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Exploring Genomes with Ensembl Prague June, 2014 Dr. Giulietta M. Spudich Ensembl EBI is an Outstation of the European Molecular Biology Laboratory. EMBL-EBI This Course Monday EBI Introduction (Giulietta) Ensembl (Giulietta) ArrayExpress (Karyn) Tuesday Phylogenies (Laura) Wednesday Proteomics (Sandra) www.ebi.ac.uk/training/Prague2014 EBI is an Outstation of the European Molecular Biology Laboratory. This Morning Ensembl Introduction Ensembl Browser Walkthrough Hands-on Exercises 11 AM Coffee BioMart 1 PM Lunch EBI is an Outstation of the European Molecular Biology Laboratory. Beginnings … 1995: 1st free-living organism: bacterium Haemophilus influenzae (1.8 million bp) 2001: First draft of the human sequence (3 gb) 2004: ‘Finished’ human sequence 2014: Polished human sequence with haplotypes (GRCh38) Today’s genomics - human 1000 Genomes Project ENCODE COURTESY OF NIH THOMAS POROSTOCKY; SOURCE: MEETINGZONE Today’s genomics – other species 6 of 24 Ensembl – Access to … 7 of 24 Ensembl Genomes - Expanding Species Bacteria, Protists, Plants, Fungi, (non-vertebrate) Metazoa 8 of 24 Ensembl Genomes – Examples http://ensemblgenomes.org Metazoa Protists Ixodes scapularis Leishmania major Schistosoma mansoni Plasmodium falciparum Anophelese gambiae Plants Arabidopsis thaliana Triticum aestivum Bacteria (10,000+) Fungi Acetobacter tropicalis Saccharomyces cerevisiae Escherichia coli Schizosaccharomyces_pombe 9 of 24 Raw sequence CGCCGGGAGAAGCGTGAGGGGACAGATTTGTGACCGGCGCGGTTTTTGTCAGCTTACTC CGGCCAAAAAAGAACTGCACCTCTGGAGCGGACTTATTTACCAAGCATTGGAGGAATATCG TAGGTAAAAATGCCTATTGGATCCAAAGAGAGGCCAACATTGCACTGCTGCGCCTCTGCTG CGCCTCGGGTGTCTTTTGCGGCGGTGGGTCGCCGCCGGGAGAAGCGTGAGGGGACAGA TTTGTGACCGGCGCGGTTTTTGTCAGCTTACTCCGGCCAAAAAAGAACTGCACCTCTGGA GCGGACTTATTTACCAAGCATTGGAGGAATATCGTAGGTAAAAATGCCTATTGGATCCAAAG AGAGGCCAACATTTTTTGAAATTTTTAAGACACGCTGCAACAAAGCAGATTTAGGACCAATA AGTCTTAATTGGTTTGAAGAACTTTCTTCAGAAGCTCCACCCTATAATTCTGAACCTGCAG ACTAAAATGGATCAAGCAGATGATGTTTCCTGTCCACTTCTAAATTCTTGTCTTAGAAGAATC TGAACATAAAAACAACAATTACGAACCAAACCTATTTAAAACTCCACAAAGGAAACCATCTTA TAATCAGCTGGCTTCAACTCCAATAATATTCAAAGAGCAAGGGCTGACTCTGCCGCTGTAC CAATCTCCTGTAAAAGAATTAGATAAATTCAAATTAGACTTAGGAAGGAATGTTCCCAATAGT AGACTAAAAGTCTTCGCACAGTGAAAT CGCCGGGAGAAGCGTGAGGGGACAGATTTGTGACCGGCGCGGTTTTTGTCAGCTTACTC CGGCCAAAAAAGAACTGCACCTCTGGAGCGGACTTATTTACCAAGCATTGGAGGAATATCG TAGGTAAAAATGCCTATTGGATCCAAAGAGAGGCCAACATTACTAAAATGGATCAAGCAGAT GATGTTTCCTGTCCACTTCTAAATTCTTGTCTTAG AATTGGTTTGAAGAACTTTCTTCAGAAGCTCCACCCTATAATTCTGAACCTGCAGTGAAAGT CCTGTTGTTCTACAATGTACACATGTAACACCACAAAGAGATAAGTCA Ensembl – unlocking the code Regulation Conserved sequence Gene Allele • Splice variants, proteins, non-coding RNA • Small and large scale sequence variation, phenotype associations • Whole genome alignments, protein trees • Potential promoters and enhancers, DNA methylation • User upload, custom data Figure adapted from the ENCODE project www.nature.com/nature/focus/encode/ 29 May 2014 11 This talk … Genome Sequencing and Browsers Ensembl Data Genes Variation Comparative Genomics Regulation Access Challenge: number of gene/protein sequences increases • UniProtKB/Swiss-Prot (e.g.Q8IU82) 542,258 • UniProtKB/TrEMBL 51,616,950 • NCBI RefSeq (e.g. NP_006570) 37,371,278 13 of 24 Is there a consensus? • Reaching a consensus coding sequence set for human and mouse. • Human 29,045 CCDS IDs -18,683 Ensembl Gene IDs (e74) • Mouse 23,093 CCDS IDs- 19,988 Ensembl GeneIDs (e72) The GENCODE set www.gencodegenes.org • Human and mouse • Not just the cds (coding sequence) • Ensembl contributes genes to GENCODE • Havana contributes genes to GENCODE • GENCODE is used by ENCODE, 1000 Genomes, and other projects. 15 of 24 This talk … Genome Sequencing and Browsers Ensembl Data Genes Variation Comparative Genomics Regulation Access Ensembl Variation Aims: • Collect, integrate and annotate all known variants • Provide tools for comparison to other genomic data • Provide a framework for access and to improve understanding Practical applications of variation Molecular and clinical medicine • Diagnosis, detection and treatment: – e.g. myotonic dystrophy, fragile X syndrome, inherited colon cancer, familial breast cancer • Pharmacogenomics "custom drugs" DNA forensics • Identification of suspects • catastrophe victims • endangered species Agriculture, livestock breeding • Disease-, insect-, and drought-resistant crops • Healthier, disease-resistant animals • Marker-assisted breeding • More nutritious produce • Reducing the costs of agriculture Anthropology, evolution, and human migration Variation Sources . dbSNP (1000 Genomes, ClinVar, etc) . ESP (Exome Sequencing Project) . UniProt . COSMIC . HGMD_Public . NHGRI-GWAS . & more … www.ensembl.org/info/genome/variation/sources_documentation Variation in the Browser Ensembl Variant Effect Predictor . Uses an Ensembl gene set to annotate: . SNPs . Indels New Interface! . Variants in regulatory regions . Structural variants REST API Web interface Perl script XM L . Publication: McLaren et al. 2010 (Bioinformatics) o v a p s o l o l s h a u c l g l n a _ t a s y i a g h t r r _ t g y s u s a t M g u s u a l e i _ S l l l o n a s M p i a a e i n n t _ r g a e o G M s a c y n d c a i o D n p l s r e n i C p o a o o a i s l r _ A h h s p p n a n o s i e y u h e c l u n p l u _ o i s a i s s P u h T s s e _ s i i r _ l _ l s e c o s _ u L p d o s a E _ h n c o c u c i s u n u i i x a c n o t d a y c i g A p lo r o v h o s m s i i r e h i o v d i i v _ e r n o r a o a n r d t _ r h e n s e i n i ig _ _ o o n o s l n s o s s t c m i m m _ e p i i p a a f t h e u u o n i s i l r u t r o t s c f i P p b a _ p i h d u l _ m c a r u a e i o h c o _ ac f t n a n n c o ra u m g _ r n e a r e _ e t u s E ic s l c r Te if ru f t n X ia O k o r a i O a h s in s a u r T op tipe S n n e h _la a o i s ip as c a r i X yzi e re i im Or P u x t uleatus te s _ a steus_ac ro _e a L Gastero p u ra us ro n M _ p e yo va a u Gadus_m orhua C tis m eu s Must ani _lu py s ela_p s_fa cif ru Da utor m i ug s nio_rerio Ailur ius_fu liar us opoda_m e ro is lanoleuca Felis_catus Petro caballus m yzo Equus_ n_m a rinus crofa Sus_s s uru us os Cio _ta cat c C na_ Bos un pa io sav _tr a_ na ign ps gn _in yi sio cu tes Tur Vi tin s s al ep lu s is c u u i n t r ri ic a Ca D p n e e e ro _ u g n s Ensembla c in s o o l n _ n p o s lu rh h t m l a T il u l i a a o a e e i b h g i s _ c c e t d m c a i r l e r t u S i e C s t O o d o d b a is la e t r n i _ i n a c _ i c r p o u e o a n c y t _ r g l l _ i r r _ s h e a l a s i s u i a g s O a _ a y v y s t r a te s p s h N o n r u g a m M m s m u y m c u _ r o o C i l _ i y r o T r a P d u s x m c i g i d u o t c c e _ c u • o e a G s c n h a I s j v b _ p m a s H c g o c i r u t e P o e e c c o a a o r D l a m r c i c u e n m _ _ l o l n o v _ h s a a o _ t m r _ i s _ b _ _ s s u t s i O c l u u g r a u i e a s e o t o p e l u l g t M a i M i r i a c i l e Whole Genome Alignmentst l o • n l R t o a d s a g y t e e n s y s Image obtained using Dendroscope (D.H. Huson and C Scornavacca, • Gene Trees Dendroscope 3: An interactive tool for rooted phylogenetic trees and networks, Syst ematic Biology, 2012 ) • Homologues Protein Families Comparative Genomics Whole genome alignments Homo sapiens ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAC-TAGGCG-GCAGAGGCGGAGC--CGCTG-TGGC---ACTGCTGCGCCTCTG-CTGCGCCTCGGGTGTCTTTTGCGGCG Ancestral sequences ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAC-TAGGCG-GCAGAGGCGGAGC--CGCTG-TGGC---TCTGCTGCGCCTCTG-CTGCGCCTCGGGTGTCTTTTGCGGCG Pan troglodytes ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAC-TAGGCG-GCAGAAGCGGAGC--CGCTG-TGGC---TCTGCTGCGCCACTG-CTGCGCCTCGGGTGTCTTTTGCGGCG Ancestral sequences ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAC-TAGGCG-GCAGAGGCGGAGC--CGCTG-TGGC---TCTGCTGCGCCTCTG-CTGCGCCTCGGGTCTCTTTTGCGGCG Gorilla gorilla gorilla ........................................................................................................................ Great apes Ancestral sequences ........................................................................................................................ Old world Pongo abelii ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAC-TAGGCG-GCAGAGGCGGAGC--CGCTG-TGGC---TGTGCTGCACCTGTG-CTGCGCCTCGGGTCTCTTTTGCGGCG monkeys Ancestral sequences ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAT-TAGGCG-GCAGAGGCGGAGC--TGCTG-TGGC--------------TCTG-CTGCGCCTCGGGTCTCTTTTGCGGCG Macaca mulatta ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCTTCTGAAAT-CAGGCG-GCAGAGGTGGAAC--TGCTGCTGGC--------------TCTG-CTGCGCCTCGGGTCTCTTTTGCGGCG Primates Ancestral sequences ACGT-GG--CCAGCGCGGGCTTGTGGCGCGAGCGTCTGAAAT-GAGGCG-GCAGAGGCGGAGC--TGCTG-TGGC--------------TCTG-CCGCGCCTCGGGTCTTTTCTGCGGCG Callithrix jacchus ACGT-GG--TCAGCGCGGGCTTGTGGCGCGAGCGTCTGAAAT-GAGGCG-GCAGAGGCGGACC--TGCTG-TGTC--------------TCTG-CCGCGCCTCCGGTCTTTTCTGCGACG Ancestral sequences ACGT-GC--CGAGAGCGGGCTTTTGGCGCGAGCGTCTGAAAT-AAGGCG-GCGGAGGCGGAGC--TGCTG-CGGCT------------------CCGCGTCTCGGGTCTTTTCTGCGGCA Mus musculus ACGG-GC--AGAGCGCGGGCTTTTCGCGGGAGCGGGAGCCGT-G----------AGGCGTTGCCGTCAGT-CAGCT-----------------ACCGCTGC------------------- Rodents Ancestral sequences ACGG-GC--AGAGCGCGGGCTTTTCGCGGGAGCGTGAGAAGT-G----------AGGCGGTGCCGTCCGT-CAGCT-----------------ACCGCAAC------------------- Rattus norvegicus ACGGCGC--AGAGCGCGGGCTTTTCGCAGGAGCGTGAGAAGT-G----------AGGCGGCGCCGTCCGT-CAGCG-----------------GCCGCAAC------------------- Glires Ancestral sequences ACGT-GC--CGAGAGCGGGCTTTTGGCGCGAGCGTCTGAAAT-AAGGCG-GCGGAGGCGGAGC--TCCTT-CAGCT------------------CCGCGTCTCGGGTCTTTTCTGCGGCA Boroeutherian Oryctolagus cuniculus ACGT-GC--CCAGAGCGGGCTTTTGGCGCGAGCGTCTGAAAA-AAGGCT-ATGGAGGCGGAGC--TCCTT-CAGCT------------------CCGCGTCTGGGGTCTTGCCTAGGGCA Ancestral sequences ACGT-GC--CGAGAGCGGGCTTTTGGCGCGAGCGTCTGAAAT-AAGGCG-GCGGAGGCGGAGC--TGCTG-CGGCT------------------CCGCGTCTCGGGTCTTTTCTGCGGCA Bos taurus ACAT-ATCCCGAGAGCAGGCTTTTGGCGCGAGAATCTGAAAC-CCGGTGGGCGGAGGTGCGGC--TGCTG-AAGTTTG----------------C--TGTCTCGGGCGG-T--------- Laurasiatheria Ancestral sequences ACGT-GCTCCGAGAGCGGGCTTTTGGCGCGAGCGTCTGAAAT-AAGGCGAGCGGAGGCGGAGC--TGCTG-GGGCTCC----------------C--TGTCTCGGGTGG-TTCTGTGGCA Canis lupus familiaris .......................................................................................................................
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  • Swabs to Genomes: a Comprehensive Workflow

    Swabs to Genomes: a Comprehensive Workflow

    UC Davis UC Davis Previously Published Works Title Swabs to genomes: a comprehensive workflow. Permalink https://escholarship.org/uc/item/3817d8gj Journal PeerJ, 3(5) ISSN 2167-8359 Authors Dunitz, Madison I Lang, Jenna M Jospin, Guillaume et al. Publication Date 2015 DOI 10.7717/peerj.960 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Swabs to genomes: a comprehensive workflow Madison I. Dunitz1,3 , Jenna M. Lang1,3 , Guillaume Jospin1, Aaron E. Darling2, Jonathan A. Eisen1 and David A. Coil1 1 UC Davis, Genome Center, USA 2 ithree institute, University of Technology Sydney, Australia 3 These authors contributed equally to this work. ABSTRACT The sequencing, assembly, and basic analysis of microbial genomes, once a painstaking and expensive undertaking, has become much easier for research labs with access to standard molecular biology and computational tools. However, there are a confusing variety of options available for DNA library preparation and sequencing, and inexperience with bioinformatics can pose a significant barrier to entry for many who may be interested in microbial genomics. The objective of the present study was to design, test, troubleshoot, and publish a simple, comprehensive workflow from the collection of an environmental sample (a swab) to a published microbial genome; empowering even a lab or classroom with limited resources and bioinformatics experience to perform it. Subjects Bioinformatics, Genomics, Microbiology Keywords Workflow, Microbial genomics, Genome sequencing, Genome assembly, Bioinformatics INTRODUCTION Thanks to decreases in cost and diYculty, sequencing the genome of a microorganism is becoming a relatively common activity in many research and educational institutions.
  • Ubin – a Manual Refining Tool for Metagenomic Bins Designed for Educational 2 Purposes 3 4 Till L.V

    Ubin – a Manual Refining Tool for Metagenomic Bins Designed for Educational 2 Purposes 3 4 Till L.V

    bioRxiv preprint doi: https://doi.org/10.1101/2020.07.15.204776; this version posted July 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 uBin – a manual refining tool for metagenomic bins designed for educational 2 purposes 3 4 Till L.V. Bornemann1, Sarah P. Esser1, Tom L. Stach1, Tim Burg2, and Alexander J. Probst1 5 6 1: Institute for Environmental Microbiology and Biotechnology, Department of Chemistry, 7 University Duisburg-Essen, Germany 8 2: Tim Burg, Im Acker 59, 56072 Koblenz, Germany 9 10 To whom the correspondence should be addressed: 11 [email protected] 12 13 Abstract 14 15 Resolving bacterial and archaeal genomes from metagenomes has revolutionized our 16 understanding of Earth’s biomes, yet producing high quality genomes from assembled 17 fragments has been an ever-standing problem. While automated binning software and their 18 combination produce prokaryotic bins in high-throughput, their manual refinement has been 19 slow and sometimes difficult. Here, we present uBin, a GUI-based, standalone bin refiner that 20 runs on all major operating platforms and was specifically designed for educational purposes. 21 When applied to the public CAMI dataset, refinement of bins was able to improve 78.9% of 22 bins by decreasing their contamination. We also applied the bin refiner as a standalone binner 23 to public metagenomes from the International Space Station and demonstrate the recovery of 24 near-complete genomes, whose replication indices indicate active proliferation of microbes in 25 Earth’s lower orbit.
  • 'Omics' Approaches to Assess the Effects of Phytochemicals in Human

    'Omics' Approaches to Assess the Effects of Phytochemicals in Human

    Downloaded from https://www.cambridge.org/core British Journal of Nutrition (2008), 99, E-Suppl. 1, ES127–ES134 doi:10.1017/S0007114508965818 q The Authors 2008 High throughput ‘omics’ approaches to assess the effects of phytochemicals . IP address: in human health studies 170.106.40.219 Jaroslava Ovesna´1*, Ondrˇej Slaby´2, Olivier Toussaint3, Milan Kodı´cˇek4, Petr Marsˇ´ık5, Vladimı´ra Pouchova´1 and Toma´sˇ Vaneˇk5 1Crop Research Institute, Drnovska´ 507, 161 06 Prague 6, Ruzyne, Czech Republic , on 2Masaryk Memorial Cancer Institute, Zluty kopec 7, 656 53 Brno, Czech Republic 01 Oct 2021 at 22:26:40 3Department of Biology, Unit of Cellular Biochemistry and Biology, University of Namur (FUNDP), 5000 Namur, Belgium 4Institute of Chemical Technology, Technicka´ 3, Praha 6, 160 00 Prague 6, Czech Republic 5Institute of Experimental Botany, Suchodol, 161 06 Prague 6, Czech Republic , subject to the Cambridge Core terms of use, available at Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents, including secondary metabolites of fruits and vegetables, may interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins) which results in metabolite content changes. Many studies have shown that food constituents may affect human health and the exact knowledge of genotypes and food constituent interactions with both genes and proteins may delay or prevent the onset of diseases. Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched.