For the Identification of Forensically Important Diptera from Belgium and France
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Gene Discovery and Annotation Using LCM-454 Transcriptome Sequencing Scott J
Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press Methods Gene discovery and annotation using LCM-454 transcriptome sequencing Scott J. Emrich,1,2,6 W. Brad Barbazuk,3,6 Li Li,4 and Patrick S. Schnable1,4,5,7 1Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, Iowa 50010, USA; 2Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50010, USA; 3Donald Danforth Plant Science Center, St. Louis, Missouri 63132, USA; 4Interdepartmental Plant Physiology Graduate Major and Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, Iowa 50010, USA; 5Department of Agronomy and Center for Plant Genomics, Iowa State University, Ames, Iowa 50010, USA 454 DNA sequencing technology achieves significant throughput relative to traditional approaches. More than 261,000 ESTs were generated by 454 Life Sciences from cDNA isolated using laser capture microdissection (LCM) from the developmentally important shoot apical meristem (SAM) of maize (Zea mays L.). This single sequencing run annotated >25,000 maize genomic sequences and also captured ∼400 expressed transcripts for which homologous sequences have not yet been identified in other species. Approximately 70% of the ESTs generated in this study had not been captured during a previous EST project conducted using a cDNA library constructed from hand-dissected apex tissue that is highly enriched for SAMs. In addition, at least 30% of the 454-ESTs do not align to any of the ∼648,000 extant maize ESTs using conservative alignment criteria. These results indicate that the combination of LCM and the deep sequencing possible with 454 technology enriches for SAM transcripts not present in current EST collections. -
Diversity and Resource Choice of Flower-Visiting Insects in Relation to Pollen Nutritional Quality and Land Use
Diversity and resource choice of flower-visiting insects in relation to pollen nutritional quality and land use Diversität und Ressourcennutzung Blüten besuchender Insekten in Abhängigkeit von Pollenqualität und Landnutzung Vom Fachbereich Biologie der Technischen Universität Darmstadt zur Erlangung des akademischen Grades eines Doctor rerum naturalium genehmigte Dissertation von Dipl. Biologin Christiane Natalie Weiner aus Köln Berichterstatter (1. Referent): Prof. Dr. Nico Blüthgen Mitberichterstatter (2. Referent): Prof. Dr. Andreas Jürgens Tag der Einreichung: 26.02.2016 Tag der mündlichen Prüfung: 29.04.2016 Darmstadt 2016 D17 2 Ehrenwörtliche Erklärung Ich erkläre hiermit ehrenwörtlich, dass ich die vorliegende Arbeit entsprechend den Regeln guter wissenschaftlicher Praxis selbständig und ohne unzulässige Hilfe Dritter angefertigt habe. Sämtliche aus fremden Quellen direkt oder indirekt übernommene Gedanken sowie sämtliche von Anderen direkt oder indirekt übernommene Daten, Techniken und Materialien sind als solche kenntlich gemacht. Die Arbeit wurde bisher keiner anderen Hochschule zu Prüfungszwecken eingereicht. Osterholz-Scharmbeck, den 24.02.2016 3 4 My doctoral thesis is based on the following manuscripts: Weiner, C.N., Werner, M., Linsenmair, K.-E., Blüthgen, N. (2011): Land-use intensity in grasslands: changes in biodiversity, species composition and specialization in flower-visitor networks. Basic and Applied Ecology 12 (4), 292-299. Weiner, C.N., Werner, M., Linsenmair, K.-E., Blüthgen, N. (2014): Land-use impacts on plant-pollinator networks: interaction strength and specialization predict pollinator declines. Ecology 95, 466–474. Weiner, C.N., Werner, M , Blüthgen, N. (in prep.): Land-use intensification triggers diversity loss in pollination networks: Regional distinctions between three different German bioregions Weiner, C.N., Hilpert, A., Werner, M., Linsenmair, K.-E., Blüthgen, N. -
EMBL-EBI Powerpoint Presentation
Processing data from high-throughput sequencing experiments Simon Anders Use-cases for HTS · de-novo sequencing and assembly of small genomes · transcriptome analysis (RNA-Seq, sRNA-Seq, ...) • identifying transcripted regions • expression profiling · Resequencing to find genetic polymorphisms: • SNPs, micro-indels • CNVs · ChIP-Seq, nucleosome positions, etc. · DNA methylation studies (after bisulfite treatment) · environmental sampling (metagenomics) · reading bar codes Use cases for HTS: Bioinformatics challenges Established procedures may not be suitable. New algorithms are required for · assembly · alignment · statistical tests (counting statistics) · visualization · segmentation · ... Where does Bioconductor come in? Several steps: · Processing of the images and determining of the read sequencest • typically done by core facility with software from the manufacturer of the sequencing machine · Aligning the reads to a reference genome (or assembling the reads into a new genome) • Done with community-developed stand-alone tools. · Downstream statistical analyis. • Write your own scripts with the help of Bioconductor infrastructure. Solexa standard workflow SolexaPipeline · "Firecrest": Identifying clusters ⇨ typically 15..20 mio good clusters per lane · "Bustard": Base calling ⇨ sequence for each cluster, with Phred-like scores · "Eland": Aligning to reference Firecrest output Large tab-separated text files with one row per identified cluster, specifying · lane index and tile index · x and y coordinates of cluster on tile · for each -
An Open-Sourced Bioinformatic Pipeline for the Processing of Next-Generation Sequencing Derived Nucleotide Reads
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.20.050369; this version posted May 28, 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 4.0 International license. An open-sourced bioinformatic pipeline for the processing of Next-Generation Sequencing derived nucleotide reads: Identification and authentication of ancient metagenomic DNA Thomas C. Collin1, *, Konstantina Drosou2, 3, Jeremiah Daniel O’Riordan4, Tengiz Meshveliani5, Ron Pinhasi6, and Robin N. M. Feeney1 1School of Medicine, University College Dublin, Ireland 2Division of Cell Matrix Biology Regenerative Medicine, University of Manchester, United Kingdom 3Manchester Institute of Biotechnology, School of Earth and Environmental Sciences, University of Manchester, United Kingdom [email protected] 5Institute of Paleobiology and Paleoanthropology, National Museum of Georgia, Tbilisi, Georgia 6Department of Evolutionary Anthropology, University of Vienna, Austria *Corresponding Author Abstract The emerging field of ancient metagenomics adds to these Bioinformatic pipelines optimised for the processing and as- processing complexities with the need for additional steps sessment of metagenomic ancient DNA (aDNA) are needed in the separation and authentication of ancient sequences from modern sequences. Currently, there are few pipelines for studies that do not make use of high yielding DNA cap- available for the analysis of ancient metagenomic DNA ture techniques. These bioinformatic pipelines are tradition- 1 4 ally optimised for broad aDNA purposes, are contingent on (aDNA) ≠ The limited number of bioinformatic pipelines selection biases and are associated with high costs. -
Sequence Alignment/Map Format Specification
Sequence Alignment/Map Format Specification The SAM/BAM Format Specification Working Group 3 Jun 2021 The master version of this document can be found at https://github.com/samtools/hts-specs. This printing is version 53752fa from that repository, last modified on the date shown above. 1 The SAM Format Specification SAM stands for Sequence Alignment/Map format. It is a TAB-delimited text format consisting of a header section, which is optional, and an alignment section. If present, the header must be prior to the alignments. Header lines start with `@', while alignment lines do not. Each alignment line has 11 mandatory fields for essential alignment information such as mapping position, and variable number of optional fields for flexible or aligner specific information. This specification is for version 1.6 of the SAM and BAM formats. Each SAM and BAMfilemay optionally specify the version being used via the @HD VN tag. For full version history see Appendix B. Unless explicitly specified elsewhere, all fields are encoded using 7-bit US-ASCII 1 in using the POSIX / C locale. Regular expressions listed use the POSIX / IEEE Std 1003.1 extended syntax. 1.1 An example Suppose we have the following alignment with bases in lowercase clipped from the alignment. Read r001/1 and r001/2 constitute a read pair; r003 is a chimeric read; r004 represents a split alignment. Coor 12345678901234 5678901234567890123456789012345 ref AGCATGTTAGATAA**GATAGCTGTGCTAGTAGGCAGTCAGCGCCAT +r001/1 TTAGATAAAGGATA*CTG +r002 aaaAGATAA*GGATA +r003 gcctaAGCTAA +r004 ATAGCT..............TCAGC -r003 ttagctTAGGC -r001/2 CAGCGGCAT The corresponding SAM format is:2 1Charset ANSI X3.4-1968 as defined in RFC1345. -
Fanniidae, Anthomyiidae, Muscidae) Described by P
Muscoidea (Fanniidae, Anthomyiidae, Muscidae) described by P. J. M. Macquart (Insecta, Diptera) Adrian C. PONT Oxford University Museum of Natural History, Parks Road, Oxford OX1 3PW (United Kingdom) and Department of Entomology, The Natural History Museum, Cromwell Road, London SW7 5BD (United Kingdom) [email protected] Pont A. C. 2012. – Muscoidea (Fanniidae, Anthomyiidae, Muscidae) described by P. J. M. Macquart (Insecta, Diptera). Zoosystema 34 (1): 39-111. DOI : http://dx.doi.org/10.5252/z2012n1a3 ABSTRACT This paper deals with the 185 new species-group taxa that P. J. M. Macquart described in the dipteran families Fanniidae, Anthomyiidae and Muscidae, together with a further 5 species-group taxa that belong to other families, 9 replacement names that he proposed, and 1 nomen nudum. Notes are provided on the Diptera collections on which Macquart worked. In the Fanniidae, there are 8 species (and 1 replacement name), in Anthomyiidae, 33 species (and 4 replacement names), and in Muscidae, 144 species (and 4 replacement names). 85 lectotypes are newly designated in order to fix the identity of the names. The following new synonyms are proposed: in Anthomyiidae: Chortophila angusta Macquart, 1835 = Botanophila striolata (Fallén, 1824); Pegomyia basilaris Macquart, 1835 = Pegomya solennis (Meigen, 1826); Anthomyia brunnipennis Macquart, 1835, and Anthomyia fuscipennis Macquart, 1835 = Pegoplata aestiva (Meigen, 1826); Hylemyia caesia Macquart, 1835 = Anthomyia liturata (Robineau-Desvoidy, 1830); Chortophila caesia Macquart, -
Multi-Scale Analysis and Clustering of Co-Expression Networks
Multi-scale analysis and clustering of co-expression networks Nuno R. Nen´e∗1 1Department of Genetics, University of Cambridge, Cambridge, UK September 14, 2018 Abstract 1 Introduction The increasing capacity of high-throughput genomic With the advent of technologies allowing the collec- technologies for generating time-course data has tion of time-series in cell biology, the rich structure stimulated a rich debate on the most appropriate of the paths that cells take in expression space be- methods to highlight crucial aspects of data struc- came amenable to processing. Several methodologies ture. In this work, we address the problem of sparse have been crucial to carefully organize the wealth of co-expression network representation of several time- information generated by experiments [1], including course stress responses in Saccharomyces cerevisiae. network-based approaches which constitute an excel- We quantify the information preserved from the origi- lent and flexible option for systems-level understand- nal datasets under a graph-theoretical framework and ing [1,2,3]. The use of graphs for expression anal- evaluate how cross-stress features can be identified. ysis is inherently an attractive proposition for rea- This is performed both from a node and a network sons related to sparsity, which simplifies the cumber- community organization point of view. Cluster anal- some analysis of large datasets, in addition to being ysis, here viewed as a problem of network partition- mathematically convenient (see examples in Fig.1). ing, is achieved under state-of-the-art algorithms re- The properties of co-expression networks might re- lying on the properties of stochastic processes on the veal a myriad of aspects pertaining to the impact of constructed graphs. -
Lancs & Ches Muscidae & Fanniidae
The Diptera of Lancashire and Cheshire: Muscoidea, Part I by Phil Brighton 32, Wadeson Way, Croft, Warrington WA3 7JS [email protected] Version 1.0 21 December 2020 Summary This report provides a new regional checklist for the Diptera families Muscidae and Fannidae. Together with the families Anthomyiidae and Scathophagidae these constitute the superfamily Muscoidea. Overall statistics on recording activity are given by decade and hectad. Checklists are presented for each of the three Watsonian vice-counties 58, 59, and 60 detailing for each species the number of occurrences and the year of earliest and most recent record. A combined checklist showing distribution by the three vice-counties is also included, covering a total of 241 species, amounting to 68% of the current British checklist. Biodiversity metrics have been used to compare the pre-1970 and post-1970 data both in terms of the overall number of species and significant declines or increases in individual species. The Appendix reviews the national and regional conservation status of species is also discussed. Introduction manageable group for this latest regional review. Fonseca (1968) still provides the main This report is the fifth in a series of reviews of the identification resource for the British Fanniidae, diptera records for Lancashire and Cheshire. but for the Muscidae most species are covered by Previous reviews have covered craneflies and the keys and species descriptions in Gregor et al winter gnats (Brighton, 2017a), soldierflies and (2002). There have been many taxonomic changes allies (Brighton, 2017b), the family Sepsidae in the Muscidae which have rendered many of the (Brighton, 2017c) and most recently that part of names used by Fonseca obsolete, and in some the superfamily Empidoidea formerly regarded as cases erroneous. -
NGS Raw Data Analysis
NGS raw data analysis Introduc3on to Next-Generaon Sequencing (NGS)-data Analysis Laura Riva & Maa Pelizzola Outline 1. Descrip7on of sequencing plaorms 2. Alignments, QC, file formats, data processing, and tools of general use 3. Prac7cal lesson Illumina Sequencing Single base extension with incorporaon of fluorescently labeled nucleodes Library preparaon Automated cluster genera3on DNA fragmenta3on and adapter ligaon Aachment to the flow cell Cluster generaon by bridge amplifica3on of DNA fragments Sequencing Illumina Output Quality Scores Sequence Files Comparison of some exisng plaGorms 454 Ti RocheT Illumina HiSeqTM ABI 5500 (SOLiD) 2000 Amplificaon Emulsion PCR Bridge PCR Emulsion PCR Sequencing Pyrosequencing Reversible Ligaon-based reac7on terminators sequencing Paired ends/sep Yes/3kb Yes/200 bp Yes/3 kb Read length 400 bp 100 bp 75 bp Advantages Short run 7mes. The most popular Good base call Longer reads plaorm accuracy. Good improve mapping in mulplexing repe7ve regions. capability Ability to detect large structural variaons Disadvantages High reagent cost. Higher error rates in repeat sequences The Illumina HiSeq! Stacey Gabriel Libraries, lanes, and flowcells Flowcell Lanes Illumina Each reaction produces a unique Each NGS machine processes a library of DNA fragments for single flowcell containing several sequencing. independent lanes during a single sequencing run Applications of Next-Generation Sequencing Basic data analysis concepts: • Raw data analysis= image processing and base calling • Understanding Fastq • Understanding Quality scores • Quality control and read cleaning • Alignment to the reference genome • Understanding SAM/BAM formats • Samtools • Bedtools Understanding FASTQ file format FASTQ format is a text-based format for storing a biological sequence and its corresponding quality scores. -
Ballyogan and Slieve Carran, Co. Clare
ISSN 1393 – 6670 N A T I O N A L P A R K S A N D W I L D L I F E S ERVICE IMPORTANT INVERTEBRATE AREA SURVEYS: BALLYOGAN AND SLIEVE CARRAN, CO. CLARE Adam Mantell & Roy Anderson I R I S H W ILDL I F E M ANUAL S 127 National Parks and Wildlife Service (NPWS) commissions a range of reports from external contractors to provide scientific evidence and advice to assist it in its duties. The Irish Wildlife Manuals series serves as a record of work carried out or commissioned by NPWS, and is one means by which it disseminates scientific information. Others include scientific publications in peer reviewed journals. The views and recommendations presented in this report are not necessarily those of NPWS and should, therefore, not be attributed to NPWS. Front cover, small photographs from top row: Limestone pavement, Bricklieve Mountains, Co. Sligo, Andy Bleasdale; Meadow Saffron Colchicum autumnale, Lorcan Scott; Garden Tiger Arctia caja, Brian Nelson; Fulmar Fulmarus glacialis, David Tierney; Common Newt Lissotriton vulgaris, Brian Nelson; Scots Pine Pinus sylvestris, Jenni Roche; Raised bog pool, Derrinea Bog, Co. Roscommon, Fernando Fernandez Valverde; Coastal heath, Howth Head, Co. Dublin, Maurice Eakin; A deep water fly trap anemone Phelliactis sp., Yvonne Leahy; Violet Crystalwort Riccia huebeneriana, Robert Thompson Main photograph: Burren Green Calamia tridens, Brian Nelson Important Invertebrate Area Surveys: Ballyogan and Slieve Carran, Co. Clare Adam Mantell1,2 and Roy Anderson3 1 42 Kernaghan Park, Annahilt, Hillsborough, Co. Down BT26 6DF, 2 Buglife Services Ltd., Peterborough, UK, 3 1 Belvoirview Park, Belfast BT8 7BL Keywords: Ireland, the Burren, insects, invertebrates, site inventory Citation: Mantell, A. -
Sequence Data
Sequence Data SISG 2017 Ben Hayes and Hans Daetwyler Using sequence data in genomic selection • Generation of sequence data (Illumina) • Characteristics of sequence data • Quality control of raw sequence • Alignment to reference genomes • Variant Calling Using sequence data in genomic selection and GWAS • Motivation • Genome wide association study – Straight to causative mutation – Mapping recessives • Genomic selection (all hypotheses!) – No longer have to rely on LD, causative mutation actually in data set • Higher accuracy of prediction? • Not true for genotyping-by-sequencing – Better prediction across breeds? • Assumes same QTL segregating in both breeds • No longer have to rely on SNP-QTL associations holding across breeds – Better persistence of accuracy across generations Using sequence data in genomic selection and GWAS • Motivation • Genotype by sequencing – Low cost genotypes? – Need to understand how these are produced, potential errors/challenges in dealing with this data Technology – NextGenSequence • Over the past few years, the “Next Generation” of sequencing technologies has emerged. Roche: GS-FLX Applied Biosystems: SOLiD 4 Illumina: HiSeq3000, MiSeq Illumina, accessed August 2013 Sequencing Workflow • Extract DNA • Prepare libraries – ‘Cutting-up’ DNA into short fragments • Sequencing by synthesis (HiSeq, MiSeq, NextSeq, …) • Base calling from image data -> fastq • Alignment to reference genome -> bam – Or de-novo assembly • Variant calling -> vcf ‘Raw’ sequence to genotypes FASTQ File • Unfiltered • Quality metrics -
Spatial and Temporal Variability of Necrophagous Diptera from Urban to Rural Areas
Medical and Veterinary Entomology (2005) 19, 379–391 Spatial and temporal variability of necrophagous Diptera from urban to rural areas C. HWANG1,3 andB. D. TURNER1,2 1Department of Life Sciences and 2Department of Forensic Science and Drug Monitoring, King’s College London, U.K. 3Department of Bioresources, Da-Yeh University, Da-Tsen, Chang-Hua County, Taiwan (current address). Abstract. The spatio-temporal variability of necrophagous fly assemblages in a linear series of habitats from central London to the rural surroundings in the south-west was studied using bottle traps between June 2001 and September 2002. A total of 3314 individuals in 20 dipteran families were identified from 127 sampling occasions. Calliphoridae accounted for 78.6% of all the dipteran speci- mens, with Calliphora vicina Robineau-Desvoidy, being the most abundant spe- cies (2603 individuals, 46.9%). Using canonical correspondence analyses (CCA) on 72 fly taxa, six sampled sites and 36 environmental variables, three habitat types corresponding to three groups of flies were identified. These were an urban habitat characterized by C. vicina, Lucilia illustris (Meigen) and L. sericata (Meigen), a rural grassland habitat, characterized by L. caesar (Linnaeus) and a rural woodland habitat characterized by Calliphora vomitoria (Linnaeus), Phaonia subventa (Harris), Neuroctena anilis (Falle´n) and Tephrochlamys flavipes (Zetterstedt). Intermediate species (L. ampullacea Villeneuve and P. pallida (Fabricius), located between the three habitats, were also found. Temporal abun- dance of the 10 most abundant species showed fluctuations between seasons, having low numbers of captured individuals during winter. Correspondence analysis showed clearly seasonal patterns at Box Hill site. The species–habitat associations suggest habitat differentiation between necrophagous guilds in this area and may be of ecological value.