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Open AccessJournal ArticleDOI

Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life

TLDR
The recovery of 7,903 bacterial and archaeal metagenome-assembled genomes increases the phylogenetic diversity represented by public genome repositories and provides the first representatives from 20 candidate phyla.
Abstract
Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently available microbial genomes. This is being addressed by advances in sequencing throughput and computational techniques that allow for the cultivation-independent recovery of genomes from metagenomes. Here, we report the reconstruction of 7,903 bacterial and archaeal genomes from >1,500 public metagenomes. All genomes are estimated to be ≥50% complete and nearly half are ≥90% complete with ≤5% contamination. These genomes increase the phylogenetic diversity of bacterial and archaeal genome trees by >30% and provide the first representatives of 17 bacterial and three archaeal candidate phyla. We also recovered 245 genomes from the Patescibacteria superphylum (also known as the Candidate Phyla Radiation) and find that the relative diversity of this group varies substantially with different protein marker sets. The scale and quality of this data set demonstrate that recovering genomes from metagenomes provides an expedient path forward to exploring microbial dark matter.

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Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences.

TL;DR: Tax4Fun2 is an R package for the prediction of functional profiles and functional gene redundancies of prokaryotic communities from 16S rRNA gene sequences that is easy-to-use, platform-independent and highly memory-efficient, thus enabling researchers without extensive bioinformatics knowledge or access to high-performance clusters to predict functional profiles.
Journal ArticleDOI

Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT

TL;DR: It is shown that the conventional best-hit approach often leads to classifications that are too specific, especially when the sequences represent novel deep lineages, and a classification method is presented that integrates multiple signals to classify sequences and metagenome-assembled genomes.
Journal ArticleDOI

Functional effects of the microbiota in chronic respiratory disease.

TL;DR: Recent advances in the understanding of the composition of the lung microbiome, including the virome and mycobiome, the mechanisms by which these microbes interact with host immunity, and their functional effects on the pathogenesis, exacerbations, and comorbidities of chronic respiratory diseases are reviewed.
Journal ArticleDOI

Diversity, ecology and evolution of Archaea

TL;DR: How genomes belonging to uncultured groups from the environment elucidate the metabolic capabilities of the Archaea and their ecological roles are discussed, while also expanding the view of the tree of life and of eukaryogenesis.
References
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Journal ArticleDOI

Fast and accurate short read alignment with Burrows–Wheeler transform

TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
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BLAST+: architecture and applications.

TL;DR: The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences.
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tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

TL;DR: A program is described, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases.
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Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
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