates of bacterial diversity to over a million species per gram of soil (Gans et al. 2005). To put these numbers into perspective, similar studies of the human gastrointestinal tract predict a mere 400 distinct bacterial phylotypes (Rajilic-Stojanovic et al. 2007). This staggering level of species diversity is even more remarkable when one considers that the number of prokaryotes reported in the National Center for Biotechnology Informa- tion molecular database is only about 15,111 (Sayers et al.