The Reconstruction of 2,631 Draft Metagenome-Assembled Genomes from the Global Oceans

Abstract

Microorganisms play a crucial role in mediating global biogeochemical cycles in the marine 14 environment. By reconstructing the genomes of environmental organisms through 15 metagenomics, researchers are able to study the metabolic potential of Bacteria and Archaea that 16 are resistant to isolation in the laboratory. Utilizing the large metagenomic dataset generated 17 from 234 samples collected during the Tara Oceans circumnavigation expedition, we were able 18 to assemble 102 billion paired-end reads into 562 million contigs, which in turn were co-19 assembled and consolidated in to 7.2 million contigs ≥2kb in length. Approximately 1 million of 20 these contigs were binned to reconstruct draft genomes. In total, 2,631 draft genomes with an 21 estimated completion of ≥50% were generated (1,491 draft genomes >70% complete; 603 high-22 quality genomes >90% complete). A majority of the draft genomes were manually assigned 23 phylogeny based on sets of concatenated phylogenetic marker genes and/or 16S rRNA gene 24 sequences. The draft genomes are now publically available for the research community at-large. 25 26

Phosphate‐limited ocean regions select for bacterial populations enriched in the carbon–phosphorus lyase pathway for phosphonate degradation

“…The classification of MAGs was based on a phylogenetic analysis of several single‐copy marker genes and is described in detail in Tully et al . (). To identify phnJ genes in these MAGs, the protein‐coding regions in the assemblies available under NCBI BioProject PRJNA391943 were downloaded and subject to a BLASTP search using the translated sequence of phnJ genes identified in the OM‐RGC.…”

“…We also included in the analysis C-P lyase sequences identified in metagenome-assembled genomes (MAGs) from Tara Oceans (Tully et al, 2018) to aid with the classification of OM-RGC C-P lyase sequences. The classification of MAGs was based on a phylogenetic analysis of several single-copy marker genes and is described in detail in Tully et al (2018). To identify phnJ genes in these MAGs, the protein-coding regions in the assemblies available under NCBI BioProject PRJNA391943 were downloaded and subject to a BLASTP search using the translated sequence of phnJ genes identified in the OM-RGC.…”

“…strain HTCC7211 (GenBank accession ABVS01000001) which also contains the C-P lyase pathway (Carini et al, 2014). Tara Oceans metagenomic reads were obtained from the European Molecular Biology Laboratory-European Bioinformatics Institute and MAG assemblies (Tully et al, 2018) were downloaded from https://ndownloader.figshare.com/files/8849371. Reads were mapped against the genome assemblies using Bowtie 2 v2.2.4 (Langmead and Salzberg, 2012) and coding DNA sequences were identified with Prodigal v2.6.2 (Hyatt et al, 2010).…”

Linking metagenomics to aquatic microbial ecology and biogeochemical cycles

“…MAGs seem to recover more complete genomes while SAGs provide nearly complete confidence in gene co‐occurrence within an individual genome. Numerous MAG and SAG reference datasets of prokaryotes from marine (Delmont et al ; Tully et al ), estuarine (Alneberg et al ), and freshwater systems (Linz et al ) now exist and are publicly available to the research community. We note, however, the need for a centrally hosted and curated database of genomes with carefully assigned phylogenetic placement similar to the 16S rRNA based “FreshTrain” (Rohwer et al ).…”

Transcriptome reconstruction and functional analysis of eukaryotic marine plankton communities via high-throughput metagenomics and metatranscriptomics

“…These methods use 70 direct assemblies of metagenomic reads to generate contigs that encompass several genes. High 71 recovery of bacterial and archaeal genomes has been achieved through traditional assembly 72 strategies from both high and low diversity environmental samples (Tully et al 2018;Dick et al 73 2009; Albertsen et al 2013). However, when dealing with complex communities of organisms, 74 traditional genome assembly approaches are often impaired by the large amount of sequence data 75 and the genome heterogeneity.…”