Evolutionary superscaffolding and chromosome anchoring to improve Anopheles genome assemblies.
Autor: | Waterhouse RM; Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland. robert.waterhouse@unil.ch., Aganezov S; Department of Computer Science, Princeton University, Princeton, NJ, 08450, USA.; Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA., Anselmetti Y; ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France., Lee J; The Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA., Ruzzante L; Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland., Reijnders MJMF; Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland., Feron R; Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland., Bérard S; ISEM, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France., George P; Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA., Hahn MW; Departments of Biology and Computer Science, Indiana University, Bloomington, IN, 47405, USA., Howell PI; Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA., Kamali M; Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.; Department of Medical Entomology and Parasitology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran., Koren S; Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA., Lawson D; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK., Maslen G; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK., Peery A; Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA., Phillippy AM; Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA., Sharakhova MV; Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.; Laboratory of Ecology, Genetics and Environmental Protection, Tomsk State University, Tomsk, Russia, 634050., Tannier E; Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, Unité Mixte de Recherche 5558 Centre National de la Recherche Scientifique, 69622, Villeurbanne, France.; Institut national de recherche en informatique et en automatique, Montbonnot, 38334, Grenoble, Rhône-Alpes, France., Unger MF; Eck Institute for Global Health and Department of Biological Sciences, University of Notre Dame, Galvin Life Sciences Building, Notre Dame, IN, 46556, USA., Zhang SV; Departments of Biology and Computer Science, Indiana University, Bloomington, IN, 47405, USA., Alekseyev MA; Department of Mathematics and Computational Biology Institute, George Washington University, Ashburn, VA, 20147, USA., Besansky NJ; Eck Institute for Global Health and Department of Biological Sciences, University of Notre Dame, Galvin Life Sciences Building, Notre Dame, IN, 46556, USA., Chauve C; Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada., Emrich SJ; Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, 37996, USA., Sharakhov IV; The Interdisciplinary PhD Program in Genetics, Bioinformatics, and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA. igor@vt.edu.; Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA. igor@vt.edu.; Laboratory of Ecology, Genetics and Environmental Protection, Tomsk State University, Tomsk, Russia, 634050. igor@vt.edu. |
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Jazyk: | angličtina |
Zdroj: | BMC biology [BMC Biol] 2020 Jan 02; Vol. 18 (1), pp. 1. Date of Electronic Publication: 2020 Jan 02. |
DOI: | 10.1186/s12915-019-0728-3 |
Abstrakt: | Background: New sequencing technologies have lowered financial barriers to whole genome sequencing, but resulting assemblies are often fragmented and far from 'finished'. Updating multi-scaffold drafts to chromosome-level status can be achieved through experimental mapping or re-sequencing efforts. Avoiding the costs associated with such approaches, comparative genomic analysis of gene order conservation (synteny) to predict scaffold neighbours (adjacencies) offers a potentially useful complementary method for improving draft assemblies. Results: We evaluated and employed 3 gene synteny-based methods applied to 21 Anopheles mosquito assemblies to produce consensus sets of scaffold adjacencies. For subsets of the assemblies, we integrated these with additional supporting data to confirm and complement the synteny-based adjacencies: 6 with physical mapping data that anchor scaffolds to chromosome locations, 13 with paired-end RNA sequencing (RNAseq) data, and 3 with new assemblies based on re-scaffolding or long-read data. Our combined analyses produced 20 new superscaffolded assemblies with improved contiguities: 7 for which assignments of non-anchored scaffolds to chromosome arms span more than 75% of the assemblies, and a further 7 with chromosome anchoring including an 88% anchored Anopheles arabiensis assembly and, respectively, 73% and 84% anchored assemblies with comprehensively updated cytogenetic photomaps for Anopheles funestus and Anopheles stephensi. Conclusions: Experimental data from probe mapping, RNAseq, or long-read technologies, where available, all contribute to successful upgrading of draft assemblies. Our evaluations show that gene synteny-based computational methods represent a valuable alternative or complementary approach. Our improved Anopheles reference assemblies highlight the utility of applying comparative genomics approaches to improve community genomic resources. |
Databáze: | MEDLINE |
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