metaVaR: introducing metavariant species models for reference-free metagenomic-based population genomics
| Autor: | Pierre Peterlongo, Christophe Ambroise, Mohammed-Amin Madoui, Romuald Laso-Jadart |
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| Přispěvatelé: | Génomique métabolique (UMR 8030), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Mathématiques et Modélisation d'Evry (LaMME), Université d'Évry-Val-d'Essonne (UEVE)-ENSIIE-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Université d'Évry-Val-d'Essonne (UEVE), Université d'Évry-Val-d'Essonne (UEVE)-ENSIIE-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Transcriptome
Population genomics 0302 clinical medicine Invertebrate Genomics Natural Selection Cluster Analysis 0303 health sciences education.field_of_study Multidisciplinary Natural selection Bacterial Genomics Applied Mathematics Simulation and Modeling Microbial Genetics Genomics Physical Sciences [SDE]Environmental Sciences Medicine Algorithms Research Article Evolutionary Processes Science Population Single-nucleotide polymorphism Sequence alignment Computational biology Microbial Genomics Biology Research and Analysis Methods Microbiology 03 medical and health sciences Clustering Algorithms Genetics Bacterial Genetics Selection Genetic Cluster analysis education 030304 developmental biology Evolutionary Biology Models Genetic Computational Biology Genetic Variation Biology and Life Sciences Bacteriology Genome Analysis Genetics Population Metagenomics Animal Genomics [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] [SDE.BE]Environmental Sciences/Biodiversity and Ecology 030217 neurology & neurosurgery Software Mathematics Reference genome |
| Zdroj: | PLoS ONE, Vol 15, Iss 12, p e0244637 (2020) PLoS ONE PLoS ONE, Public Library of Science, 2020, ⟨10.1371/journal.pone.0244637⟩ PLoS ONE, 2020, ⟨10.1371/journal.pone.0244637⟩ |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0244637⟩ |
| Popis: | MotivationThe availability of large metagenomic data offers great opportunities for the population genomic analysis of uncultured organisms, especially for small eukaryotes that represent an important part of the unexplored biosphere while playing a key ecological role. However, the majority of these species lacks reference genome or transcriptome which constitutes a technical barrier for classical population genomic analyses.ResultsWe introduce the metavariant species (MVS) model, a representation of the species only by intra-species nucleotide polymorphism. We designed a method combining reference-free variant calling, multiple density-based clustering and maximum weighted independent set algorithms to cluster intra-species variant into MVS directly from multisample metagenomic raw reads without reference genome or reads assembly. The frequencies of the MVS variants are then used to compute population genomic statistics such asFSTin order to estimate genomic differentiation between populations and to identify loci under natural selection. The MVSs construction was tested on simulated and real metagenomic data. MVs showed the required quality for robust population genomics and allowed an accurate estimation of genomic differentiation (ΔFST<0.0001 and < 0.03 on simulated and real data respectively). Loci predicted under natural selection on real data were all found by MVSs. MVSs represent a new paradigm that may simplify and enhance holistic approaches for population genomics and evolution of microorganisms.AvailabilityThe method was implemented in a R package,metaVaR.https://github.com/madoui/MetaVaRContactamadoui@genoscope.cns.fr |
| Databáze: | OpenAIRE |
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