A compendium of multi-omic sequence information from the Saanich Inlet water column

Abstract

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Figure 1. Summary of multi-omic samples collected in Saanich Inlet time series.

(a) Oxygen concentration contour for CTD data (February 2008 onward) indicating 16 sampling depths for water column geochemistry and high-resolution (HR) DNA samples for SSU libraries (small black dots) and six major depths for large volume (LV) samples for meta-genomics, -transcriptomics, -proteomics and LV SSU libraries (large black dots). (b) Sample inventory from February 2006 to October 2014 indicating multi-omic datasets included in this manuscript (solid black), in previous publications (gray) and accompanying datasets currently undergoing processing and analysis (open gray).

Figure 2. Data Validation figures for SSU rRNA tag sequencing and metagenomes.

(a) 454 PyroTags for small subunit rRNA gene showing number of raw reads versus read length for large volume samples (99 samples in total) (left) and high resolution samples (311 samples in total) (right). (b) Metagenomic assemblies for two samples from different depths showing average fold coverage versus contig length and percentage GC versus average fold coverage for contigs.

Figure 3. Data validation figures for metatranscriptomes and metaproteomes.

(a) Metatranscriptomic reads for two samples from different depths showing distribution of reads over read quality (left) and percentage GC (right). (b) Metaproteome showing number of detected peptides (top) and detected proteins (bottom) for each depth sampled, colour coded by cruise ID. Higher number of detected proteins than peptides is due the sequence redundancy in the metagenomic database used to identify peptides.