Dataset Information

Two Metatranscriptomic Profiles through Low-Dissolved-Oxygen Waters (DO, 0 to 33 µM) in the Eastern Tropical North Pacific Ocean.

ABSTRACT: We present 16 seawater metatranscriptomes collected from a marine oxygen-deficient zone (ODZ) in the eastern tropical North Pacific (ETNP). This data set will be useful for identifying shifts in microbial community structure and function through oxic/anoxic transition zones, where overlapping aerobic and anaerobic microbial processes impact marine biogeochemical cycling.

SUBMITTER: Mattes TE

PROVIDER: S-EPMC8830328 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Two Metatranscriptomic Profiles through Low-Dissolved-Oxygen Waters (DO, 0 to 33 µM) in the Eastern Tropical North Pacific Ocean.

Mattes Timothy E TE Burke Susan S Rocap Gabrielle G Morris Robert M RM

Microbiology resource announcements 20220210 2

We present 16 seawater metatranscriptomes collected from a marine oxygen-deficient zone (ODZ) in the eastern tropical North Pacific (ETNP). This data set will be useful for identifying shifts in microbial community structure and function through oxic/anoxic transition zones, where overlapping aerobic and anaerobic microbial processes impact marine biogeochemical cycling. ...[more]

PMID: 35142554

Similar Datasets

Project description:The world's oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed "fragment recruitment," addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed "extreme assembly," made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS.

Project description:As consequences of global warming sea-ice shrinking, permafrost thawing and changes in fresh water and terrestrial material export have already been reported in the Arctic environment. These processes impact light penetration and primary production. To reach a better understanding of the current status and to provide accurate forecasts Arctic biogeochemical and physical parameters need to be extensively monitored. In this sense, bio-optical properties are useful to be measured due to the applicability of optical instrumentation to autonomous platforms, including satellites. This study characterizes the non-water absorbers and their coupling to hydrographic conditions in the poorly sampled surface waters of the central and eastern Arctic Ocean. Over the entire sampled area colored dissolved organic matter (CDOM) dominates the light absorption in surface waters. The distribution of CDOM, phytoplankton and non-algal particles absorption reproduces the hydrographic variability in this region of the Arctic Ocean which suggests a subdivision into five major bio-optical provinces: Laptev Sea Shelf, Laptev Sea, Central Arctic/Transpolar Drift, Beaufort Gyre and Eurasian/Nansen Basin. Evaluating ocean color algorithms commonly applied in the Arctic Ocean shows that global and regionally tuned empirical algorithms provide poor chlorophyll-a (Chl-a) estimates. The semi-analytical algorithms Generalized Inherent Optical Property model (GIOP) and Garver-Siegel-Maritorena (GSM), on the other hand, provide robust estimates of Chl-a and absorption of colored matter. Applying GSM with modifications proposed for the western Arctic Ocean produced reliable information on the absorption by colored matter, and specifically by CDOM. These findings highlight that only semi-analytical ocean color algorithms are able to identify with low uncertainty the distribution of the different optical water constituents in these high CDOM absorbing waters. In addition, a clustering of the Arctic Ocean into bio-optical provinces will help to develop and then select province-specific ocean color algorithms.

Dataset Information

Two Metatranscriptomic Profiles through Low-Dissolved-Oxygen Waters (DO, 0 to 33 µM) in the Eastern Tropical North Pacific Ocean.

Publications

Two Metatranscriptomic Profiles through Low-Dissolved-Oxygen Waters (DO, 0 to 33 µM) in the Eastern Tropical North Pacific Ocean.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets