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Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes
- Source :
- Nature Biotechnology, Nature Biotechnology, Nature Publishing Group, 2014, 32, pp.822-828. ⟨10.1038/nbt.2939⟩, Nature Biotechnology, 2014, 32, pp.822-828. ⟨10.1038/nbt.2939⟩, Nature Biotechnology, Nature Publishing Group, 2014, 32 (8), pp.822-828. ⟨10.1038/nbt.2939⟩, Nature Biotechnology 32 (2014), Nature Biotechnology, 32, 822-828, Nielsen, H B, Almeida, M, Juncker, A S, Rasmussen, S, Li, J H, Sunagawa, S, Plichta, D R, Gautier, L, Pedersen, A G, Le Chatelier, E, Pelletier, E, Bonde, I, Nielsen, T, Manichanh, C, Arumugam, M, Batto, J M, dos Santos, M B Q, Blom, N, Borruel, N, Burgdorf, K S, Boumezbeur, F, Casellas, F, Dore, J, Dworzynski, P, Guarner, F, Hansen, T, Hildebrand, F, Kaas, R S, Kennedy, S, Kristiansen, K, Kultima, J R, Leonard, P, Levenez, F, Lund, O, Moumen, B, Le Paslier, D, Pons, N, Pedersen, O, Prifti, E, Qin, J J, Raes, J, Sorensen, S, Tap, J, Tims, S, Ussery, D W, Yamada, T, Renault, P, Sicheritz-Ponten, T, Bork, P, Wang, J, Brunak, S, Ehrlich, S D & Meta, H I T C 2014, ' Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes ', Nature Biotechnology, vol. 32, no. 8, pp. 822-828 . https://doi.org/10.1038/nbt.2939
- Publication Year :
- 2014
-
Abstract
- Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.
- Subjects :
- Cellular immunity
polypeptide
[SDV]Life Sciences [q-bio]
SHORT READ ALIGNMENT SEQUENCES SYSTEMS ALGORITHMS MICROBIOTA PROTEIN LIFE SETS TREE TOOL
complex metagenomic sample
Applied Microbiology and Biotechnology
Genome
Microbiologie
Databases, Genetic
genetic element
Cluster Analysis
sets
short read alignment
ComputingMilieux_MISCELLANEOUS
Genetics
0303 health sciences
tool
metagenomic
tree
Lactococcus lactis
IL-12
Molecular Medicine
Biotechnology
life
Microbial Genomes
antigen specific immune response
Biomedical Engineering
Bioengineering
Computational biology
[SDV.BID]Life Sciences [q-bio]/Biodiversity
cellular immunity
Biology
algorithms
Microbiology
03 medical and health sciences
Genetic variation
microbiota
Microbiome
Gene
genome
030304 developmental biology
adjuvant activity
VLAG
030306 microbiology
Metagenomics
WIAS
Microbial genetics
sequences
systems
protein
Subjects
Details
- Language :
- English
- ISSN :
- 10870156
- Volume :
- 32
- Database :
- OpenAIRE
- Journal :
- Nature Biotechnology
- Accession number :
- edsair.doi.dedup.....121e69b6466f2fc83a6a9b77a47c9d05